JP6700784B2 - Travel time estimation system and travel time estimation method - Google Patents

Description

  The present invention relates to a travel time estimation system and a travel time estimation method for estimating a travel time required to travel in a predetermined section.

  Conventionally, when large-scale events such as shrines and shrines, outdoor concerts and expositions are held, it is necessary to prepare for unexpected situations as well as crowds of visitors inside and around the venue. Therefore, security companies often carry out security.

  For this reason, there is known a conventional technique in which a security company places security guards in a predetermined place in and around the venue according to a security plan. For example, in Patent Document 1, a security company formulates a security plan for an event, assigns security guards to each security officer, and causes each security officer to carry a mobile phone that can access a server of a host computer. An event security system is disclosed that enables a company to grasp the data of the number of people getting off at each event venue in real time.

  By using the Patent Document 1, it becomes possible for the security company and the security staff to grasp the trend of visitors to the event site and perform security according to the number of visitors.

JP-A-2002-297757

  However, although the above-mentioned Patent Document 1 can grasp the total number of visitors, it cannot detect the congestion that occurs locally. For example, when congestion occurs in a specific section, security guards should be placed in such sections, the passage of such sections should be restricted, and visitors should be guided to other sections, depending on the situation. Appropriate security is required, but the actual situation is that such judgment of the situation is left to the security staff and the person in charge.

  Therefore, it has been required to accurately grasp the pedestrian congestion situation in a specific section in real time. As an index of the congestion situation, it is effective to estimate the travel time required to travel in a predetermined section.

  In the case of a vehicle traveling on a highway, it is possible to estimate the travel time required to travel in a predetermined section with relatively high accuracy. However, in the case of a pedestrian, it is difficult to estimate the travel time because it has characteristics such as a high degree of freedom of movement and a variety of behaviors such as stopping and stopping at a store.

  For these reasons, it is an important issue how to accurately estimate the travel time required for traveling in a predetermined section in consideration of the characteristics of pedestrians. It should be noted that such a problem is not limited to pedestrians, and similarly occurs in other moving bodies such as bicycles and vehicles passing through the street.

  The present invention has been made in order to solve the above-mentioned problems of the prior art, and is a travel time estimation system and travel time estimation capable of accurately estimating the travel time required for a mobile body to move in a predetermined section. The purpose is to provide a method.

To solve the above problems and achieve the object, the present invention is a corresponding plurality of mobile bodies and a passing time of a predetermined measurement value of the movement time required for the movement of the segment and the predetermined section with a mobile terminal A collection unit that collects each attached measurement information, and a selection unit that selects a plurality of measurement information from the measurement information collected by the collection unit, based on the characteristics of the moving body that is the estimation target of the traveling time, The measurement value of the travel time for each passage time included in each measurement information selected by the selection unit is weighted, and the movement at a predetermined time is based on the moving average of the weighted measurement values of the travel time. And a calculating unit that calculates an estimated value of the moving time of the moving body that is the target of time estimation , wherein the calculating unit approximates a variation in the measured values of the moving time included in the measurement information to a normal distribution, the weights of the weighted with the deviation from the mean of the distribution and wherein the Sageruko.

Further, in the present invention according to the above invention, the selection unit uses a lower limit and/or an upper limit set for the traveling time as a characteristic of the moving body, and a measured value of the traveling time is the lower limit and/or the upper limit. It is characterized in that the plurality of pieces of measurement information are selected by excluding the measurement information that deviates from.

Further, in the invention , in the above invention, the collecting unit is a first time when wireless communication is established between the first terminal device arranged at a start point of the predetermined section and the mobile terminal, Collection of measurement information including a measurement value of traveling time calculated using a second time when wireless communication is established between the second terminal device arranged at the end point of the predetermined section and the mobile terminal It is characterized by doing.

Further, in the present invention according to the above-mentioned invention, when the identification information of the mobile terminal acquired by the wireless communication corresponds to an exclusion condition registered in advance, the measurement information about the mobile terminal is obtained. Is excluded from the collection target.

Further, in the present invention according to the above-mentioned invention, in the case where the collecting unit establishes wireless communication a plurality of times within a predetermined time between the same mobile terminal and the first terminal device, the wireless communication is performed. When the maximum radio field intensity is set to the first time, and when wireless communication is established a plurality of times between the same mobile terminal and the second terminal device within a predetermined time, the wireless communication is performed. It is characterized in that the measurement information including the measured value of the travel time calculated with the time when the radio wave intensity of the communication becomes maximum as the second time is collected.

Further, in the present invention according to the above-mentioned invention, when the number of the measurement information collected by the collecting unit decreases at a ratio of a predetermined value or more, the calculation unit calculates an estimated value of the travel time calculated in the past. It is characterized in that a new estimated value of the travel time is calculated by performing correction based on the standard value of the travel time obtained according to the length of the predetermined section.

Further, the present invention includes a collecting step of collecting a plurality of moving bodies having a mobile terminal is a predetermined moving time required to move the section measured value and the measurement information associating the passing time of the predetermined interval, respectively A selection step of selecting a plurality of pieces of measurement information from among the pieces of measurement information collected in the collection step based on the characteristics of the moving body that is the target of travel time estimation, and the measurement information selected in the selection step. The moving time measurement value for each passing time included is weighted, and based on the moving average of the weighted moving time measurement values, the moving time of the moving body that is the estimation target of the moving time at a predetermined time. look including a calculation step of calculating an estimated value, said at calculation step, the variation of the measurement values of travel time included in the measurement information approximating a normal distribution, the with the deviation from the mean of the normal distribution the weights of the weighting characterized and Sageruko.

According to the present invention, can be moving body is accurately estimated travel time required to move a predetermined interval.

