Travel time analysis system and travel time analysis method

Abstract

To know a relation of whether or not public transport is utilized with an access time and an egress time.SOLUTION: A travel time analysis system consists of a computation server and an information distribution server. The computation server comprises: a utilization determination section for separating travel data, in which a location of a person is stored in a time sequential manner, into travel data relating to a person who utilizes public transport and travel data relating to a person who does not utilize public transport based on a location of a public transport utilization place; and an access / egress time calculation section for calculating an access time from a departure place in the travel data to the public transport utilization place and an egress time from the public transport utilization place to a destination in the travel data on the basis of whether or not public transport is utilized. The information distribution server comprises a display screen creation section for displaying the calculated access time and egress time on a display device on the basis of whether or not public transport is utilized.SELECTED DRAWING: Figure 18

Description

[Technical field]

[0001] The present invention relates to a travel time analysis system and a travel time analysis method, and in particular to a technology for analyzing travel time between a place of stay, such as a home or a workplace, and a place of use of public transportation, such as a station or a bus stop, by using location information acquired via a smartphone app or the like and user number data held by a transportation business operator. [Background technology]

[0002] With the advent of an era of population decline, the impact of the spread of infectious diseases, and the trend toward encouraging remote work, the management of transportation companies is becoming increasingly difficult year by year. Maintaining and securing transportation means in a region is an important issue that should be addressed by the entire region, with cooperation between local governments, transportation companies, and local residents, in various aspects such as urban development, economic promotion, the environment, resident health, and quality of life. In response to this trend, in recent years, it has been recommended that local governments take the lead in creating regional public transportation plans as master plans for the region and periodically review said plans. When creating a regional public transportation plan, it is necessary to first consider measures from the perspective of users by conducting on-site surveys, interviews, and sorting out issues using data.

[0003] Representative examples of such field surveys include large-scale questionnaire surveys such as metropolitan transportation censuses and person trip surveys. These questionnaire surveys are conducted at intervals of 5 to 10 years to collect data on what kind of people traveled, for what purpose, from where to where, and by what means of transportation. By analyzing this survey data, it is possible to understand the gap between the actual state of travel and the current public transportation services. Therefore, questionnaire surveys are very useful in considering improvement policies for public transportation services. However, questionnaire surveys are very costly, and the response rate is usually around 10%, making it difficult to obtain a sufficient amount of data.

[0004] On the other hand, in recent years, the use of data collected and accumulated during railway operations has been expanding, and there is a movement to replace part of the questionnaire survey data with data held by transportation operators. In fact, the latest survey for the Metropolitan Transportation Census has also changed to a method of tabulating the usage record of railway IC cards, which has had a major effect, such as greatly increasing the amount of data that can be collected through the survey.

[0005] However, there is quite a bit of information that can only be known from conventional questionnaire survey data. One example is the time it takes to arrive from a starting point such as one's home to the nearest train station or bus stop (access time), and the time it takes to arrive at one's destination after getting off a train or bus (egress time). Access time and egress time are known to be important factors that affect the utilization rate of public transportation. Quantitatively and regularly grasping the actual situation of these is useful from the perspective of planning regional transportation policies aimed at increasing the utilization rate of public transportation. Examples of such regional transportation policies include park-and-ride, shared bicycles, and on-demand buses.

[0006] The people flow analysis system of Patent Document 1 accepts the specification of an area on a map, calculates the people flow in the specified area for each transportation means based on multiple people flow data including time and location information, and displays the people flow as a movement line. The people flow analysis system of Patent Document 2 performs network analysis and clustering on the movement of people between any points in the analysis area, and analyzes macro-movement between clusters and micro-movement within clusters. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] International Publication No. 2016 / 067369 [Patent Document 2] Patent Publication No. 2021-47763 Summary of the Invention [Problem to be solved by the invention]

[0008] The people flow analysis system of Patent Document 1 can classify the movement of people in a specified area by transportation means using location information acquired via a smartphone app, etc. The people flow analysis system of Patent Document 2 can analyze the movement of people in a specified area from both macro and micro perspectives based on OD data (number of people per departure / arrival area) such as mobile phone base station information and data on the number of people getting on and off at stations or bus stops, and can calculate the number of vehicles, drivers, etc. required to provide a transportation service.

