JP3452191B2 - VEHICLE PLANNING PLANNING SUPPORT SYSTEM, COMPUTER-READABLE RECORDING MEDIUM RECORDING PROGRAM FOR CAUSING COMPUTER TO EXECUTE THE FUNCTION AS THE SYSTEM, AND VEHICLE LOCATION PLANNING SUPPORT METHOD - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a vehicle layout plan planning support system and method, and more particularly to a system and method for supporting planning of a layout plan for allocating vehicles such as taxis in a plurality of districts.

[0002]

[Prior Art] When there are multiple districts within a business area,
Since it is difficult to theoretically analyze the placement plan that decides how and where to place vehicles such as taxis in which of the plurality of districts, it is usually created by intuition based on past experience. It was For example, if there are multiple (3) districts A, B, and C in the business area, it is difficult to determine whether the taxi currently in district A is to remain in district A or to be moved to district B or district C. , The income that you can expect when you are in each district and the travel time to that district (unnecessary when you are in district A) are intricately involved as factors to be judged. I was taking into consideration the factors.

[0003]

However, in the vehicle layout plan based on the intuition, the accuracy of the layout plan varies greatly depending on the person who formulates the layout plan, and the layout plan cannot be formulated by only a limited number of people. I had problems such as that. Therefore, in the present invention, there is no such problem,
It is an object of the present invention to provide a system and method for assisting anyone to accurately plan a vehicle layout.

[0004]

In order to solve the above problems, a vehicle layout planning support system of the present invention (hereinafter, referred to as
It is called "this system". ) Is a system for supporting the planning of the placement plan of vehicles to be placed in a plurality of districts, and stores demand record data regarding operating hours and income of the vehicles corresponding to predetermined cases for each district. Performance data storage means, case classification acceptance means for accepting the case classification corresponding to the layout plan to be planned, position acceptance means for accepting the district to which the vehicle currently belongs, and case acceptance means for the case accepted Actual data read means for reading the demand actual data from the actual data storage means corresponding to cases, a case in which the vehicle remains in the current district accepted by the position accepting means, and a plurality of districts The expected amount of income per unit time of moving to each of the districts different from the district currently belonging to the actual data An expected value calculation means for calculating using 該需 main record data read by looking out means, comprising a a system.

[0005] Here, the "vehicle" includes a wide range of people carrying or carrying luggage, and is not particularly limited, and examples thereof include taxis, buses, trains, and home delivery vehicles. The "demand performance data" means data relating to operating hours and income of the vehicle corresponding to predetermined cases for each district, and is not particularly limited, but it is vacant (immediately upon request. Although it is not in the state of wages and vehicles despite being able to enter the state of wages and vehicles, fare (in the state of actually getting passengers and luggage to get the fare), the vehicle (in reality) Does not carry passengers or luggage, but is in the state where passengers or luggage are picking up passengers or luggage while getting fare), break (state not being rented or intercepted even if requested) ) The time when the vehicle state transits between the four states, the fare, etc. can be given as an example.

Here, "predetermined case classification" (hereinafter, simply referred to as "case classification") means case classification due to a predetermined factor that may affect the demand of the vehicle. That is, the demand for vehicles can be influenced by factors such as the day of the week and the time of day. Therefore, the accuracy of the planning for planning is improved by classifying the cases depending on the factors that can influence the demand for these vehicles. . The factors of the case classification are
It may be any factor that may affect the demand for the vehicle (the factor may be multiple or singular), for example, including at least one of the relationship to a holiday, the day of the week, the time of day, and the presence or absence of precipitation. May be The demand for vehicles such as taxis is related to holidays (here, it means whether the day including the boarding time or the time when luggage is loaded is the day before the holiday, the day before the holiday, the day after the holiday, or other day), the day of the week ( Here, it means the day of the week to which the boarding time or the time when the luggage is loaded belongs, the time zone (here, the time when the boarding time or the time when the luggage is loaded belongs to), and the presence or absence of rain (rain or It means whether or not it is snowing.), And the degree of influence of these factors on vehicle demand is difficult to express in a regular way using mathematical formulas. Therefore, it is possible to easily improve the accuracy of the planned placement plan by processing these factors according to the case.

In this system as described above, the actual result data storage means stores the demand actual result data concerning the operating time and the income of the vehicle corresponding to the predetermined case classification for each district, and the case classification acceptance means makes the plan. The case classification corresponding to the layout plan to be accepted is accepted, and the location accepting means accepts the district to which the vehicle currently belongs. Then, the actual result data reading unit reads the demand actual result data corresponding to the case classification received by the case classification receiving unit from the actual result data storage unit.
Finally, the expected amount calculating means determines whether the vehicle remains in the area where the vehicle is currently received by the position receiving means, and whether the vehicle is present in each of the plurality of districts different from the area to which the vehicle currently belongs. Expected income amount per unit time of moving to each, dividing the income amount of fare etc. by operating time using demand actual result data (corresponding to case classification) read by actual result data reading means Calculated by that. As a result, this system will calculate the expected amount of income per unit time when the vehicle remains in the current district as it is and when it moves to each of the different districts of the multiple districts. Since it is calculated, it is possible to support the planning of the placement plan of vehicles to be placed in multiple districts according to the size of this expected income (basically, vehicle placement such that vehicles exist in areas with large expected earnings). Make a plan.).

It is also possible that the factor of the case classification includes at least two types of business forms, that is, a sink and a center car dispatch, and the expected income amount is calculated for each business form (hereinafter, This case is referred to as "calculation by business type"). Here, the "sink" business mode refers to a business mode in which a passenger is requested to load or carry luggage while traveling in an empty state and enters a rented state. On the other hand, the "center dispatch" business mode is a business mode that changes from an empty state to a rented or intercepted state by picking up passengers or picking up luggage according to instructions from the office that manages vehicle operation etc. Say. Note that each vehicle may have a business form in which the business forms of these sinks and center dispatch are mixed, and at this time, they are divided into three types: "sink", "center dispatch", and "mixing of sink and center dispatch". The determined business form may be included in the factors for performing the case classification. Since the vehicle demand fluctuates greatly depending on the difference in these business forms, the expected income amount is greatly influenced by the difference in the business forms, and therefore it is preferable to calculate each of these business forms. It is difficult to express the degree of influence of these business forms on the expected income amount in a regular manner using mathematical formulas. Therefore, it is possible to easily improve the accuracy of the planned vehicle placement plan by processing the business form according to the case.

In the case of calculation by business type, when the business type is sink, the actual demand data includes data for determining a fare actual amount, a sink location travel time, a customer search time, and a boarding time. The amount may be calculated by the fare actual amount / (sending place moving time + customer search time + boarding time). By calculating the expected income amount by such a formula, when the business form is sinking, the expected amount of income per unit time corresponding to the case classification received by the case classification receiving means is expected. The amount of income can be calculated accurately. Here, the “actual fare amount” means the actual fare amount obtained in each area, and the demand result data of each area corresponding to the case classification received by the case classification reception means is read from the result data storage means. Then, it may be calculated using the actual fare amount obtained in each district included in the read demand actual data. In addition, "actual fare amount" here means
When there are a plurality of fare amounts corresponding to each district and the case classification, the fare amount may be a representative value of these plural fare amounts.
It is possible to exemplify the median value of the plurality of fare amounts that exist. "Sinking place moving time" means the time required to move to a customer search place, which is a place to look for a customer. In the case of operating as a business form), it is possible to exemplify the travel time and the like from the district that currently belongs to the different district. It should be noted that the term "sinking place moving time" used here means that there are a plurality of results of the moving place moving time of the same section corresponding to each case (for example, when there are a plurality of movements from the area A to the area B). It may be a representative value of the plurality of existing flowing place movement times, and the representative value is, for example, an average value of the plurality of actual flowing place movement times, a median value of the plurality of existing flowing place movement times, or the like. be able to. "Boarding time" means the time that the customer was on board. In addition, the "ride time" referred to here is the representative value of the actual ride time results when there are multiple actual ride time values obtained in each district to which the ride position belongs, corresponding to each case classification. The representative value may be, for example, an average value of the plurality of actual riding time results, a median value of the plurality of actual riding time results, or the like. The “customer search time” refers to the time required for the vehicle to search for a customer at the customer search place, and may be calculated by, for example, (required time-rest time-sink location travel time-boarding time). Here, the "required time" means the time from dropping the previous customer to the dropping of the present customer, the "break time" means the time in the break state, and the "ride time" is as described above. The term "customer search time" used here is defined as a representative value of the plurality of actual customer search time results when there are a plurality of actual values of customer search time obtained in each district corresponding to each case classification. The representative value may be, for example, an average value of the plurality of existing customer search time results, a median value of the plurality of existing customer search time results, or the like.

In the case of the calculation by business type, when the business type is center dispatch, the demand result data includes data for determining a fare actual amount, a center location moving time, a waiting time, a pick-up time, and a boarding time. The expected income amount may be calculated by the fare actual amount amount / (center location moving time + waiting time + pickup time + ride time). By calculating the expected income amount with such a formula, when the business form is center dispatch, it is the expected income amount per unit time corresponding to the case classification received by the case classification receiving means. The expected amount of income can be calculated accurately. Here, the “actual fare actual amount” is the same as the “actual fare actual amount” described in the case where the above-mentioned business form at the time of calculation by business form is “flow”, and therefore description thereof is omitted here. In addition,
It is also the same as here that the “actual fare amount” may be a representative value of a plurality of fare amounts when there are a plurality of fare amounts corresponding to each district and the case classification. The "center location moving time" here means the time required to move to at least one of the areas to which the waiting place, which is a place to wait until receiving a dispatch instruction from the center, such as a vehicle Is moving to a different area from the area to which it currently belongs and waiting at a waiting place existing in the different area to wait for a dispatch instruction from the center (business mode is center dispatch) The moving time and the like can be exemplified. Note that the "center location movement time" referred to here is a case where there are a plurality of center location movement time records of the same section corresponding to each case (for example, there are a plurality of movements from a district A to a standby location in a district B). In some cases), a representative value of the plurality of existing center location movement times may be used as the representative value, and the representative value may be an average value of the plurality of existing center location movement times or a median value of the plurality of existing center location movement times. Etc. can be illustrated. The “waiting time” means the time from when the vehicle arrives at the waiting place until the vehicle dispatch instruction is received from the center. In addition,
The "waiting time" here may be a representative value of the waiting time results that exist when there are a plurality of waiting time results corresponding to the same case classification in the same district,
Examples of the representative value include an average value of the plurality of existing waiting time results, a median value of the plurality of existing waiting time results, and the like. The "pick-up time" is the time from receiving the dispatch instruction from the center when receiving a dispatch instruction from the center while waiting at the waiting place to receiving the passenger etc. until receiving the passenger etc. Say. In addition, the "pick-up time" referred to here may be a representative value of the plurality of pick-up time results that exist when there are a plurality of pick-up time results corresponding to the same case classification in the same area. ,
For example, the average value of the plurality of existing vehicle pick-up time results, the median value of the plurality of existing vehicle pick-up time results, and the like can be exemplified. The "ride time" is the same as the "ride time" described when the above-mentioned business style in the calculation according to the business style is sinking, and therefore its description is omitted here. The same applies to the "ride time" here, which may be a representative value of a plurality of ride time results when there are a plurality of ride time results corresponding to each district (district to which the ride position belongs) and cases. .

In the case where the business mode is the center vehicle dispatch in the calculation according to the business mode, the demand result data includes data for determining the fare actual amount, the center location travel time, the waiting time, the intercepting time, and the boarding time, When the expected income amount is calculated by the fare actual amount / (center location moving time + waiting time + pick-up time + boarding time), the waiting time is the number of vehicles currently waiting in each area and the current belonging Estimated travel time of the vehicle from each district to each district, actual vehicle generation speed, which is the frequency per unit time when passengers get on each area and become actual vehicles, and passengers get off from the actual vehicle state and empty Is determined by using the empty vehicle occurrence speed, which is the frequency per unit time in the standby state waiting for center dispatch in each area. Good. The waiting time is, as described above,
This is the time from when the vehicle arrives at the standby location until it receives a vehicle dispatch instruction from the center.Since the center usually issues vehicle dispatch instructions in the order in which the vehicle arrives at the standby location, when the vehicle arrives at the standby location, the vehicle will arrive before the vehicle. Can be calculated by dividing the number of vehicles on standby from that number by one vehicle by the actual vehicle generation speed, which is the frequency per unit time when passengers in each area get into actual vehicles. it can. When the vehicle arrives at the waiting place, the number of vehicles waiting there before the vehicle is calculated from the number of vehicles currently waiting in each area (referred to as "currently waiting number"), By receiving a vehicle dispatch instruction within the expected travel time of the vehicle to each district, the number of vehicles currently standing by is reduced by the number of vehicles (referred to as "actual vehicle generation number"), and the wage is paid within the estimated travel time. It can be calculated by adding the number of passengers that get off from the running state and become empty (standby state waiting for center dispatch in each area). That is, the standby time is calculated by the formula: (current standby number-
It can be calculated by the number of actual vehicles generated + the number of empty vehicles generated + 1) / the actual vehicle generation speed. Then, the actual vehicle generation number can be calculated by multiplying the estimated travel time by the actual vehicle generation speed, and the empty vehicle generation number can be calculated by multiplying the estimated travel time by the empty vehicle generation speed. Therefore the waiting time is given by the formula:
(Current standby number-expected travel time x actual vehicle generation speed + expected travel time x empty vehicle generation speed + 1) / actual vehicle generation speed.

The actual vehicle generation speed may be obtained by any method. For example, the actual value of the actual vehicle generation speed generated for each case in each district is stored and the area corresponding to the layout plan to be planned is stored. The actual value may be read and used according to the case (hereinafter, referred to as “actual vehicle generation speed memory acquisition method”). Also,
An actual vehicle generation speed storage unit that stores the actual value of the actual vehicle generation speed for each actual vehicle case classification that is a case classification based on a factor including at least a part of the case classification factor, and a variable factor that affects the demand of the vehicle. Actual vehicle variable factor result storage means for storing the actual value of the variable factor indicating the degree (hereinafter, referred to as “variable factor actual data”) for each actual vehicle case, and the actual vehicle variable factor actual memory for each actual vehicle case An actual vehicle relationship determining means for obtaining an actual vehicle relationship, which is a relationship between the variable factor and the actual vehicle generated speed, from the actual value of the variable factor stored in the means and the actual value of the actual vehicle generated speed stored in the actual vehicle generated speed storage means. And an actual vehicle relationship storage unit that stores the actual vehicle relationship obtained by the actual vehicle relationship determining unit for each actual vehicle case, and a plan value of the variable factor corresponding to the layout plan to be planned. A variation factor accepting means to be attached, an actual vehicle relation reading means for reading the actual vehicle relation from the actual vehicle relation storing means corresponding to the case classification accepted by the case classification acceptance means, and a variation accepted by the variation factor acceptance means. An actual vehicle simulation means including an actual vehicle generation speed calculating means for calculating an actual vehicle generation speed using the planned value of the factor and the actual vehicle relationship read by the actual vehicle relationship reading means is further provided. The actual vehicle generation speed calculated by the actual vehicle generation speed calculation means may be used. Here, the "variable factor" refers to a factor considered in the present system that may or may affect the demand of the vehicle in the present system. Therefore, the variable factor may be selected regardless of the case classification factor. For example, a factor overlapping the variable factor and the case classification factor (a factor included in both the variable factor and the case classification factor). There may or may not be. The actual value of the variable factor (variable factor actual data) stored in the actual vehicle variable factor actual result storage unit by the actual vehicle relationship determining unit.
And the actual vehicle relationship, which is the relationship between the variation factor and the actual vehicle generated speed, is determined from the actual vehicle generated speed actual value stored in the actual vehicle generated speed storage means. For this reason, it is preferable to use, as a variable factor, a case that can be well represented by one type of actual vehicle relationship (for example, a relational expression) among the cases. By doing so, the actual vehicle simulation means functions as follows. That is, the actual vehicle generated speed storage means stores the actual value of the actual vehicle generated speed for each actual vehicle case, the actual vehicle variation factor actual result storage means stores the variable factor actual data for each actual vehicle case, and the actual vehicle relationship determination means The actual vehicle relationship, which is the relationship between the variable factor and the actual vehicle generation speed, is determined from the actual variation value actual data stored in the actual vehicle generation speed storage means and the actual vehicle generation speed storage value stored in the actual vehicle generation speed storage means. The actual vehicle relationship determined by the actual vehicle relationship storage means is stored for each actual vehicle case by the actual vehicle relationship storage means. Then, the variation factor acceptance means accepts the planned value of the variation factors corresponding to the layout plan to be planned, and the actual vehicle relation reading means accepts the actual vehicle relation corresponding to the case classification accepted by the case classification acceptance means. Is read from the actual vehicle relation storage means, and the actual vehicle generation speed calculation means uses the planned value of the variation factor accepted by the variation factor acceptance means and the actual vehicle relation read by the actual vehicle relation reading means. The actual vehicle generation speed is calculated.
Although the actual vehicle relationship is stored in the actual vehicle relationship storage means for each actual vehicle case, since the actual vehicle case classification is a case classification based on a factor including at least a part of the case classification factor, the case classification acceptance means The actual vehicle case classification corresponding to the case classification received by can be determined, and the actual vehicle relationship corresponding to the case classification received by the case classification receiving means can be read from the actual vehicle relationship storage means. . For example, when the factors of the case classification of the actual vehicle are two factors F and G, and the factors of the case classification are three factors of F, G, and H (the case classification of the actual vehicle is the factor F, G, When the case classification is determined by the factors F, G, and H, the factors F and G are included.
Based on the above, the actual vehicle case classification corresponding to the determined case classification can be determined. The actual vehicle case classification is a case classification based on a factor including at least a part of the case classification factors. It is sufficient if the actual vehicle case classification factor 1 and the case classification factor 1 are at least the same. All the factors of the case classification and all the factors of the case classification may completely match (in this case, the case classification of the actual vehicle and the case classification have exactly the same concept). As described above, in order to obtain the actual vehicle generated speed with sufficient accuracy by the actual vehicle generated speed memory acquisition method, a huge number of case classifications are required. Therefore, the number of cases can be significantly reduced while maintaining high accuracy. The actual vehicle relationship (the relationship between the variation factor and the actual vehicle generation speed obtained from the variation factor actual data and the actual vehicle generation speed actual value) obtained by the actual vehicle relationship determination means constitutes the variation factor actual data. It may be represented by a linear linear expression obtained by adding a term obtained by multiplying each numerical value and a coefficient corresponding thereto. By doing so, since the actual vehicle relationship is expressed by a linear linear expression, the actual vehicle relationship can be easily determined without a complicated calculation formula, and the actual vehicle generated speed is obtained by using the obtained actual vehicle relationship. Can be easily calculated.

The variation factor may include at least one of a discomfort index and a severe cold index. By the actual vehicle relation determining means, the actual vehicle relation between the actual value of the actual vehicle generated speed and the variable factor actual data is obtained for each actual vehicle case. At this time, the influence of the discomfort index or the severe cold index on the actual vehicle generated speed is , It is easy to express it by a regular one using mathematical formulas. Therefore, if the discomfort index and the severe cold index are factors of variation, the number of cases can be reduced, and the present system can be simplified. Further, the discomfort index or the severe cold index itself or information for calculating these may be automatically acquired from an external information source of the present system, and may further include information capturing means in communication with the external information source. . By doing so, the information fetching means automatically fetches information for obtaining the discomfort index or the severe cold index (the discomfort index, the severe cold index itself or information for calculating these) without requiring any special operation. So it's convenient not to forget to import. It should be noted that the communication with the external information source may be performed by any method as long as the information can be surely taken in, for example, the Internet, a telephone line (including wired, mobile phone, PHS, etc.),
Wireless or the like may be used. Further, the variation factor may include a sudden influence factor corresponding to a sudden change in the actual vehicle generation speed. The actual vehicle generation speed is not usually related, but it may vary greatly depending on something that occurs suddenly or occurs. Even in such a case, by including a sudden influence factor corresponding to a sudden change in the actual vehicle generation speed as a variable factor, it is possible to maintain the accuracy of demand prediction sufficiently high. For example, when considering the effect of an event to be held, the sudden impact factor is multiplied by the number of participants in the event that affects the actual vehicle generation speed for each district and the proportion of the vehicle user among the number of participants. It may include an event index. By doing this, if you know the number of participants in the event and the ratio of vehicle users to the number of participants,
It is possible to calculate with high accuracy the actual vehicle generation speed in the area affected by the event. It should be noted that even if there is snowfall or snowfall in an area where snowfall or snowfall is rare, it can be dealt with by a sudden influence factor. In addition, the variable factor may include economic data regarding an economic situation that affects the actual vehicle generation speed. Since the demand for vehicles (actual vehicle generation speed) is greatly influenced by the economic situation, the actual vehicle occurrence rate can be accurately calculated even if the economic situation changes by including the economic data regarding the economic situation in the variable factors. . As the economic data used here, it is preferable to use those that are indicators of the economic recession, such as the consumer price index in the monthly statistical report published by the national and local governments, monthly income and expenditure per household, school district
The number of households by town can be given as an example.

