JP5671748B2 - Transfer time calculation system and transfer time calculation method - Google Patents

Description

  The present invention relates to a computer system for generating information related to a railway user and a railway station, and more particularly to a technique for analyzing a transfer in a station premises of a railway user from use history data of an IC card ticket.

  When heading for the first place using a transportation means such as an airplane, a train, or a bus, a method for searching for a route from a departure place to a destination using a route search system or the like is widely used. In a train transfer guidance by a general route search system, in the case of a search result including a transfer, the time when the train arrives at the transfer station and the departure time of the train after the transfer are presented. Between the arrival time of the train before the transfer and the departure time of the train after the transfer actually includes the time to move within the station and the time to wait for the next train. However, in the route search system, the method of presenting the total time is the mainstream, so the user often does not know the time to actually walk inside the station.

  Furthermore, the travel time in the station premises used in the transfer guidance system is generally determined for each company that provides a transfer search engine. This travel time often relies on surveys by investigators, and it takes time to investigate and is not updated unless there is a major problem or change (for example, a change in passage due to construction of a station). There was a problem that it was not possible to cope with. For example, in a busy time zone such as morning and evening, it is considered that the transfer movement time is longer than that in a quiet time zone such as daytime, but such fine adjustment is generally not performed.

  By the way, with the advancement of wireless sensor devices, GPS, non-contact IC technology, etc., action history information extracted by acquiring the position and action data of people and objects in various industrial fields and analyzing the acquired data is marketed. It is used for such as. For example, since an identifier for uniquely identifying each card is given to an IC card ticket of a railway, the IC card boarding can be performed by associating the location of the ticket gate through which the IC card ticket has passed and the store where the ticket was purchased. It becomes possible to grasp the behavior of the ticket owner to some extent.

  On the other hand, in Patent Document 1, in a navigation system that searches and guides a route including a connection from a departure place to a destination using a transportation facility, the connection time at the connection place is optimized according to the actual situation. A system that performs route search and guides an optimum route is disclosed.

JP 2006-193020 A

  In the technique described in Patent Document 1 described above, from the viewpoint of route guidance, the route search is optimally calculated by statistically calculating the transfer time (transfer time) at a certain station and storing the calculated results. Turn into. However, since the user must enter the actual time required, it is difficult to avoid mistakes in the user's input and input of subjective values, and it is difficult to collect data over a long period of time. Therefore, it is difficult to investigate time-series changes.

  An object of the present invention is to efficiently and accurately calculate the transfer travel time in a station premises from the use history of an electronic ticket.

A typical example of the invention disclosed in the present application is as follows. That is, a transfer time calculation system configured by a computer having a processor and a memory, wherein a user of a transportation facility includes a travel log including an identifier of a route using the transportation facility and a traveling time of the route, and the transportation facility. The transfer pattern information including the route and the standard travel time from the boarding station to the stop station are retained, and the data of the same route as the route included in the transfer pattern information is extracted from the travel log and extracted. Statistical processing means for statistically processing the travel time of the obtained data and calculating a value representative of the characteristics of the extracted data, and the shortest travel time from the same route data as the route included in the transfer pattern information. a shortest time calculating means for determining, based on said calculated representative value and the shortest travel time, with a transfer time calculating means for calculating a transfer period, a time the shortest The calculation means extracts data of the same route as the route included in the transfer pattern information from the travel log, obtains the shortest travel time from the extracted data, and the minimum value of the shortest travel time is the standard value. If the travel time is greater than a value obtained by multiplying a predetermined positive value, the minimum value of the shortest travel time is set to a value obtained by multiplying the standard travel time by a predetermined positive value, and the transfer time calculating means From the value representative of the travel time of the route from the first station to the second station to the second station, the shortest travel time of the route from the first station to the third station, The transfer time at the third station is calculated by subtracting the shortest travel time of the route from the third station to the second station.

  According to the representative embodiment of the present invention, the transfer travel time in a station can be calculated efficiently and accurately.

It is a figure which shows the outline of a general station premises. It is a figure explaining the breakdown of the required time when moving by train from the station X to the station Y. It is a figure explaining the breakdown of the required time in the case of changing a train once at the station C when moving from the station A to the station B by a train. It is a figure explaining calculation of transfer walk movement time in a transfer station. 1 is an overall configuration diagram of an information processing system according to an embodiment of this invention. It is a figure explaining the data structure of position log data with ID. It is a figure explaining the data structure of purchase log data with ID. It is a figure explaining the structure of master data. It is a figure explaining the structure of movement log data. It is a figure explaining the procedure which produces | generates movement log data from the utilization log | history of a traffic system non-contact IC card. It is a figure explaining the combination of the station which can be utilized when calculating the transfer travel time in a transfer station. It is a figure explaining the data structure of a transfer pattern list. It is a figure explaining the process sequence which extracts the candidate of a transfer pattern. It is a figure explaining the data structure of the shortest time list. It is a figure explaining the data structure of a transfer movement time list. It is a figure which shows the process sequence which calculates | requires the shortest time of the movement pattern which does not include a transfer. It is a figure which shows the process sequence which calculates | requires the transfer movement time in a transfer station. It is a figure which shows the process sequence which calculates | requires a representative (average) value from the arrangement | sequence set in which time data were stored. It is a figure which shows the process sequence which evaluates the difference of the relative value of the calculated representative (average) transfer time, and actual transfer time. It is explanatory drawing which shows the example which totaled the transit time for every user. It is a figure which shows the example of a screen of the transfer movement time map for users. It is a figure which shows the example of a screen of the transfer time change graph for users. It is a figure which shows the example of the transfer route search screen for users. It is the figure which showed the example of the transfer route search result screen for users.

  With reference to FIGS. 1 to 22, an example of a method for calculating a transfer walking time in a transfer station according to an embodiment of the present invention and an example of a system that provides information to users and companies will be described.

  FIG. 1 is a diagram showing an outline of a station premises.

  In general, as shown by the flow line 102, the movement in the station premises is often on foot, and the user who enters from this station walks from the ticket gate 101 to the platforms 103 and 104 where the intended route arrives and departs. Moving. In addition, a user who changes the route at this station moves on foot from the home 103 to the home 104, for example.