[0009] However, the people flow analysis system of Patent Document 1 and the people flow analysis system of Patent Document 2 do not analyze the relationship between access time and egress time and the use of public transportation such as trains, buses, etc. Therefore, an object of the present invention is to know the relationship between access time and egress time and the use of public transportation. [Means for solving the problem]

[0010] The travel time analysis system of the present invention is a travel time analysis system consisting of a calculation server and an information distribution server, wherein the calculation server is equipped with a usage determination unit that separates movement data, which stores people's positions in chronological order, into movement data relating to people who used public transportation and movement data relating to people who did not use public transportation based on the positions of places where public transportation was used, and an access / egress time calculation unit that calculates the access time from the departure point in the movement data to the place where public transportation was used, and the egress time from the place where public transportation was used to the destination of the movement data, for each case where public transportation was used or not; and the information distribution server is equipped with a display screen creation unit that displays the calculated access time and egress time on a display device for each case where public transportation was used or not. Other means will be described in the description of the preferred embodiment of the invention. Effect of the Invention

[0011] According to the present invention, it is possible to know the relationship between the access time and egress time and whether or not public transportation is used. [Brief description of the drawings]

[0012] [Figure 1] FIG. 2 is a diagram illustrating access time and egress time. [Diagram 2] FIG. 2 is a diagram illustrating a processing procedure and a data flow according to the present embodiment. [Diagram 3] FIG. 1 is a diagram showing the configuration of a travel time analysis system. [Figure 4] This is an example of station and line information. [Diagram 5] 1 is an example of movement data. [Figure 6] This is an example of the results of railway passenger separation. [Figure 7] This is an example of map and statistical information. [Figure 8] This is an example of train and bus usage history. [Figure 9] 13 is an example of a time calculation result. [Figure 10] 13 is a flowchart of a railway usage determination process; [Figure 11] 13 is a flowchart of an access egress time calculation process. [Figure 12] FIG. 13 is a diagram for explaining the distribution of access / egress times, etc. [Figure 13] 13 is a flowchart of a procedure for processing a compilation of railroad and bus usage records. [Figure 14] 13 is a flowchart of a number-of-person information complementation process. [Figure 15] 13 is a flowchart of a condition setting process. [Figure 16] 13 is an example of a management screen. [Figure 17] 13 is a flowchart of a display screen creation process; [Figure 18] 13 is an example of an analysis result display screen. [Figure 19] 13 is an example of an analysis result display screen. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Hereinafter, an embodiment of the present invention (the present embodiment) will be described in detail with reference to the drawings. In the present embodiment, "railroad" is a general term for public transportation including route buses. "Station" is an example of a place where public transportation is used, and is a concept including a railway station as well as a route bus stop. In the present embodiment, a "user" is a person who uses a service provided by the travel time analysis system and can use local public transportation. When a user uses public transportation, the user is also called a "railroad user", and when not, the user is also called a "non-railroad user". A typical example of a non-railroad user is a local resident who travels between his / her residence and facilities other than the station (department stores, hospitals, etc.) located near the station.

[0014] FIG. 1 is a diagram explaining access time and egress time. A railway user departs from departure point 1, passes through entrance station 2 and exit station 3, and arrives at destination 4. For example, in the morning, departure point 1 is often the railway user's residence, and destination 4 is the railway user's workplace, school, etc. In the afternoon, it is the opposite. Access time 5 is the time from when the railway user departs from departure point 1 until he or she arrives at entrance station 2. Egress time 6 is the time from when the railway user departs from exit station 3 until he or she arrives at destination 4.

[0015] Access time 5 and egress time 6 are also defined for non-railroad users. Access time 5 for non-railroad users is the time from when a non-railroad user leaves departure point 1 until when the non-railroad user arrives at a facility (department store, etc.) near entrance station 2. Egress time 6 for non-railroad users is the time from when a non-railroad user leaves a facility near exit station 5 until when the non-railroad user arrives at destination 4.