Any method may be used to obtain the empty vehicle generation speed. For example, the actual value of the empty vehicle generation speed generated for each case in each area is stored and the area corresponding to the layout plan to be planned. Alternatively, the actual value may be read out and used according to the case classification (hereinafter, referred to as “empty vehicle generation speed memory acquisition method”). Also,
An empty vehicle generation speed storage unit that stores the actual value of the empty vehicle generation speed for each empty vehicle case classification that is a case classification based on a factor that includes at least a part of the case classification factor, and a variable factor that affects the demand of the vehicle. An empty vehicle variation factor result storage unit that stores an actual value of a variation factor indicating a degree for each empty vehicle case, and an actual value of the variation factor stored in the empty vehicle variation factor result storage unit for each empty vehicle case An empty vehicle relationship determining unit that obtains an empty vehicle relationship that is a relationship between a variable factor and an empty vehicle occurrence speed from the actual value of the empty vehicle occurrence speed stored in the empty vehicle occurrence speed storage unit, and the empty vehicle relationship determination unit that determines the empty vehicle relationship. Empty vehicle relationship storage means for storing the empty vehicle relationship for each empty vehicle case, variable factor acceptance means for accepting the planned value of the variable factor corresponding to the layout plan to be planned, and the case classification Corresponding to the case classification received by the attaching means, the empty vehicle relation reading means for reading the empty vehicle relation from the empty vehicle relation storage means, the plan value of the variation factor accepted by the variation factor acceptance means, and the empty vehicle relation reading means The empty vehicle generation speed calculation means further includes an empty vehicle generation speed calculation means for calculating an empty vehicle generation speed using the empty vehicle relationship read by The empty vehicle generation speed may be used. Here, the "variation factor" is the same as the "variation factor" described in the method of obtaining the actual vehicle generation speed. Then, from the fluctuation factor actual result data stored in the empty vehicle variation factor actual result storage means by the empty vehicle relation determining means and the actual value of the empty vehicle generation speed stored in the empty vehicle generation speed storage means, the variation factor and the empty vehicle generation speed. The empty car relationship, which is the relationship with For this reason, it is preferable to use, as a variation factor, a factor that can be successfully expressed by one set of the empty vehicle relationships (for example, a relational expression) among the cases. By doing so, the empty vehicle simulation means functions as follows. That is, the actual value of the empty vehicle generation speed is stored for each empty vehicle case by the empty vehicle generation speed storage means, the variable factor actual data is stored for each empty vehicle case classification by the empty vehicle variation factor actual result storage means, and the empty vehicle relation determination means is used. When the empty vehicle relationship, which is the relationship between the variable factor and the empty vehicle occurrence speed, is the empty vehicle, based on the variable factor actual result data stored in the variable factor actual result storage means and the actual value of the empty vehicle occurrence speed stored in the empty vehicle occurrence speed storage means The empty vehicle relationship determined by the empty vehicle relationship storage means is stored for each empty vehicle case by the empty vehicle relationship determination means. Then, the variable factor acceptance means accepts the planned value of the variable factor corresponding to the layout plan to be planned, and the empty vehicle relation reading means accepts the empty vehicle relation corresponding to the case classification accepted by the case classification acceptance means. Is read from the empty vehicle relation storage means, and the empty vehicle generation speed calculation means uses the planned value of the variation factor accepted by the variation factor acceptance means and the empty vehicle relation read by the empty vehicle relation reading means. The empty vehicle generation speed is calculated. The empty vehicle relationship storage means stores the empty vehicle relationship for each empty vehicle case, but since the empty vehicle case classification is a case classification by a factor including at least a part of the case classification factors, the case classification acceptance means It is possible to determine the empty vehicle case classification corresponding to the case classification accepted by the case classification, and the empty vehicle relationship corresponding to the case classification accepted by the case classification acceptance means can be read from the empty vehicle relationship storage means. . For example, when there are two factors F, G for the case classification of the empty vehicle, if the factors for the case classification are three factors of F, G, H (the case classification for the empty vehicle is the factor F, G,
The case is divided by factors F and G including F and G that are a part of H. ), When the case classification is determined by the factors F, G, H, the empty vehicle case classification corresponding to the determined case classification can be determined based on the factors F, G. The empty vehicle case classification is a case classification based on a factor including at least a part of the case classification factors. It is sufficient if the empty vehicle case classification factor 1 and the case classification factor 1 are at least the same. All the factors of the case classification and all the factors of the case classification may completely match (in the case of this complete match, the empty case classification and the case classification have exactly the same concept). As described above, in order to obtain the empty vehicle generation speed with sufficient accuracy by the empty vehicle generation speed memory acquisition method, a huge number of case classifications are required. However, use of the empty vehicle case classification and the relation (for example, a relational expression) together Therefore, the number of cases can be significantly reduced while maintaining high accuracy. The empty vehicle relationship (the relationship between the variation factor and the empty vehicle generation speed obtained from the variation factor actual data and the actual value of the empty vehicle generation speed) obtained by the empty vehicle relation determining means constitutes the variation factor actual data. It may be represented by a linear linear expression obtained by adding a term obtained by multiplying each numerical value and a coefficient corresponding thereto. By doing so, since the empty vehicle relationship is expressed by a linear primary expression, the empty vehicle relationship can be easily determined without a complicated calculation formula, and the obtained empty vehicle relationship is used to generate an empty vehicle generation speed. Can be easily calculated.

[0015] The vehicle may further include notifying means for notifying the vehicle of the expected income amount calculated by the expected amount calculation means. By doing so, when the vehicle remains in the area to which the vehicle has currently been received by the position receiving means (when the vehicle), or when the vehicle moves to each of different districts different from the district to which the vehicle currently belongs. The expected amount of income per unit time can be known to the crew member of the vehicle, and the crew member can decide which district to consider in consideration of his / her own situation and preference. In addition, "notifying the expected amount of income" referred to here means
Not only is it necessary to notify the specific value of the expected income amount, but it also includes notification of the size of the expected income amount for each district and the district with the highest expected income amount. The notification means is not particularly limited as long as it can notify the vehicle of the expected income amount from the system, and is not particularly limited. For example, to identify the size of the voice, the expected income amount of each district. , A radio and a telephone (including a mobile phone and a PHS) for transmitting a signal for identifying the district with the largest expected income amount to the vehicle, and the like.

The present system has a performance input means for inputting performance data (which may include the demand performance data itself or may coincide with the demand performance data itself) for creating the demand performance data for each vehicle. You may have. The result input means is mounted on each vehicle, and writes the result data relating to each vehicle cumulatively in the result storage medium for each state change of the vehicle, and the result storage medium arranged on the system main body side. And a result reading means for reading the result data written in. Here, "every state change" means "at any time of transition between the four states of empty vehicle, rent, pick-up vehicle, and break", but in the case of all transitions between these states. It does not have to be Further, "cumulatively write" means that sequentially generated data is written in a state where the data can be grasped later in time series. By doing so, the actual result data relating to each vehicle is cumulatively written in the actual result storage medium by the actual result writing means mounted in each vehicle, and the actual result storage means is arranged by the actual result reading means arranged on the system main body side. The performance data written in the medium is read out, and the performance data is stored in the system body. Therefore, since data is exchanged between each vehicle and the system body through the lightweight and small record storage medium such as an IC card, a flexible disk (floppy disk), and a compact disk,
It is possible to reduce the labor when inputting the result data regarding each vehicle into the system main body.

The present system can also be realized by incorporating a program for causing a computer to execute the function of the above system, and the program can be recorded in a recording medium readable by the computer. .

Further, in order to solve the above-mentioned problems, a method for supporting a vehicle layout plan of the present invention (hereinafter referred to as "this method") is to prepare a vehicle layout plan for a plurality of districts. A method of supporting using a computer, which corresponds to a predetermined case classification for each district,
A performance data storage step of storing demand performance data relating to the operating hours and income of the vehicle, a case classification reception step of receiving the case classification corresponding to the layout plan to be planned, and a position reception of receiving the district to which the vehicle currently belongs. A step, a performance data reading step for reading the demand performance data stored by the performance data storing step, which corresponds to the case classification received by the case classification receiving step, and a vehicle receiving by the position reception step. The expected income amount per unit time of the case where it remains in the currently belonging district as it is, and the case of moving to each of the districts different from the district where the current belongs among the plurality of districts, the actual data reading step Expected amount calculation using the actual demand data read by Consisting comprises a step, and a method.

Here, "vehicle", "demand performance data",
The “predetermined case classification” is the same as that described in the present system, and thus the description thereof is omitted here.

In the present method as described above, the demand result data relating to the operating time and income of the vehicle corresponding to the predetermined case classification for each district in the result data storing step is stored, and the plan is prepared in the case classification receiving step. Case classification corresponding to the layout plan to be performed is accepted, and in the position acceptance step, the district to which the vehicle currently belongs is accepted. Then, in the actual result data reading step, the demand actual result data corresponding to the case classification received in the case classification receiving step is read. Finally, in the expected amount calculation step, when the vehicle remains in the area where the vehicle is currently accepted (in the location acceptance step) The expected income amount per unit time of moving to each of the cases is calculated using the demand actual result data (corresponding to case classification) read in the actual result data reading step. As a result, this method determines the expected amount of income per unit time for each of the cases where the vehicle remains in the area to which it currently belongs and where it moves to each of the areas that are different from the area to which it currently belongs. Since it is calculated, it is possible to support the planning of the placement plan of vehicles to be placed in multiple districts according to the size of this expected income (basically, vehicle placement such that vehicles exist in areas with large expected earnings). Make a plan.).

It is also possible that the factors of the case classification include at least two types of business forms of sinking and center dispatch, and the expected income amount is calculated for each business form (hereinafter, This case is referred to as "calculation by business type"). Since the business forms of "sink" and "center dispatch" are the same as those described in the present system, the description thereof is omitted here. Note that each vehicle may have a business form in which the business forms of these sinks and center dispatch are mixed, and at this time, they are divided into three types: "sink", "center dispatch", and "mixing of sink and center dispatch". It is also the same as the present system that the determined sales form may be included in the factors for performing the case classification. Since the vehicle demand fluctuates greatly depending on the difference in these business forms, the expected income amount is greatly influenced by the difference in the business forms, and therefore it is preferable to calculate each of these business forms. It is difficult to express the degree of influence of these business forms on the expected income amount in a regular manner using mathematical formulas. Therefore, it is possible to easily improve the accuracy of the planned vehicle placement plan by processing the business form according to the case.

In the case of calculation by business type, when the business type is sink, the actual demand data includes data for determining a fare actual amount, a moving time of a sink location, a customer search time, and a boarding time. The amount may be calculated by the fare actual amount / (sending place moving time + customer search time + boarding time). By calculating the expected income amount by such a formula, when the business form is sinking, the expected amount of income per unit time corresponding to the case classification received by the case classification receiving means is expected. The amount of income can be calculated accurately. The “actual fare actual amount”, the “passage time traveling time”, the “customer search time”, and the “boarding time” are the same as those described in the present system, and therefore the description thereof is omitted here.

In the case of the calculation by business type, if the business type is center dispatch, the demand actual data includes data for determining a fare actual amount, a center location moving time, a waiting time, a pick-up time, and a boarding time, The expected income amount may be calculated by the fare actual amount / (center location moving time + waiting time + pickup time + boarding time). By calculating the expected income amount with such a formula, when the business form is center dispatch, it is the expected income amount per unit time corresponding to the case classification received by the case classification receiving means. The expected amount of income can be calculated accurately. Here, "actual fare actual amount", "center location travel time", "waiting time", "pick-up time", and "ride time" are the same as those described in the present system, and therefore description thereof is omitted here. .

As described above, the waiting time is the number of vehicles that are waiting from the front of the vehicle when the vehicle arrives at the waiting place, plus the number of the one vehicle, and the passengers in each district. It can be calculated by dividing by the actual vehicle generation speed which is the frequency per unit time of getting on the vehicle, which is calculated by the formula: (current standby vehicle number-actual vehicle generated vehicle number + empty vehicle generated vehicle number + 1) / actual vehicle generated vehicle speed. Further, this formula can be rewritten as the formula: (current standby number-expected travel time x actual vehicle generation speed + expected travel time x empty vehicle generation speed + 1) / actual vehicle generation speed. Any method may be used to obtain the actual vehicle generation speed used when obtaining these waiting times. For example, the actual value of the actual vehicle generation speed generated for each case in each district is stored, and the layout plan to be planned. The actual value may be read and used according to the area and the case corresponding to (hereinafter, referred to as “actual vehicle generation speed memory acquisition method”). Also, an actual vehicle generation speed storing step of storing the actual value of the actual vehicle generation speed for each actual vehicle case classification, which is a case classification due to a factor including at least a part of the case classification factor, and a variation affecting the demand of the vehicle. Actual vehicle variable factor actual result storing step of storing the actual value of the variable factor indicating the degree of the factor for each actual vehicle case, and the actual result of the variable factor stored in the actual vehicle variable factor actual result storing step for each actual vehicle case The actual vehicle relationship determination step of obtaining an actual vehicle relationship, which is the relationship between the variation factor and the actual vehicle generated speed, from the value and the actual value of the actual vehicle generated speed stored in the actual vehicle generated speed storage step, and the actual vehicle relationship determination step. And an actual vehicle relationship storing step of storing the actual vehicle relationship for each case of the actual vehicle, and a plan of the variable factors corresponding to the layout plan to be planned. In the actual vehicle relationship storing step for reading the actual vehicle relationship stored in the actual vehicle relationship storing step, which corresponds to the case classification received in the case classification receiving step, and in the fluctuation factor receiving step An actual vehicle simulation step further comprising an actual vehicle generation speed calculation step of calculating an actual vehicle generation speed using the received planned value of the variable factor and the actual vehicle relationship read in the actual vehicle relationship reading step. Then, the actual vehicle generation speed calculated in the actual vehicle generation speed calculation step may be used. Here, the “variation factor” is as described in the present system, and therefore its explanation is omitted here. By doing so, the actual vehicle simulation step functions as follows. That is, the actual value of the actual vehicle generation speed is stored for each actual vehicle case in the actual vehicle generation speed storage step, the variation factor actual data is stored for each actual vehicle case in the actual vehicle variation factor actual result storage step, and the actual vehicle generation speed is stored in the actual vehicle relation determination step. When the actual vehicle relationship, which is the relationship between the variable factor and the actual vehicle generation speed, is the actual vehicle based on the variation factor result data stored in the variation factor result storage step and the actual value of the actual vehicle generation speed stored in the actual vehicle generation speed storage step The actual vehicle relationship determined for each case and determined in the actual vehicle relationship determination step in the actual vehicle relationship determination step is stored for each actual vehicle case. Then, in the variation factor acceptance step, the plan value of the variation factor corresponding to the layout plan to be planned is accepted, and in the actual vehicle relation reading step, the actual vehicle relation corresponding to the case classification accepted in the case classification acceptance step. Is read out, and the actual vehicle generation speed is calculated in the actual vehicle generation speed calculation step using the planned value of the fluctuation factor accepted in the fluctuation factor acceptance step and the actual vehicle relationship read in the actual vehicle relationship reading step. It In the actual vehicle relationship storage step, the actual vehicle relationship is stored for each actual vehicle case. However, since the actual vehicle case classification is a case classification that includes at least a part of the case classification factors, the case classification acceptance step The actual vehicle case classification corresponding to the case classification received by can be determined, and the actual vehicle relationship corresponding to the case classification received by the case classification receiving step can be read. For example, when the factors of the case classification of the actual vehicle are two factors F and G, and the factors of the case classification are three factors of F, G, and H (the case classification of the actual vehicle is the factor F, G, F which is a part of H,
The case is divided according to factors F and G including G. ), When the case classification is determined by the factors F, G, H, the actual vehicle case classification corresponding to the determined case classification can be determined based on the factors F, G. As described above, the actual vehicle case classification is a case classification by a factor including at least a part of the case classification factors, and the actual vehicle case classification factor 1 and the case classification factor 1 are at least the same. It is sufficient if all the factors of the actual vehicle case classification and all the factors of the case classification are completely the same (in this case, the actual vehicle case classification and the case classification are exactly the same concept). Become.). As described above, in order to obtain the actual vehicle generated speed with sufficient accuracy by the actual vehicle generated speed memory acquisition method, a huge number of case classifications are required. Therefore, the number of cases can be significantly reduced while maintaining high accuracy. The actual vehicle relationship (relationship between the variation factor and the actual vehicle generation speed obtained from the variation factor actual data and the actual vehicle generated speed actual value) obtained in the actual vehicle relationship determination step constitutes the variation factor actual data. It may be represented by a linear linear expression obtained by adding a term obtained by multiplying each numerical value and a coefficient corresponding thereto. By doing so, since the actual vehicle relationship is expressed by a linear linear expression, the actual vehicle relationship can be easily determined without a complicated calculation formula, and the actual vehicle generated speed is obtained by using the obtained actual vehicle relationship. Can be easily calculated.

Any method may be used to obtain the vacant vehicle generation speed. For example, the actual value of the vacant vehicle generation speed generated for each case in each area is stored and the area corresponding to the layout plan to be planned is stored. Alternatively, the actual value may be read out and used according to the case classification (hereinafter, referred to as “empty vehicle generation speed memory acquisition method”). Also,
A vacant vehicle generation speed storage step of storing the actual value of the vacant vehicle generation speed for each vacant vehicle case classification which is a case classification by a factor including at least a part of the case classification factor, and a variable factor affecting the demand of the vehicle. An empty vehicle variation factor result storage step of storing an actual value of a variation factor indicating the degree for each empty vehicle case, and an actual value of the variation factor stored in the empty vehicle variation factor result storage step for each empty vehicle case An empty vehicle relationship determining step for obtaining an empty vehicle relationship, which is a relationship between a variable factor and an empty vehicle occurrence speed, from the actual value of the empty vehicle occurrence speed stored in the empty vehicle occurrence speed storing step; An empty vehicle relationship storage step of storing empty vehicle relationships for each empty vehicle case and a plan value of the variable factor corresponding to the layout plan to be planned are received. A variable factor acceptance step of attaching, a vacant vehicle relation reading step of reading the vacant vehicle relation stored in the vacant vehicle relation storing step corresponding to the case classification accepted by the case classification acceptance step, and acceptance in the variation factor acceptance step And a vacant vehicle generation speed calculating step of calculating a vacant vehicle generation speed using the planned value of the variable factor and the vacant vehicle relation read in the vacant vehicle relation reading step. hand,
The empty vehicle generation speed calculated in the empty vehicle generation speed calculation step may be used. Here, the "variation factor" is the same as that described in the present system, and therefore the description thereof is omitted here. By doing so, the empty vehicle simulation step functions as follows.
That is, the actual value of the empty vehicle generation speed is stored for each empty vehicle case in the empty vehicle generation speed storage step, the variation factor actual data is stored for each empty vehicle case in the empty vehicle variation factor actual result storage step, and the empty vehicle is determined in the empty vehicle relation determination step. When the empty vehicle relationship, which is the relationship between the variable factor and the empty vehicle occurrence speed, is empty, based on the variable factor result data stored in the variable factor actual result storage step and the actual value of the empty vehicle occurrence speed stored in the empty vehicle occurrence speed storage step The empty vehicle relationship that is obtained for each case and that is obtained in the empty vehicle relationship determination step in the empty vehicle relationship determination step is stored for each empty vehicle case. Then, in the variation factor acceptance step, the plan value of the variation factor corresponding to the layout plan to be planned is accepted, and in the empty vehicle relation reading step, the empty vehicle relation corresponding to the case classification accepted in the case classification acceptance step. In the empty vehicle generation speed calculation step, the empty vehicle generation speed is calculated using the plan value of the fluctuation factor accepted in the fluctuation factor acceptance step and the empty vehicle relationship read in the empty vehicle relationship reading step. It In the empty vehicle relationship storing step, the empty vehicle relationship is stored for each empty vehicle case. However, since the empty vehicle case classification is a case classification by a factor including at least a part of the case classification factor, the case classification acceptance step The empty vehicle case classification corresponding to the case classification received by can be determined, and the empty vehicle relationship corresponding to the case classification received by the case classification receiving step can be read. For example, when there are two factors F, G for the case classification of the empty vehicle, if the factors for the case classification are three factors of F, G, H (the case classification for the empty vehicle is the factor F, G, When the case division is determined by the factors F, G, and H, the determination is made based on the factors F and G. An empty vehicle case classification corresponding to the case classification can be determined. As described above, the empty vehicle case classification is a case classification by a factor including at least a part of the case classification factors, and the empty vehicle case classification factor 1 and the case classification factor 1 are at least the same. It is sufficient if all the factors of the case classification of the empty vehicle and all the factors of the case classification are completely the same (in this case, the case classification of the empty vehicle and the case classification are exactly the same concept). Become.). As described above, in order to obtain the empty vehicle generation speed with sufficient accuracy by the empty vehicle generation speed memory acquisition method, a huge number of case classifications are required. However, use of the empty vehicle case classification and the relation (for example, a relational expression) together Therefore, the number of cases can be significantly reduced while maintaining high accuracy. The empty vehicle relationship (relationship between the variation factor and the actual vehicle generation speed obtained from the variation factor actual data and the actual value of the empty vehicle generation speed) obtained in the empty vehicle relation determination step constitutes the variation factor actual data. It may be represented by a linear linear expression obtained by adding a term obtained by multiplying each numerical value and a coefficient corresponding thereto. By doing so, since the empty vehicle relationship is expressed by a linear primary expression, the empty vehicle relationship can be easily determined without a complicated calculation formula, and the obtained empty vehicle relationship is used to generate an empty vehicle generation speed. Can be easily calculated.