  Depending on the station, there may be a plurality of passages between the ticket gate and the platform, or between the platforms. Those who frequently use such stations are considered to know empirically which ticket gates and passages are the closest and convenient.

  FIG. 2 is a diagram for explaining the breakdown of the required time when moving from the station X201 to the station Y202 by train.

The time required to get on the train through the ticket gate at station X201, move to station Y202, get off the train, and pass the ticket gate at station Y202 can be divided into the following four times.
Time required = Tx_in + Tw + Tr + Ty_out

  Here, Tx_in (211) is a travel time from the ticket gate of the station X201 to the platform where the train arrives, and Tw (212) is a time waiting for the train to arrive at the platform of the station X201. Tr (213) is the actual time of getting on the train, and Ty_out (214) is the travel time from getting off the train to exit the ticket gate of station Y202.

  In this case, the travel time (Tx_in (211)) from the ticket gate of the station X201 to the platform where the train arrives within the time required for the user who rushed to arrive at the destination as soon as possible, and the train The travel time (Ty_out (214)) from the exit to the exit of the station Y202 is the smallest (for example, close to 0). Furthermore, the breakdown of the time required for a user who has fortunately arrived at the station X201 and arrived at the platform is that the time to wait for the train to arrive at the platform (Tw (212)) is almost zero. Become.

  FIG. 3 is a diagram for explaining the breakdown of the required time when the train is transferred once at the station C205 when moving from the station A203 to the station B204 by train.

  Take the train through the ticket gate of station A203, get off the train at station C205, move on foot, change to another train, move to station B204, get off the train, and take time to pass the ticket gate of station 204 Time can be divided into the following seven times.

Time required = Ta_in + Tw1 + Tr1 + Tx + Tw2 + Tr2 + Tb_out
Here, Ta_in (215) is the travel time from the station A203 through the ticket gate to the platform where the train arrives, and Tw1 (216) is the time to wait for the train to arrive at the platform. In addition, Tr1 (217) is the time when the first train is actually taken, and Tx (218) gets off the first train at the station C205 and moves to the home where the next train comes. It is time until. Further, Tw2 (219) is a time for waiting for the second train to come at the home, and Tr2 (220) is a time for actually getting on the second train. Finally, Tb_out (221) is the travel time from when the second train gets off at the station B204 until the ticket gate of the station B204 is exited.

  In this case, the times Tr1 (217) and Tr2 (220) actually on the train are almost the same for all users except for the case where the express train and each station stop coexist. The other five times Ta_in (215), Tw1 (216), Tx (218), Tw2 (219), and Tb_out (221) have individual differences depending on the user, such as the degree of urgency of each person and the timing of the schedule. large. However, Ta_in (215), Tx (218), and Tb_out (221), which are times related to walking movement, are more likely to approach 0 as people who are in a hurry, as in the case described in FIG. Tw1 (216) and Tw2 (219), which are waiting times, are closer to 0 as people who get on the train without waiting luckily.

  FIG. 4 is a diagram for explaining the calculation of the transfer walking travel time 218 at the transfer station C when the train is changed once at the station C when moving from the station A 203 to the station B 204. In FIG. 4, the method of obtaining the transfer walking travel time Tx (218) at the transfer station C using the breakdown of the required time of the three travel patterns from the station A203 to the station B204, the station A203 to the station C205, and the station C205 to the station B204. Will be described.

  First, (1) in FIG. 4 is similar to the pattern shown in FIG. 3, the train passes through the ticket gate of station A203, gets off the train at station C, moves on foot, and transfers to another train to change the station. It is explanatory drawing at the time of moving to B204, getting off the train, and passing through the ticket gate of the station 204 to Tall_1 (224) as the total required time and Tall_1 (224) divided into seven times 215 to 221.

  FIG. 4 shows two movement patterns (2) and (3) arranged side by side. The time required to get on the train through the ticket gate of station A203, get off the train at station C205, and pass the ticket gate. The breakdown of the required time of Tall_2 (225) and the required time Tall_3 (226) from the train through the ticket gate of the station C205 to the train B204, getting off the train at the station B204 and passing through the ticket gate is shown.

  That is, in the movement pattern (2), the time Tall_2 (225) required for getting on the train through the ticket gate of the station A203, getting off the train at the station C205 and passing through the ticket gate is as shown in FIG. The travel time Ta_in (215) from the ticket gate to the platform where the train arrives, the time Tw1 (216) waiting for the train to arrive at the platform, the time Tr1 (217) that actually takes the train, There are four types of travel time Tc_out (222) until the train exits from the ticket gate of station C205. In addition, in the movement pattern (3), the required time Tall_3 (226) required to get on the train through the ticket gate of the station C205, get off the train at the station B204, and pass the ticket gate is also the train time after passing through the ticket gate of the station C205. Travel time Tc_in (223) to the home to come, time Tw2 (219) to wait for the train to arrive at the home, time Tr2 (220) actually getting on the train, and the ticket gate of station B204 after getting off the train It is divided into four movement times Tb_out (221) until leaving.

  Users with short travel times Tall_1 (224), Tall_2 (225), and Tall_3 (226) of these three movement patterns have a train waiting time close to 0 due to the arrival of the train when it arrives at the platform. As for the movement on the premises, it can be said that the movement was quick and efficient due to the proximity from the ticket gate to the home. Focusing on such short data, the travel time Ta_in (215), Tc_in (223) from the ticket gate of the station to the platform where the train arrives, and the time Tw1 (216) for waiting for the train to arrive at the platform , Tw2 (219) and the travel times Tc_out (222) and Tb_out (221) from the train at the target station to the exit of the ticket gate are considered to be close to 0 and have a small individual difference.