[0016] FIG. 2 is a diagram for explaining the processing procedure and data flow of this embodiment. The code for each processing procedure is the code for the “○ part” that is the subject of the operation, with “b” added. The specific contents of each processing procedure and each data will be described later. In the railway use determination processing procedure 135b, the railway use determination unit 135 uses the movement data 124 to create the railway user separation result 125. In the access / egress time calculation processing procedure 136b, the access / egress time calculation unit 136 uses the railway user separation result 125 and the result of the condition setting processing procedure 145b to create the time calculation result 128. That is, the railway use determination unit 135 has a function of separating movement data related to people who used public transportation (railway users) from movement data related to people who did not use public transportation (railway non-users). In addition, the access / egress time calculation unit 136 has a function of calculating the access time from the departure point to the location where public transportation is used, and the egress time from the location where public transportation is used to the destination of the movement data, depending on whether or not public transportation is used.

[0017] In a condition setting process step 145b, the condition setting unit 145 accepts conditions from the user. In a railroad and bus usage record tabulation process step 137b, the railroad and bus usage record tabulation unit 137 corrects the number of railroad users and the number of non-railroad users using the railroad and bus usage history 127 and the result of the condition setting process step 145b. In a number of people information complementation process step 138b, the number of people information complementation unit 138 corrects the number of railroad users and the number of non-railroad users using the railroad user separation result 125 and the result of the railroad and bus usage record tabulation process step 137b.

[0018] (Configuration of travel time analysis system, etc.) FIG. 3 is a diagram showing the configuration of the travel time analysis system 105. The travel time analysis system 105 includes a data server 120, a calculation server 130, and an information distribution server 140. The data server 120 includes a database 121. The database 121 stores station and route information 123, travel data 124, railway user separation results 125, map and statistical information 126, railway and bus usage history 127, and time calculation results 128. The calculation server 130 includes a communication interface 131, a processor 132, a memory 133, and a program 134. The program 134 includes a railway usage determination unit (usage determination unit) 135, an access and egress time calculation unit 136, a railway and bus usage record counting unit (usage record counting unit) 137, and a number of people information complementing unit 138. The information distribution server 140 includes a communication interface 141, a processor 142, a memory 143, and a program 144. The program 144 is composed of a condition setting unit 145 and a display screen creation unit 146. Each server may be distributed in an independent housing, and the configuration within each server may also be distributed in an independent housing. Each program is read into each memory under the control of the processor, and executes a process (step) designated in advance.

[0019] A user 101 carries a user terminal device 102. The user terminal device 102 can use a technology of a global navigation satellite system such as a global positioning system (GPS). In other words, the user terminal device 102 can calculate its own position (latitude and longitude) based on radio waves received from a plurality of communication satellites. The user 101 can be a railway user 103. When using public transportation, the railway user 103 passes through a ticket gate at an entrance station 2 and an exit station 3. The user terminal device 102 and the ticket gate are connected to a travel time analysis system 105 via a wired or wireless network 106.

[0020] A traffic planner 116 views a conference display 114. The conference display 114 and an external system 113 are connected to the travel time analysis system 105 via a wired or wireless network 115. An administrator uses an administrator terminal device 111. The administrator terminal device 111 is connected to a calculation server 130 and an information distribution server 140 via a wired or wireless network 112. In FIG. 3, due to space limitations, the administrator and the administrator terminal device 111 are depicted inside the travel time analysis system 105, but in reality, they are outside.

[0021] (Station and route information) 4 is an example of the station / route information 123. The station / route information 123 consists of station information 310 and route information 320. In the station information 310, in association with a station ID stored in a station ID column 311, a station name is stored in a station name column 312, an owning company is stored in an owning company column 313, a location is stored in a location column 314, and a latitude and longitude is stored in a latitude and longitude column 315. The station ID in the station ID column 311 is an identifier that uniquely identifies a station. The station name in the station name column 312 is the name of the station. The owning company in the owning company column 313 is the name of the owner of the station. The location in the location column 314 is the location of the station. The latitude and longitude in the latitude and longitude field 315 are the latitude and longitude of the station location.