The information processing apparatus may further include a notification step of notifying the vehicle of the expected income amount calculated in the expected amount calculation step. By doing so, when the vehicle is still in the district (to which the vehicle belongs) currently accepted in the position acceptance step,
The crew member of the vehicle can know the expected amount of income per unit time of moving to each of the districts different from the district to which the vehicle currently belongs, and the crew member's own situation and preference. You can decide which district to take into consideration. Note that "notifying the expected amount of income" here is as described in the present system, and therefore the description is omitted here. The means for notifying in the notifying step is also as described in the present system, and therefore its explanation is omitted here.

The present method is a result input step for inputting the result data (may include the demand result data itself or may coincide with the demand result data itself) for creating the demand result data for each vehicle. A record writing step of cumulatively writing the record data of each vehicle in the record storage medium for each state change of each vehicle, and a record reading step of reading the record data written in the record storage medium. , May be included. Here, “every state change” and “cumulatively write” are the same as those described in the present system, and therefore the description is omitted here. By doing so, the actual result data regarding each vehicle is cumulatively written in the actual result storage medium in each actual vehicle in the actual result writing step in each vehicle, and the actual result data written in the actual result storage medium in the actual result reading step is read. Issued,
Actual data is stored. Therefore, since data transfer between each vehicle and the system main body is performed via the lightweight and small record storage medium such as an IC card, a flexible disk (floppy disk), a compact disk, etc., the record data concerning each vehicle It is possible to reduce the labor when inputting.

[0028]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings, but the present invention is not limited thereto.

Here, a system and method for supporting the planning of a placement plan for placing taxis serving as vehicles in a plurality of districts will be described. FIG. 1 is a schematic configuration diagram showing connections among the taxi 11, the sales office 31, and the base 51. With reference to FIG. 1, the connection of each part of the system will be described. In addition, in the present embodiment, the factors of the predetermined case classification (the case classification), the actual vehicle case classification, and the empty vehicle case classification are all the same (business mode including sink and center vehicle dispatch). , The presence / absence of rain, the day of the week, and the time of day), but the factors of the case classification, the actual vehicle case classification, and the empty vehicle case classification may be different from each other as necessary. . For example, the business mode including the factors for classifying the cases and dispatching to the center, the presence or absence of rainfall, the day of the week,
There may be four factors of the time zone and three factors of the business mode including the case of the actual vehicle and the factor of the empty vehicle, the day of the week, and the time zone including the center dispatch.

The taxi 11 includes a global positioning system (hereinafter referred to as "GPS") 13 for detecting the current position of the taxi 11, a data receiving unit 15 for detecting the speed of the taxi 11, a GPS 13 and a data receiving unit 15. A control unit that obtains data from and calculates actual data (data for creating demand actual data (may include the actual demand actual data or may coincide with the actual demand actual data).) 23,
It has a display unit 17 for displaying the result data and the like, and a data writing unit 19 for writing the result data in the IC card 21 as the result storage medium. These GPS 13, data receiving unit 15, display unit 17, and data writing unit 19
The control unit 23 and the control unit 23 are connected by a cable 25 so that data can be exchanged. In this embodiment, the GPS
13, the data receiving unit 15, the data writing unit 19, and the control unit 23 form a performance writing unit, and the performance writing unit, as described later, mounts performance data regarding a taxi mounted on a taxi for each state change of the taxi. Is cumulatively written in the IC card 21 (result storage medium). Although only one taxi 11 is shown here, a plurality of taxis similar to this exist.

The business office 31 has an IC card 21 (actual result storage medium) in which actual result data concerning the taxi 11 is written.
The card reading unit 33 for reading the actual result data and the business office computer 35 for processing and storing the actual result data read by the card reading unit 33. Card reading unit 33 and sales office computer 35
And are connected by a cable 37 so that data can be exchanged. In this embodiment, the card reading unit 3
Reference numeral 3 corresponds to the result reading means arranged on the system body side. The system main body means the rest of the entire system except the vehicle (the taxi 11 in this case). Then, in the present embodiment, the actual result data regarding the taxi 11 is passed through the IC card 21 (actual result storage medium), but the present invention is not limited to this. The taxi 11 may be used to deliver the performance data. At that time, the performance data may be delivered every time the state of the taxi changes, or the performance data may be delivered every time a fixed time elapses.
May be delivered every time the vehicle moves a certain distance, and may be delivered at a timing when these state changes, a certain time elapses, and a certain distance movement are combined.

The base 51 is mainly a first base computer 53 for calculating the actual vehicle speed and the empty vehicle speed, and a second base computer 58 for mainly calculating the expected income amount.
And a data server 55 serving as a storage device for the first base computer 53 and the second base computer 58 (actual data storage means, actual vehicle generation speed storage means, variable factor actual result storage means, actual vehicle relation storage means, empty vehicle generation speed storage means And works as a vacant vehicle-related storage means). The first base computer 53, the second base computer 58, and the data server 55 are connected by a cable 59 so that they can freely exchange data with each other. The first base computer 53 receives the performance data stored in the business office computer 35 through the cable 41, and
The variable factor actual data indicating the degree of the variable factor affecting the demand of the taxi 11 or the data necessary for calculating the variable factor actual data is fetched and output to the data server 55.

Here, the actual data includes district information (information that at least reveals in which district the boarding or alighting occurred) and case-separation factors (business mode including sinks and center vehicles, rainfall). Existence, day of the week, time zone 4
It depends on the factor. In the present embodiment, it becomes a case division factor of the case division, the actual vehicle case division, and the empty vehicle case division. ), Which includes factor information other than the presence or absence of rainfall, and information for each case can be extracted for each district. Also, regarding the variable factor actual data itself or the data required to calculate it, it is necessary to clarify the district information so that each data belongs to which district and which day of the week and time zone it belongs to. And case classification information is included. Therefore, it becomes clear which of the variable factor actual data is relevant to which variable data actual data itself or the data necessary for calculating it (referred to as variable factor actual data, etc.). In addition, when the correspondence relationship between each data of the actual data and the variable factor actual data is not uniquely determined by the district information and the case-separated information (for example, when both data extend over a plurality of weeks). For example, district information and case classification based on only three factors of business type, day of the week, and time zone may not be able to be dealt with unambiguously because there are different days even on the same day.) It suffices to appropriately give other attributes (for example, date) to both data and clarify the corresponding relationship between both data by also referring to the other attributes of both data. The data server 55 includes rainfall information indicating the presence / absence of rainfall in the boarding area and the disembarking area, which are included in each data of the actual data (area information and case classification information of each data and Depending on other attributes, the presence / absence of precipitation in the boarding area and the disembarking area is read out from the variable factor result storage means that also stores information on the presence / absence of precipitation, and is associated with the actual data. After storing the actual result data in the data server 55 first, even if the information on the presence / absence of precipitation is stored in the data server 55 in a corresponding relationship with the actual result data, the actual data and the information on the presence / absence of precipitation are associated with each other. While it may be stored in the data server 55), the demand actual result data is stored, and the variable factor actual result data is also stored. From this point of view, the data server 55 stores the demand result data corresponding to the predetermined case classification for each district, and thus functions as the performance data storage means and also stores the variable factor performance data for each case classification. Therefore, it also functions as a variable factor result storage means (functions as both an actual vehicle variation factor result storage means and an empty vehicle variation factor result storage means).

In the present embodiment, the data (including the variable factor performance data, etc.) taken in by the first base computer 53 is weather, temperature (° C.), wind direction, wind speed (m / s), precipitation (mm). ), Humidity (%), and the first base computer 53 automatically collects data from the homepage of a private weather information provider, which is an external information source of the present system, for each district using the Internet 57 at a predetermined time. That is, the first base computer 53 is in contact with the homepage of the private weather information provider, which is the external information source, via the Internet 57, and also serves as an information fetching means. It should be noted that here, the information collection from the homepage is given as an example, but the present invention is not limited to this, and it goes without saying that the information may be collected using a wired or wireless dedicated line or the like. The first base computer 53 may automatically collect the information at predetermined time intervals. Weather, temperature (℃), wind direction, wind speed (m / s), precipitation (m)
As for the m) and humidity (%), as described above, it becomes clear which district each data belongs to, which day of the week and time zone of the case classification, and the year and month when each data was collected. It contains information that makes the day clear. Note that the first base computer 53 and the business office computer 35 are connected by the cable 41 to exchange data in the present embodiment, but the present invention is not limited to this, and may be, for example, a wired telephone or the Internet. Data may be exchanged using a mobile phone, PHS, wireless, or the like.

As described above, the demand result data stored in the data server 55 includes the boarding area where the passenger gets in and the area where the passenger disembarks, and it becomes clear which case these belong to. There is. That is, the stored demand record data includes the actual vehicle generation speed (the frequency per unit time when passengers get into each area to become an actual vehicle. In addition, each ride is an actual vehicle occurrence in the area to which the boarding place belongs. The actual value of the frequency and the vacant vehicle speed (the frequency per unit time when the passenger gets off from the actual vehicle and becomes vacant and waits for center dispatch in each area) Note that in the present embodiment, each disembarkation is classified into the actual value of the vacant vehicle occurrence frequency of the district to which the disembarking place belongs.) Since the factors of the actual vehicle case classification and the empty vehicle case classification are the same, they are included in each of the actual vehicle case classification and the empty vehicle case classification). Also it acts as a vacant space generating speed storage means.

When a predetermined amount of demand performance data is accumulated in the data server 55, the first base computer 53
Calculates the number of boarding times and the number of boarding times that belong to each case for each district from the demand result data stored in the data server 55. On the other hand, the first base computer 53
Is a data server 55 as a variable factor result storage means.
From the above, the variable factor actual data is read out for each case for each district. Then, the first base computer 53, for each case of each actual vehicle in each district, the number of times of boarding (the number of times of boarding per time zone, which is one of the factors of the case classification, is the actual value of the actual vehicle generation speed) and the variation factor. The actual vehicle relationship, which is the relationship between the variation factor and the actual vehicle generation speed, is obtained from the actual data (here, the first base computer 53 functions as the actual vehicle relationship determining means). Also, the first base computer 53
For each empty case in each district, the number of drop-offs (the number of drop-offs per time zone, which is one of the factors for dividing cases, is the actual value of the empty vehicle generation speed) and the variable factor The empty vehicle relationship, which is the relationship with the generation speed, is obtained (here, the first base computer 53 functions as empty vehicle relationship determining means). Note that here, the factors for the case classification of the actual vehicle and the factors for the case classification of the empty vehicle match. The actual vehicle relationship and the empty vehicle relationship obtained by the first base computer 53 are stored in the data server 55 for each case (actual vehicle case, empty vehicle case) for each district. That is, the data server 55 functions as an actual vehicle relationship storage means when storing the actual vehicle relationship and as an empty vehicle relationship storage means when storing the empty vehicle relationship.

When the state of the taxi 11 changes, the position information including the longitude and latitude of the current taxi 11 detected by the GPS 13 and the state change information are automatically transferred to the base 51 by the control unit 23. Emitted by radio. At the base 51, the second base computer 58 receives this signal and fetches the position information and the accompanying state change information. In addition, taxi 1 of the location information
The transmission from 1 and the reception at the base 51 are still A
VM system (Automatic Vehicle)
Monitoring System A system that manages the state of automobiles such as taxis using wireless. )
Since it is already known, the description is omitted here. The second base computer 58 determines the area to which the taxi 11 currently belongs based on the position information, and the taxi 1 that has been identified.
Accepts the district to which 1 currently belongs (position acceptance means). The status change information of each taxi in each area is
The second base computer 58 grasps the number of taxis in each district and the current situation of those taxis (standby for each district).

On the other hand, if the state change information is information indicating that the passenger has exited the vehicle and became empty, the second base computer 5
Reference numeral 8 serves to receive the case classification corresponding to the layout plan to be planned (case classification receiving means). Specifically, here, regarding the two factors of the case classification, that is, the day of the week and the time zone, the current data emitted by the built-in clock of the second base computer 58 is taken as it is, and the rainfall is one of the factors of the case classification. Regarding the presence or absence of the information, the operator of this system inputs the information that corresponds to each district by referring to the weather forecast of each district. Note that the presence or absence of rainfall need not be input by the operator in this way, but the corresponding data may be automatically captured via the Internet through the information capturing means. As described above, the presence / absence of rainfall in each district, the day of the week, and the case classification depending on the time of day are accepted, and the second base computer 58 responds to these factors from the data server 55, which is the actual data storage means, of the rainfall in the district. The demand actual result data of each district is read out according to the presence / absence, day of the week, and time zone (actual data reading means). Further, since the read demand performance data is classified into two types of business forms, that is, a sink and a center vehicle dispatch, the demand base data is classified according to these business forms, and the second base computer 58 divides each business form into each business form. Calculate the expected income amount in the district (expected amount calculation means).
In the calculation of the expected income amount for each business type, the actual vehicle generation speed and the empty vehicle generation speed used when calculating the expected income amount according to the business pattern of the center vehicle distribution (for calculating the waiting time) are the first base computer 53. And is transmitted from the first base computer 53 to the second base computer 58. That is, the second base computer 58 that receives the case classification corresponding to the layout plan to be planned.
The (case classification receiving means) notifies the first base computer 53 of the case classification received. The first base computer 53 that has received the notification reads out the actual vehicle relationship corresponding to the notified case classification from the data server 55 that is the actual vehicle relationship storage means (actual vehicle relationship reading means), and the empty vehicle relationship corresponding to the notified case classification. Is read out from the data server 55, which is the empty vehicle-related storage means (empty vehicle-related reading means). On the other hand, the first base computer 53, which is an information fetching means, reports the weather, temperature (° C.), wind direction, wind speed (m / s), and precipitation amount (m) corresponding to each case and each area.
m), the planned values of the fluctuation factors including humidity (%), etc. are taken in from the website of the private weather information provider, which is an external information source, via the Internet 57, and the planned values of the fluctuation factors are calculated and accepted from them (Reception of fluctuation factors) means). Then, the actual vehicle generated speed is calculated using the received planned value of the variable factor and the read actual vehicle relationship (actual vehicle generated speed calculation means), and the second base computer 5
8 (standby time calculation unit). Similarly, an empty vehicle generation speed is calculated using the received plan value of the variable factor and the read empty vehicle relationship (empty vehicle generation speed calculation means) and transmitted to the second base computer 58 (standby time calculation unit). To be done.

Finally, the second base computer 58 wirelessly notifies the calculated expected income amount for each business type by region to the taxi 11 which is vacant when the passenger gets off. In the notified taxi 11, the crew members of the taxi 11 can know the expected income amount by displaying the expected income amount according to each business type on each display in the vehicle. It should be noted that transmission of the expected income amount to the taxi 11, reception by the taxi 11, etc. are still AV.
Since it is known as the M system, its explanation is omitted here. Further, here, the notified expected income amount for each region according to the business mode is displayed on the display existing in the vehicle, but in addition to this or separately, it may be output by voice.

Next, taxi 11, sales office 31, and base 5
The systems arranged in 1 and 2 will be described in detail. First, the system located in the taxi will be described in detail. FIG. 2 shows a mounting body 61 mounted on the taxi 11.
The external configuration of is shown. The on-board body 61 is integrated with a taxi fare meter, and includes a main body 63, a first image monitor 65a (mainly displaying contents displayed by a conventional taxi fare meter, for example, current fare, etc.) and a second image. An image monitor 6 that constitutes a part of the display unit 17 and includes a monitor 65b (mainly displaying actual result data and expected income amount for each business type transmitted from the center)
5, status change buttons 67a, 67b, 67c, 67d
(The state change button 67a is used when renting, and the state change button 67b is used when the vehicle is empty.
c is pressed when the vehicle is in the state of the vehicle, and the state change button 67d is pressed when the vehicle is in a break. It should be noted that when the fare is paid in the sink business mode, the upper part 6 of the state change button 67a
When 7aa is pressed and the fare is paid in the business mode of center dispatch, by pressing the lower part 67ab of the state change button 67a, the distinction of these business modes is recorded as a part of the actual result data as described later. Hereinafter, pushing the state change button 67a means pushing the upper portion 67aa and pushing the lower portion 67a.
Both including pressing b. ), An IC card recorder 71 that is a data writing unit 19 that writes actual data into the IC card 21, and a display data selection button 69 that selects the type of actual data displayed on the second image monitor 65b.
a, 69b (when the display data selection button 69a is pressed, the most recent data is displayed and the display data selection button 69a is displayed.
When b is pressed, the oldest data is displayed. ) Has. Moreover, the GPS receiver 13 that supplies information such as the current position of the taxi 11 to the mounting body 61 may be provided in the mounting body 61, and a known method (for example, collecting a signal to a speedometer). ), The data receiving unit 15 for detecting the speed of the taxi 11 and supplying it to the mounting main body 61.

The mounting body 61 will be described. First,
The first image monitor 65a and the second image monitor 65b forming the image monitor 65 are each formed of an independent color liquid crystal display. First monitor 6
5a mainly displays the contents displayed by the conventional taxi fare meter, for example, displays the current fare and the state of the vehicle (classification of fare, empty car, pick-up and break, and late-night surcharge, etc.). To do. The second image monitor 65b is mainly for displaying the actual data and the expected income amount of each business type transmitted from the center, and as described above, which of the display data selection buttons 69a and 69b is pressed down. You can select the type of actual data displayed by, and when the center notifies you of the expected income amount for each business type, it will be automatically displayed (the expected income amount is displayed. Therefore, the actual data can be displayed by pressing down either of the display data selection buttons 69a and 69b.).
Then, the state change button 67a (when the fare is driven by the sink, the upper 67aa is pushed, when the fare is paid by the center, the lower 67ab is pushed), 67b, 67c, 67d.
Are pushed down by the crew (driver) when the taxi 11 is rented, emptied, picked up, or taken a break. When any of these state change buttons 67a, 67b, 67c, 67d is pushed down, the main body 63 (control section 23) senses that, and the main body 63 (control section 23) causes the data writing section 19 to operate.
The actual data to be written is provided to the barrel IC card recorder 71, and the writing to the IC card 21 is instructed. The actual result data written in the IC card 21 will be described in detail later. Note that here, the display data selection buttons 69a, 69b and the state change buttons 67a, 67b, 67 are used.
Although mechanical buttons are used as in c and 67d, other pointing devices such as a joystick and a mouse can also be used by using a touch panel.

The IC card recorder 71 is designed so that the IC card 21 (not shown in FIG. 2) can be inserted / removed, and data is written in the inserted IC card 21 according to an instruction from the main body 63 (control unit 23). The data written in the inserted IC card 21 can be read. The main body 63 is a computer having a program for controlling it built therein. FIG. 3 is a schematic block diagram showing the hardware configuration of the main body 63. The main body 63 is a CPU 151a that performs arithmetic processing, a CPU
A RAM 151b serving as a work area of the 151a, a ROM 151c for recording a control program and the like, and an interface 151d for exchanging information with other components of the mounting main body 61 and the like.

FIG. 4 shows the hardware and ROM 15 of FIG.
Main body 63 realized by the program recorded in 1c
The functional block diagram of is shown. Functionally, the main body 63 has a position receiving unit 101, a time receiving unit 103, a speed receiving unit 105,
The state receiving unit 107, the charge calculating unit 109, the write data generating unit 111, the data reading unit 113, the data selecting unit 115, the output unit 117, the placement plan receiving unit 119, and the state transmitting unit 121.

The position receiving unit 101 is the GPS receiver 1
3 receives the position data consisting of latitude and longitude and writes the position data into the data generation unit 111.
To the status transmission unit 121. Time reception unit 103
Accepts input of time data consisting of the year and month and day of the year from the GPS receiver 13, and the charge calculation unit 10
9 and the write data generator 111. Although the GPS receiver generates and supplies the time data here, it goes without saying that the time data may be generated and supplied by a normal clock, or may be generated and supplied by a clock built in the main body 63.

The speed receiving unit 105 is the data receiving unit 1
Input of speed data of the taxi 11 detected by 5 is accepted and output to the charge calculation unit 109. The status reception unit 107 uses the status change buttons 67 (67a, 67b, 6).
7c, 67d), which accepts an input as to which is pressed, and charges it by the charge calculation unit 109, the output unit 117,
The data is output to the write data generator 111 and the status transmitter 121 in parallel. If the state change button 67a is pressed here, its upper part 67aa is pressed or its lower part 67ab is pressed.
It is output so that the write data generation unit 111 can recognize whether or not was pressed.