Then, take the train through the ticket gate of station A203, get off the train at station C, move on foot, change to another train, move to station B204, get off the train, and pass the ticket gate of station B204 From the shortest time of Tall_1 (224), get on the train through the ticket gate of station A203, take the shortest time of Tall_2 (225) to get off the train at station C205 and pass the ticket gate, and pass through the ticket gate of station C205 By taking the train and subtracting the minimum time of the time Tall_3 (226) required to get off the train at the station B204 and pass the ticket gate, the transfer walking travel time Tx (218) at the station C is obtained using the following equation. Can.
Tall_1- (Tall_2 + Tall_3) = Tx- (Tc_out + Tc_in)

  In the above equation, Tc_in (223) and Tc_out (222) are 0 in the shortest time between the movement pattern of getting on the train at station A203 and getting off at station C205 and the movement pattern of getting on the train at station C205 and getting off at station B204. Close value. Further, even when Tc_in (223) and Tc_out (222) are values that are not negligible, it is possible to relatively calculate the change in transfer walking time at station C.

  FIG. 5 is an overall configuration diagram of the information processing system according to the embodiment of this invention.

  The main components of the system are a contactless IC card (or a portable terminal incorporating an IC chip having an equivalent function) 106 possessed by a user 105, a ticket gate 101 installed at a station, a ticket gate The network 107 transmits data acquired in 101 to a server group. The server group includes a history server 111, a calculation server 112, and an information distribution server 113, and accumulates and analyzes use data of the non-contact type IC card 106. A detailed description of the non-contact IC card 106 and the ticket gate 101 will be omitted.

  When the user 105 holding the non-contact type IC card 106 passes the ticket gate 101, the ticket gate 101 collects position information including a user ID for identifying the IC card 106, a passage date and time, and the collected information is converted into the ticket gate. The data is stored in the machine 101 and transferred to the data server 108 at a predetermined timing.

  The data server 108 accumulates the data collected by the ticket gate 101 as original data. In addition, the data server 108 transmits necessary data to the history server 111 via the network 107 when the data is received or at a predetermined timing (for example, every hour, every other day). Data is collected in the same manner from card reader terminals, POS cash register terminals, vending machines, etc. installed in stations in the vicinity of the station or around the station other than the ticket gate 101, for example. For example, when a user 105 holding a non-contact type IC card 106 holds the card over a card reading terminal installed in a store, the card reading terminal gives a user ID, date, amount, etc. for identifying the IC card 106. The purchase information including it is accumulated and transferred to the data server 108 at a predetermined timing.

  The history server 111, the calculation server 112, and the information distribution server 113 included in the server group are connected to the network 107, and communicate with the user terminals 116 and 118 between the servers and between the ticket gates 101. Can do. In the present embodiment, the history server 111, the calculation server 112, and the information distribution server 113 are described as server groups. However, the functions of these server groups may be executed by one or a plurality of physical computers. .

  The history server 111 is a computer having a network interface, a CPU, a memory, and a storage unit, and receives user data collected by a terminal such as the ticket gate 101 from the data server 108 via the network 107, and stores the data. Recorded in the unit 121. The history server 111 includes an ID location log data 122 for storing each user's location history, an ID purchase log data 123 for storing a purchase history, basic master data 124 related to a station, and an ID location log. The movement log data 125 obtained by primarily processing the data 122 is stored. When the basic master data 124 related to the station is updated, it is input from the outside of the system and updated.

  The calculation server 112 generates movement data of the IC card user using the data stored in the history server 111, and calculates the movement time for each section and in the station premises. The calculation server 112 is a computer mainly including a network interface 138, a CPU 131, a memory 132, and a storage unit 133. The network interface 138 is an interface for connecting to the network 107. The storage unit 133 stores data such as a travel log generation program 134, a travel time calculation program 135 for each section, a station premises travel time calculation program 136, and statistical values and index values obtained by the calculation process. Part 137. The storage unit 133 is a non-volatile storage device such as a hard disk drive, a CD-ROM drive, or a flash memory, for example. Note that the storage unit 133 may divide and record various programs and various data in a plurality of recording devices.

  When each program group is executed, data to be analyzed is read from the history server 111 and temporarily stored in the memory 132, and the programs 134, 135, and 136 are read into the memory and executed by the CPU 131. Realize the function. The execution timing of these programs may be, for example, the timing requested by the user, new data added to the history server 111, or batch processing executed at a time determined every day.

  The information distribution server 113 is a computer that includes network interfaces 143 and 144, a CPU 145, a memory 146, and a recording unit 147. The network interfaces 143 and 144 are interfaces for connecting to the network 107. The recording unit 147 is a nonvolatile storage device such as a hard disk drive, a CD-ROM drive, or a flash memory, and records various programs and various data. The recording unit 147 may divide and record various programs and various data in a plurality of recording devices.

  The information distribution server 113 provides information such as station characteristic evaluation values and own behavior tendency to the portable information terminal 116 and the home or public information terminal 118 (users 115 and 117) via the Internet 114. . The recording unit 147 records the search processing program 142 and the information distribution program 143. The CPU 145 executes various functions of the information distribution server 113 by reading various programs recorded in the recording unit 147 into the memory and executing them. Specifically, by executing the search processing program 141, data is searched based on the conditions input by the user. Also, by executing the information distribution program 142, information processed for presentation to the user is distributed. These pieces of information are basically generated at the timing when each user accesses the information distribution server 113.

  6A and 6B are explanatory diagrams showing the structure of typical data stored in the history server 111 for one record.

  As shown in FIG. 6A, the ID-attached location log data 122 includes a log ID 241, a user ID 242 of the target user, a station ID 243 associated with information about which data reading terminal has passed, and a use time that has passed through the reading terminal. 244 and usage type 245 such as entry or exit. Here, the usage type is information indicating the type of processing such as “entrance” or “participation” in the case of a ticket gate or entry / exit gate log, and “purchase” in the case of a log for a merchandise sales terminal.

  Further, as shown in FIG. 6B, the purchase log data with ID 123 includes a log ID 251, a user ID 252 of the target user, a store ID 253 associated with information about which data reading terminal (product sales terminal) has passed, Information such as the use time 254 passing through the reading terminal and the nearest station ID 255 is included.