[0022] In the route information 320, the route name is stored in the route name column 322, the direction is stored in the destination column 323, the station ID is stored in the station ID column 324, and the running order is stored in the running order column 325 in association with the route ID stored in the route ID column 321. The route ID in the route ID column 321 is an identifier that uniquely identifies a route. Two route IDs are assigned to the same route depending on the direction. The route name in the route name column 322 is the name of the route. The direction in the direction column 323 indicates the direction in which the vehicle is traveling, either "upbound" or "downbound." The station ID in the station ID column 324 is an identifier that uniquely identifies a station. The running order in the running order column 325 is the order of stations at which a train (local train) stops.

[0023] (Movement data) 5 is an example of the movement data 124. In the movement data 124, in association with a trip ID stored in a trip ID field 301, a user ID is stored in a user ID field 302, a date and time is stored in a date and time field 303, weekdays and holidays are stored in a weekday and holiday field 304, latitude and longitude are stored in a latitude and longitude field 305, and attributes are stored in an attribute field 306. The trip ID in the trip ID column 301 is an identifier that uniquely identifies a trip. A trip is a series of going-out behaviors by a user. If there are n time periods during which the user does not move during a certain going-out behavior, the going-out behavior constitutes n+1 trips. The user ID in the user ID column 302 is an identifier that uniquely identifies a user.

[0024] The date and time in the date and time column 303 is the year, month, day, hour, minute, and second at the time the latitude and longitude were acquired. If the user terminal device 102 stays in one position and does not move, there is no record of the movement data 124 for the date and time in between. The weekday / day off field 304 displays either "weekday" indicating that the date and time is a weekday, or "day off" indicating that the date and time is not a weekday. The latitude and longitude in the latitude and longitude field 305 are the latitude and longitude of the location of the user terminal device 102 carried by the user. If the user is a railroad user, the latitude and longitude of the first record among the records having the same trip ID are the latitude and longitude of the departure point 1, and the latitude and longitude of the last record are the latitude and longitude of the destination 4. The attributes in the attribute column 306 are any information that indicates the characteristics of the user, and in this case are gender and age group.

[0025] The movement data 124 does not store all movements of all users. Some users who move around in an area do not carry a user terminal device 102, and even if they do, some have the GPS function set to "OFF." Records of the movement data 124 are created at a date and time period that is short enough that the user's movement trajectory can be accurately determined.

[0026] (Railway user separation results) 6 is an example of the railroad user separation result 125. In the railroad user separation result 125, in association with the trip ID stored in the trip ID field 401, a user ID is stored in a user ID field 402, a travel start time is stored in a travel start time field 403, a travel end time is stored in a travel end time field 404, a railroad use start time is stored in a railroad use start time field 405, a railroad use end time is stored in a railroad use end time field 406, a travel start point is stored in a travel start point field 407, a travel end point is stored in a travel end point field 408, a railroad use start station ID is stored in a railroad use start station ID field 409, and a railroad use end station ID is stored in a railroad use end station ID field 410.

[0027] The trip ID in the trip ID column 401 is the same as the trip ID in FIG. The user ID in the user ID column 402 is the same as the user ID in FIG. The travel start time in the travel start time field 403 is the year, month, day, hour, minute, and second at which the user departs from the departure point 1 . The travel end time in the travel end time field 404 is the year, month, day, hour, minute, and second of when the user arrives at destination 4. The railway use start time in the railway use start time column 405 is the year, month, day, hour, minute, and second when the user passes through the entrance station 2. If the user is not a railway user, "-" is stored in the column (similarly for columns 406, 409, and 410). The railway use end time in the railway use end time field 406 is the year, month, day, hour, minute, and second at the time the user passed through the exit station 3 .

[0028] The movement start point in the movement start point field 407 is the latitude and longitude of the departure point 1 . The movement end point in the movement end point field 408 is the latitude and longitude of the destination 4 . The railway use start station ID in the railway use start station ID field 409 is the station ID of entrance station 2. The railway use end station ID in the railway use end station ID field 410 is the station ID of exit station 3 . 1 is the time obtained by subtracting the travel start time 403 from the travel start time 405. The egress time 6 is the time obtained by subtracting the train use end time 406 from the travel end time 404.