The fare calculation unit 109 gives a signal indicating that the state change button 67a, which is pushed when the vehicle has become a fare, has been pushed, or the state change button 67c, which has been pushed when the vehicle has been picked up. When received from the reception unit 107,
Calculation of the fare (fee) is started depending on whether the pressed state change button is the state change button 67a (fare) or the state change button 67c (carrying). This fare calculation has a predetermined calculation method for each of the fare and the vehicle, and is obtained from the elapsed time obtained from the time data output from the time reception unit 103 and the speed data output from the speed reception unit 105. This is performed in consideration of the moving distance and the speed data output from the speed accepting unit 105 when necessary (the method of calculating the fare of a taxi is known, and therefore the description thereof is omitted here). The calculated current fare is the write data generation unit 111 and the output unit 11
7 is output in parallel. Then, the state accepting unit 107 sends a signal indicating that the state change button 67b, which is pushed when the vehicle is empty, is pushed, or the state change button 67d, which is pushed when the vehicle is in a break, is pushed.
When 09 is accepted, the fare calculation is stopped at that time. It should be noted that if the state change button 67c that is pressed when the vehicle is greeted is pressed and then the vehicle runs, and if the state change button 67a that is pressed when the vehicle is rented is pressed, the state change button 67c is pressed. State change button 67 after
State change button 67 in addition to the pick-up charge until a is pressed
The rent fee after "a" is pressed is added. It should be noted that, here, only the fare and the car are considered as the states for obtaining the fare, but other states, for example, waiting or the like may be considered.

The status transmission section 121 uses the status change button 67.
When a signal indicating that any one of (67a, 67b, 67c, 67d) is pressed is received from the state receiving unit 107, the state change button 67 (67a, 67b, 67c, 6).
State receiving unit 1 of which one of 7d) has been pressed
The signal from 07 and the signal from the position reception unit 101, which is composed of position data composed of latitude and longitude received from the GPS receiver 13, are wirelessly transmitted (in the present embodiment, a commercial wireless is used) to the base. 51 to the second base computer 58. The base 51 (second base computer 58) receives this signal,
The (second base computer 58) can understand at which position each taxi 11 has changed and what state.

The write data generator 111 is the position data from the position receiver 101 (specifically, longitude and latitude).
And time data from the time reception unit 103 (specifically,
Year and month), the fare from the fare calculation unit 109, and the push down detection signal of the state change button 67 from the state reception unit 107 (the upper portion 67aa of the state change button 67a when the state change button 67a is pressed). Also included is a signal that allows identification of whether or not was pressed or its lower portion 67ab was pressed.) And write data is generated. Then, the status change button 67 from the status reception unit 107
The write data generated each time the push-down detection signal is received is transmitted to the IC card recorder 71. The IC card recorder 71 that has received the write data automatically writes the received write data in the IC card 21. Here, the write data generated by the write data generation unit 111 includes a push down detection signal of the state change button 67 from the state reception unit 107 to the write data generation unit 11.
1 is the date and time when received, and the position (longitude / latitude) when the write data generation unit 111 receives the depression detection signal of the state change button 67 from the state reception unit 107 and the depression detection signal of the state change button 67. Status reception unit 10
7, the fare (amount) when the writing data generation unit 111 receives the data, the type of the state change button 67 that has been pushed down (if the state change button 67a is pushed down, either the upper portion 67aa or the lower portion 67ab thereof) It also distinguishes whether or not was pushed down). It should be noted that here, a fixed IC card is used for each crew member (driver), and information (for example, a crew member's identification number, etc.) is used so that each IC card can be recognized from the beginning on each IC card. ) Has been written. Then, at the same time as the start of work (that is, leaving the vehicle), the flight attendant ICs the IC card 21.
The IC card recorder 71 is inserted into the card recorder 71, so that the inserted time is written in the inserted IC card as the departure date and time, and at the same time as the end of work (that is, the entry), the crew member presses the pull-out button (not shown) so that the IC card recorder 71 The time when the pull-out button is pressed is written in as the storage date and time, and the IC card is ejected from the IC card recorder 71.

The data reading unit 113 receives the command from the data selecting unit 115 and reads the data written in the IC card in accordance with the command, thereby reading the IC card recorder 7.
1, and outputs the read data to the data selection unit 115. The data selection unit 115 receives a signal indicating that the display data selection buttons 69a and 69b have been pressed. When the display data selection button 69a is pushed down, the data reading unit 113 is instructed to read the data written in the IC card from the most recent data to the oldest data in order, and the display data selection button 69b is pushed down. In the case where the data is written in the IC card, the data reading unit 113 reads the old data in order from the old data to the new data.
To order. Then, the data selection unit 115 outputs the data received from the data reading unit 113 to the output unit 117.

The placement plan receiving unit 119 is calculated by the base 51 (second base computer 58) when the passenger gets off the vehicle and the state changes to an empty state. 11 receives the signal about the expected income amount according to each business type, and outputs the received data about the expected income amount according to each business type to the output unit 117.

The output unit 117 synthesizes the charge up to the present calculated by the charge calculation unit 109 and the state of the taxi 11 received from the state reception unit 107 (fare, empty car, pick-up vehicle, break) into an image. Output to the first image monitor 65a. Then, the output unit 117 combines the expected income amount for each business type received from the placement plan receiving unit 119 with an image and outputs the image to the second image monitor 65b. This allows the crew members of the taxi 11 to know the expected amount of income, and how to make decisions after that (whether in the sink or in the center dispatch, in which district) Can be obtained. When the output unit 117 receives the data from the data selection unit 115, the output unit 117 combines the data from the data selection unit 115 with an image and outputs the image to the second image monitor 65b. Then, display data selection buttons 69a and 69b
When a predetermined time elapses from the time when is pressed down,
The data output from the data selection unit 115 to the output unit 117 is stopped.

The main body 63 can also be realized by incorporating a program for achieving the above functions or the following operations in a general computer, and this program can be read by the computer.
It can be recorded on a recording medium such as a ROM. Further, the program can also be read from a storage medium provided remotely via a communication network such as the Internet.

Next, the I stored the data in this way
The contents of the C card 21 will be described. Table 1 shows a table schematically showing the recorded contents of the IC card 21.

[0054] (Table 1) Example of recorded contents of IC card 1. Crew member code NO. Three 2. Departure date and time 7:48 am, Tuesday, April 20, 1999 3. Arrival date and time 8:21 pm, Tuesday, April 20, 1999 4. Performance             Status change Date and time Change position Fares    Data 1 Rent (sink) April 20, 133.4582E 0                             08:11 35.8643N    Data 2 Vacant April 20 133.4961E 620                             8:17 35.9006N    Data 3 Pick-up April 20 133.5003E 0                             8:55 35.8908N    Data 4 Fares (Center dispatch) April 20 133.5059E 500                             8:59 35.9084N    Data 5 Vacant April 20 133.4799E 2100                             9:12 35.9503N    Data 6 Break April 20 133.3988E 0                             9:34 36.0291N    Data 7 Vacant April 20 133.3988E 0                             9:44 36.0291N    Data 8 Rent (sink) April 20 133.3329E 0                             10:01 36.0791N    Data 9 Empty April 20 133.3653E 1650                             10:09 36.1020N                                   ・                                   ・

Table 1 shows crew code No. 1 of 3 crew members
A part (first part) of the actual result data on April 20, 1999 (Tuesday) is shown. The actual data will be described with reference to Table 1. The data written in the IC card is composed of data representing a crew member (crew member code), a departure date and time, a receipt date and time, and an actual result showing a change over time. First, regarding the data representing the crew members, each crew member code (here, 3) is made to match the code of each IC card. In other words, the same crew member always uses the same IC card. Regarding the departure date and the entry date and time, as described above, the time when the crew inserts the IC card 21 into the IC card recorder 71 at the start of work and the IC card 21 when the crew finish at the end of work.
And the time when a pull-out button (not shown) is pushed to pull out the card from the IC card recorder 71. The actual results showing changes over time can be obtained by the crew members using the state change buttons 67 (67aa, 67ab, 67b, 67).
(c, 67d) is written cumulatively in the order in which the button is pressed each time the button is pressed.
State change according to the type of, the change date and time, the change position indicated by a pair of longitude and latitude, and the fare when the state change button 67 is pressed.

The specific contents shown in Table 1 will be described below. Crew member code NO. The crew of No. 3 will leave and start working at 7:48 am (Departure date and time) on April 20, 1999 (Tuesday) at 8:21 pm (Departure date and time) on the same day.
Has finished working at the warehouse. (Data 1) After starting work, the company was operating in a sinking business mode, but at 8:11 on the same day, passengers got on board and were in a fare state. At this time, it is recorded that the crew member presses the upper portion 67aa of the state change button 67a at the same time as getting on the vehicle, and the renting state is set in the sink business mode. At this time, the date and time and the position are also recorded. At this time, the fare is 0 because the fare has just started. (Data 2) Passengers boarded in Data 1 are delivered to their destination and are vacant. After the arrival at the destination, it is recorded that the crew member pushed the state change button 67b to be in an empty state. At this time, the date and time (8:17) and the position are also recorded. In addition, 620 yen is recorded as the fare from data 1 to data 2. (Data 3) After the data 2, in the area where the data 2 occurs (that is, the area to which 133.4961E and 35.9006N belong), switch to the center vehicle dispatch business mode, and wait for the instruction of the center vehicle in the area. became. Then, at 8:55, the center instructed by radio to pick up passengers. Therefore, at the same time, it is recorded that the crew member has pressed the state change button 67c to enter the state of getting on and off, and the date and time and the position are also recorded at the same time. (Data 4) 8:59 at the data 3
A minute arrived at the passenger. At the same time when the passenger is put on the seat, the crew member can detect the lower portion 67ab of the state change button 67a.
It is recorded that the car is in a rented state in the business mode of dispatching the center, and the date and time and the position are also recorded at the same time. At this time, since data 3 to data 4 are paid vehicles, 500 yen is recorded as the fare for the vehicle. Then, the fare generated from the fare later from data 4 will be added to this fare (500 yen) which is the vehicle fare. (Data 5) The passenger who got on in Data 4 was carried to the destination, and the passenger got off at 9:12. After the arrival at the destination, it is recorded that the crew member has pushed the state change button 67b to be in an empty state, and the date and time (9:12) and the position are also recorded at the same time. In addition, 2100 yen is recorded as the fare from data 3 to data 5. Therefore, it can be seen that the fare from the data 3 to the data 4 was 500 yen, and the fare added in the rented state from the data 4 to the data 5 was 1600 yen (2100 yen-500 yen). (Data 6) After Data 5, we decided to take a break because we were operating in the sink business mode but passengers could not be found. It is recorded that the crew member has pressed the state change button 67d to enter the rest state, and at this time, the date and time (9:34) and the position are also recorded. Of course the fare is zero. (Data 7) Data 6 entered a break, but returns to business again. It is recorded that the crew member has pressed the state change button 67b to be in an empty state (that is, a business state), and at this time, the date and time (9:44) and the position are also recorded. Since I was taking a break from data 6 to data 7,
The positions recorded in both data are the same. The rest state between data 6 and data 7 is 10 minutes (9: 4
4 minutes-9: 34). (Data 8) Data 7 turned into the business state again, and when it was operating in the sink business mode, passengers were found. At the same time when the passenger is put on, the crew member changes the state button 67a.
It is recorded that the upper part 67aa is pressed and the renting state is set in the sink business form, and the date and time (10:01) and the position are also recorded at the same time. (Data 9) Passengers boarded in Data 8 are delivered to the destination and are emptied. After the arrival at the destination, it is recorded that the crew member has pushed the state change button 67b to be in an empty state, and at this time, the date and time (10:09) and the position are also recorded. Note that the fare from data 8 to data 9 is 1650 yen.

Subsequently, the mounting main body 6 having the above-mentioned structure
The first operation will be described focusing on the operation of the main body 63. FIG. 5 shows a flowchart showing the operation of the main body 63. First, as the taxi 11 moves, the GPS receiver 13
Receives position data consisting of latitude and longitude one after another and time data. In the main body 63, the GPS receiver 13
The position receiving unit 101 receives new position data from the GPS receiver 13 and the time receiving unit 103 receives new time data from the GPS receiver 13 (s101). Position reception section 1
The position data received by 01 and the time data received by the time receiving unit 103 are always the write data generating unit 1
11 is supplied. The position data received by the position reception unit 101 is constantly supplied to the state transmission unit 121,
The time data received by the time reception unit 103 is constantly supplied to the charge calculation unit 109. And the data receiving unit 15
Detects the vehicle speed of the taxi 11 continuously by a known method. In the main body 63, the speed receiving unit 105 receives the vehicle speed data from the data receiving unit 15 (s102). Then, the vehicle speed data received by the speed reception unit 105 is constantly supplied to the charge calculation unit 109.

Here, the state accepting portion 107 of the main body 63 judges whether or not any of the state change buttons 67 has been pressed (s103). When the state change button 67 has been pressed (YES), the state change button 67 (67aa). , 67ab, 67b, 67c, 6
The status reception unit 107 notifies the charge calculation unit 109, the output unit 117, the write data generation unit 111, and the status transmission unit 121 so that which of the 7d) has been pressed can be known. Upon receiving this notification, the state transmitting unit 121 receives the data indicating which state change button 67 from the state receiving unit 107 is pressed and the position data from the position receiving unit 101 when the data is received from the state receiving unit 107. And are combined and wirelessly transmitted to the base 51 (second base computer 58) (s104). In addition, here, the wireless transmission is made to the base 51 (second base computer 58) only when any one of the state change buttons 67 is pressed, but the present invention is not limited to this, and for example, the state change button In addition to the case where 67 is pressed, the current state and position data may be periodically transmitted at regular intervals. And
The write data generation unit 111, which has received the notification from the state reception unit 107, receives data indicating which state change button 67 from the state reception unit 107 has been pressed and the position reception unit 1.
01 from position data, time data from time reception unit 103, and charge data from charge calculation unit 109 (described later)
And write data is created from the above, and the created write data is transmitted to the IC card recorder 71 (s10).
5). On the other hand, in s103, when the state accepting unit 107 determines that none of the state change buttons 67 has been pressed (NO), the process proceeds to s110 described later.

Further, the charge calculation unit 109, which has received the notification from the state reception unit 107, determines that the state change button 67a determined to be pressed in s103 is the state change button 67a (state change button 67aa or state change button 67).
a)) or the state change button 67c (that is, whether the state changes to the fare-running state or the greeting state) (s106), and the state change button 67 is determined.
If it is a or the state change button 67c (that is, if the state is changed to the fare or the state of receiving) (YES), the fare calculation unit 109 starts calculation of the fare and outputs fare data indicating the current fare. Output to the section 117 is started (s1
07). The output of the fare data to the output unit 117 is continued until the fare calculation is completed in s109 described later, and the output unit 117 which has received the fare data displays the image data indicating the current fare on the first image monitor 65a. The current fare amount is displayed on the first image monitor 65a (the output unit 117 receives the data indicating the current state supplied from the state receiving unit 107, and the state is displayed on the first image monitor 65a). By supplying the image data for displaying, whether the vehicle is rented, vacated, picked up, or rested is displayed on the first image monitor 65a.). On the other hand, in s106, the state change button 6 determined to be pressed in s103
When it is determined that 7 is neither the state change button 67a nor the state change button 67c (that is, when the state change is not to the renting or the receiving state) (NO), s1 to be described later.
Go to 08.

Then, the state change button 67 judged to be pressed in s103 is the state change button 67b (change to an empty state) or the state change button 67d (change to a rest state), and the state change button 67 is At s103 when it is determined that the button has been pressed, the fee calculation unit 109 determines whether or not the vehicle is in the fare-running state or the state of receiving the vehicle (s108), and if so (YES), the fee calculation unit 109 ends the calculation of the fee ( s109). The output of the fare data from the charge calculation unit 109 to the output unit 117 is completed by performing a predetermined payment procedure. If the determination in s108 is no, go to s110, which will be described later.

Then, the output section 117 has the placement plan receiving section 11
When it is judged that 9 has received the signal relating to the expected amount of income for each business district calculated by the base 51 (second base computer 58) and transmitted to the taxi 11 (s110), it is determined that the signal has been received. In (YES), the output unit 11 that has received the data regarding the expected income amount.
7 supplies the image data displaying the expected income amount to the second image monitor 65b, and the expected income amount for each business type is displayed on the second image monitor 65b (s111).
In addition, the placement plan receiving unit 119 is configured to store after receiving the signal regarding the expected income amount for each business type for each region, which is transmitted from the base 51 (second base computer 58) to the taxi 11. Then, the output unit 117 determines whether or not the placement plan receiving unit 119 receives the signal regarding the expected income amount, and the output unit 117 determines only when the placement plan receiving unit 119 receives the signal regarding the expected income amount.
Judgment is based on the presence or absence of the signal sent to. And output section 1
If 17 determines that the placement plan receiving unit 119 has not received the signal regarding the expected income amount for each business type, the process proceeds to s113 described below.

Next, the data selection unit 115 determines whether any of the display data selection buttons 69 (69a, 69b) has been pressed (s112). Displayed data selection button 6
The data reading unit 1 reads the data corresponding to the nine types (69a, 69b) from the IC card recorder 71.
13, the data reading unit 113 accesses the IC card recorder 71 according to the command to read predetermined data, and the predetermined data is the data reading unit 11
3 is output to the output unit 117 via the data selection unit 115 (s113). After that, the output unit 117 receives the predetermined data and outputs it as image data to the second image monitor 65b (s114).
The data written in the card 21 can be displayed and viewed on the second image monitor 65b. Any of the display data selection buttons 69 (69a, 6
9b) If it is determined that the button has not been pressed (NO), the process proceeds to s115 described below. Then, it is judged whether the work is finished (s115), and the work is finished (end), s
Return to 101. In addition, on the second image monitor 65b,
Even if the output unit 117 outputs the image data so that the expected income amount for each business type and the data written in the IC card 21 are displayed at the same time, only one of them is displayed. May be.
In the latter case, when the placement plan receiving unit 119 receives the expected income amount, the expected income amount is displayed, and then one of the display data selection buttons 69 (69a, 69b) is pressed or The expected income amount may be displayed for a predetermined time after the expected income amount is displayed.

Second, the system installed in the sales office 31 will be described in detail. The system arranged in the business office 31 is composed of a business office computer 35 and a card reading unit 33 connected to the business office computer 35. The business office computer 35 is a general computer having a program for controlling it built therein, and the card reading unit 33 is a general IC that can read the data written in the IC card 21 and provide the business office computer 35 with the data. I am using a card reader. Taxi 11 as described above
When the driver finishes the business and finishes the work, the crew member presses the IC card 21 not shown in the drawing to remove the IC card 21 from the IC card recorder 71 of the taxi 11
Remove the card 21 and bring the IC card 21 to the system located in the sales office 31. Then, the crew member or an office worker of the sales office inserts the IC card 21 into the card reading unit 33, and starts reading the performance data written in the IC card 21. IC card 2
The data read by the card reading unit 33 from 1 is sequentially transmitted from the card reading unit 33 to the business office computer 35 via the cable 37. Since such an IC card 21 is used for each crew member, a plurality of crew members are used if there is more than one crew member, and thus the read data is stored for each crew member (crew member code) in the office computer 35. It is organized and stored. Then, within a predetermined period (for example, in this embodiment, 1
All performance data related to sales on the day (if IC card 21 is one, it is all of the performance data written on that one, and if there are multiple IC cards 21, the performance is written on the multiple IC cards 21. All the data) is the office computer 35
After being organized and stored in the office computer 35, the first office computer 53 and the office computer 3 are transferred from the office computer 35.
The total performance data is transmitted to the first base computer 53 via the cable 41 that connects the data 5 to the first base computer 53. The content of the total performance data is a set of a plurality of sets (when there are a plurality of crew members) shown in Table 1 for each crew member code. Note that the sales offices can be distinguished by the crew codes (for example, the crew members belonging to the sales office have the crew codes 1 to 6, and the crews belonging to the sales office have the crew codes 11 to 18). etc). Although not shown here, such a sales office 31
Exists, in other words, one base 51 collects data from a plurality of business offices 31. The system installed in the sales office 31 reads out the actual result data written in the IC card 21 here, arranges the read actual result data for each crew member (crew member code), and stores the organized result. It has a role of transmitting data to the first base computer 53, but it is not always essential.
If the system arranged in the base 51 is made to play the above-mentioned role, this system can be constructed without the system arranged in the business office 31.