FIG. 1 is a diagram showing a system configuration of a travel time estimation system. FIG. 2 is an explanatory diagram of the calculation of the measurement value of the traveling time and the calculation of the estimated value of the traveling time. FIG. 3 is a configuration diagram showing an internal configuration of the management device shown in FIG. FIG. 4 is an explanatory diagram of data stored in the storage unit of the management device. FIG. 5: is a block diagram which shows the internal structure of a guard terminal. FIG. 6 is a flowchart showing the processing operation of the security guard terminal. FIG. 7 is a flowchart showing the processing operation of the management device. FIG. 8 is a flowchart showing a detailed processing procedure of the detection data selection processing based on the radio field intensity shown in FIG. FIG. 9 is a flowchart showing a detailed processing procedure of the fixed device exclusion processing shown in FIG. 7. FIG. 10 is a flowchart showing a detailed processing procedure of the detection data selection processing according to the detection frequency shown in FIG. FIG. 11 is a flowchart showing a detailed processing procedure of the selection processing of the measurement value of the traveling time shown in FIG. 7. FIG. 12 is a flowchart showing a detailed processing procedure of the estimated travel time value calculation processing shown in FIG. 7. FIG. 13 is an explanatory diagram of a specific example of the detection data selection processing based on the radio field intensity. FIG. 14 is an explanatory diagram of the calculation of the estimated value of the travel time when the detection frequency is reduced. FIG. 15 is an explanatory diagram for setting a plurality of sections.

  Hereinafter, preferred embodiments of a travel time estimation system and a travel time estimation method according to the present invention will be described in detail with reference to the accompanying drawings. In the embodiment described below, a travel time estimation system that estimates a travel time required for a pedestrian to travel in a predetermined section will be described.

  FIG. 1 is a diagram showing a system configuration of a travel time estimation system. As shown in FIG. 1, guards are arranged at the start point Po and the end point Pd of a predetermined section, respectively, and the guards carry a mobile terminal. The mobile terminal carried by the guard placed at the starting point Po is the guard terminal Tg1, and the mobile terminal carried by the guard placed at the ending point Pd is the guard terminal Tg2.

  When a pedestrian near the starting point Po carries the portable terminal Tu1, and this portable terminal Tu1 has a wireless LAN router function, for example, when the tethering function of the portable telephone terminal is on, the portable terminal Tu1 automatically The SSID (Service Set Identifier), which is the identification name of the access point, is transmitted to the surroundings.

  Therefore, when the mobile terminal Tu1 is present at a distance communicable with the security guard terminal Tg1, the security guard terminal Tg1 can receive the SSID of the mobile terminal Tu1. The guard terminal Tg1 transmits the detection data in which the received SSID of the mobile terminal Tu1 is associated with the reception time to the management device 10.

  Similarly, when a pedestrian near the end point Pd carries a mobile terminal Tu2 and the mobile terminal Tu2 has a wireless LAN router function, the mobile terminal Tu2 transmits the SSID of its own access point to the surroundings. When the security guard terminal Tg2 receives the SSID of the mobile terminal Tu2, the security guard terminal Tg2 transmits the detection data in which the received SSID of the mobile terminal Tu2 is associated with the reception time to the management device 10.

  The process of receiving the SSID, generating the detection data in association with the time, and transmitting the detection data to the management device 10 can be realized by, for example, an application program operating on the security guard terminals Tg1 and Tg2.

  When the management device 10 acquires the detection data from the security guard terminal Tg1 and the security guard terminal Tg2, the management device 10 sets the time indicated by the detection data received from the security guard terminal Tg1 as the passage time of the start point Po, and the detection data received from the security guard terminal Tg2. Is stored as the passing time of the end point Pd. Then, if the passing times at the start point and the end point are obtained for the same SSID, the difference is calculated as the measurement value of the travel time.

  The management device 10 accumulates the measured value of the traveling time calculated based on the detection data thus obtained from the mobile terminals of a plurality of pedestrians, and calculates the estimated value of the traveling time from the accumulated measured value of the traveling time. To do. Specifically, the management device 10 calculates the moving average using the measured values of the plurality of moving times, and sets the calculation result as the estimated value of the moving time.

  Here, the management device 10 selects detection data, selects a travel time measurement value, and sets weights for the moving average, based on the characteristics of a pedestrian whose travel time is estimated.

  First, a pedestrian has a characteristic that the moving speed is relatively low. For this reason, the mobile terminals Tu1 and Tu2 are located for a long time in a communicable distance with the security guard terminals Tg1 and Tg2, and communication between the mobile terminals Tu1 and Tu2 and the security guard terminals Tg1 and Tg2 may be established multiple times. is assumed. If the time of communication that occurs when the pedestrian approaches the guard or when the pedestrian moves away from the guard is used, the position of the pedestrian becomes inaccurate, and the travel time cannot be accurately obtained. Therefore, the radio wave intensity at the time of wireless communication is included in the detection data, and when a plurality of detection data having the same SSID and a time within a predetermined range are obtained, the management device 10 has the highest radio wave intensity. The detection data is selected and used to calculate the travel time measurement value.

  Further, the security guard terminals Tg1 and Tg2 may receive the SSID from another communication device, for example, a fixed access point, instead of the pedestrian's mobile terminals Tu1 and Tu2. When such a fixed access point communicates with only one of the security guard terminals Tg1 and Tg2, no problem occurs. However, if it is possible to communicate with both of the guard terminals Tg1 and Tg2, the travel time measurement value is calculated from the detection data generated by the communication with the fixed access point. Therefore, the management device 10 excludes inappropriate detection data such as detection data originating from a fixed access point. Specifically, a character string used for the SSID of a fixed access point or the like is registered in advance as an exclusion list, and the detection data including the character string associated with the SSID is excluded. The character string used for the SSID of the fixed access point is, for example, a carrier name or a facility name.

  Further, when the pedestrian continuously walks and moves from the start point Po to the end point Pd, the moving time falls within a certain range. When the measured travel time is extremely small, detection data is generated by communication between the guard terminals Tg1 and Tg2 and the vehicle or bicycle instead of the pedestrian, and the measured travel time of the vehicle or bicycle is calculated. It is likely that you did. If the measured travel time is extremely large, it is possible that a pedestrian may have stayed at a store midway for a long time. Is not appropriate for use in calculating.

  Therefore, the management device 10 sets the upper limit and the lower limit of the measured value of the travel time according to the length of the predetermined section, that is, the length of the road from the start point Po to the end point Pd, and the travel time that does not deviate from the upper limit or the lower limit. Is used to calculate the estimated travel time.

  In addition, a pedestrian has a characteristic that the variation in traveling time is large. This is caused by the high degree of freedom of movement, such as the original individual difference in walking speed, the case of rushing through the predetermined section, and the case of slowly moving while looking around. Further, a behavior such as a stop for a short time also causes a variation in the traveling time.

  Therefore, the management device 10 approximates the variation of the measurement value of the travel time to a normal distribution, sets the weight for the measurement value of the travel time such that the weight becomes smaller as the deviation from the average in the normal distribution is set, and the weight is applied. The estimated value of the traveling time is calculated by the weighted moving average.