  The ID-added position log data 122 and the ID-added purchase log data 123 may be transmitted and stored each time new data is generated, or may be collected in a time zone (for example, midnight) when usage is reduced. May be sent. The history server 111 side performs storage processing in accordance with the log data transmission timing.

  FIG. 7 is an explanatory diagram showing the structure of the master data 124 stored in the history server 111.

  First, the station master 260, which is basic data related to a station, includes information such as a station ID 261 for identifying a station, a station name 262, a railway company 263, a location 264 such as an address, and a latitude / longitude 265. If there is a change in the configuration of stations and routes, data is added and modified as needed.

  The route master 270, which is basic data relating to the route, includes information such as a route ID 271 for identifying a route, a route name 272, a railway company 273, and a route type 274 for distinguishing between a normal train and an express train.

  A station / route relation master 280 that is basic data for associating a station and a route includes a route ID 281 for identifying the route, a station ID 282 of the station included in the route, a sequence number 283 for managing the sequence of the station, and a stop station Alternatively, it includes information such as a station type 284 for identifying whether the station is a passing station, and a required time 285 from the first station.

  Furthermore, the route master 290 that is basic data regarding the route includes a route ID 291 for identifying the route, an entrance station ID 292, an exit station ID 293, and information on the route IDs and transfer station IDs for the number of routes to be boarded. For example, in the case of taking the train only once in the movement from the entry station ID 292 to the entry station ID 293, the data is stored in the route ID 1 (294) indicating the route on which the ride is taken. In addition, when moving from the entrance station ID 292 to the exit station ID 293, when taking the train more than once, the route ID 1 (294) indicating the route to be boarded, the transfer station ID 1 (295) identifying the transfer station, and the next train to be boarded are shown. Data is sequentially stored in accordance with the value of the number of times of boarding 301, such as route ID2 (296).

  Further, the route master 290 includes information such as the number of times of boarding 301, the standard time 302, the shortest time 303, and the fare 304 indicating comprehensive information of the route. When there are a plurality of routes corresponding to the combination of the entry station ID 292 and the entry station ID 293, the route with the highest use frequency is generally assigned as the first route.

  Store data master 310 includes information such as store ID 311, store name 312, store address 313, operating company name 314, and nearest station ID 315. The operating company name 314 is the name of a business operator that operates the store. Further, the nearest station ID 315 can be associated with the station ID by the address information of the store. In addition to these pieces of information, for example, by storing data such as store scales and business types, it becomes possible to perform more diverse analysis.

  When there is a change, these master data 124 (for example, a station, a route, and a store) are input and updated from outside the system.

  FIG. 8 is an explanatory diagram showing the structure of the movement log data 125 stored in the history server 111.

  The movement log data 125 is data after primary processing generated from the ID-added position log data 122 and the ID-added purchase log data 123, and passes through a log ID 321 for identifying a log, a user ID 322 of a target user, and a ticket gate. The admission date and time 323 indicating the time of entering the station, the admission date and time 324 indicating the time of entry from the station after passing through the ticket gate, the admission station ID 325, the admission station ID 326, the payment amount 327 indicating the fee for the movement, the route It includes information such as a route ID 328 for associating with route information included in the master 290 and a purchase flag 329 indicating whether or not there is a purchase using the same IC card between the entry date 323 and the entry date 324. In addition to these pieces of information, for example, the movement log data 125 may include information on the purchased store and the nearest station of the store.

  FIG. 9 is a diagram illustrating a procedure for generating the movement log data 125 from the usage data of the traffic contactless IC card 106.

  The storage processing in the history server 111 will be described as being performed by batch processing once every day at a predetermined time.

  First, with reference to the user IDs 242 and 252 and the use times 244 and 254 included in the newly-added ID-added location log data 122 and ID-added purchase log data 123, all data are rearranged in order of user ID and time (step) 400).

  Next, the processing of steps 402 to 411 is repeated for the data rearranged in step 400 by the number of user IDs (step 401).

  First, the variables for storing the entrance station, the entry date / time, the entry station, the entry date / time and the purchase flag are initialized (step 402).

  Next, the data arranged in the order of time are taken out one by one, and case-separation processing is performed according to the value of the usage type 245 (step 403).

  When the value of the usage type 245 is “admission” (step 404), the value of the station ID 243 is set in the variable of the entrance station, the value of the usage time 244 is set in the variable of the entry date and time, and “0” is set in the variable of the purchase flag. Is set (step 405).

  On the other hand, when the value of the usage type 245 is “purchasing” (step 410), if the entry station and the entry date / time variable are set, “1” is set to the purchase flag variable, and the entry station and If no value is set in the entry date / time variable, this data is ignored and processing proceeds to the next data (step 411).

  When the value of the usage type 245 is “participation” (step 406), the value of the station ID 243 is set as the variable of the entry station and the variable of the entry date / time only when the values of the entry station and the entry date / time variable are set. The value of the use time 244 is set in (step 407). Further, the corresponding route is searched from the route master 290 using the values of the two variables of the entrance station and the entry station, and the matched route ID 291 is extracted (step 408). Finally, log ID, user ID, entry date / time, entry date / time, entry station ID, entry station ID, payment amount, and route ID information are stored in the movement log data 125 (step 409). Here, a serial number is set in the log ID 321.

  FIG. 10 is a diagram illustrating combinations of departure / arrival stations that can be used when calculating the transfer travel time at transfer station C.

  For example, when it is desired to determine the travel time for transferring from route 1 (360) to route 2 (361) at transfer station C (362), any station on route 1 (360) is entered and any of route 2 (361) is entered. A combination of departure and arrival stations 373 that participates in that station is selected. That is, when the stations S1 to S3 (363 to 365) are selected as the departure station area 371 and the stations E1 to E3 (366 to 368) are selected as the arrival station area 372, the transfer travel time at the transfer station C (362). Since the combinations 373 of departure / arrival stations that can be used when calculating the value are determined by all combinations of departure and arrival stations, nine combinations are possible in this figure.

  Note that combinations of departure / arrival stations that include routes that may pass through places other than the transfer station C (362) are desirably determined beforehand because the routes are not uniquely determined.