Thirdly, the system arranged at the base 51 will be described in detail. The system arranged at the base 51 includes a first base computer 53 and a second base computer 58.
And a data server 55 that serves as a storage device for the first base computer 53 and the second base computer 58 (the first base computer 53, the second base computer 58, and the data server 55 are mutually free). Is connected by a cable 59 so that data can be transmitted and received. The first base computer 53 and the second base computer 58 are built-in programs for controlling them in a general computer (a CRT display and a keyboard are connected), and the data server 55 is the first base computer. It has a mass storage device capable of storing data from the computer 53 and the second base computer 58 and outputting the stored data to the first base computer 53 and the second base computer 58. Then, the first base computer 53 can freely access the Internet communication network 57 to obtain necessary data. FIG. 6 is a schematic block diagram showing the hardware configuration of the first base computer 53. The first base computer 53 is a CP that performs arithmetic processing.
U251a, RAM that becomes the work area of CPU251a, etc.
251b, ROM 251 for recording control programs and the like
c, a CRT display 253, a keyboard 255, and an interface 251d for exchanging information with other components. FIG. 7 is a schematic block diagram showing the hardware configuration of the second base computer 58. The second base computer 58 is a CPU that performs arithmetic processing.
351a, RAM3 which becomes the work area and the like of CPU351a
51b, ROM 351c for recording control programs,
It has a CRT display 353, a keyboard 355, and an interface 351d for exchanging information with other components.

FIG. 8 shows the hardware of FIG. 6 and the ROM 25.
The functional block diagram of the 1st base computer 53 implement | achieved by the program recorded on 1c is shown. The first base computer 53 is functionally equivalent to the demand record data reception unit 2
01, actual vehicle relation determining unit 203 (actual vehicle relation determining means), actual vehicle relation reading unit 205 (actual vehicle relation reading means), actual vehicle generation speed calculation unit 207 (actual vehicle generation speed calculation unit), information acquisition unit 209, fluctuation factor acceptance unit 211 (Variation factor accepting means), rainfall information reading section 213, empty vehicle relationship determining section 215 (empty vehicle relationship determining means), empty vehicle relationship reading section 2
17 (vacant vehicle-related reading means), empty vehicle generation speed calculation unit 2
19 (empty vehicle generation speed calculation means).

The demand result data receiving unit 201 receives the result data from the business office computer 35 via the cable 41, and calculates the longitude / latitude data indicating the position where each state change is included in the received result data. The district (changing district) to which the position that changed each state belongs is determined. Figure 9
[Fig. 3] is a schematic diagram showing the relationship between business areas and districts. Figure 9
The "district" of the case classification factors will be explained with reference to. The figure shown in FIG. 9 shows a business area 190 of a taxi company. The business area 190 is distinguished from the non-business area 194 by a regional boundary line 192. The business district 190 is divided into district A, district B, district C, district D, district E, district F, and district G by the district boundary line 196.
It is divided into 7 districts. Here this border line 1
The positions of 92 and the district boundary line 196 are stored in the first base computer 53 by the longitude and the latitude. Therefore, if the position is specified by the longitude and the latitude, it can be surely determined to which of the above-mentioned seven districts it belongs. Therefore, the state change position data included in the actual data (change position in Table 1)
Can identify in which district the state change occurred. For example, the riding position of data 1 in Table 1 (133.
4582E, 35.8643N) is the position indicated by a cross in FIG. 9, it means that the state change of data 1 (boarding here) has occurred in the area F. Cases are classified according to such predetermined areas, and the respective state changes are classified by area.

In this way, the actual result data obtained by the actual demand data receiving unit 201 determining in which district each state change has occurred can be obtained from the actual demand data receiving unit 201 by the data server 55 (actual data storage means and actual vehicle generation speed). (Functions as a storage unit and an empty vehicle generation speed storage unit). The data server 55 as the actual result data storage unit, the actual vehicle generation speed storage unit, and the empty vehicle generation speed storage unit stores the actual result data received from the demand actual result data reception unit 201. On the other hand, as will be described later, it is a variable factor result storage means (functions as both an actual vehicle variation factor result storage means and an empty vehicle variation factor result storage means) fetched by the information fetching unit 209 via the Internet 57 or a keyboard. From the variation factor performance data stored in the data server 55, the rainfall information reading unit 213 reads the presence / absence of rainfall when the above-mentioned state changes of the performance data stored in the data server 55 occur. Then, the rainfall information reading unit 213 adds the presence / absence of rainfall when each state change occurs to each state change of the performance data stored in the data server 55. Here, the actual data is the data server 5 first.
5, the presence / absence of rainfall is added to the actual result data, but the present invention is not limited to this. For example, the actual data and the presence / absence of precipitation at that time are associated with each other. It may be stored together in the data server 55. In this way, the actual data is added with the presence or absence of rainfall to become the actual demand data (stored together with all the case division factors, the actual demand data). Here, Table 2 shows an example of the demand record data stored in the data server 55 with the information about the presence or absence of rainfall added thereto. The changed areas in Table 2 are given as an example, and the changed areas and the areas shown on the map in FIG. 9 are not associated with each other here. As for the presence / absence of precipitation, the precipitation data (m
If m) is 1 mm or more per hour, it is judged that there is precipitation, and if it is less than that, it is judged that there is no precipitation. If there is precipitation, it is represented as 1, and if it does not, it is represented as 0. From the precipitation data on the day when each state change occurred,
District and time zone in which each state change occurred (for example, for April 20, 1999 (Tuesday) in Table 2, crew code N
O. 3 、 Data 1 is district F and time zone at 8 o'clock (described later)
become. ) Corresponding data (in the previous example, 1999
On April 20th (Tuesday) of the year, the precipitation amount data corresponding to the district F and the time zone of 8:00) are extracted and judged.

[0068] (Table 2) Content example of demand performance data stored in the data server    (Tuesday, April 20, 1999)    1. Crew member code NO. Three     Departure date and time 7:48 am, April 20, 1999     Arrival date and time 8:21 pm April 20, 1999     Performance           State change Date and time Change area Fare Precipitation    Data 1 Fare (sink) April 20 District F 0 1                           8:11    Data 2 Empty April 20 District B 6200                           8:17    Data 3 Pick-up April 20 District D 0 0                           8:55    Data 4 Fares (Center dispatch) April 20 District A 500 0                           8:59    Data 5 Empty car April 20 District C 2100 1                           9:12    Data 6 Break April 20 District G 0 1                           9:34    Data 7 Empty April 20 District G 0 0                           9:44    Data 8 Rent (sink) April 20 District E 0 0                           10:01    Data 9 Empty vehicle April 20 District B 1650 0                           10:09                                 ・                                 ・ 2. Crew member code NO. Four     Departure date and time 7:25 am, Tuesday, April 20, 1999     Stocking date and time 8:07 pm, Tuesday, April 20, 1999     Performance           Status change Date and time Change location Fare Precipitation    Data 1 Rent (sink) April 20 District C 0 1                           7:33                                 ・                                 ・ 3. Crew member code NO. 5     Departure date and time 8:28 am, Tuesday, April 20, 1999     Date and time of storage 9:29 pm, Tuesday, April 20, 1999     Performance           Status change Date and time Change location Fare Precipitation    Data 1 Rent (sink) April 20 District G 0 0                           9:01                                 ・                                 ・ (For April 21, 1999)    1. Crew member code NO. 1     Departure date and time 7:42 am Wednesday, April 21, 1999     Date and time of storage 8:20 pm, Wednesday, April 21, 1999     Performance           Status change Date and time Change location Fare Precipitation    Data 1 Rent (sink) April 21 District B 0 1                           7:49                                 ・                                 ・ 2. Crew member code NO. Two                      ・                      ・                      ・ (For Thursday, April 22, 1999)                  ・                  ・

Then, the information fetching unit 209 causes the weather, temperature (° C.), wind direction, wind speed (m /
s), the amount of precipitation (mm), and the humidity (%) indicating actual data are automatically collected from the homepage of a private weather information provider, which is an external information source of this system, via the Internet 57. The weather, temperature (℃), wind direction, wind speed (m / s), precipitation (mm), and humidity (%) are
As mentioned above, it includes information that identifies which district each data relates to, and the date and time when the data was collected. Then, using the keyboard connected to the first base computer 53, these collected data can be corrected or deleted, and further data can be added to the collected data. further,
These weather information detection devices (for example, thermometer, hygrometer, precipitation meter, etc.) are installed in the business office 31, and the weather information data detected by these detection devices is taken into the business office computer 35, and the business office computer 35 is installed. The data may be transmitted to the first base computer 53 by using the cable 41. In such a case, there are 31 sales offices in each district.
If so, it is possible to collect the weather information data of each district using the information network within the company. Furthermore, the event index, which is a sudden influence factor used as a variation factor in the present embodiment, is input to the information capturing unit 209 via a keyboard. The event index is the number of participants in events that affect vehicle demand in the districts (district A, district B, district C, district D, district E, district F, district G) and the number of taxi users It is multiplied by a ratio (this ratio is hereinafter referred to as “impact degree”). The event index is input to the information capturing unit 209 so that the district in which the event has influenced the vehicle demand, the date when the event is held, and the time zone in which the event has influenced the vehicle demand are clarified. To be done. In addition, when the holding time of the event spans multiple time zones, if the event index is calculated in consideration of how the event participants use the taxi during the holding time (that is, the usage pattern) Well, for example, when taxi users occur on average during the holding time (for example, blood donation), they are allocated on average over the plurality of time zones, or taxi use is concentrated at the beginning and end of the holding time. When a person occurs (for example, a concert), it may be dealt with by allocating to the time zone to which the start time and the end time belong. Even if a human examines these allocations and inputs only the result, the utilization pattern is input to the first base computer 53 and the first base computer 5 is input.
3 may be allocated according to a predetermined rule. Then, here, the event index is input to the first base computer 53 by operating the keyboard connected to the first base computer 53, but it is not always necessary to directly input the event index, and the event index is input to the event. The number of participants and the degree of influence may be input to cause the first base computer 53 to calculate the event index.
The variable factor performance data and the like (including the event index) thus collected are such that the information capturing unit 209 makes it possible to clarify the date and time zone in which each data was collected for which district. From the variable factor result storage means (actual vehicle variation factor result storage means, empty vehicle variation factor result storage means) to the data server 55, and the date and time when each data was collected by the data server 55 for which district and It is remembered so that the time zone is clear. Table 3 shows an example of the variable factor performance data and the like stored in the data server 55. The precipitation amount in Table 3 shows the total precipitation amount in each time period. In addition, in the variable factor performance data (including the event index), the business form (flowing) is selected from the factors of the case classification (here, all the factors of the case classification, the actual vehicle classification, and the empty vehicle classification are the same). , Center dispatch) is not relevant, so the day is divided into 7 of Sunday, Monday, Tuesday, Wednesday, Thursday, Friday, and Saturday, and the time zone is divided into 24 from 00:00 to 23:00, so a total of 168 Street (7 × 24 = 16
It is input in association with the case classification of 8). In other words,
When associating the demand actual data and the variable factor actual data (including the event index) which are also classified by the business form, the business form is not associated. If there is no data for each case classification (for example, if the measurement is not performed for each case classification or cannot be measured), use adjacent or similar data,
Alternatively, an estimated value from adjacent or similar data may be used.

[0070] (Table 3) Example of contents of variable factor performance data etc. stored in the data server    (Date of data collection: Tuesday, April 20, 1999)    Region Time Zone Weather Temperature Wind Direction Wind Speed Precipitation Humidity Event Index   A 0:00 Sunny 17 South 1.0 0 60 50   A 1:00 Sunny 16 South 1.5 0 65 30   A 2 o'clock Sunny 14 South 2.5 0 60 10   A 3 o'clock Cloudy 13 Southeast 2.0 3 75 0   ・   ・   A 23 o'clock rain 19 south 3.5 10 8 00      B 0:00 Cloudy 18 Southwest 1.5 0 650   B 1:00 Cloudy 17 Southwest 1.00 650   ・   ・   B 23:00 rain 20 west 4.5 0 85 20      C   ・   ・   G 23:00 Cloudy 19 Southwest 2.0 0 75 0    (Data collection date: Wednesday, April 21, 1999)    Region Time Zone Weather Temperature Wind Direction Wind Speed Precipitation Humidity Event Index   A 0:00 AM Rain 19 South 4.0 15 850   ・   ・   G 23:00 Cloudy 19 Southwest 2.0 0 75 0    (Date of data collection: April 22, 1999 (Thursday))   ・   ・

Then, when the demand result data relating to a predetermined amount of riding is accumulated in the data server 55 (actual vehicle generation speed storage means), the actual vehicle relation determining unit 203 determines the date from the demand result data stored in the data server 55. In addition to counting the number of rides that belong to each area (classified as the area to which the boarding position belongs) for each actual vehicle case,
The data server 55 stores the variable factor performance data corresponding to the date, district, and case classification corresponding to the counted number of boardings.
It is read from (actual vehicle variation factor result storage means). As a result, the actual vehicle relation determining unit 203 creates a set of the counted number of times of riding and the read variable factor performance data for each actual vehicle for each year, month, and day. As described above, the number of rides is counted by business type, but the variable factor performance data and the like do not consider the business type. Then, the actual vehicle relationship determination unit 203 obtains the actual vehicle relationship, which is the relationship between the variation factor and the actual vehicle generation speed, from the number of times of riding (actual value of the actual vehicle generation speed) and the variation factor actual data for each case of the actual vehicle.

Here, the same factors are used for the case classification, the actual vehicle case classification, and the empty vehicle case classification.
It was carried out by four factors: two types of business, sink and center dispatch, and the presence or absence of rainfall. Of these four factors, the day of the week and the time of day are determined by the occurrence of boarding. One of the cases is “day of the week”
It was the day of the week, Sunday, Monday, Tuesday, Wednesday, Thursday, Friday, or Saturday. Specifically, the day of the week is indexed from the day (boarding date, if necessary, year is considered) in the change date and time included in the demand record data, and the factor of the "day of week" is determined by the indexed day of the week. Classify by deciding which belongs to. Although this is not the case in the present embodiment, the cases may be classified according to the relationship with holidays. Here, "relationship with holiday" means that the fact that occurred (for example, boarding) is the day before the holiday (Sunday, public holiday, Saturday in some cases, etc.), the day of the holiday, the day after the holiday (the day after the holiday), and other days. It means which day of the day (the day before the holiday, the day of the holiday, or the day after the holiday does not apply). Then, the cases may be classified according to both the “day of the week” and the “relationship with respect to the holiday”. Further, among holidays, regular holidays (usually Sunday, including Saturday in some cases) and holidays may be treated separately.

The "time zone" of the case classification factors is in which time zone the boarding occurred. In the present embodiment, the time zone from 30 minutes before every hour from 0:00 to 23:00 and just 1 hour is referred to as the hour (that is, n: 30 belongs to (n + 1) hours, and is less than n: 30). But before it belongs at n o'clock). As described above, in the present embodiment, all the time zones have the same length as one hour, but the lengths of the respective time zones may be different. The factors of this time zone are classified by determining which time zone they belong to from the time of the change date and time included in the demand record data.

The "two types of business forms, that is, sink and center dispatch", among the classification factors, is a classification according to which business form the passenger got in, and there is no particular destination and the state is empty. If you find a passenger and get on board while running in
From the center that manages taxi business (usually set up a reception phone there and contact the taxi when you receive a dispatch request), you will be instructed to pick up passengers by radio or telephone etc. If it is allowed, it will be classified as a “center dispatch” business type. It should be noted that this is distinguished by whether the crew member pressed the upper part 67aa or the lower part 67ab of the status change buttons 67a when the fare was paid, and the fare in the status change included in the demand performance data is Since (sink) or (center dispatch) is also written, use this to classify.

The "presence / absence of precipitation" among the case classification factors is judged by the precipitation amount (mm) included in the read variable factor performance data, etc., and the precipitation amount (mm) is 1 hour (ie, In the present embodiment, it is determined that there is precipitation (represented as "1") if it is 1 mm or more per hour in each time zone, and if it is less than that, it is determined that there is no precipitation (represented as "0"). . As described above, in the present embodiment, cases are classified according to the day of the week, the time of day, two types of business modes of sink and center dispatch, and the four factors of whether or not there is precipitation (case classification, actual vehicle classification, empty vehicle classification). Therefore, in the case of the present embodiment, the day is classified into 7 of Sunday, Monday, Tuesday, Wednesday, Thursday, Friday, and Saturday, and the time zone is 24 hours from 0:00 to 23:00.
There are 672 cases (7 × 24 × 2 × 2 = 672) in total, as the sales form is divided into 2 types, the sink and the center car dispatch, and the presence or absence of precipitation. Will be. And in the district, district A,
District B, District C, District D, District E, District F, District G 7
Since it is divided into 4 areas, including the district, there are 4704 streets (6
72 × 7 = 4704).

In this embodiment, the factors of variation are
The discomfort index and the event index, which is a factor that influences the accident, were used. The variable factors are not limited to these, and as mentioned above, the cold weather index may be changed to the discomfort index and the severe cold index may be used, and economic data on economic conditions that affect taxi demand will be used. It goes without saying that it is okay. Although the presence / absence of precipitation is used as a case classification factor here, the presence / absence of precipitation may be included in the variation factors and excluded from the case classification factors. This discomfort index is for data server 5
The temperature t (° C.) and the humidity U (relative humidity, unit%) for each time zone for each district, which are included in the variable factor actual result data read out from 5 (actual vehicle and empty vehicle variable factor actual result storage means), are used. Then, the actual vehicle relation determining unit 203 calculates the expression: 0.81t +
Calculate by 0.01U (0.99t-14.3) + 46.3 for each district and each time zone. In the severe cold season, the severe cold index may be used instead of the discomfort index, and the severe cold index is determined by the temperature t (° C) and the wind speed v (m / sec).
Calculated using the formula: (1 + 0.272v) (1-0.04t). In addition, the event index is the data server 55
The numerical values (see Table 3) included in the variable factor actual data read out from (actual vehicle and empty vehicle variable factor actual result storage means) were used as they were. In this way, the actual vehicle relationship determination unit 20
Table 4 shows an example of the set of the number of times of boarding, the discomfort index, and the event index, which are calculated by each of the cases, for each year, month, and day, and for each case, which are created by No. 3. It should be noted that the numerical values listed in Table 4 are examples, and are not consistent with the numerical values in the above table.

[0077]   (Table 4) An example of a set of the number of boarding times and the discomfort index and the event index    (Date of data collection: Tuesday, April 20, 1999)    Area Day of the week Time of day Business form Rainfall Yes No Number of boarding Discomfort index Event index   A fire 0 sink 0 13 60 50   A fire 0 center dispatch 0 9 60 50   A fire 1 sink 0 8 55 30   A fire 1 center dispatch 0 7 55 30   A fire 2 sink 0 5 45 10   A fire 2 center dispatch 0 5 45 10               ・               ・   A Tue 23 Center dispatch 1 18 7 5 0      B fire 0 sink 0 22 70 0   B Tue 0 Center dispatch 0 19 70 0               ・               ・   ・   ・   G Tue 23 Center dispatch 0 8 7 5 0    (Data collection date: Wednesday, April 21, 1999)    Area Day of the week Time of day Business form Rainfall Yes No Number of boarding Discomfort index Event index   A water 0 sink 1 19 80 0   ・   ・   G water 23 center dispatch 0 10 70 0    (Date of data collection: April 22, 1999 (Thursday))    Area Day of the week Time of day Business form Rainfall Yes No Number of boarding Discomfort index Event index   A tree 0 sink 0 10 55 0   ・   ・   G Thu 23 Center dispatch 0 5 50 0    (Date of data collection: Friday, April 23, 1999)                                     ・                                     ・

Then, as described above, the actual vehicle relation determining unit 203 classifies the actual vehicle for each district (district A, district B, district C, district D, district E, district F, district G) (factors are day of the week, For each of the four factors of time zone, business form, and whether or not there is rainfall, the variable factors and the actual vehicle generation speed are determined from the number of boardings (actual value of actual vehicle generation speed) and the variable factor actual data (here, discomfort index and event index). The relationship of the actual vehicle is calculated. Here, the number of rides and the variable factor performance data (discomfort index,
The actual vehicle relationship with the (event index) is obtained as a linear linear expression that is obtained by adding each numerical value that constitutes the variable factor actual data, that is, the numerical value of the discomfort index, the numerical value of the event index, and the term multiplied by the corresponding coefficient. . That is, the number of boarding times (w) for each case for each district is a linear linear expression of w = a + cy + dz (hereinafter, this expression is referred to as “this relational expression”).
Indicated by. Here, a is an offset term (constant term) that is not affected by the variable factor performance data. y is a numerical value of the discomfort index, and c is a coefficient by which y is multiplied. z is a numerical value of the event index, and d is a coefficient by which z is multiplied.

That is, in the present embodiment, to obtain the actual vehicle relation is to obtain the constants a, c, and d of this relational expression for each district and for each case. A method of obtaining the constants a, c, and d is obtained for each case by each case from a plurality of sets of (w, y, z) classified for each case by each case. Therefore, the constants (a, c,
The group of d) will exist for each case for each district. Any known method using a plurality of sets of (w, y, z) may be used as the method of obtaining the specific constants a, c, d (the simplest method is to solve simultaneous linear equations). Since there are many methods known, their explanations are omitted here. Further, the constants a, c, and d may be determined by using a so-called statistical method, and for example, a multiple regression analysis method or the like can be preferably used. Although this relational expression is expressed as the sum of the three terms of a, cy, and dz, the terms having a small contribution rate may be deleted (the coefficient of the terms may be 0). An example of the method of determining the constant by these statistical methods will be described later. In this way, the relationship between the variable factor and the actual vehicle generation speed is obtained from the number of rides (actual value of the actual vehicle generation speed) and the variable factor actual data (here, the discomfort index and the event index) for each area in each case. You can ask for a relationship. Then, the actual vehicle relationship determined by the actual vehicle relationship determining unit 203 for each of the cases for each case (this relational expression w = a + cy + d in which the constants a, c, and d are determined).
z) is output from the actual vehicle relationship determining unit 203 to the data server 55, which is an actual vehicle relationship storage unit, for each real vehicle case for each area, and the output actual vehicle relationship is an actual vehicle for each area by the data server 55, which is an actual vehicle relationship storage unit. It is stored for each case.