  In this way, the management device 10 acquires the detection data generated by the security guard terminals arranged at the start point Po and the end point Pd of the predetermined section by detecting the mobile terminals carried by a plurality of pedestrians, and from the detection data. A pedestrian calculates and accumulates a measurement value of the traveling time required for the pedestrian to move in a predetermined section, and calculates an estimated value of the traveling time from the accumulated measurement value of the traveling time. In addition, the management device 10 selects the detection data, the measurement value of the travel time, and the weight of the moving average based on the characteristics of the pedestrian whose travel time is estimated. By thus estimating the travel time by applying the characteristics of the pedestrian, it is possible to accurately estimate the travel time required for the pedestrian to move in the target section.

  Next, the calculation of the measurement value of the travel time and the calculation of the estimated value of the travel time will be described. FIG. 2 is an explanatory diagram of the calculation of the measurement value of the traveling time and the calculation of the estimated value of the traveling time. As shown in FIG. 2A, the Po passing time, which is the time when the same pedestrian is located near the starting point Po of the route, and the Pd passing time, which is the time located near the ending point Pd of the route, are acquired. By doing so, the management device 10 can calculate the time required for the pedestrian to move and pass on this route as the measurement value of the moving time. The length of the route may be divided by the travel time to obtain the speed value. However, in the present embodiment, the measurement value of the travel time is used as it is.

  After calculating the travel time measurement values for a plurality of pedestrians, the management device 10 calculates an estimated travel time value by a moving average as shown in FIG. For example, when the number of moving average data N=10, the measured values of 10 moving times at which the Pd passage time is close to the present time are selected, and the average value is set as the estimated value of the current moving time. .. The moving average is weighted.

により求める。なお、係数ｗ_t,iは、Δｘ_t,iに対する重みであり、次のように求める。

Specifically, when the measured value x _t travel time at a certain time t is obtained, the estimated value y _t of the movement time of the pedestrian at the time t,

Ask by. The coefficient w _{t, i} is the weight for [Delta] x _{t, i,} determined as follows.

That is, when an extremely large moving time x _t is measured as compared with the estimated value of the moving time one time before, the weight w _t,i is reduced. The difference _{Δx t = x t -y t-} 1 and the estimated value y _t-1 of x _t and 1 time before the travel time, and follows a normal distribution N (0, σ), is to the weight of the moving average .

  Next, the internal configuration of the management device 10 shown in FIG. 1 will be described. FIG. 3 is a configuration diagram showing an internal configuration of the management device 10 shown in FIG. As illustrated in FIG. 3, the management device 10 is connected to the display unit 11 and the input unit 12, and includes a communication unit 13, a storage unit 14, and a control unit 15.

  The display unit 11 is a liquid crystal panel, a display device, or the like. The input unit 12 is a keyboard, a mouse, or the like. The communication unit 13 is an interface unit for performing data communication with the security guard terminals Tg1, Tg2 and the like via a communication line.

  The storage unit 14 is a storage device such as a hard disk device or a non-volatile memory, and stores guard data 14a, pedestrian characteristic data 14b, detection data 14c, measured travel time data 14d, and estimated travel time data 14e.

  The security guard data 14a is data for managing security guards, and is associated with security guard identification information, security guard terminal identification information carried by the security guard, current position of the security guard, current status, and the like. There is. The pedestrian characteristic data 14b is data indicating the characteristics of a pedestrian whose travel time is estimated.

  The detection data 14c is detection data received from the security guard terminals Tg1, Tg2, and the like. The measured travel time data 14d is data indicating the measured value of the travel time of a pedestrian, and associates the SSID indicated in the detection data, the passing time of the start point Po, the passing time of the end point Pd, and the measured value of the moving time. There is. The estimated travel time data 14e indicates an estimated travel time value calculated from the travel time measurement values shown in the measured travel time data 14d.

  The control unit 15 is a control unit that controls the entire management device 10, and includes a security state management unit 15a, a pedestrian characteristic management unit 15b, a detection data management unit 15c, a travel time calculation unit 15d, a travel time estimation unit 15e, and a pedestrian. It has a characteristic application unit 15f and an estimation result transmission unit 15g. In practice, programs corresponding to these functional units are stored in a ROM or a non-volatile memory (not shown), and these programs are loaded into a CPU (Central Processing Unit) and executed to execute the security state management unit 15a. The pedestrian characteristic management unit 15b, the detection data management unit 15c, the travel time calculation unit 15d, the travel time estimation unit 15e, the pedestrian property application unit 15f, and the estimation result transmission unit 15g are caused to execute respective processes.

  The security status management unit 15a is a processing unit that sets areas and routes to be protected, arranges security guards, manages the status of each security officer, and manages the security target area and security status. The security status management unit 15a updates the security data 14a when the security status changes.

  The pedestrian characteristic management unit 15b is a processing unit that manages the pedestrian characteristic data 14b indicating the characteristic of the pedestrian whose travel time is to be estimated. The pedestrian characteristic data 14b includes the variance of pedestrian travel time, the number of data used to calculate the moving average, the standard value of the travel time, the lower limit and the upper limit of the travel time measured value used to calculate the estimated travel time, A detection frequency reduction rate threshold value, an SSID exclusion list, a MAC address exclusion list, and the like can be included.

  Here, the standard value of the traveling time is a value obtained by dividing the length of the road from the start point to the end point by the speed of a general pedestrian. The threshold value of the detection frequency reduction rate is set so as to change the method of calculating the estimated value of the travel time when the number of acquisitions of valid detection data per hour is significantly reduced. The change of the method of calculating the estimated value of the travel time depending on the detection frequency will be described later. The SSID exclusion list defines detection data to be excluded from selection by designating a character string or the like indicating that the SSID is a fixed access point. Similar to the SSID exclusion list, the MAC address exclusion list is a list that defines detection data to be excluded from selection by MAC address.

  When the detection data management unit 15c receives the detection data from the security guard terminal, the detection data management unit 15c performs a process of adding the received detection data to the detection data 14c in the storage unit 14. The detection data includes the reception time of the SSID of the mobile terminal by the security guard terminal, the terminal ID that is identification information of the security guard terminal, the SSID of the mobile terminal, the MAC address of the mobile terminal, and the radio field intensity at the time of receiving the SSID. Further, the detection data management unit 15c refers to the guard data 14a based on the terminal ID, identifies the place where the guard terminal is arranged, and includes it in the detection data 14c.