[0029] (Maps and statistics) 7 is an example of the map and statistical information 126. The map and statistical information 126 is made up of map information 500 and population distribution 510. In the map information 500, area names are stored in an area name column 502 and map files are stored in a map file column 503 in association with area IDs stored in an area ID column 501.

[0030] The area ID in the area ID column 501 is an identifier that uniquely identifies an area. An area is a part that constitutes a region. An area may be an administrative division, or may be an unrelated grid on a map. The granularity, shape, and area of ​​an area are arbitrary. The area name in the area name column 502 is the name of the area. The area name here is the name of the administrative division of the area. The map file in the map file column 503 is the name of the electronic map file of the area.

[0031] In the population distribution 510, the number of residents is stored in a resident number column 512, the gender in a gender column 513, and the age group in an age column 514, in association with the area ID stored in an area ID column 511. The area ID in the area ID column 511 is an identifier that uniquely identifies an area. The number of residents in the number of residents column 512 is the number of residents residing in the area. The gender in the gender column 513 indicates the gender of the resident. The age group in the age column 514 indicates the age group of the resident.

[0032] (Train and bus usage history) 8 is an example of the train / bus usage history 127. The train / bus usage history 127 consists of an IC ticket history 600 and a ticket gate passage history 610. In the IC ticket history 600, in association with a train / bus trip ID stored in a train / bus trip ID column 601, an entrance station is stored in an entrance station column 602, an exit station is stored in an exit station column 603, an entrance time is stored in an entrance time column 604, an exit time is stored in an exit time column 605, and attributes are stored in an attribute column 606.

[0033] The railroad / bus trip ID in the railroad / bus trip ID column 601 is an identifier that uniquely identifies a railroad / bus trip. A railroad / bus trip is a series of movements from an entrance station 2 to an exit station 3 in which a railroad user uses an IC ticket (transportation IC card). The entrance station in the entrance station column 602 is the station ID of entrance station 2. The exit station in the exit station column 603 is the station ID of exit station 3. The entrance time in the entrance time column 604 is the year, month, day, hour, minute, and second at the time when the railroad user passes through the ticket gate at entrance station 2 . The exit time in the exit time column 605 is the year, month, day, hour, minute, and second at the time the railroad user passes through the ticket gate at the exit station 3 . The attributes in the attribute column 606 are the same as those in FIG.

[0034] In the ticket gate passage history 610, weekday and day off days are stored in a weekday / day off column 612, the exit time zone is stored in an exit time zone column 613, the number of people is stored in a number of passengers column 614, and the ticket type is stored in a ticket type column 615, in association with the entry and exit stations stored in an entry and exit station column 611. The entry / exit stations in the entry / exit station column 611 are a combination of the station ID of the entry station 2 and the station ID of the exit station 3 . The weekday off in the weekday off column 612 is either "weekday" indicating that the participation time period falls on a weekday, or "off" indicating that it falls on any other day. The exit time zone in the exit time zone column 613 is the time zone in which the railroad user passes through the ticket gate at the exit station 3 . The number in the number of people column 614 is the number of people using the railway. The ticket type in the ticket type field 615 is either a "commuter pass," indicating that the railroad user has used a commuter pass, or a "non-commuter pass," indicating that the user has used a one-time ticket.

[0035] (Time calculation result) FIG. 9 is an example of the time calculation result 128. In the time calculation result 128, in association with the departure area ID stored in the departure area ID column 701, the arrival area ID column 702 stores an arrival area ID, the station ID column 703 stores a station ID, the weekday / weekend column 704 stores a weekday / weekend, the analysis period column 705 stores an analysis period, the time period column 706 stores a time period, the attribute column 707 stores an attribute, the number of railway users column 708 stores a number of railway users, the number of non-railroad users column 709 stores a number of railway users, the access time of railway users column 710 stores a number of non-railroad users access times column 711 stores a number of non-railroad users access times column 712 stores a number of non-railroad users access times column 713 stores a number of non-railroad users access times column 714 stores a number of non-railroad users access times column 715 stores a number of non-railroad users access times column 720 stores a number of non-railroad users access times column 721 stores a number of non-railroad users access times column 722 stores a number of non-railroad users access times column 723 stores a number of non-railroad users access times column 724 stores a number of non-railroad users access times column 725 stores a number of non-railroad users access times column 726 stores a number of non-railroad users access times column 727 stores a number of non-railroad users access times column 728 stores a number of non-railroad users access times column 727 ...