An example of a method for obtaining the constant of the above relational expression described above by a statistical method will be shown. The constant determination method here is composed of constant calculation and verification. Figure 10
7 is a flowchart showing the operation of the actual vehicle relationship determination unit 203 in the constant calculation. The constant calculation, which is the first half of the constant determination method, will be described with reference to FIG. First,
An expression is created by removing one term selected from the group consisting of variable terms cy and dz from the relational expression w = a + cy + dz, and each created expression is stored in a storage area together with the relational expression w = a + cy + dz ( s701). That is, w = a + dz (hereinafter, referred to as “first expression”) from which cy is removed, dz
W = a + cy (hereinafter referred to as “second formula”) from which the first relational expression w is removed.
= A + cy + dz are stored in the storage area. Next, a plurality of groups of (w, y, z) classified into the area where the constants a, c, and d are to be obtained and the case classification are extracted (s70).
2). For example, in district A, Tuesday, at midnight,
To find the constants a, c, and d that correspond to the cases of business mode shedding and no rainfall, the number of rides (w) corresponding to district A, Tuesday, time zone 00:00, business mode shedding, and no rainfall , The discomfort index (y) and the event index (z) may be extracted. Taking Table 4 as an example, (13, 60, 50) is extracted as one set of (w, y, z), and other than that. Also, a group of (w, y, z) corresponding to district A, Tuesday, 0 o'clock, business mode, and no rainfall is extracted. Of the three expressions, the first expression and the second expression stored in the storage area in s701, and the relational expression, one expression (one for which a constant is not calculated) is read (s703) and extracted in s702. w, y,
constants a, c, d from the multiple sets of z) by the method of least squares.
(The constant included in the term removed from this relational expression in s701 is set to 0) (s704). s
The constants a, c, and d calculated by 704 are converted to s703.
It is stored in the storage area together with the formula stored in s701 in association with the formula read in (s705). Finally, it is determined whether or not the constants have been calculated for all of the expressions stored in s701 (s706), and when the constants have been calculated for all (YES), the constant calculation ends and the test described below is performed. If the calculation has not been completed (NO), step s703 is performed to calculate the constant of the constant undetermined formula.

FIG. 11 is a flow chart showing the operation of the actual vehicle relation determining unit 203 in the verification. The test, which is the latter half of the constant determination method, will be described with reference to FIG. In the test, the respective relational expressions in which the constants a, c, and d are calculated by the constant calculation (s701 to s706 shown in FIG. 10), the three expressions of the first expression, and the second expression are shown below. ANOVA is performed as described above, and one of them is selected. A multiple regression analysis of variance table is shown in Table 5 (p explanatory variables, data number n).

[0082]      Table 5 ANOVA table for multiple regression        Variable factor Sum of squares Degree of freedom Unbiased variance Variance ratio    Variation due to regression SR p VR = SR / p                                                        F0 = VR / VE Residual fluctuation SE n-p-1 VE = SE / (n-p-1)    Total fluctuation Sr n-1

As a basic principle, assuming that the residuals from regression follow a normal distribution, the variance ratio F0 = VR / VE becomes an F distribution with degrees of freedom (p, n−p−1). Therefore, the significance of the multiple regression equation is calculated as follows: "Null hypothesis H0: The obtained multiple regression equation is w
Useless to estimate , The significance level α%
The value corresponding to F (p, n−p−1: α) of the F-distribution with respect to the value of the dispersion ratio F0 = VR / VE is compared, and if F0 = VR
If / VE> F (p, n−p−1: α), H0 is rejected at the risk rate α% and the multiple regression equation is accepted. Hereinafter, the test is performed using this. First, the constant a by the constant calculation (s701 to s706 shown in FIG. 10),
3 of the relational expression, the first expression, and the second expression for which c and d are calculated
One formula is read from the formula (s801). Then, SR of the formula read in s801 from the plurality of sets of (w, y, z) extracted in s702 of constant calculation (Table 5
(Reference is known about the calculation method) (s80
2). Then, as in s802, SE is calculated (s
803). Calculated SR and degree of freedom p (number of explanatory variables)
VR (= SR / p) is calculated from and the calculated SE
And the number of data n and the degree of freedom p (the number of explanatory variables), VE (=
SE / (np-1)) is calculated and F0 is calculated using the calculated VR and VE.
(= VR / VE) is calculated (s804). On the other hand, F (p, n−p−) corresponding to the number of data n, the degree of freedom p, and the predetermined risk factor α from the F-distribution table stored in advance.
The value of 1: α) is calculated (s805). It should be noted that this can also be obtained by performing integral calculation without using the distribution table. Then, it is determined whether or not F0> F (p, n-p-1: α) (s806), and if F0> F (p, n-p-1: α) (YES), it is read in s801. The formula (test formula: test formula) is stored (s807), and F0> F
If it is not (p, np-1: α), the process returns to (NO) s801, the untested formula is read, and the test is performed again. After storing the formulas in s807, it is judged whether all three formulas to be tested have been tested (s808). When it is judged that all three formulas have been tested (YES), among the formulas stored in s807. To F0 calculated from s804
If the maximum value is selected and output (s809), the work is finished, and if it is determined that all three equations have not been tested (NO), the process proceeds to s801. As described above, the constant of this relational expression (including 0) can be obtained, and if the above is done for each district for each case, all the actual vehicle cases for each district (that is, in all districts) The actual vehicle relationship (relational expression) can be determined for all cases of the actual vehicle.

In the above description, the actual vehicle relationship is obtained, and the obtained actual vehicle relationship (relational expression) is stored in the data server 55, which is an actual vehicle relationship storage means. Data server 55 as a means
The obtained empty vehicle relationship (relational expression) can be stored in. That is, when the demand actual result data regarding a predetermined amount of getting off is accumulated in the data server 55 (empty vehicle occurrence speed storage means), the empty vehicle relation determining unit 215 causes the data server 55.
From the actual demand data stored in the table, the number of disembarkations that belong to each district (classified by the location where passengers disembark) belong to each empty case is counted, and the number of disembarked counts is counted. The variable factor result data corresponding to the date, district, and empty vehicle case classification corresponding to are read from the data server 55 (empty vehicle variable factor result storage means).
As a result, the empty vehicle relation determining unit 215 creates a set of the counted number of times of disembarking and the read variable factor performance data for each empty vehicle case for each district for each date. As described above, the number of disembarking passengers is counted for each business type, but the variable factor performance data and the like do not consider the business type. Then, the empty vehicle relation determination unit 215 determines the number of times of getting off (actual value of empty vehicle occurrence speed) for each empty vehicle case for each district.
Then, the empty vehicle relationship, which is the relationship between the variable factor and the empty vehicle generation speed, is obtained from the variable factor actual data. As the method for obtaining the empty vehicle relationship, the same method as the above-described method for obtaining the actual vehicle relationship can be performed, and therefore the description thereof is omitted here.

Then, the actual vehicle-related reading section 205 divides the case corresponding to the layout plan to be planned received by the case classification receiving section (second base computer 58) (the factors are the day of the week, the time zone, the business form, and the rainfall). When the case classification reception unit (the second base computer 58) notifies of the presence / absence, the actual vehicle relationship corresponding to the case is read from the data server 55, which is the actual vehicle relationship storage means, and the read actual vehicle. The relationship is notified to the actual vehicle generation speed calculation unit 207. On the other hand, the information fetching unit 209 fetches the planned value of the variable factor corresponding to the layout plan to be planned through the keyboard connected to the first base computer 53, and receives the planned value of the fetched variable factor. Notify the unit 211. Here, the planned values of the fluctuation factors are the numerical value (predicted value) of the discomfort index and the event index (predicted value), which are taken into account by the information capturing unit 20 via the keyboard for each district.
9 takes in. Note that both the discomfort index value (predicted value) and the event index (predicted value) are captured via the keyboard for each district, but the discomfort index value (predicted value) and the event index (predicted value) Either or both of (value) and may be automatically fetched via the Internet 57. The fluctuation factor reception unit 211 notifies the actual vehicle generation speed calculation unit 207 of the planned values (numerical value of discomfort index (predicted value), event index (predicted value)) of the fluctuation factor notified from the information capturing unit 209 for each district. To do. Then, the actual vehicle generation speed calculation unit 207 receives from the actual vehicle relation (the relational expression w = a + cy + dz, the constants a, c, and d are the relational expressions) notified from the actual vehicle relation reading unit 205 and the fluctuation factor acceptance unit 211. An actual vehicle generation speed (w) is calculated using the notified planned values (numerical value (predicted value) of discomfort index: y, event index (predicted value): z) of the fluctuation factors, and the calculated actual vehicle The generation speed (w) is notified to the waiting time calculation unit (second base computer 58) of the expected amount calculation unit described later.

Similarly, the vacant-vehicle-related reading unit 217, when notified by the case-dividing receiving unit of the case-division corresponding to the layout plan to be made by the case-dividing receiving unit, determines the vacant-vehicle relation corresponding to the case-dividing. It is read from the data server 55, which is an empty vehicle relation storage means, and the empty vehicle relationship thus read out is notified to the empty vehicle generation speed calculation unit 219. On the other hand, the plan values (numerical value of discomfort index (predicted value), event index (predicted value)) corresponding to the layout plan to be planned, which is captured by the information capturing unit 209, are
11 is notified, and the variable factor acceptance unit 211 notifies the empty vehicle generation speed calculation unit 219. Then, the empty vehicle generation speed calculation unit 219 receives the empty vehicle relationship (relational expression v = e + fy + gz, constants e, f, notified from the empty vehicle relationship reading unit 217).
g is an already-established relational expression) and a planned value (numerical value (predicted value) of discomfort index: y, event index (predicted value): z) of the fluctuation factor notified from the fluctuation factor reception unit 211. The empty vehicle generation speed (v) is calculated, and the calculated empty vehicle generation speed (v) is notified to the waiting time calculation unit (second base computer 58) of the expected amount calculation unit described later.

Next, the second base computer 58 will be described with reference to FIGS. 12 and 13. FIG. 12 shows a functional block diagram of the second base computer 58 realized by the hardware of FIG. 7 and the program recorded in the ROM 351c. Functionally, the second base computer 58 has a case division receiving unit 401 (case division receiving unit), a performance data reading unit 403 (actual data reading unit), a state position receiving unit 405 (position receiving unit), an expected amount calculation unit. 411 (expected amount calculation means) and a notification unit 441 (notification means). FIG. 13 shows the expected amount calculation unit 41.
It is a functional block diagram showing 1 in detail. The expected amount calculation unit 411 is functionally a traveling time determination unit 417, a business type classification unit 413, a flow fare actual result determination unit 415, a flow customer search time determination unit 419, a flow boarding time determination unit 421, and a flow expected income calculation. Department 423, each district standby number grasping part 42
5, center fare performance determination unit 429, pick-up time determination unit 43
1, center boarding time determination unit 433, standby time calculation unit 43
5, center expected income amount calculation unit 437, expected income output unit 4
And 39.

Each time the state of the taxi 11 changes, the position information including the longitude and latitude where the taxi 11 currently exists and the state change information are automatically transmitted to the base station 51 by radio. The status position accepting unit 405 of the second base computer 58 of the base 51 receives the signal including the issued position information and status change information. Here, the state position reception unit 4
05 determines from which area the state change has occurred based on the received position information, and uses a case classification reception unit 401 and an expected amount calculation unit 411 to identify a signal that can identify the state change and the area where the state change has occurred. It transmits in parallel to each district standby number grasping part 425 of. The state position acceptance unit 405 determines from which position information the latitude and the latitude belong to which region it belongs to by the demand record data acceptance unit 201 in FIG. 9 based on the longitude and latitude data. Since it can be performed in the same manner as the calculation of, the description is omitted here.

Then, the case classification reception unit 401 receives the state change information transmitted from the state position reception unit 405 as described above, and if it is the information that the passenger got off and became vacant, The case classification corresponding to the layout plan to be planned is accepted. Specifically, here, regarding the two factors of the case classification, that is, the day of the week and the time zone, the current data emitted by the built-in clock of the second base computer 58 is taken as it is, and the rainfall is one of the factors of the case classification. Regarding the presence or absence of the information, the operator of this system inputs the information corresponding to each district through the keyboard, referring to the current weather and weather forecast of each district. Note that the presence or absence of rainfall need not be input by the operator in this way, but the corresponding data may be automatically captured via the Internet through the information capturing means. Further, the two factors of the day of the week and the time zone may be input by the operator of the present system via a keyboard or the like connected to the second base computer 58. As described above, the case classification receiving unit 401 receives the three factors of the presence / absence of rainfall in each area, the day of the week, and the case classification of the time zone. In addition, the business form is not entered here among the case classification factors, and the expected income amount is notified to the taxi separately for the two types of business patterns of the sink and the center vehicle dispatch. The expected income amount may be notified only for the input business mode by inputting one of the business modes of the flow and the center dispatch to 401. Then, the case classification receiving unit 401 transmits the received case classification factor data (day of the week, time zone, presence of rainfall) in parallel to the actual data reading unit 403, the vacant vehicle-related reading unit 217, and the actual vehicle-related reading unit 205. . As described above, the empty vehicle relation reading unit 217 that has received the case division factor data from the case division reception unit 401 reads out the empty vehicle relation corresponding to the case division factor from the data server 55, which is the empty vehicle relation storage unit, and reads it. The vacant vehicle occurrence speed calculation unit 219 is notified of the determined vacant vehicle relationship.
Similarly, the actual vehicle relationship reading unit 205 that has received the data of the case classification factor from the case classification reception unit 401 reads the actual vehicle relationship corresponding to the case classification factor from the data server 55 that is the actual vehicle relationship storage unit, as described above. The read relationship of the actual vehicle is notified to the actual vehicle generation speed calculation unit 207.

On the other hand, the actual result data reading unit 403 which has received the data of the case classification factor from the case classification receiving unit 401.
Extracts, from the demand performance data stored in the data server 55, which is the performance data storage means, the data whose state has changed to wages (wage change data) and which matches the received case classification factor. . That is, the change in fare on the day of the week included in the received case classification factor, and the change in fare during the time period included in the received case classification factor, and the presence / absence of rainfall included in the received case classification factor Only the wage change data corresponding to the above are extracted. Then, the actual data reading unit 403 pays attention to each process of one wage starting from the extracted wage change data. This is because each time the fare starts from the fare change data, this time after the previous fare was finished by the passenger getting off (after leaving the business and starting business, in the case of the first fare, leaving) The time until the end of the renting of the vehicle is terminated by the passengers getting off, and this is considered as one renting process this time, and each of the renting process is analyzed as one data. Specifically, the actual result data reading unit 403
After the one fare starting from the extracted fare change data is completed by the passenger getting off the train immediately before that (after leaving the business and starting business, in the case of the first fare, leaving ) To the end of this fare run by passengers getting off the train as one run of this fare run. For example, taking Table 1 above as an example, if the data 4 in Table 1 is the change data of wages that matches the case-separating factor when received, the wage process starts from data 2 in Table 1 and It is finished by the data 5 in 1. The actual demand data included in one wage process starting from the wage change data that matches the received case classification factor (in the example of Table 1 above, data 2, data 3, data 4, data 5) is put together. Demand performance data (hereinafter referred to as "data bundle") that has been included in one wage process
Say. ) May be singular or plural.
The actual data reading unit 403 transmits such a data bundle to the moving time determination unit 417 and the business type classification unit 413 of the expected amount calculation unit 411.

The traveling time determining unit 417 classifies the data bundles from the actual data reading unit 403 into those having the same boarding area and getting-off area (for example, boarding at the area A and getting off at the area A). One group, one that got on in area A and got off in area B is another group, and ... one that got on in area B and got off in area A is yet another group, Those who get on in Area B and get off in Area B are divided into groups, such as. Then, the travel time determination unit 417 determines that the boarding area and the exiting area are the same (group)
The time taken from getting on to getting off is extracted from the data bundle classified into. Then, the travel time determination unit 417 sets the median value of the extracted times as the expected travel time from the boarding area to the disembarking area. For example, boarding in Area A and going to Area B
Assuming that the time extracted from the data bundle that got off at 4 minutes and 6 minutes, the median of these is 5 minutes ((4 + 6) /
2) is the expected travel time from Area A to Area B. The travel time determination unit 417 determines the expected travel time from all areas to all areas (including movement within the same area) by performing this as the boarding area and the disembarking area for all areas. You can Table 6 shows an example of the expected travel time from each determined district to each district. From the example in Table 6, the expected travel time from district A to district A is 5 minutes on Tuesdays, at 10:00, and when there is no rainfall. From district C to district B
It can be seen that the expected travel time to is 10 minutes. Then, the travel time determination unit 417 stores the determined expected travel time data from each area to each area, and the later-described expected flow income calculation unit 423, standby time calculation unit 435, and expected center income calculation unit 437, which will be described later. The expected travel time data is sent to the expected income calculation unit 423, the waiting time calculation unit 435, and the center expected income calculation unit 437 in response to the request from the user.

[0092]   (Table 6) Expected travel time from each district to each district (Tuesday, 10:00 am, no rain) Shi)                 Disembarkation area Area A Area B Area C ...        Riding area           Area A 5 minutes 12 minutes 14 minutes ...           Area B 9 minutes 6 minutes 11 minutes ...           Area C 15 minutes 10 minutes 7 minutes ...             ・ ・ ・ ・             ・ ・ ・ ・

On the other hand, the business type classification unit 413 classifies each data bundle according to whether the business type in the data bundle transmitted from the actual data reading unit 403 is flow or center vehicle allocation, and the data bundle whose business form is flow is Flow rate deciding part 4
15, the sending customer search time determination unit 419, the flow-on boarding time determination unit 421, the data bundle of the business form is the center dispatch, the center fare record determination unit 429, the intercept time determination unit 43
1, transmitted to the center boarding time determination unit 433.

The flow fare performance determination unit 415 receives the received data bundle of the business type (the data transmitted from the business type classification unit 413) in which district (district A, district B, district C, district). D, district E, district F, district G). Then, the actual fare amount (fare charge) is extracted from the data bundle in which the boarding places are classified into the same area, and the median of the extracted fare amounts is set as the expected fare amount in the same area. For example, the fare amount extracted from the data bundle in the area A is 620 yen, 750 yen, 800 yen, 900 yen, 2
If it is 600 yen, the median of these fares is 80.
0 yen is the expected fare for Area A. Then, the flow-through fare performance determination unit 415 determines the expected fare amount for each district in this way, and sends them to the flow-through expected income amount calculation unit 423. The sink customer search time determination unit 419 determines an expected value of the customer search time, which is the time required to discover a passenger in the same business area as a sink. For this reason, the sink customer search time determination unit 419 determines, from the received data bundle of the sales type (transmitted from the sales type classification unit 413), the exit area to which the exit position, which is the end of the previous rent, belongs. A data bundle in which the boarding area to which the boarding position where the rent is started this time belongs is extracted, and the extracted data bundle is further classified by boarding area. Then, the running customer search time determination unit 419 extracts the time from the exit time at which the previous fare ends to the boarding time at which the fare starts this time from the data bundle classified into the same boarding area, and the extraction is performed. The median of the determined time is set as the expected customer search time in the same area. For example, from the data bundle classified into area A, the time from the last getting off time to the current getting on time is 9 minutes,
Assuming that these are extracted as 15 minutes, 18 minutes, 35 minutes, and 49 minutes, 18 minutes, which is the median of these times, is the expected customer search time in the area A. And the sink customer search time determination unit 41
9 determines the expected customer search time for each district in this way, and sends them to the expected income calculation unit 423. The sink boarding time determination unit 421 determines which district (district A, district B, district C, district D, or district) the boarding place is for the received data bundle of the sales form (transmitted from the sales form classification unit 413). E, district F, district G). Then, the actual boarding time (the time from the current boarding time to the current boarding time) is extracted from the data bundle in which the boarding places are classified into the same area, and the median of the extracted boarding times is calculated as the expected value of the same area. The boarding time. For example, the boarding time extracted from the data bundle boarded in the area A is 6 minutes, 9
Assuming that the minutes, 10 minutes, 18 minutes, and 45 minutes are 10 minutes, which is the median of the boarding times, is the expected boarding time of the area A. Then, the flow-on boarding time determination unit 421 determines the expected boarding time for each district in this way, and sends them to the flow-through expected income calculation unit 423.