  Further, when selecting the combination of departure and arrival stations, it is possible to mechanically extract the combination of departure and arrival stations using the master data 124 by designating the target transfer station and the front and rear routes. .

  FIG. 11 is an explanatory diagram showing the data structure of the transfer pattern list 340.

  As described with reference to FIG. 10, the transfer pattern list 340 is data for managing a combination of departure and arrival stations for calculating transfer travel time at any transfer station. The transfer pattern ID 341, the transfer station ID 342, and the transfer numbers are serial numbers. Route IDs 343 of routes that get to the station, route IDs 344 of routes that get on from the transfer station, and route IDs (345, 348,...) For all combinations having the pattern of transferring from the route 343 to the route 344 at the transfer station 342. , Entry station ID (346,...) And entry station ID (347,...). That is, the transfer pattern list 340 includes a combination of a route ID, an entrance station ID, and an exit station ID corresponding to the number of patterns to be transferred from the route 343 to the route 344 at the transfer station 342.

  FIG. 12 is a diagram illustrating a processing procedure for extracting a transfer pattern candidate.

  The transfer pattern list 340 is stored in the storage unit 137 of the calculation server 112, and is generated and updated at the same timing as new storage and update of the route master 290 accumulated in the history server 111.

  First, all route information whose value of the number of boarding times 301 is 2 is extracted from all data of the route master 290 (step 500), and the table of the transfer pattern list 340 is initialized (step 501). By extracting route information with the number of boarding times of 2, it is possible to extract a route including only one transfer.

  Next, the processing of steps 503 to 507 is repeated one by one for all the route information extracted in step 500 (step 502).

  First, the combination of “transfer station ID 1 (295), route ID 1 (294), route ID 2 (296)” of the extracted route information is “transfer station ID 342, route 343 before transfer, route 344 after transfer” in the transfer pattern list 340. It is determined whether there is a record that matches the combination of "" (step 503).

  If the combination of the extracted route information does not exist in the transfer pattern list 340 (step 504), a new record is created in the transfer pattern list 340, and the transfer station ID 342, the pre-transfer route 343, the post-transfer route 344, and the route ID 1 (345). , Entry station ID1 (346), entry station ID1 (347), transfer station ID1 (295), route ID1 (294), route ID2 (296), route ID2, route ID2, entry station ID (292) of route master 290 ), The data of the participating station ID (293) are stored (step 505).

  On the other hand, when the combination of the extracted route information exists in the transfer pattern list 340 (step 506), the route ID of the route master 290, the entry of the route IDi, the entrance station IDi, and the exit station IDi of the corresponding transfer pattern list 340, An entry station ID and an entry station ID are added and stored (step 507).

  FIG. 13A and FIG. 13B are diagrams showing the structure of data for storing the values of the shortest time and the value of the transfer travel time for all combinations (movement patterns) of entrance stations and exit stations that do not include transfer.

  Similar to the transfer pattern list 340, the shortest time list 380 and the transfer travel time 390 are stored in the storage unit 137 of the calculation server 112, and the ID location log data 122 and the ID purchase log data 123 are stored in the history server 111. Newly accumulated and generated and updated at a timing when the movement log data 125 is updated (for example, at regular time intervals).

  As shown in FIG. 13A, the shortest time list 380 includes an entry station ID 381, an entry station ID 382, the shortest time data 383, a data start period 384, an end period 385, and a time zone used for obtaining the shortest time. Information such as 386.

  As shown in FIG. 13B, the transfer travel time list 390 is used to obtain a transfer station ID 391, a pre-transfer route 392, a post-transfer route 393, a transfer travel time data 394, a standard travel time data 395, and a transfer travel time 394. It includes information such as a start period 396 and an end period 397 of the used data and a time zone 398.

  Here, with respect to the items of the data start periods 384 and 396, the data end periods 385 and 397, and the time zones 386 and 398, a predetermined time unit (for example, a unit of one month, a unit of one hour, etc.) is set in advance by external input. It is set and classified according to the value of the entry time 323 or the entry time 324 of the movement log data 125 according to the set value.

  FIG. 14 is a diagram illustrating a processing procedure for obtaining the shortest time of a movement pattern that does not include transfer.

  The shortest time list 380 is stored in the storage unit 137 of the calculation server 112. The generation and update of the shortest time list 380 are performed at the same timing as the movement log data 125 stored in the history server 111 is newly stored and updated.

  First, all the route information whose value of the number of boarding times 301 is 1 is extracted from all the data of the route master 290 (step 600), and the processing of steps 602 to 608 is repeated for each extracted route information (step 601). By extracting the route information with the number of boarding times of 1, it is possible to extract a route that does not include a transfer and obtain the shortest time.

  In step 602, all data having the same entry date 323 (or entry date 324) and route ID 328 values are extracted from the movement log data 125, and the shortest time variable ST is set to the standard time 302 × constant value of the route master data. Initialization is performed (step 602).

  Here, the constant is a positive value and may be set in advance as a fixed value. The reason for setting an initial value multiplied by a positive constant value is that data is cut off by a value of standard time 302 × constant multiple so that an extremely long value is not extracted as the shortest time even in a section where the number of data is small. It is to make it. In addition, the data start period, end period, and time zone type are set in advance, and the same processing is performed for the combination of all set data start periods, end periods, and time zones. An example of processing when the data start period, end period, and time zone are determined is shown.

  In step 602, the day of the week may be added to the data extraction condition.

  Next, the processing in steps 604 to 607 is repeated for all the movement log data extracted in step 602 one by one (step 603).

  Specifically, referring to the values of the entry date 323 and the entry date 324 of the movement log data, the value obtained by subtracting the entry time from the entry time (entry time−entry time) is smaller than the value of the shortest time variable ST (step 604), a value obtained by subtracting the entry time from the entry time is set in the shortest time variable ST (step 605).

  On the other hand, when the value obtained by subtracting the entry time from the entry time is equal to or greater than the value of the shortest time variable ST (step 606), the next movement log data is processed (step 607).