[0036] The departure area ID in the departure area ID column 701 is the area ID of the area to which departure point 1 belongs (departure area). The arrival area ID in the arrival area ID column 702 is the area ID of the area (arrival area) to which the destination 4 belongs. The station ID in the station ID column 703 is the station ID of a station that belongs to or is adjacent to the departure area or arrival area. A plurality of station IDs may correspond to one combination of departure area ID and arrival area ID. The weekday / holiday in the weekday / holiday column 704 is either "weekday" indicating that the time period is on a weekday, or "holiday" indicating that it is on any other day.

[0037] The analysis period in the analysis period column 705 is the year and month that are the subject of people flow analysis. The time period in the time period column 706 is the time range that is the subject of people flow analysis. The attributes in the attribute column 707 are the same as those in FIG. The number of railroad users in the number of railroad users field 708 is the number of users (railroad users) who are estimated to have actually boarded or disembarked at the station identified by the station ID. The word "estimated" means that the time calculation result 128 is created based on the movement data 124, and since the movement data 124 does not store all the movements of all users, the time calculation result 128 also does not store all the movements of all users. The number of non-railroad users in the number of non-railroad users column 709 is the number of users (non-railroad users) who are presumed to have stopped in the vicinity of a station specified by a station ID or left the station, but did not actually board or disembark. The meaning of "presumed" is as described above. Non-railroad users move around the vicinity of a station, seemingly like railroad users, for a purpose other than boarding or disembarking.

[0038] The railway user access time in the railway user access time column 710 is a statistical value (average, median, mode, etc.) of the time it takes for railway users to arrive at the station identified by the station ID after departing from each departure point 1. The access time for non-railroad users in the access time for non-railroad users column 711 is a statistical value of the time it takes for a non-railroad user to arrive at a facility near the station identified by the station ID after departing from each departure point 1. The railroad user egress time in the railroad user egress time column 720 is a statistical value of the time it takes for a railroad user to arrive at each destination 4 after departing from a station specified by a station ID. The egress time for non-railroad users in the egress time for non-railroad users column 721 is a statistical value of the time it takes for a non-railroad user to arrive at their respective destination 4 after departing from a facility near the station identified by the station ID.

[0039] (Railway use determination processing procedure) FIG. 10 is a flowchart of the railway usage determination process procedure 135b. In step S101, the railway usage determination unit 135 of the calculation server 130 reads the station and line information 123 (FIG. 4) from the data server 120. In step S102, the railway usage determination unit 135 reads the movement data 124 (FIG. 5) from the data server 120. In step S103, the railway usage determination unit 135 starts the process of repeating steps S106 and S107 for each trip ID. In step S104, the railway usage determination unit 135 starts the process of repeating steps S106 and S107 for each record of the same trip ID (that is, for each date and time). In step S105, the railway usage determination unit 135 acquires unprocessed station IDs from the station information 310, and starts the process of repeating steps S106 and S107 for each station identified by the acquired station ID.

[0040] In step S106, the railroad use determination unit 135 determines whether the distance between the travel data 124 and the station is short. Specifically, the railroad use determination unit 135 calculates the distance between the latitude and longitude 305 of the travel data 124 and the latitude and longitude 315 of the station information 310, and compares the calculated distance with the "railroad use determination threshold" input by the user (administrator). If the distance is equal to or less than the threshold (step S106 "Yes"), the railroad use determination unit 135 proceeds to step S107, and otherwise (step S106 "No"), the railroad use determination unit 135 returns to step S105 and acquires other unprocessed station IDs.