On the other hand, the number-of-standby-vehicles grasping unit 425 in each district receives the information about the state change of each taxi from the state position reception unit 405, and in each district, each taxi is in any state including the standby state in the center dispatch. Figure out what. As described above, the target taxi for which the current placement plan should be made is the state position reception unit 405.
Each district standby vehicle number grasping section 425 has grasped that the taxi has received the state change information that the state has changed to an empty vehicle. The expected income amount calculation unit 423 is notified of the district in which it is located.

As described above, the expected paying income calculation unit 423 determines the expected fare amount for each area from the actual fare performance determining unit 415 and the expected customer search time for each district from the observing customer search time determining unit 419. And the sink boarding time determination unit 42
From 1 to the expected boarding time for each area, it is possible to obtain information on which area the taxi that is the target of the current allocation plan is located. Then, as described above, it is possible to obtain from the travel time determination unit 417 an expected travel time to be used as a travel time for travel to another area from the area where the taxi that is the target of the current layout plan exists. Table 7 shows examples of the expected fare amount for each district, the expected customer search time for each district, and the expected boarding time for each district, which are received by the flow expected revenue calculation unit 423.

[0097]    (Table 7) Expected fare amount and expected customer search time received by the sink expected income calculation unit Example of expected boarding time (Tuesday, 10:00 am, no rain)      Area Expected fare Expected customer search time Expected boarding time        A 100 yen 10 minutes 10 minutes        B 200 yen 20 minutes 20 minutes        C 300 yen 30 minutes 30 minutes         ・         ・

The expected income calculation unit 423 using the above-mentioned information determines whether the taxi which is the target of the placement plan remains in the current area, and whether the taxi currently belongs to among the plurality of areas. It is possible to calculate the expected income amount per unit time when moving to each different district. That is, the expected income amount per unit time of the taxi (when the business mode is sink) is the formula: (Expected fare amount) / ((Sink location travel time) + (Expected customer search time) + (Expected boarding time) ) Can be calculated for each region. In addition, here, the sink location travel time uses the expected travel time obtained from the travel time determination unit 417, and is considered only when the district is changed from now on, and is treated as 0 when the sink is flowed in the same district without changing the district. . For example,
An example will be described in which the target taxi for which the placement plan should be planned is currently in district B. The expected amount of income when moving to district A (changing districts) from now on is (expected fare amount) / ((sink travel time) + (expected customer search time) + (expected boarding time) = 100 / (9+
10 + 10). Note that the data of the area B ride to the area A drop-off in Table 6 is used for 9 (minutes) of the traveling time of the sink location, and the expected fare amount, expected customer search time,
The expected boarding time uses the one in district A in Table 7. The expected amount of income in the case of leaving the area B (without changing the area) from now on is (expected fare amount) / ((sink moving time) + (expected customer search time) + (expected boarding time) = 2
It is calculated by 00 / (0 + 20 + 20). In addition,
The sink location travel time is set to 0 because the location is the same in the same district without changing the district.
The expected boarding time uses the one in district B in Table 7. The expected amount of income when moving to District C (changing the district) from now on is (expected fare amount) / ((sink moving time) + (expected customer search time) + (expected boarding time) =
It is calculated by 300 / (11 + 30 + 30). In addition, for the 11 (minutes) of the time required to move to the sink, the data from boarding area B to getting off area C in Table 6 are used.
The expected customer search time and the expected boarding time are those of district C in Table 7. The expected income amount in other areas other than this can be calculated in the same manner. As described above, the sink expected income amount calculation unit 423 calculates the expected income amount of the sink in each district, and calculates the expected income amount output unit 43 for each.
Notify 9. The expected income output unit 439 collectively transmits the expected income amount of the center vehicle dispatch and the expected income amount of the sink in each district, which will be described later, to the notification unit 441, and the allocation unit 441 makes an arrangement plan. The expected tax amount is notified to the target taxi via radio.

Then, the data bundle in which the business pattern is classified into the center vehicle allocation by the business pattern classification unit 413 is transmitted to the center fare performance determination unit 429, the intercepting vehicle time determination unit 431, and the center boarding time determination unit 433. The center fare performance determination unit 429 receives the data bundle of the received business form of the center vehicle dispatch (the data transmitted from the business form classification unit 413) in which district (district A, district B, district C, district D,). Classify according to whether it is district E, district F, or district G). Then, the actual fare amount is added from the data bundle in which the boarding places are classified into the same area (in the case of the center dispatch, the pick-up fee and the fare fee are added. Data consisting of data 2 to data 5 in Table 1) (2100 yen in a bundle) is extracted, and the median value of the extracted fare amounts is set as the expected fare amount of the same area. Since the method of obtaining the median value is the same as in the case of the above-described flow, the description is omitted here. Then, the center fare performance determination unit 429 determines the expected fare amount for each district in this way and sends them to the center expected income calculation unit 437. The reception time determination unit 431 receives the data bundle of the received business type from the center vehicle (the one transmitted from the business type classification unit 413) in which district (district A, district B, district C, district D, district). E, district F, district G). Then, from the data bundle in which the boarding places are classified into the same area, the actual pick-up time (the time from the receipt of the dispatch instruction from the center to the passenger getting on. For example, the time from data 3 to data 4 in Table 1) And the median value of the extracted vehicle pick-up times is set as the expected vehicle pick-up time of the same area. Since the method of calculating the median value has been described above, the description is omitted here. Then, the vehicle oncoming time determination unit 431 determines the expected vehicle oncoming time for each district in this way, and transmits them to the center expected income calculation unit 437. It should be noted that as the arrival time, the expected travel time in each area stored by the travel time determination unit 417 can be used. For example, the value from the boarding area A to the disembarking area A of the expected travel time data in Table 6 ( 5
Minutes) can also be used as the expected pick-up time in area A. Similarly, the value from boarding area B to getting off area B (6 minutes)
Can be set as the expected pick-up time in the area B, and the value (7 minutes) from the boarding area C to the getting-off area C can be set as the expected pick-up time in the area C. The center boarding time determination unit 433
The received business form is a data bundle of the vehicle dispatched by the center (transmitted from the business form classification unit 413) where the boarding place is any of the districts (district A, district B, district C, district D, district E, district F, district G). ) Classify according to. Then, the actual boarding time (the time from the current boarding time to the current boarding time) is extracted from the data bundle in which the boarding places are classified into the same area, and the median of the extracted boarding times is calculated as the expected value of the same area. The boarding time. Since the method of calculating the median value has been described above, the description is omitted here. Then, the center boarding time determination unit 433
Determines the expected boarding time for each district in this way and transmits them to the center expected income calculation unit 437.

[0100] The standby time calculation unit 435 uses the information on the number of waiting units for each district to find out the number of standby taxis in the center vehicle in each district and information on which district the target taxi for which the current placement plan should be prepared exists. The actual vehicle generation speed calculation unit 207 receives the actual vehicle generation speed in each area, and the empty vehicle generation speed calculation unit 219 receives the empty vehicle generation speed in each area. Then, as described above, it is possible to obtain, from the movement time determination unit 417, the center place movement time for moving from the area where the taxi, which is the target of the current placement plan, to another area. Table 8 shows an example of the number of waiting vehicles, the actual vehicle occurrence speed and the empty vehicle occurrence speed for each area received by the waiting time calculation unit 435, and the area where the taxi that is the target of the current allocation plan exists.

[0101] (Table 8) The number of standby vehicles, actual vehicle generation speed, and Vacancy generation speed and the area where there is a target taxi for which a placement plan is currently planned, Example (Tuesday, 10:00 am, no rainfall) 1. Existing taxi area for which a layout plan should be planned: Area B 2. Standby number, actual vehicle speed and empty vehicle speed for each area      District Waiting vehicle number Actual vehicle generation speed Empty vehicle generation speed        A 1 unit 3 units / hour 2 units / hour        B 1 unit 1 unit / hour 0 unit / hour        C 3 units 8 units / hour 4 units / hour                               ・                               ・

From the information listed in Table 8, the standby time calculation unit 435 calculates the formula: ((current standby number-center location moving time x actual vehicle generation speed + center location moving time x empty vehicle generation speed + 1) / actual vehicle generation speed. ), The waiting time for each district is calculated, and the calculated waiting time for each district is transmitted to the center expected income calculation unit 437. The calculation of the waiting time is performed as follows.・ Region A Standby Time = ((Current Standby Number-Center Location Travel Time x Actual Vehicle Generation Speed + Center Location Travel Time x Empty Vehicle Generation Speed + 1)
/ Actual vehicle speed) = ((1-9 / 60 x 3 + 9/60 x
2 + 1) / 3 × 60 Here, as the number of currently waiting vehicles, the number of waiting vehicles in the area A in Table 8 is used, and the center location moving time is expected moving time data from each area provided by the moving time determining unit 417 to each area. The value (9 minutes) from boarding area B to getting off area A in (Table 6) is used and divided by 60 (9/60)
Is to convert the unit from minutes to hours. As the actual vehicle generation speed and the empty vehicle generation speed, the actual vehicle generation speed and the empty vehicle generation speed in the area A in Table 8 were used. It should be noted that the reason for multiplying by 60 at the end is to obtain the standby time in minutes.・ Region B Standby Time = ((Current Standby Number-Center Location Travel Time x Actual Vehicle Generation Speed + Center Location Travel Time x Empty Vehicle Generation Speed + 1)
/ Actual vehicle generation speed) = ((1-0 / 60 x 1 + 0/60 x
0 + 1) / 1 × 60 As for the number of currently waiting vehicles, the number of waiting vehicles in area B in Table 8 is used, and for the center location moving time, the existing area of the target taxi for which the allocation plan should be planned is area B and the area is changed. Since there is no such thing (as in district B), the time for moving to the center location is set to 0. The division by 60 is for converting the unit from minutes to hours. As the actual vehicle generation speed and the empty vehicle generation speed, the actual vehicle generation speed and the empty vehicle generation speed in Area B in Table 8 were used, respectively. Finally, 60
The reason for multiplying is to obtain the waiting time in minutes.・ Region C Standby Time = ((Current Standby Number-Center Location Travel Time x Actual Vehicle Generation Speed + Center Location Travel Time x Empty Vehicle Generation Speed + 1)
/ Actual vehicle generation speed) = ((3-11 / 60 × 8 + 11/6
0 × 4 + 1) / 8 × 60 Here, the number of waiting vehicles currently in the district C in Table 8 is used as the number of waiting vehicles currently, and the expected movement from each district to each district provided by the movement time determination unit 417 is used as the center location movement time. The value (11 minutes) from the boarding area B to the getting-off area C of the time data (Table 6) is used and divided by 60 (11
/ 60) is for converting the unit from minutes to hours.
The actual vehicle generation speed and the empty vehicle generation speed are shown in Table 8 respectively.
The actual vehicle occurrence speed and the empty vehicle occurrence speed in district C in the above are used. It should be noted that the reason for multiplying by 60 at the end is to obtain the standby time in minutes. Hereinafter, the waiting time may be similarly calculated for other areas. Then, the waiting time calculation unit 435 transmits the calculated waiting time for each district to the center expected income calculation unit 437.

As described above, the expected center income calculation unit 437 calculates the expected fare amount for each district from the center fare performance determination unit 429, the expected arrival time for each district from the intercept time determination unit 431, and the center. The boarding time determining unit 433 receives the expected boarding time for each district, and the waiting time calculating unit 435 receives the waiting time for each district and information about the district where the taxi as a target for which an arrangement plan is to be prepared currently exists.
Then, as described above, the expected center income calculation unit 437.
Is an expected location travel time to be used as a center location travel time for a taxi, which is a target for which an arrangement plan is to be planned, to move from an area where it currently exists to another area.
It can be obtained from 7. Table 9 shows the expected fare amount for each district, the expected pick-up time for each district, the expected boarding time for each district, the expected waiting time for each district, and the taxi received by the center expected income calculation unit 437. Take the example of an existing district.

[0104] (Table 9) Expected fare amount for each district received by the center expected income calculation unit, each district Expected pick-up time for each area, expected boarding time for each area, expected waiting time for each area, An example of the area where the taxi currently exists 1. Existing area of the taxi: Area B 2. Expected fare amount, expected pick-up time, expected boarding time, expected waiting time for each area Area Expected fare Expected pick-up time Expected boarding time Expected waiting time   A 100 yen 4 minutes 10 minutes 10 minutes   B 200 yen 6 minutes 20 minutes 20 minutes   C 300 yen 6 minutes 30 minutes 30 minutes                               ・                               ・

The center expected income calculation unit 437 using such information is different from the case where the taxi which is the object of the layout plan remains in the area where it currently exists and the area to which the taxi currently belongs among the plurality of areas. Calculate the expected income per unit time when moving to each district. That is, the expected income amount per unit time of the taxi (when the business form is dispatched to the center) can be distinguished by the formula: (actual fare actual amount / (center location travel time + waiting time + waiting time + boarding time)) Can be calculated. Here, the center location movement time is taken into consideration only when the district is changed from now on, and is treated as 0 when operating by center vehicle dispatch within the same district without changing the district. For example, a case where a taxi as a target for which an arrangement plan should be planned is currently in the district B will be described as an example. Area A from now on
Expected income when moving to (change district) and conducting business by center dispatch = (actual fare actual amount / (center location moving time + waiting time + waiting time + boarding time)) = 100 /
It is calculated by (9 + 10 + 4 + 10). Note that 9 minutes of the center location travel time uses the data from the area B ride to the area A drop-off in Table 6, and the actual fare amount, the waiting time, the pick-up time, and the boarding time are shown in Table 9 for the area A. Expected fare amount, expected waiting time, expected pick-up time, and expected boarding time are used respectively. Area B from now on (does not change district)
Expected income when operating as a center vehicle without change =
(Actual fare amount / (Center location travel time + Standby time + Pick-up time + Ride time)) = 200 / (0 + 20 + 6 + 20)
Calculated by In addition, the center location travel time is set to 0 because business is carried out by center vehicle dispatch within the same district without changing the district. Actual fare amount, waiting time, pick-up time, and boarding time are the expected fare amount of district B in Table 9, Expected waiting time, expected pick-up time, and expected boarding time are used respectively. Expected income when moving to district C (changing districts) and operating by center dispatch = (actual fare actual amount / (center location moving time + waiting time + waiting time + boarding time))
= 300 / (11 + 30 + 6 + 30). Note that 11 minutes of the center location travel time uses the data from the area B ride to the area C disembarkation in Table 6, and the actual fare amount, the waiting time, the pick-up time, and the boarding time are shown in Table 9 Expected fare amount, expected waiting time, expected pick-up time, and expected boarding time are used respectively. The expected income amount in other areas other than this can be calculated in the same manner. As described above, the expected center income calculation unit 437 calculates the expected income amount for sales by center dispatch in each district, and notifies the expected income output unit 439 of each. The expected income output unit 439 collectively transmits the expected income amount of the sink in each district and the expected income amount of the business by the center vehicle dispatch in each district to the notification unit 441, and the notification unit 441 makes an arrangement plan. The taxi that is the target should be notified of these expected income amounts via radio.

Next, the operations of the first base computer 53 and the second base computer 58 having the above configurations will be described. First, in FIG. 14, mainly inputting actual data,
FIG. 15 shows a flowchart of an operation relating to calculation of an actual vehicle generation speed and calculation of an empty vehicle generation speed, FIG.
The flowchart of the operation | movement regarding determination of an actual vehicle relationship and an empty vehicle relationship is mainly shown. The operation of the first base computer 53 will be described with reference to FIGS. 14 to 16 in order.

Referring to FIG. 14, the operations mainly relating to the input of actual data, the calculation of the actual vehicle generation speed, and the calculation of the empty vehicle generation speed will be described. First, the demand result data receiving unit 201 determines whether or not the result data is received from the business office computer 35 via the cable 41 (s30).
1) If it is determined that the data has been received (YES), the area (change area) to which the position having each state change belongs from the data of the longitude and latitude indicating the position having each state change included in the received actual data. ) Is calculated (s302). If the demand record data reception unit 201 determines that the record record data has not been received (NO), the process proceeds to s305 described below. The actual result data in which the area (changed area) whose state has changed is determined in s302 is the demand actual result data reception unit 201.
Sent to the data server 55 and stored (s30
3). On the other hand, as will be described later, from the variation factor record data stored in the data server 55 by the information capture unit 209 via the Internet 57 or the keyboard, the above-mentioned respective state changes of the record data stored in the data server 55 The rainfall information read-out unit 213 reads out the presence / absence of rainfall when the user awakes, and the rainfall information read-out unit 213 additionally indicates the presence / absence of rainfall in each state change of the performance data stored in the data server 55 (s304).

Then, the actual vehicle relation reading unit 205 determines whether or not the case classification corresponding to the vehicle allocation plan to be planned is notified from the case classification reception unit 401 (second base computer 58) (s305), and the case classification is performed. When it is determined that the data has been received (YES), the actual vehicle relationship corresponding to the case classification is read from the data server 55 that is the actual vehicle relationship storage means, and the read actual vehicle relationship is calculated by the actual vehicle generation speed calculation unit 2
07 is notified (s306). When the actual vehicle relation reading unit 205 determines that the case division corresponding to the vehicle allocation plan to be planned is not received from the case division reception unit 401 (second base computer 58) (NO), the process proceeds to s311 described below. go. On the other hand, the information fetching unit 209 fetches the planned value of the variation factor corresponding to the layout plan to be planned through the keyboard connected to the first base computer 53, and receives the planned value of the fetched variation factor. The unit 211 is notified (s307). Then, the actual vehicle generation speed calculation unit 207 calculates the actual vehicle generation speed by using the actual vehicle relationship notified from the actual vehicle relationship reading unit 205 and the planned value of the variation factor notified from the variation factor reception unit 211. The calculated actual vehicle generation speed is notified to the waiting time calculation unit 435 (second base computer 58) of the expected amount calculation unit 411 (s308). Empty car-related reading unit 2
When 17 determines that it has been accepted in s305, the empty vehicle relationship corresponding to the case classification is read from the data server 55, which is the empty vehicle relationship storage means, and the read empty vehicle relationship is notified to the empty vehicle generation speed calculation unit 219 (s309). Then, in s307, the planned value of the variation factor captured by the information capturing unit 209 is notified to the variation factor receiving unit 211, and from the variation factor receiving unit 211 to the empty vehicle generation speed calculation unit 219. Then, the empty vehicle generation speed calculation unit 2
Numeral 19 calculates an empty vehicle occurrence speed using the empty vehicle relationship notified from the empty vehicle relationship reading unit 217 and the planned value of the fluctuation factor notified from the fluctuation factor acceptance unit 211, and the calculated empty vehicle occurrence speed Is notified to the waiting time calculation unit 435 (second base computer 58) of the expected amount calculation unit 411 (s310). Then, it is determined whether or not the work is completed (s311). When the work is completed (YES), the work is completed (end), and when the work is not completed (NO) s301
Return to.

The operation mainly relating to information acquisition will be described with reference to FIG. First, the information importing unit 209 determines whether or not it is a predetermined time at which information such as variation factor performance data is to be imported (s321), and when it is determined that the information is at a predetermined time (YES), the weather, Temperature (℃), wind direction, wind speed (m / s), precipitation (m
m) and the actual data indicating the humidity (%) are automatically fetched from the homepage of the private weather information provider, which is an external information source of this system, via the Internet 57 (s32).
2). When the information capturing unit 209 determines that it is not the predetermined time at which the information such as the variation factor actual result data should be captured (NO), the process returns to s321. Then, when s322 ends, the information capturing unit 209 further inputs the event index, which is a sudden influence factor, via the keyboard (s3
23). The event index input via the keyboard is stored by the information capturing unit 209, and when the stored event index exists, it is used. The variable factor performance data and the like (including the event index) thus collected are such that the information capturing unit 209 makes it possible to clarify the date and time zone in which each data was collected for which district. From the variable factor result storage means (actual vehicle and empty vehicle variation factor result storage means) to the data server 55 (s324),
The data server 55 stores each data so as to clarify the date and time zone in which the data was collected for which district. Then, it is judged whether or not the work is completed (s325), and if the work is completed (YES), the work is completed (end), and if the work is not completed (NO) s.
Return to 321.