  After the processing of Steps 604 to 607 is completed for all the movement log data, the entry of the entry station ID, entry station ID, shortest time variable ST, data start period, data end period, and time zone is displayed in the shortest time list 380. Is newly added (step 608).

  FIG. 15 is a diagram illustrating a processing procedure for obtaining a transfer travel time at a transfer station.

  The transfer travel time list 390 is stored in the storage unit 137 of the calculation server 112, and is generated and updated at the same timing as new storage and update of the travel log data 125 stored in the history server 111.

  First, all the data stored in the transfer pattern list 340 are extracted, and the processing of steps 701 to 713 is repeated one by one (step 700).

  Next, a variable of the average moving time list having an array structure is initialized (step 701).

  Next, the number of route IDs included in each data extracted from the transfer pattern list 340 is checked, and Steps 703 to 712 are repeated by the number of route IDs (Step 702).

  First, referring to the route ID item from the movement log data 125, all data including “route IDi” in the transfer pattern list data is extracted, and the variables of the required time list and the shortest time variables ST1 and ST2 are initialized (step) 703).

  Here, the data start period, end period, and time zone type may be set in advance. The same processing is performed for the combination of all set data start periods, end periods, and time zones. An example of processing when one data start period, end period, and time zone are determined will be described.

  In step 703, the day of the week may be added to the data extraction condition.

  Next, the processing in steps 705 to 708 is repeated one by one for all the movement log data extracted in step 703 (step 704). By this iterative process, Tall_1 (224) shown in FIG. 4 can be obtained.

  Specifically, the value obtained by subtracting the admission time from the admission time with reference to the value of the admission date / time 323, the value of the admission date / time 324 and the value of the standard time 302 of the route master 290 of the movement log data (entry time-entry time) Is smaller than the value of route standard time 302 × constant d (step 705), a value obtained by subtracting the entry time from the entry time is set in the required time list (step 706). Here, the constant d is a positive value, and may be set as a fixed value in advance. The reason for setting a positive fixed value for the constant d is that the data is cut off by the value of the route standard time 302 × the constant d so that an extremely long value is not extracted as the average movement time even in a section where the number of data is small. It is to make it.

  Further, by referring to the value of the purchase flag included in the movement log data 125 and limiting to data that is highly likely not to be purchased during movement, the ratio of data that has been purely moved is increased, The accuracy of the average value of the required time can be increased. Furthermore, when there are a plurality of routes from the departure station to the arrival station, the route used can be determined using the value of the nearest station in the purchase information.

  On the other hand, when the value obtained by subtracting the entry time from the entry time is larger than the route standard time 302 × the constant d (step 707), the next movement log data is processed (step 708).

  After the processing of steps 705 to 708 is completed for all the movement log data, the average time T_ave is calculated using the data of the required time list (step 709). A method for calculating the average time T_ave will be described later.

  Next, referring to the value of the entry station ID 381 and the value of the entry station ID 382 from the shortest time list 380, the value of the entry station ID 346 of the currently set transfer pattern list 340 and the value of the entry station ID 381 of the shortest time list 380 are set. Are further extracted, and data in which the value of the transfer station ID 342 in the transfer pattern list 340 matches the value of the entry station ID 382 in the shortest time list 380 is extracted, and the value of the shortest time 383 is set in the variable ST1 (step ST1). 710).

  Similarly, referring to the value of the entry station ID 381 and the value of the entry station ID 382 in the shortest time list 380, the value of the transfer station ID 342 in the currently set transfer pattern list 340 and the value of the entry station ID 381 in the shortest time list 380 are set. Are further extracted, and data in which the entry station ID 347 in the transfer pattern list 340 and the entry station ID 381 in the shortest time list 380 match are extracted, and the value of the shortest time 383 is set in the variable ST2 (step 711). .

  Next, a value (T_ave− (ST1 + ST2)) obtained by subtracting the sum of the shortest time variables ST1 and ST2 from the average time T_ave is calculated and added to the variable in the average movement time list (step 712).

  After the repetition processing is completed, a representative average travel time is calculated from the average travel time list and stored in the item of the transfer travel time 394 of the corresponding data in the transfer travel time list 390 (step 713). The value of the standard transfer travel time 395 is also calculated in the same manner as the transfer travel time 394 described above and stored in the standard time 302 in the route master 290. Since the standard transfer travel time 395 is obtained by calculating a representative average travel time, detailed description thereof is omitted. Here, a method for obtaining a representative average moving time will be described later.

  FIG. 16 is a diagram illustrating a processing procedure for obtaining a representative (average) value from an array set in which time data is stored.

First, an average value μ and a standard deviation σ are calculated from the entire array set in which time data is stored (step 800). As a formula for obtaining the average value and the standard deviation, a general formula can be used. When the number of data is N and the data is X1, X2,... Xn, the formula can be obtained by the following formula.
Average μ = (X1 + X2 + X3 +... + Xn) / N
Standard deviation [sigma] = sqrt {{(X1- [mu]) <2 +> (X2- [mu]) <2 +> + .. + (Xn- [mu]) 2} / N}

  Next, the processing in steps 802 to 803 is repeated for the elements of the array set in which the time data is stored (step 801).

  First, the value of the time data is referred to, and if the value is smaller than the average value μ−standard deviation σ × constant or larger than the average value μ + standard deviation σ × constant (step 802), the time data is outlier. Are deleted from the array set in which the original time data is stored (step 803). If this constant value is small, an outlier is judged severely and a lot of data is excluded.

  After the repetition processing is completed, a value representative of the group (for example, an average value, a median value, etc.) is calculated from the remaining time data array set, and the transfer travel time 394 and the standard transfer travel time 395 in the transfer travel time list 390 are calculated. Data is newly stored in the item.

  FIG. 17 is a diagram illustrating a processing procedure for evaluating the difference between the calculated relative value of the representative (average) transfer travel time and the actual transfer travel time.

  First, all the records stored in the transfer travel time list 390 are extracted, and a variable diff corresponding to the average difference is initialized (step 850).

  Next, the processing in steps 851 to 852 is repeated for the extracted records. The value of the transfer movement time 394 of the extracted transfer movement time list data is set in the variable T_ave. Further, the value of the standard transfer travel time 395 is set to the variable T_def (step 851).