  The moving time calculation unit 15d is a processing unit that updates the measured moving time data 14d with the detection data received from the security guard terminal and calculates the measured value of the moving time. Specifically, when the traveling time calculation unit 15d receives the detection data from the security guard terminal Tg1, the traveling time calculation unit 15d sets the received time as the passage time of the start point Po of the SSID indicated in the detection data. Further, when the travel time calculation unit 15d receives the detection data from the security guard terminal Tg2, the travel time calculation unit 15d sets the received time as the passage time of the end point Pd of the SSID. Then, the movement time calculation unit 15d calculates the difference between the passage times of the SSIDs for which the passage times of the start point and the end point are obtained, and sets the difference as the measured value of the movement time of the SSID.

  The travel time estimation unit 15e is a processing unit that calculates an estimated travel time value from a plurality of travel time measurement values accumulated in the measured travel time data 14d. Specifically, the travel time estimation unit 15e calculates a weighted moving average of the measurement values of the travel time, and stores the calculation result in the estimated travel time data 14e as an estimated value of the travel time.

  Based on the pedestrian characteristic data 14b, the pedestrian characteristic application unit 15f selects the detection data, the measurement value of the traveling time, and sets the weight for the moving average, thereby estimating the traveling time with the pedestrian characteristic. It is a processing unit to be applied.

  When a plurality of pieces of detection data having the same SSID and a time within a predetermined range are obtained, the pedestrian characteristic application unit 15f selects the detection data having the maximum radio field intensity and moves by the movement time calculation unit 15d. Used to calculate the time measurement value.

  Further, the pedestrian characteristic application unit 15f refers to the SSID exclusion list or the MAC address exclusion list of the pedestrian characteristic data 14b, excludes the detection data corresponding to these lists, and determines the travel time of the travel time calculation unit 15d. Let the measurement value be calculated.

  Further, the pedestrian characteristic application unit 15f refers to the upper limit and the lower limit of the measured value of the traveling time shown in the pedestrian characteristic data 14b, excludes the measured value of the traveling time that deviates from the upper limit or the lower limit, and moves the traveling time. The estimation unit 15e causes the travel time to be estimated.

  Further, the pedestrian characteristic application unit 15f uses the threshold value of the detection frequency reduction rate shown in the pedestrian characteristic data 14b, and uses the detection data when the number of acquisitions of effective detection data per hour is significantly reduced. Instead of newly calculating the travel time measured value and the travel time estimated value, the travel time estimated value is updated by correcting the already calculated travel time estimated value.

  In addition, the pedestrian characteristic application unit 15f approximates the variation of the measured values of the travel time to a normal distribution, and sets the weight for the measured value of the travel time so that the weight becomes smaller as the deviation from the average in the normal distribution becomes smaller. The estimated value of the moving time is calculated by the weighted moving average to which the weight is applied.

  The estimation result transmission unit 15g is a processing unit that transmits the estimated value of the travel time shown in the estimated travel time data 14e to another device. Specifically, the estimated travel time can be transmitted in response to an inquiry from the security guard terminal.

  Next, the data stored in the storage unit 14 of the management device 10 will be described. FIG. 4 is an explanatory diagram of data stored in the storage unit 14 of the management device 10. The guard data 14a shown in FIG. 4A corresponds to the guard ID, which is the identification information of the guard, with the terminal ID, which is the identification information of the guard terminal carried by the guard, the location, the state, and the like. Attached. The placement location includes the start point Po and the end point Pd, and indicates the current position of the security guard. The state shows the current state of the guard, such as guarding, moving, waiting, and troubleshooting.

  When the detection data is received from the security guard terminal, the security guard data 14a is referred to based on the terminal ID of the security guard terminal of the transmission source to identify which security guard is carried, the current location and the state. Is.

  In FIG. 4A, it is shown that the guard with the guard ID “G0001” carries the guard terminal with the terminal ID “Tg0001” and the state is “guarding” at the location “P1”. There is.

  The pedestrian characteristic data 14b shown in FIG. 4B is data indicating the characteristics of the pedestrian whose travel time is estimated. In FIG. 4B, the pedestrian characteristic data 14b is the distribution of pedestrian travel times, the number of data used for calculating the moving average, the standard value of the travel time, and the measurement of the travel time used for calculating the estimated travel time. It includes a lower limit setting value of the value, an upper limit setting value of the traveling time measurement value used for calculating the estimated traveling time, a threshold value of the detection frequency reduction rate, an SSID exclusion list, a MAC address exclusion list, and the like.

  The detection data 14c illustrated in FIG. 4C is data in which time, terminal ID, location, SSID, MAC address, and radio field intensity are associated with each other. The time, terminal ID, SSID, MAC address, and radio wave intensity are included in the detection data received from the security guard terminal. The placement location is determined by the detection data management unit 15c referring to the guard data 14a based on the terminal ID and identifying the location where the guard terminal is placed.

  FIG. 4C shows detection data generated by the security guard terminal having the terminal ID “Tg0001” communicating with the mobile terminal at time “10:05:40”. At this time, the security guard terminal is located at the location "P1", the SSID of the mobile terminal is "user00x", the MAC address is "xx.xx... ", and the radio field intensity is "-." It was 40 dBm”.

  The measured travel time data 14d illustrated in FIG. 4D is data in which the SSID of the mobile terminal, the passage time of the start point Po of the mobile terminal, the passage time of the end point Pd of the mobile terminal, and the measurement value of the travel time are associated with each other. In FIG. 4D, the mobile terminal whose SSID is “user00x” passes the start point Po at time “10:05:40” and the end point Pd passes at time “10:12:10”, and the travel time is It indicates that it was “390 seconds”.

  The estimated travel time data 14e shown in FIG. 4(e) shows a state in which the estimated travel time of a predetermined section having a start point of "Po" and an end point of "Pd" is "400 seconds".

  Next, the internal configuration of the security guard terminal will be described. FIG. 5: is a block diagram which shows the internal structure of a guard terminal. The guard terminals Tg1 and Tg2 shown in FIG. 1 have the same configuration as the guard terminal 20 shown in FIG.