With reference to FIG. 16, the operation mainly relating to the determination of the relationship between the actual vehicle and the empty vehicle will be described. First,
When the actual vehicle relationship determination unit 203 determines whether or not the demand result data regarding a predetermined amount of boarding has been accumulated in the data server 55 (s341), and determines that it has been accumulated (YE
S), the actual vehicle relationship determination unit 203 counts the number of times of boarding that belongs to each actual vehicle case for each district from the actual demand data stored in the data server 55 (s3).
Along with 42), the variable factor performance data corresponding to the counted number of times of boarding, the date, the district, and the case classification are read from the data server 55 (s343). In addition, when the actual vehicle relationship determination unit 203 determines in s341 that the predetermined amount of demand performance data is not stored in the data server 55 (NO), the process proceeds to s347 described later. Then, the actual vehicle relationship determination unit 203 creates a set of the counted number of times of boarding and the read variation factor performance data and the like (s
344). After that, the actual vehicle relationship determination unit 203 obtains and determines the actual vehicle relationship, which is the relationship between the variation factor and the actual vehicle generation speed, from the number of boarding times and the variation factor actual result data for each real vehicle case classification (s345). And the actual vehicle-related determination unit 2
03 notifies the data server 55, which is the actual vehicle relationship storage means, of the output of the determined actual vehicle relationship (s346), and causes the data server 55 to store the relationship. Similarly, the vacant vehicle relationship determination unit 2
15 determines whether or not the demand result data relating to a predetermined amount of getting off is accumulated in the data server 55 (s347),
If it is determined that they have been accumulated (YES), the empty vehicle relationship determination unit 215 counts the number of times of disembarkation that belongs to each empty vehicle case classification for each district from the actual demand data stored in the data server 55 (s348). At the same time, the variable factor record data corresponding to the counted number of disembarking times, the district, and the case classification are read from the data server 55 (s349). In addition, the empty vehicle relation determination unit 215
When it is determined in s347 that the predetermined amount of demand actual data is not stored in the data server 55 (NO),
Go to s353 described later. And the vacant vehicle-related determination unit 215
Creates a set of the counted number of getting-off vehicles and the read out variation factor performance data and the like (s350). After that, the empty vehicle relationship determination unit 215 determines and determines an empty vehicle relationship, which is a relationship between the variable factor and the empty vehicle occurrence speed, from the number of alighting times and the variable factor actual data for each empty vehicle case for each district (s).
351). Then, the empty vehicle relation determining unit 215 outputs and notifies the data server 55, which is an empty vehicle relation storage means, of the obtained empty vehicle relation (s352), and causes the data server 55 to store it. After that, it is judged whether the work is completed (s3
53) If the work is finished (YES), the work is finished (end), and if it is not finished (NO), the process returns to s341.

FIG. 17 shows a flowchart of the operation of the second base computer. The operation of the second base computer 58 will be described with reference to FIG. First, the state position reception unit 405 determines whether or not a signal including position information and state change information emitted from a taxi is received (s3).
71). When it is determined in s371 that the state position reception unit 405 has received the signal (YES), the state position reception unit 405 determines in which district the state change has occurred from the received position information, and then determines. (S372), a signal for identifying the state change and the district in which it occurs can be transmitted in parallel to the case classification receiving unit 401 and each district standby unit number grasping unit 425 of the expected amount calculating unit 411. s371
If the state position accepting unit 405 determines that the signal has not been received (NO), the process returns to s371. And
The case classification receiving unit 401 receives the state change information transmitted from the state position receiving unit 405, and determines whether or not the information indicates that the passenger has exited and became empty (s37).
3). In step s373, the case classification acceptance unit 401 determines that the status change information is information that the passenger has exited and became empty (YES), the case classification acceptance unit 40.
1 receives the case classification corresponding to the layout plan to be planned (s374). The case classification receiving unit 401 stores the received case classification and stores the case classification receiving unit 401.
Treats the stored case classification as accepted until the stored case classification is rewritten. s3
If the case classification acceptance unit 401 determines in 73 that the state change information is not information that the passenger has exited and became empty (NO), the process proceeds to s384 described below. Then, the case classification receiving unit 401 transmits the received data of the case classification factors in parallel to the actual data reading unit 403, the empty vehicle relation reading unit 217, and the actual vehicle relation reading unit 205. The actual data reading unit 403, which has received the data of the case separation factor from the case separation receiving unit 401, selects the data whose state has changed to wages from the demand actual data stored in the data server 55, which is the actual data storage means. Out of the (running change data), data that matches the case classification factor received is extracted. The performance data reading unit 403, for each wage starting from the extracted wage change data,
This fare is from the time when the previous fare was terminated by the passenger's disembarkation (after leaving the garage and opening the business, or in the case of the first fare for the first rent) until this fare is terminated by the passenger's disembarkation. It is regarded as one process, and each wage process is read as one data in a data bundle (s375). The actual data reading unit 403 transmits such a data bundle to the moving time determination unit 417 and the business type classification unit 413 of the expected amount calculation unit 411. The travel time determination unit 417 classifies each of the data bundles from the actual data reading unit 403 into the same riding area and alighting area, and then the traveling time determination unit 417 classifies these data areas into a boarding area and alighting area. The time taken from getting on and off the vehicle is extracted from the data bundles that are classified into the same items (groups).
Then, the travel time determination unit 417 sets the median value of the extracted times as the expected travel time from the boarding area to the disembarking area. By performing this for all districts as the boarding district and the unloading district, the traveling time determination unit 4 can calculate the expected traveling time from all districts to all districts (including movement within the same district).
17 is determined (s376). On the other hand, business type classification unit 4
13 classifies each data bundle according to whether the business form in the data bundle transmitted from the performance data reading unit 403 is flow or center vehicle dispatch (s377), and the data bundle whose business form is flow is flow rate fare performance determination unit 415. , The sending customer search time determining unit 419 and the sending ride time determining unit 421.
29, pick-up time determination unit 431, center boarding time determination unit 4
33.

As described above, the running fare performance determining unit 415
Determines the expected fare amount for each district from the received data bundle of the sales pattern, and the sink customer search time determination unit 419 determines the expected customer search time for each district from the received data bundle of the sales pattern And the sink boarding time determination unit 4
21 determines the expected boarding time for each district from the received data bundle of the flow of business (s378), and the expected fare amount, the expected customer search time, and the expected boarding time are transmitted to the flowing expected income amount calculation unit 423. It Anticipated income calculation part 4
23 is the expected fare amount for each district from the flow fare performance determination unit 415, the expected customer search time for each region from the flow customer search time determination unit 419, and the flow-on boarding time determination unit 421.
While receiving the expected boarding time for each district from,
It is possible to obtain information on which area the target taxi for which the current allocation plan should be made exists in, and the expected travel time to move from the area where the target taxi for which the current allocation plan is to be present to another area. The moving time determination unit 41
7, the expected income amount due to the sink is calculated from these pieces of information (s379). On the other hand, as described above, the center fare performance determination unit 429 determines the expected fare amount for each district based on the received business form data bundle of the center dispatch, and the intercepting vehicle time determination unit 431 determines that the received business form is center dispatch. The expected boarding time for each district is determined from the data bundle, and the center boarding time determination unit 433 determines the expected boarding time for each district from the data bundle of the received business form center dispatch (s380). The expected fare amount, the expected pick-up time, and the expected boarding time are transmitted to the center expected income calculation unit 437. The waiting time calculation unit 435 calculates the waiting time for each district as described above (s381).
Then, the calculated waiting time for each district is transmitted to the center expected income calculation unit 437. As described above, the center expected income calculation unit 437 is a case where the taxi as a target for which a layout plan is to be prepared is present in the area where it is,
The expected income amount per unit time when moving to each of the plurality of districts different from the district to which it currently belongs is calculated (s382). The center expected income calculation unit 437 notifies the expected income output unit 439 of each calculated expected income amount. The expected income output unit 439 collectively transmits the expected income amount of the sink in each district and the expected income amount of the business by the center vehicle dispatch in each district to the notification unit 441, and the notification unit 441 makes an arrangement plan. These expected income amounts are transmitted via radio to the taxi which is the target (s383). After that, it is judged whether or not the work is completed (s384), and when the work is completed (YE
S) The work is ended (end), and when the work is not ended (NO), the process returns to s371.

In this embodiment, the base 51 is configured by the two computers of the first base computer 53 and the second base computer 58, but the number of computers is appropriately set depending on the computer used. Needless to say, it may be determined, for example, it may be configured by only one computer or may be configured by three or more computers.

[Brief description of drawings]

FIG. 1 is a schematic configuration diagram showing a connection between a taxi, a sales office, and a base.

FIG. 2 is an external configuration diagram of a mounting body mounted on a taxi.

FIG. 3 is a schematic block diagram showing a hardware configuration of a main body.

4 is a functional block diagram of a main body realized by the hardware of FIG. 3 and a program recorded in a ROM.

FIG. 5 is a flowchart showing the operation of the main body.

FIG. 6 is a schematic block diagram showing a hardware configuration of a first base computer.

FIG. 7 is a schematic block diagram showing a hardware configuration of a second base computer.

8 is a functional block diagram of a first base computer realized by the hardware of FIG. 6 and a program recorded in a ROM.

FIG. 9 is a schematic diagram showing the relationship between business areas and districts.

FIG. 10 is a flowchart showing an operation of an actual vehicle relation determining unit in constant calculation.

FIG. 11 is a flowchart showing an operation of an actual vehicle relation determining unit in the verification.

12 is a functional block diagram of a second base computer realized by the hardware of FIG. 7 and a program recorded in a ROM.

FIG. 13 is a functional block diagram showing in detail an expected amount calculation unit.

FIG. 14 is a flowchart of the operation of the first base computer mainly regarding input of actual data, calculation of actual vehicle generation speed, and calculation of empty vehicle generation speed.

FIG. 15 is a flowchart of the operation of the first base computer mainly regarding information acquisition.

FIG. 16 is a flowchart of the operation of the first base computer mainly relating to determination of an actual vehicle relationship and an empty vehicle relationship.

FIG. 17 is a flowchart of the operation of the second base computer.

[Simple explanation of symbols]

11 Taxi (vehicle) 13 Global Positioning System (GP
S) 15 Data receiving unit 17 Display unit 19 Data writing unit 21 IC card (result storage medium) 23 Control unit 25 Cable 31 Sales office 33 Card reading unit 35 Sales office computer 37 Cable 41 Cable 51 Base 53 First base computer 55 Data Server 57 Internet 58 Second base computer 59 Cable 61 Main body 63 Main body 65 Image monitor 65a First image monitor 65b Second image monitor 67a, 67b, 67c, 67d, 67aa, 67ab
Status change buttons 69a, 69b Display data selection button 71 IC card recorder 101 Position acceptance unit 103 Time acceptance unit 105 Speed acceptance unit 107 Status acceptance unit 109 Charge calculation unit 111 Write data generation unit 113 Data reading unit 115 Data selection unit 117 Output unit 119 Arrangement plan receiver 121 Status transmitter 151a, 251a, 351a CPU 151b, 251b, 351b RAM 151c, 251c, 351c ROM 151d, 251d, 351d Interface 190 Business area 192 Area boundary 194 Non-business area 196 Area boundary 201 Demand Actual data acceptance unit 203 Actual vehicle relation determination unit 205 Actual vehicle relation reading unit 207 Actual vehicle occurrence speed calculation unit 209 Information importing unit 211 Variable factor acceptance unit 213 Rainfall information reading unit 215 Empty vehicle relation determination 217 Empty vehicle-related reading section 219 Empty vehicle occurrence speed calculation section 253, 353 CRT display 255, 355 Keyboard 401 Case classification acceptance section 403 Actual data read section 405 State position acceptance section 411 Expected amount calculation section 413 Business mode classification section 415 Flow rate results Determining unit 417 Travel time determining unit 419 Flowing customer search time determining unit 421 Flowing boarding time determining unit 423 Flowing expected income calculation unit 425 Waiting number grasping unit for each region 429 Center fare actual result determining unit 431 Interception time determining unit 433 Center boarding time determination Unit 435 Standby time calculation unit 437 Center expected income amount calculation unit 439 Expected income output unit 441 Notification unit

─────────────────────────────────────────────────── ─── Continuation of the front page (56) References JP-A 64-4885 (JP, A) JP-A 7-6296 (JP, A) JP-A 8-87699 (JP, A) JP-A 9- 153098 (JP, A) JP 9-282597 (JP, A) JP 9-330497 (JP, A) JP 11-283186 (JP, A) (58) Fields investigated (Int.Cl. ⁷ , DB name) G08G 1/123 G08G 1/00 G06F 17/60 G07C 5/00 G07B 11/00-17/04

Claims (17)

(57) [Claims] Claims: 1. A system for supporting the planning of an arrangement plan of vehicles to be placed in a plurality of districts, and demand record data regarding operating hours and income of the vehicles corresponding to predetermined cases for each district. A result data storage means, a case classification acceptance means for accepting the case classification corresponding to the layout plan to be planned, a position acceptance means for accepting the district to which the vehicle currently belongs, and a case classification acceptance means In addition, corresponding to the case classification, actual result data reading means for reading the demand actual result data from the actual result data storage means, a case in which the vehicle remains in the area to which the vehicle currently belongs accepted by the position accepting means, If you move to each of the different districts from the current district, and the expected amount of income per unit time of An expected value calculation means for calculating using 該需 main record data read by the achievements data reading means, comprising a vehicle arrangement planning support system. 2. The case classification factor includes at least two types of business forms of a sink and a center vehicle dispatch, and the expected income amount is calculated for each business form. The vehicle layout planning support system described in. 3. In the case where the business form is sinking, the demand result data includes data for determining a fare actual amount, a sink location moving time, a customer search time, and a boarding time, and the expected income amount is a fare result. Forehead / (Sinking place moving time +
The vehicle layout planning support system according to claim 2, which is calculated by (customer search time + boarding time). 4. When the business form is center dispatch, the demand actual data includes data for determining a fare actual amount, a center location moving time, a waiting time, a pick-up time, and a boarding time, and the expected income amount is The vehicle placement plan planning support system according to claim 2 or 3, which is calculated by the actual fare amount / (center location moving time + waiting time + pickup time + ride time). 5. The waiting time is the number of vehicles currently waiting in each district, the expected travel time of the vehicle from each of the districts currently belonging to each district, and passengers in each district. The actual vehicle generation speed, which is the frequency per unit time of becoming an actual vehicle, and the empty vehicle speed, when the passenger gets off from the actual vehicle state and becomes an empty vehicle, becomes a standby state waiting for center dispatch in each district The vehicle placement planning support system according to claim 4, which is determined by using the generation speed. 6. An actual vehicle generation speed storage means for storing the actual value of the actual vehicle generation speed for each actual vehicle case classification which is a case classification based on a factor including at least a part of the case classification factors, and influences the demand of the vehicle. The actual value of the variation factor indicating the degree of the variation factor is stored for each actual vehicle case, and the variation stored in the actual vehicle variation factor result storage unit for each actual vehicle case An actual vehicle relationship determining means for obtaining an actual vehicle relationship, which is a relationship between the variable factor and the actual vehicle generated speed, from the actual value of the factor and the actual value of the actual vehicle generated speed stored in the actual vehicle generated speed storage means, and the actual vehicle relationship determining means. An actual vehicle relationship storage means for storing the actual vehicle relationship obtained by the above for each actual vehicle case, and a variation factor acceptance means for accepting a planned value of the variation factors corresponding to the layout plan to be planned. An actual vehicle relationship reading unit that reads the actual vehicle relationship from the actual vehicle relationship storage unit and that corresponds to the case classification received by the case classification receiving unit; and a plan value of the variation factor accepted by the variation factor acceptance unit and the The vehicle according to claim 5, further comprising: an actual vehicle generation speed calculating means for calculating an actual vehicle generation speed using the actual vehicle relationship read by the actual vehicle relationship reading means; Placement planning support system. 7. A vacant vehicle generation speed storage means for storing the actual value of the vacant vehicle generation speed for each vacant vehicle case classification, which is a case classification due to a factor including at least a part of the case classification factors, and an influence on the demand of the vehicle. The empty vehicle variation factor result storage means for storing the actual value of the variation factor indicating the degree of the variation factor for each empty vehicle case, and the variation stored in the empty vehicle variation factor result storage means for each empty vehicle case An empty vehicle relationship determining means for obtaining an empty vehicle relationship which is a relationship between the variable factor and the empty vehicle occurrence speed from the actual value of the factor and the actual value of the empty vehicle occurrence speed stored in the empty vehicle occurrence speed storage means, and the empty vehicle relationship determining means. Empty vehicle relationship storage means for storing the empty vehicle relationship determined by the above for each empty vehicle case, and variable factor acceptance means for accepting the planned value of the variable factors corresponding to the layout plan to be planned. An empty vehicle relationship reading unit that reads the empty vehicle relationship from the empty vehicle relationship storage unit and that corresponds to the case classification received by the case classification receiving unit; The empty vehicle generation speed calculating means for calculating an empty vehicle generation speed using the empty vehicle relation read by the empty vehicle relation reading means, and an empty vehicle simulation means including: Vehicle placement planning support system. 8. The vehicle placement plan planning support system according to claim 1, further comprising notifying means for notifying the vehicle of the expected income amount calculated by the expected amount calculation means. . 9. A computer-readable recording medium recording a program for causing a computer to execute the function as the vehicle layout planning support system according to any one of claims 1 to 8. 10. A method for assisting the planning of a placement plan of vehicles to be placed in a plurality of districts by using a computer, wherein the computer corresponds to each of the districts corresponding to a predetermined case classification. A performance data storage step of storing demand performance data relating to operating hours and income; a case classification reception step of receiving the case classification corresponding to the layout plan to be planned; a position reception step of receiving the district to which the vehicle currently belongs, A result data reading step for reading the demand result data stored by the result data storing step, which corresponds to the case classification received by the case classification receiving step, and the vehicle received by the position reception step, The existing district as it is, and the district to which the current district belongs among the plurality of districts The expected amount of revenue per unit of time in the case, to go to each of the different each district,
An expected amount calculation step of calculating using the demand record data read by the record data read step, and a vehicle layout planning support method. 11. The case classification factor includes at least two types of business forms of a sink and a center dispatch, and the expected income amount is calculated for each business form. The vehicle layout planning support method described in. 12. When the business form is a sink, the demand result data includes data for determining a fare record amount, a sink location travel time, a customer search time, and a boarding time, and the expected income amount is a fare record. Forehead / (Sinking place moving time +
The vehicle layout planning support method according to claim 11, which is calculated by (customer search time + boarding time). 13. When the business form is center dispatch, the demand result data includes data for determining a fare actual amount, a center location moving time, a waiting time, a pick-up time, and a boarding time, and the expected income amount is The vehicle layout planning support method according to claim 11 or 12, which is calculated by the fare actual amount / (center location moving time + waiting time + pickup time + ride time). 14. The waiting time is the number of vehicles currently waiting in each district, the expected travel time of the vehicle from each of the districts currently belonging to each district, and passengers in each district. The actual vehicle generation speed, which is the frequency per unit time of becoming an actual vehicle, and the empty vehicle speed, when the passenger gets off from the actual vehicle state and becomes an empty vehicle, becomes a standby state waiting for center dispatch in each district The vehicle placement planning support method according to claim 13, which is determined by using the generation speed. 15. An actual vehicle generation speed storing step of storing the actual value of the actual vehicle generation speed for each actual vehicle case classification, which is a case classification by a factor including at least a part of the case classification factors, and an influence on the demand of the vehicle. The actual vehicle variable factor actual result storing step of storing the actual value of the variable factor indicating the degree of the variable factor for each actual vehicle case, and the variation stored in the actual vehicle variable factor actual result storing step for each actual vehicle case An actual vehicle relationship determining step of obtaining an actual vehicle relationship which is a relationship between the variable factor and the actual vehicle generated speed from the actual value of the factor and the actual value of the actual vehicle generated speed stored in the actual vehicle generated speed storing step; An actual vehicle relationship storing step of storing the actual vehicle relationship determined by the above for each actual vehicle case, and the variation corresponding to the layout plan to be planned. A variable factor acceptance step of accepting a planned value of a factor, an actual vehicle relation reading step of reading out the actual vehicle relation stored in the actual vehicle relation storage step corresponding to the case classification accepted by the case classification acceptance step, and the variation An actual vehicle generation speed calculation step for calculating an actual vehicle generation speed using the planned value of the fluctuation factor received in the factor reception step and the actual vehicle relationship read in the actual vehicle relationship reading step; 15. The vehicle layout planning support method according to claim 14, wherein the computer further executes the method. 16. An empty vehicle generation speed storing step of storing the actual value of the empty vehicle generation speed for each empty vehicle case classification, which is a case classification by a factor including at least a part of the case classification factor, and an influence on the demand of the vehicle. The variable value actual result storage step of storing the actual value of the variable factor indicating the degree of the variable factor for each empty vehicle case, and the variation stored in the empty vehicle variable factor result storage step for each empty vehicle case An empty vehicle relationship determining step for obtaining an empty vehicle relationship which is a relationship between the variable factor and the empty vehicle occurrence speed from the actual value of the factor and the actual value of the empty vehicle occurrence speed stored in the empty vehicle occurrence speed storing step; A vacant vehicle relationship storing step of storing the vacant vehicle relationship obtained by the above for each case of the vacant vehicle, and the fluctuation corresponding to the arrangement plan to be planned A variable factor receiving step of receiving a planned value of a factor, an empty vehicle relationship reading step of reading out the empty vehicle relationship stored in the empty vehicle relationship storing step corresponding to the case classification received by the case classification receiving step, and the variation A vacant vehicle generation speed calculation step for calculating a vacant vehicle generation speed using the planned value of the variation factor received in the factor reception step and the vacant vehicle relation read in the vacant vehicle relation reading step, 16. The method according to claim 14, further comprising:
The vehicle layout planning support method described in. 17. The computer further performs a notification step of notifying the vehicle of the expected income amount calculated by the expected amount calculation step.
The vehicle layout planning assistance method according to any one of 0 to 16.