  Then, the absolute value of the value obtained by subtracting T_def from T_ave (T_ave−T_def) is added to the variable diff (step 852).

  After the repetition processing is completed, the variable diff is divided by the number of records extracted from the transfer travel time list 390 to obtain an average difference value between the transfer travel time 394 and the standard transfer travel time 395 (step 853). If the standard transfer travel time 395 has a high accuracy and the value of this difference is sufficiently reliable, the absolute value of the transfer travel time can be increased by adding the average difference value to the transfer travel time 394. Can be obtained.

  FIG. 18 shows an example in which transit times are tabulated for each user.

The transit times of all users are tabulated for each user, and the users are classified based on the transit tendency of users who have a transit count of a predetermined number or more. As an example of classification, for example,
a. A person who makes a connection in a short time (eg, always close to the shortest) b. A person who makes a slow connection in a long time c. A person whose tendency changes greatly depending on the time of day or day of the week, and a person who does not change d. It can be classified as a person who has a difference between a frequently used station (area) and a station that is not frequently used, and a person who has no difference.

  With such a classification, it is possible to infer the usage tendency related to the transfer for each user and use it for guidance, guidance, and the like based on the user's tendency.

  FIG. 19 is an example of a screen generated and distributed by the information distribution server 113, and is a diagram illustrating a screen example of a user transfer travel time map.

  In the screen example shown in FIG. 19, station A910, station B911, station C912, station D913, station E914, station F915, station G916, station H917, route 1 (900), route 2 (901) and route 3 (902) are displayed. A map containing the map is displayed. According to this schematic map, station C912 and station E914 are transfer stations. For example, at the transfer station C912, the train travels from the direction of the A station 910 and travels toward the station B911 via the station C912. The train travels from the station B911 and travels through the station C912 toward the station A910. A pattern that moves from the station B911 and travels to the station D913 via the station C912, and a train that travels from the station D913 and travels to the station B911 via the station C912 There are four directions of pattern transfer. That is, different values are also calculated for the transfer walking time in the direction of four transfers. By displaying the transfer time in an easy-to-understand manner for each pattern, it is possible to provide a screen on which the transfer time required for each direction can be intuitively grasped.

  FIG. 20 is a diagram illustrating an example of a screen generated and distributed by the information distribution server 113, and a screen example of a transfer time change graph for users.

  In the screen example shown in FIG. 20, for example, the transfer travel time is set on the vertical axis 1000 and the time is set on the horizontal axis 1001, and the result of calculating the transfer walk travel time for each time zone is displayed in a graph 1002. By displaying the transfer walking travel time in a graph by time zone, it is possible to estimate the change in transfer travel time and the degree of congestion by time zone.

  In addition, by representing the transfer walking travel time in the daytime period as 1 and expressing the transfer walking travel time in other time periods as a ratio, it is possible to intuitively grasp the time transition of congestion.

  Further, by calculating the rate of increase / decrease in the walking time for transfer between the daytime and morning / evening hours, it can be compared with the congestion level of other stations.

  Information for generating the screens of FIGS. 19 and 20 is stored in the storage unit 137 of the calculation server 112, and the users 115 and 117 access the predetermined Web page using the information terminals 116 and 118. The search processing program 141 is executed according to the conditions specified by selecting a station or area using a pull-down menu or the like, and necessary information is acquired. The information distribution program 142 edits the information acquired by the search processing program 141 and distributes the information to the information terminals 116 and 118.

  FIG. 21 is a diagram illustrating an example of a transfer route search screen 1100 for a user that is generated and distributed by the information distribution server 113.

  On the transfer route search screen 1100 distributed from the server 113, the search processing program 141 is executed in response to the conditions specified by the users 115 and 117, the information distribution program 142 edits the search result, and the information terminals 116 and 118 Delivered to.

  First, the users 115 and 117 use the information terminals 116 and 118 to select display contents from, for example, a pull-down menu on a Web browser screen. These display conditions can be set by the users 115 and 117 using an input interface such as a setting screen or a mouse or a keyboard.

  For example, the users 115 and 117 input the departure station 1101, arrival station 1102, date 1103, time 1104, type 1105 for selecting departure time or arrival time, and search result display order 1106 on the transfer route search screen 1100. Or select. Note that the date and time are set in advance as the current date and time, and initial values are set when the user does not select them. The information terminals 116 and 118 transmit the designated condition to the search processing program 141.

  The display order on the transfer route search screen is generally the order of time required, the order of the amount of money, etc., but by using the calculation result of the transfer walking travel time in the transfer station premises according to the present invention, the search results are displayed in the order of walking travel time. Can be displayed. This is an optional function that sorts the search results in ascending order of time for walking to the user who wants to reduce walking.

  Furthermore, it is possible to introduce an optional function for displaying in order of routes with a low degree of congestion using the result of the walking time for transfer walking by time zone.

  FIG. 22 is a diagram showing an example of a user transfer route search result screen 1200 generated and distributed by the information distribution server 113, and shows a screen in which the search results are rearranged in ascending order of walking time.

  The search processing program 141 is executed according to the menu selected by the users 115 and 117 on the transfer route search screen 1100 using the information terminals 116 and 118, and the distribution program 142 edits and distributes the search results.

  As a result of executing the search processing program 141 under the condition that the departure place is A station and the arrival station is B station, a pattern of changing at C station and a pattern of changing at D station are extracted. The distribution program 142 rearranges the search results in ascending order of walking time, generates a screen in which the pattern for changing at the C station is route 1 and the pattern for changing at the D station is route 2 and distributes the screen to the user.

  In the embodiment of the present invention, an example in which the use history of a traffic non-contact IC card is used to obtain the transfer walking time is shown. In addition to this, the location information and purchase history acquired by a mobile phone or the like are used. By performing analysis together, it is possible to obtain a transfer time with improved accuracy and quality.

  As described above, according to the embodiment of the present invention, the behavior data of the station user obtained from the history information (train getting-on / off data) of the traffic system IC card used by many people every day is analyzed. As a result, the transfer travel time in the station can be obtained more accurately.