  As shown in FIG. 5, the security guard terminal 20 includes a display unit 21, an input unit 22, a wireless communication unit 23, a storage unit 24, and a control unit 25.

  The display unit 21 is an output interface such as a liquid crystal panel. The input unit 22 is an input interface such as a key or a touch panel used for an input operation by a security guard. The display unit 21 and the input unit 22 may be integrated as a touch panel display. The wireless communication unit 23 is a communication interface for wirelessly communicating with the management device 10 and the like.

  The storage unit 24 is a storage device such as a hard disk device or a non-volatile memory, and stores its own device data 24a and map data 24b. The own device data 24a includes the terminal ID of the own device and the like.

  The control unit 25 is a control unit that controls the entire security guard terminal 20, and includes a detection processing unit 25a, a detection data transmission unit 25b, and an estimation result output unit 25c. In practice, the programs corresponding to these functional units are stored in a ROM or a non-volatile memory (not shown), and these programs are loaded into a CPU (Central Processing Unit) and executed, whereby the detection processing unit 25a, The detection data transmission unit 25b and the estimation result output unit 25c are caused to execute the respective processes.

  The detection processing unit 25a is a processing unit that receives the SSID of the mobile terminal to detect the presence of an access point located around the own terminal. When the detection processing unit 25a detects the access point, the detection data transmission unit 25b detects the received SSID by associating the time information, the MAC address of the mobile terminal, the terminal ID of the own device, and the radio wave intensity at the time of receiving the SSID. A processing unit that generates data and sends it to the management device 10.

  The estimation result output unit 25c is a processing unit that makes an inquiry to the management device 10 to acquire an estimated travel time value and outputs the acquired estimated travel time value using the display unit 21 or the like. With the output using the display unit 21, it is possible to show the target section on the map using the map data 24b and to display the estimated value of the travel time of the section.

  Next, the processing operation of the security guard terminal will be described. FIG. 6 is a flowchart showing the processing operation of the security guard terminal. The processing operation shown in FIG. 6 is repeatedly executed by the security guard terminal.

  When the process is started, the detection processing unit 25a first determines whether the SSID is detected (step S101). If the SSID is not detected (step S101; No), the security guard terminal ends the process as it is.

  If the SSID is detected (step S101; Yes), the detection data transmitting unit 25b generates detection data by associating the SSID with the time information, the MAC address of the mobile terminal, the terminal ID of the own device, and the radio wave intensity at the time of receiving the SSID. Then, (step S102), it transmits to the management apparatus 10 (step S103), and a process is complete|finished.

  Next, the processing operation of the management device 10 will be described. FIG. 7 is a flowchart showing the processing operation of the management device 10. When the detection data management unit 15c of the management device 10 receives the detection data from the guard terminal, the detection data management unit 15c adds the received detection data to the detection data 14c of the storage unit 14 to accumulate the detection data (step S201). ..

  The pedestrian characteristic application unit 15f performs a process of selecting detection data based on the radio field intensity (step S202). Although details of this processing will be described later, this processing allows selection of detection data in a state in which the pedestrian is closest to the guard.

  In addition, the pedestrian characteristic application unit 15f uses the SSID exclusion list or the MAC address exclusion list to perform the fixed device exclusion process (step S203). Although the details of this processing will be described later, this processing can exclude the detection data originating from a fixed access point and employ the detection data having a high possibility of being a pedestrian.

  If the detection data is not adopted as a result of the fixed device exclusion process (step S204; No), the movement time calculation unit 15d ignores the detection data (step S211) and ends the process.

  If the detection data is adopted as a result of the fixed device exclusion processing (step S204; Yes), the pedestrian characteristic application unit 15f performs detection data selection processing according to the detection frequency (step S205). For details of this processing, refer to FIG. As will be described later, when the number of acquisitions of valid detection data per hour is significantly reduced by this processing, it is determined that the detection data is not adopted.

  If the detection data is not adopted as a result of the detection data selection process based on the detection frequency (step S206; No), the movement time calculation unit 15d ignores the detection data (step S211) and ends the process.

  If the detection data is selected as a result of the detection data selection process based on the detection frequency (step S206; Yes), the movement time calculation unit 15d calculates a measurement value of the movement time using the detected detection data (step S206). S207).

  The pedestrian characteristic application unit 15f performs a process of selecting the measurement value of the travel time (step S208). Although the details of this process will be described later, this process determines that the measurement value of the moving time deviating from the upper limit or the lower limit is not adopted.

  If the measurement value of the travel time is not adopted as a result of the selection process of the measurement value of the travel time (step S209; No), the travel time estimation unit 15e ignores the measurement value of the travel time (step S212). , The process ends.

  If the measurement value of the travel time is adopted as a result of the selection processing of the measurement value of the travel time (step S209; Yes), the travel time estimation unit 15e uses the calculated measurement value of the travel time to calculate the travel time. An estimated value calculation process is performed (step S210), and the process ends.

  Next, the details of the detection data selection processing based on the radio field intensity shown in FIG. 7 will be described. FIG. 8 is a flowchart showing a detailed processing procedure of the detection data selection processing based on the radio field intensity shown in FIG.

  The pedestrian characteristic application unit 15f first determines whether new detection data has been acquired (step S301). If new detection data is acquired (step S301; Yes), the pedestrian characteristic application unit 15f determines whether or not the detection data of the same SSID is being held at the same point (step S302).

  If the detection data of the same SSID is not held at the same point (step S302; No), the pedestrian characteristic application unit 15f holds the detection data (step S303). If the detection data of the same SSID is being held at the same point (step S302; Yes), the pedestrian characteristic application unit 15f determines that the radio field intensity indicated by the new detection data is higher than the radio field intensity of the retained detection data. Is also strong (step S306). If the radio field intensity indicated by the new detection data is stronger than the radio field intensity of the held detection data (step S306; Yes), the held detection data is updated to the new detection data (step S307). ..

  After step S303 or after step S307, or when the radio field intensity indicated in the new detection data is less than or equal to the radio field intensity of the held detection data (step S306; No), or when there is no new detection data (Step S301; No), the pedestrian characteristic application unit 15f determines whether or not there is detection data for which a predetermined time has elapsed from the holding or updating (Step S304).

  If there is no detection data for which a predetermined time has passed since the holding or updating (step S304; No), the pedestrian characteristic application unit 15f proceeds to step S301. On the other hand, if there is detection data for which a predetermined time has elapsed since the holding or updating (step S304; Yes), the pedestrian characteristic application unit 15f selects the corresponding detection data (step S305) and returns to the original processing.