[0041] In step S107, the railroad use determination unit 135 temporarily holds station IDs of station information 310 whose distance from the latitude and longitude 305 of the movement data 124 is determined to be equal to or less than the threshold. As the repetitive process progresses, multiple station IDs are held here. These station IDs identify stations that the user passed through (by railroad).

[0042] In step S108, the rail use determination unit 135 extracts a rail use start station ID and a rail use end station ID. Specifically, from among the station IDs held in step S107, the rail use determination unit 135 extracts the one with the earliest date and time in the corresponding travel data 124 as the rail use start station ID, and extracts the one with the latest date and time as the rail use end station ID.

[0043] In step S109, the railroad usage determination unit 135 creates the railroad user separation result 125 (FIG. 6). Specifically, the railroad usage determination unit 135 uses the movement data 124, the station and line information 123, and the extraction result in step S108 to create the railroad user separation result 125 and stores it in the data server 120. Incidentally, records such as those in the third and sixth lines of the railroad user separation result 125 are created for non-railroad users who have never passed through step S107. Thereafter, the railroad usage determination processing procedure 135b is terminated.

[0044] (Access / Egress Time Calculation Procedure) FIG. 11 is a flowchart of the access / egress time calculation process 136b. In step S201, the access / egress time calculation unit 136 of the calculation server 130 acquires the conditions of the analysis area. Specifically, the access / egress time calculation unit 136 acquires the conditions of the analysis area (departure area, arrival area, analysis period, granularity of time zone, granularity of attribute (age), and threshold value for railway use judgment) that the condition setting unit 145 acquires in advance from the user (administrator).

[0045] In step S202, the access / egress time calculation unit 136 reads the railway user separation result 125 (FIG. 6) from the data server 120. In step S203, the access / egress time calculation unit 136 acquires an unprocessed trip ID from the railroad user separation result 125, and starts the process of repeating steps S204 to S206 for each acquired trip ID. In step S204, the access / egress time calculation unit 136 converts the movement start point and the movement end point into an area ID. Specifically, the access / egress time calculation unit 136 refers to the map information 500 (FIG. 7) and converts each of the movement start point and the movement end point of the railroad user separation result 125 into an area ID.

[0046] In step S205, the access / egress time calculation unit 136 determines whether the converted area ID meets the analysis area conditions. Specifically, if the converted area ID meets the departure area or arrival area acquired in step S201 (step S205 "Yes"), the access / egress time calculation unit 136 proceeds to step S206. Otherwise (step S205 "No"), the access / egress time calculation unit 136 returns to step S203 and acquires an unprocessed trip ID.

[0047] In step S206, the access / egress time calculation unit 136 temporarily holds the corresponding data. Specifically, the access / egress time calculation unit 136 holds records of the railway user separation result 125 whose movement start point or movement end point corresponds to the departure area or arrival area to be analyzed by the user (administrator). In step S207, the access / egress time calculation unit 136 calculates the access time and egress time of the railway users, and calculates their respective distributions and statistics. The distribution is, for example, a histogram with the horizontal axis representing time and the vertical axis representing the number of cases.

[0048] In step S208, the access / egress time calculation unit 136 calculates the access time of non-railway users and the egress time of non-railway users, and calculates their respective distributions and statistical values. In step S209, the access / egress time calculation unit 136 creates the time calculation result 128 (FIG. 9) before correction and stores it in the data server 120. Specifically, the access / egress time calculation unit 136 creates the time calculation result 128 using the processing results up to step S208. At this time, the access / egress time calculation unit 136 calculates the number of railway users 708 and the number of non-railroad users 709 by counting the number of records in the railway user separation result 125 (FIG. 6). These are corrected to values ​​closer to the actual situation in a process described later. Thereafter, the access / egress time calculation processing procedure 136b ends.