In particular, the shortest travel time of the route from station A to station C and the shortest travel time of the route from station C to station B are subtracted from the average travel time of the route from station A to station C to station B. Therefore, since the transfer time at station C is calculated,
In addition, since the shortest travel time is obtained by excluding data whose minimum travel time is much larger than the standard travel time, extremely long values are not extracted as the shortest time even in sections where the number of data is small. Travel time can be determined.

  In addition, since the average travel time is obtained by excluding data whose travel time is much longer than the standard time, an extremely long value is not extracted as the average travel time even in a section with a small number of data, and an appropriate average travel time is obtained. Can do.

  In addition, when calculating transfer travel time, detailed travel time can be calculated according to conditions such as by direction, weekday / holiday, time zone, season, etc., so the degree of congestion in each condition can be indexed It is possible to distribute information according to the user's request.

  Further, by analyzing the change in transfer travel time, it is possible to provide information reflecting the change in the station structure and the behavior tendency of the station user.

  Furthermore, it is possible to provide transfer guidance that ranks according to the size of the transfer travel time based on the transfer travel time of the transfer station obtained by the method of the embodiment of the present invention for a user who wants to reduce travel on foot. And such a transfer guidance program can be provided.

  Although the embodiments of the present invention have been described above, it will be understood by those skilled in the art that the present invention is not limited to the above-described embodiments and can be implemented with various modifications.

101 ticket gate 106 IC card 107 network 108 data server 111 history server 112 calculation server 113 information distribution server 114 Internet 115, 117 users 116, 118 information terminal

Claims (8)

A transfer time calculation system configured by a computer including a processor and a memory,
The travel user includes a travel log including the identifier of the route using the transport and the travel time of the route, transfer pattern information including the route of the transport, and a standard travel time from the boarding station to the stop station. And hold
Statistics for extracting data of the same route as the route included in the transfer pattern information from the movement log, statistically processing the movement time of the extracted data, and calculating a value representative of the characteristics of the extracted data Processing means;
From the data of the same route as the route included in the transfer pattern information, the shortest time calculation means for obtaining the shortest travel time;
A transfer time calculating means for calculating a transfer time based on the calculated representative value and the shortest travel time;
The shortest time calculation means includes:
Extract the data of the same route as the route included in the transfer pattern information from the travel log,
Of the extracted data, find the shortest travel time,
If the minimum value of the shortest travel time is greater than a value obtained by multiplying the standard travel time by a predetermined positive value, the minimum value of the shortest travel time is multiplied by a predetermined positive value. Set to
The transfer time calculation means calculates the route from the first station to the third station from a value representative of the travel time of the route from the first station to the third station. A transfer time calculation system characterized in that the transfer time at the third station is calculated by subtracting the shortest transfer time and the shortest transfer time of the route from the third station to the second station.   2. The transfer time calculation system according to claim 1, wherein the statistical processing unit does not use, for the statistical processing, data in which the travel time of the route is equal to or longer than a predetermined time.   The transfer time calculation system includes:
  Holds route information including data on the number of rides at the transfer station, transfer station, get-off station and route,
  The transfer pattern information generating means for extracting data with the number of times of boarding twice from the route information and adding the route of the extracted data to the transfer pattern information. Transfer time calculation system.   The travel log includes the date and time of entering or leaving the station to use the transportation,
  The statistical processing means and the shortest time calculating means accept input of at least one parameter of time zone, season and day of the week,
  The statistical processing means extracts, from the travel log, data in which the route is the same, and the received parameter and the entry date / time or entry date / time match.
  The shortest time calculation means obtains the shortest travel time of data in which the route is the same and the received parameter matches the entry date / time or entry date / time. The transfer time calculation system according to any one of the above.   A transfer time calculation method executed in a transfer time calculation system configured by a computer including a processor and a memory,
  The transfer time calculation system includes a travel log including a route identifier used by a transportation user and a travel time of the route;
Holding the transfer pattern information including the route of the transportation and the standard travel time from the boarding station to the getting-off station,
  The method
  Statistics for extracting data of the same route as the route included in the transfer pattern information from the movement log, statistically processing the movement time of the extracted data, and calculating a value representative of the characteristics of the extracted data Processing steps;
  From the data of the same route as the route included in the transfer pattern information, the shortest time calculation step for obtaining the shortest travel time;
  A transfer time calculating step of calculating a transfer time based on the calculated representative value and the shortest travel time;
  In the shortest time calculation step,
  Extracting the same route data as the route included in the transfer pattern information from the travel log,
  Of the extracted data, find the shortest travel time,
  If the minimum value of the shortest travel time is greater than a value obtained by multiplying the standard travel time by a predetermined positive value, the minimum value of the shortest travel time is multiplied by a predetermined positive value. Set to
  In the transfer time calculation step, from the value representative of the travel time of the route from the first station to the third station and changing to the second station, the route from the first station to the third station is calculated. A transfer time calculation method, wherein the transfer time at the third station is calculated by subtracting the shortest travel time and the shortest travel time of the route from the third station to the second station.   6. The transfer time calculation method according to claim 5, wherein, in the statistical processing step, data whose moving time of the route is a predetermined time or longer is not used for the statistical processing.   The transfer time calculation system holds route information including data of the number of times of transfer at a transfer station, transfer station, alighting station, and a route,
  6. The method according to claim 5, further comprising: a transfer pattern information generating step of extracting data having two boarding times from the route information and adding the route of the extracted data to the transfer pattern information. 6. The transfer time calculation method according to 6.   The travel log includes the date and time of entering or leaving the station to use the transportation,
  In the statistical processing step and the shortest time calculating step, an input of at least one parameter of time zone, season and day of the week is accepted,
  In the statistical processing step, the route is the same, and data in which the accepted parameter matches the entry date / time or the entry date / time is extracted from the travel log,
  8. The shortest time calculation step, wherein the shortest travel time of data in which the route is the same and the received parameter coincides with the admission date or time is determined. The transfer time calculation method according to any one of the above.

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