  Next, details of the fixed device exclusion process shown in FIG. 7 will be described. FIG. 9 is a flowchart showing a detailed processing procedure of the fixed device exclusion processing shown in FIG. 7.

  The pedestrian characteristic application unit 15f reads the SSID indicated in the detection data, refers to the SSID exclusion list of the pedestrian characteristic data 14b, and determines whether the SSID indicated in the detection data is registered in the SSID exclusion list. The determination is made (step S401). Then, if the SSID indicated in the detection data is registered in the SSID exclusion list (step S401; Yes), it is determined that the detection data is not adopted (step S405), and the process returns to the original process.

  If the SSID indicated in the detection data is not registered in the SSID exclusion list (step S401; No), the pedestrian characteristic application unit 15f reads the MAC address indicated in the detection data and MACs the pedestrian characteristic data 14b. By referring to the address exclusion list, it is determined whether or not the MAC address indicated in the detection data is registered in the MAC address exclusion list (step S402). Then, if the MAC address indicated in the detection data is registered in the MAC address exclusion list (step S402; Yes), it is determined that the detection data is not adopted (step S405), and the process returns to the original process.

  If the MAC address indicated in the detection data is not registered in the MAC address exclusion list (step S402; No), the pedestrian characteristic application unit 15f continuously receives the detection data having the same SSID for a certain period of time. It is determined whether or not there is (step S403). Then, if the detection data having the same SSID is continuously received for a certain period of time (step S403; Yes), it is determined that the detection data is not adopted (step S405), and the process returns to the original process. On the other hand, if the detection data having the same SSID has not been continuously received for a certain period of time (step S403; No), it is determined that the detection data is adopted (step S404), and the process returns to the original process.

  Next, details of the detection data selection processing based on the detection frequency shown in FIG. 7 will be described. FIG. 10 is a flowchart showing a detailed processing procedure of the detection data selection processing according to the detection frequency shown in FIG.

  The pedestrian characteristic application unit 15f determines whether or not the reduction rate of the detection frequency of the adopted effective detection data is equal to or higher than the threshold value of the detection frequency reduction rate shown in the pedestrian characteristic data 14b (step S501). ). If the reduction rate of the detection frequency of the effective detection data is less than the threshold value (step S501; No), the pedestrian characteristic application unit 15f determines that the detection data is adopted (step S502), and returns to the original processing.

  If the reduction rate of the detection frequency of the effective detection data is equal to or higher than the threshold value (step S501; Yes), the pedestrian characteristic application unit 15f determines that the detection data is not adopted (step S503). Then, the standard value of the travel time calculated based on the distance between the points is specified (step S504), the estimated value of the travel time is corrected using this standard value of the travel time, and the estimated travel time data 14e is updated. Then (step S505), the process returns to the original process.

  Next, details of the selection process of the measurement value of the traveling time shown in FIG. 7 will be described. FIG. 11 is a flowchart showing a detailed processing procedure of the selection processing of the measurement value of the traveling time shown in FIG. 7.

  The pedestrian characteristic application unit 15f determines whether or not the calculated measurement value of the travel time is less than the lower limit setting value shown in the pedestrian characteristic data 14b (step S601). If the calculated travel time measurement value is less than the lower limit setting value (step S601; Yes), the pedestrian characteristic application unit 15f determines that the calculated travel time measurement value is not adopted (step S604), Return to original processing.

  If the calculated travel time measurement value is equal to or greater than the lower limit setting value (step S601; No), the pedestrian characteristic application unit 15f indicates the calculated travel time measurement value in the pedestrian characteristic data 14b. It is determined whether or not the upper limit set value is exceeded (step S602). If the calculated travel time measurement value exceeds the upper limit setting value (step S602; Yes), the pedestrian characteristic application unit 15f determines that the calculated travel time measurement value is not adopted (step S604). ), and returns to the original processing. Then, if the calculated travel time measurement value is less than or equal to the upper limit setting value (step S602; No), the pedestrian characteristic application unit 15f determines that the calculated travel time measurement value is adopted (step S603). , Return to the original processing.

  Next, details of the travel time estimated value calculation process shown in FIG. 7 will be described. FIG. 12 is a flowchart showing a detailed processing procedure of the estimated travel time value calculation processing shown in FIG. 7.

  The pedestrian characteristic application unit 15f approximates the dispersion of the measurement values of the travel time to a normal distribution, and sets the weight for the measurement value of the travel time by the deviation from the average in the normal distribution (step S701). The moving time estimation unit 15e applies the set weight to the measured value of the moving time to calculate the weighted moving average (step S702), and stores the calculation result in the estimated moving time data 14e as a new estimated value of the moving time. Then (step S703), the process returns to the original process.

  Next, a specific example of the detection data selection processing based on the radio field intensity will be described. FIG. 13 is an explanatory diagram of a specific example of the detection data selection processing based on the radio field intensity. In FIG. 13, a pedestrian carrying the mobile terminal Tu1 passes through a predetermined section from the start point Po to the end point Pd. The guard placed at the start point Po has a guard terminal Tg1, and the guard placed at the end point Pd has a guard terminal Tg2.

  In the process in which the pedestrian approaches the starting point Po, first, at time t11, communication between the mobile terminal Tu1 and the security guard terminal Tg1 is established, and detection data is generated. Note that, in FIG. 13, the generated detection data is indicated by a white circle. After that, communication is established in each of the times t12 to t17, and the detection data is similarly generated. Here, from time t12 to t14, the pedestrian is approaching the starting point Po, and the radio field intensity gradually increases. Therefore, the held detection data is sequentially updated. In FIG. 13, up to what time the detection data is held is indicated by a solid line connected to a white circle. From time t15 to t17, the pedestrian is moving away from the starting point Po, and the radio field intensity gradually decreases. Therefore, the held detection data is not updated, and the detection data at time t14 continues to be held.

  When a predetermined time has elapsed while holding the detection data at time t14, the detection data at time t14 is selected, and the time indicated by this detection data is used as the passage time of the pedestrian's starting point Po.

  Similarly, in the process in which the pedestrian approaches the end point Pd, first, communication is established between the mobile terminal Tu1 and the guard terminal Tg2 at time t21, and detection data is generated. After that, communication is established in each of the times t22 to t27, and the detection data is similarly generated. Here, from time t22 to t24, the pedestrian is approaching the end point Pd, and the radio wave intensity gradually increases. Therefore, the held detection data is sequentially updated. From time t25 to t27, the pedestrian is moving away from the end point Pd, and the radio field intensity gradually decreases. Therefore, the held detection data is not updated, and the detection data at time t24 continues to be held.

  When a predetermined time elapses while holding the detection data at time t24, the detection data at time t24 is selected, and the time indicated by this detection data is used as the passage time of the pedestrian end point Pd.

  As described above, by selecting the detection data according to the radio field intensity, the time when the pedestrian comes closest to the start point Po and the end point Pd can be used as the passage time, and the measurement value of the traveling time can be accurately calculated. ..

  Next, the calculation of the estimated value of the travel time when the detection frequency decreases will be described. FIG. 14 is an explanatory diagram of the calculation of the estimated value of the travel time when the detection frequency is reduced. In the example shown in FIG. 14, the number of pedestrians in the target section is small until time “17:22”, and there are many pedestrians from time “17:22” to time “17:44”. It is in a crowded state, and after the time "17:44", it is a quiet state in which the number of pedestrians is small.

  In the quiet state until the time “17:22”, there are few obstacles to walking, and it is possible to walk at a normal walking speed. Therefore, the estimated value of the travel time is a value close to the standard value of the travel time (a value obtained by dividing the length of the road from the start point to the end point by the speed of a general pedestrian). At this time, the estimated travel time can accurately indicate the actual travel time of the target section.

  In the congestion state from the time “17:22” to the time “17:44”, the speed of the pedestrian decreases. Therefore, the estimated value of the traveling time is a value larger than the standard value of the traveling time. Also at this time, the estimated travel time accurately represents the actual travel time of the target section. In particular, since the actual traveling time deviates from the standard traveling time value in a crowded state, it is effective to use the estimated traveling time value.

  In a quiet state after time “17:44”, it is considered that there are few obstructive factors for walking and that it is possible to pass at normal walking speed. However, because there are few pedestrians and the number of detection data is decreasing, when the estimated moving speed is calculated using the moving average, the estimated moving time is affected by the measured moving time in a congested state. The value is larger than the actual situation.

  Therefore, the pedestrian characteristic application unit 15f newly calculates the measured value of the travel time and the estimated value of the travel time using the detection data when the number of acquisitions of the effective detection data per hour is significantly reduced. Instead, the estimated travel time is updated by correcting the already calculated travel time estimate. Although any method can be used for this correction, for example, the estimated value of the traveling time may be corrected so as to approach the standard value of the traveling time at a constant rate from the end of congestion.

  After that, if a sufficient number of detection data is obtained after returning to the non-existent state, the traveling time can be accurately estimated by calculating the traveling time measurement value and the traveling time estimated value again. .. Specifically, when the reduction rate of the detection frequency of valid detection data is less than the threshold value, the process returns to the process of calculating the estimated value of the travel time using the measured value of the travel time.

  Although the estimation of the travel time of a single section has been illustrated above for the sake of simplicity, the present invention can estimate the travel times of a plurality of sections. When there are a plurality of sections, data defining the sections are provided, and pedestrian characteristic data 14b, measured travel time data 14d, and estimated travel time data 14e are provided for each section. FIG. 15 is an explanatory diagram for setting a plurality of sections.

  In FIG. 15A, points P1 to P7 are present, and the points are sections. Specifically, "P1" and "P2", "P2" and "P3", "P1" and "P4", "P4" and "P3", "P1" and "P5", "P5" and "P5" There are sections for each combination of "P2", "P2" and "P6", "P6" and "P7", and "P7" and "P3".

  FIG. 15B shows the definition data of the section, which uniquely identifies the section by selecting the start point Po and the end point Pd from the points P1 to P7 and gives the section ID. Specifically, the point “P1” is selected as the start point Po and the point “P2” is selected as the end point Pd in the section with the section ID “R1”. Similarly, in the section with the section ID “R2”, the point “P2” is selected as the start point Po and the point “P3” is selected as the end point Pd.

  In this way, if a plurality of sections are managed and the estimated value of the travel time of each section is calculated, it becomes possible to efficiently select the section. For example, when moving from the point P1 to the point P2, if the estimated value of the travel time of the section R1 and the sum of the estimated values of the travel times of the sections passing through the point P5 are compared, a route that can reach the point P2 sooner Can be selected.

  As described above, in the travel time estimation system according to the embodiment, the plurality of pedestrians having the mobile terminal associate the measured value of the travel time required to travel in the predetermined section with the passage time of the predetermined section. Based on the characteristics of pedestrians that are stored and estimated for travel time, select multiple travel time measurement values from the stored travel time measurement values, and select pedestrians from the selected travel time measurement values. Since the estimated value of the travel time is calculated, the travel time required for the pedestrian to travel in the predetermined section can be accurately estimated.

  Furthermore, by selecting the detection data of the mobile terminal used to calculate the measurement value of the travel time based on the pedestrian characteristics and performing weighting based on the pedestrian characteristics when calculating the estimated value of the travel time, the travel time can be further reduced. It can be estimated accurately.

  In addition, the said Example demonstrated the structure which acquires SSID from the portable terminal which a pedestrian carries, and uses it for estimation of moving time. In such a configuration, it is preferable to call on a pedestrian to turn on the tethering function. It is not necessary to acquire the SSID from the mobile terminals of all pedestrians, and it is possible to estimate the travel time if there is a person carrying a mobile terminal that provides the SSID among the pedestrians, but a mobile terminal that provides the SSID. This is because if there are many, the travel time can be estimated more stably.

  Further, the mobile terminal is not limited to a terminal having a telephone function. A mobile router or the like may be used as long as it is a terminal carried by a pedestrian. Even when the mobile router is used, the detection data can be generated from the SSID or MAC address of the mobile router.

  Further, if the mobile terminal carried by the pedestrian can be identified by wireless communication, the travel time according to the present invention can be estimated, and therefore the use of the SSID is not limited. For example, while providing a wireless LAN router function on the security guard terminal side, a pedestrian can access the wireless LAN via the security guard terminal by preparing contents such as information about events in a server connectable via the security guard terminal. May be motivated. In this case, since the pedestrian connects to the wireless LAN as a client, the MAC address of the pedestrian's mobile terminal may be associated with the time and transmitted to the management device.

  Alternatively, the mobile terminal carried by the pedestrian and the security guard terminal may communicate with each other according to a communication standard such as Bluetooth (registered trademark) to acquire the identification information of the mobile terminal carried by the pedestrian. In this case, it is not necessary to complete the pairing, and the identification information of the mobile terminal transmitted and received at the stage of trying the pairing may be transmitted to the management device in association with the time.

  Further, in the above embodiment, the guard terminal is used to acquire the identification information from the portable terminal carried by the pedestrian. Therefore, it is possible to flexibly change the section whose travel time is to be estimated by moving the guard. For example, even if the entrance and exit of the event venue are different, or even if the main route becomes unavailable and it is necessary to estimate the travel time of the alternative route, it is possible to immediately respond.

  In the above embodiment, the case where the security guard terminal is used to obtain the identification information from the portable terminal carried by the pedestrian has been described as an example, but fixed communication equipment is arranged on the route to fix the fixed communication. The facility may be configured to acquire the identification information of the mobile terminal of the pedestrian. Also, existing communication equipment can be used.

  Further, the estimation result of the traveling time is not limited to the above-mentioned embodiment, and can be arbitrarily used. For example, the result of traffic control can be quantitatively evaluated by measuring in real time how the travel time of a pedestrian changes as a result of the traffic control organizing traffic. Also, the evaluation result can be fed back to the guard.

  Moreover, since the movement time can be estimated in real time for each movement direction, it is possible to arrange the guards using the movement direction. For example, if the estimated travel time is large on the one road toward the event venue and small on the return road from the event venue, guards may be assigned to guide people to the event venue. it can. If the estimated travel time is large both in the direction of going to the event venue and in the direction of returning, there is a possibility that an accident may have occurred at the scene, so there is a need to take measures such as dispatching multiple security guards. Is possible.

  Further, the configurations and processes disclosed in the above-described embodiments are merely examples, and can be appropriately modified and implemented. For example, the guard terminal may be configured to perform the detection data selection processing or the fixed device exclusion processing based on the radio field intensity.

  Further, although the pedestrian is described as an example in the above embodiment, the present invention may be applied to other moving bodies such as a bicycle and a vehicle.

  INDUSTRIAL APPLICABILITY The travel time estimation system and the travel time estimation method according to the present invention are suitable for accurately estimating the travel time required for a mobile body to travel in a predetermined section.

10 management device 11, 21 display unit 12, 22 input unit 13 communication unit 14, 24 storage unit 14a guard data 14b pedestrian characteristic data 14c detection data 14d measurement movement time data 14e estimated movement time data 15, 25 control unit 15a security State management unit 15b Pedestrian characteristic management unit 15c Detection data management unit 15d Travel time calculation unit 15e Travel time estimation unit 15f Pedestrian characteristic application unit 15g Estimated result transmission unit 20, Tg1, Tg2 Guard terminal 23 Wireless communication unit 24a Own device Data 24b Map data 25a Detection processing unit 25b Detection data transmission unit 25c Estimation result output unit Tu1, Tu2 Mobile terminal Po Start point Pd End point P1 to P7 points

Claims (7)

A collecting unit that collects a plurality of moving bodies having a mobile terminal measurement information associating the passing time of the measured value and the predetermined section of the moving time required for the movement of a predetermined interval, respectively,
A selection unit that selects a plurality of pieces of measurement information from the measurement information collected by the collection unit, based on the characteristics of the moving body that is the target of travel time estimation;
The measurement value of the travel time for each passage time included in each measurement information selected by the selection unit is weighted, and the movement at a predetermined time is based on the moving average of the weighted measurement values of the travel time. And a calculation unit that calculates an estimated value of the travel time of the moving object that is the target of time estimation ,
The calculation unit approximates the variation of the measurement value of the traveling time included in the measurement information to a normal distribution, and lowers the weighting weight according to the deviation from the average in the normal distribution.
Travel time estimation system which is characterized a call. The selection unit uses the lower limit and/or the upper limit set for the traveling time as the characteristics of the moving body, excludes measurement information in which a measured value of the traveling time deviates from the lower limit and/or the upper limit, The travel time estimation system according to claim 1 , wherein the measurement information is selected. The collecting unit includes a first time when wireless communication is established between the first terminal device arranged at the start point of the predetermined section and the mobile terminal, and a first time point arranged at the end point of the predetermined section. claim 1 or 2, characterized in that to collect measurement information including a measured value of the movement time calculated by using the second time that the wireless communication has been established between the second terminal device and the mobile terminal The travel time estimation system described in. When the identification information of the mobile terminal acquired by the wireless communication corresponds to a pre-registered exclusion condition, the collection unit excludes measurement information related to the mobile terminal from a collection target. The travel time estimation system according to claim 3 . When the wireless communication is established a plurality of times within the predetermined time between the same mobile terminal and the first terminal device, the collecting unit determines the time at which the radio field intensity of the wireless communication becomes maximum. When the wireless communication is established a plurality of times within the predetermined time between the same mobile terminal and the second terminal device as the first time, the time when the radio wave intensity of the wireless communication becomes maximum is set. The travel time estimation system according to claim 3 or 4 , wherein measurement information including a measurement value of travel time calculated as the second time is collected. When the number of the pieces of measurement information collected by the collection unit decreases at a rate higher than a predetermined value, the calculation unit obtains an estimated value of the travel time calculated in the past according to the length of the predetermined section. The travel time estimation system according to any one of claims 1 to 5 , wherein a new travel time estimation value is calculated by performing correction based on the standard travel time value. A collecting step of collecting a plurality of moving bodies moving time required for movement of the predetermined section measurements and measurement information associating the passage time of said predetermined section with the mobile terminal,
A selection step of selecting a plurality of pieces of measurement information from the measurement information collected by the collection step, based on the characteristics of the moving body that is the target of travel time estimation;
The measurement value of the traveling time for each passage time included in each measurement information selected by the selecting step is weighted, and the movement at a predetermined time is based on the moving average of the weighted measurement values of the traveling time. look including a calculation step of calculating an estimate of travel time of the moving object which is a time to be estimated,
In the calculating step, the variation in the measurement value of the traveling time included in the measurement information is approximated to a normal distribution, and the weighting weight is reduced according to the deviation from the average in the normal distribution.
Travel time estimation method, wherein a call.

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