[0049] (Distribution of access and egress times, etc.) FIG. 12 is a diagram for explaining the distribution of access and egress times. The display screen creation unit 146 of the information distribution server 140 displays the graph shown in FIG. 12 on the user terminal device 102, the administrator terminal device 111, or the conference display 114 (displays on a display device). "A. Distribution" is, for example, a histogram of access times from when a railway user departs from each departure point 1 to when the user arrives at a specific entrance station 2 in a specific analysis area. "B. Statistics" is, for example, a statistical value of access times. "C. Relationship diagram" is, for example, a diagram showing the relationship between the distance between each user's departure point 1 and entrance station 2 and the access time. These data are also created for egress times, and can also be created for non-railway users.

[0050] (Rail and bus usage record compilation process procedure) 13 is a flowchart of the railroad and bus usage record tallying process procedure 137b. First, the relationship between the IC ticket history 600 and the ticket gate passage history 610 (FIG. 8), which is the premise of FIG.

[0051] The IC passenger ticket history 600 is created by a transportation operator. Each time a railway user contactlessly inserts a transportation IC card into a ticket gate at the entrance station 2 and the exit station 3, one record of the IC passenger ticket history 600 is created. The number of records becomes huge. Therefore, in order to reduce the burden on calculation and storage resources, the records of cases in which a commuter pass was used, which account for the majority of the records of the IC passenger ticket history 600, are often deleted. As a result, the IC passenger ticket history 600 only collects and accumulates cases in which a non-commuter pass was used. In other words, the number of railway passengers who used a commuter pass is an additional number to the total number of records of the IC passenger ticket history 600. There is a "first discrepancy" that cannot be ignored between the actual total number of railway passengers who used a transportation IC card and the number of records of the IC passenger ticket history 600.

[0052] The ticket gate passage history 610 is also created by the transportation company. Each time a user inserts a ticket (magnetic card) into the ticket gate at the entrance station 2 and the exit station 3, the number of people in the corresponding record in the ticket gate passage history 610 increases by "1". Compared to the IC ticket history 600, the number of records in the ticket gate passage history 610 is an order of magnitude smaller. Therefore, unlike the IC ticket history 600, some data in the ticket gate passage history 610 is not deleted. Therefore, in order to fill the first gap, the ticket gate passage history 610 is used (described in detail later).

[0053] Railway users use either a transportation IC card or a magnetic card. The transportation IC card is a concept that includes electronic cards stored in the user terminal device 102. For ease of understanding, it is assumed below that there is no overlap between the number of people (number of records) in the IC passenger ticket history 600 and the number of people in the ticket gate passage history 610. Even if the exit time period in the ticket gate passage history 610 is rough, such as in units of one hour, the entry time and exit time in the IC passenger ticket history 600 are in units of seconds. Therefore, by using the IC passenger ticket history 600 and the ticket gate passage history together, it becomes possible to perform people flow analysis in units of, for example, five minutes.

[0054] In step S301, the railroad / bus usage record aggregation unit 137 of the calculation server 130 acquires the conditions of the analysis area. Specifically, the railroad / bus usage record aggregation unit 137 acquires the conditions of the analysis area that the condition setting unit 145 acquires in advance from the user (administrator).

[0055] In step S302, the train / bus usage record aggregation unit 137 reads the ticket gate passage history 610 (FIG. 8) from the data server 120. Specifically, the train / bus usage record aggregation unit 137 acquires a combination of records (also called "data to be processed") that have the same entry / exit stations, weekdays / holidays, and exit times from the ticket gate passage history 610. Here, multiple data to be processed are acquired. Each of the data to be processed consists of one record whose ticket type is "commuter pass" and one record whose ticket type is "non-commuter pass."

[0056] In step S303, the train / bus usage record aggregation unit 137 calculates the ratio of "total / non-commuter pass." Specifically, the train / bus usage record aggregation unit 137 divides the total number of people in the data to be processed by the number of people in the records whose ticket type is "non-commuter pass," and sets the result as "multiplication factor A." The number of "multiplication factors A" calculated is equal to the number of data to be processed.

[0057] In step S304, the train / bus usage record aggregation unit 137 reads the IC ticket history 600 (FIG. 8) from the data server 120. Specifically, the train / bus usage record aggregation unit 137 acquires a group of records (also called a "processing target group") that belong to the entry / exit stations, weekdays / weekends, and exit timeslots of the processing target data from the IC ticket history 600. The number of processing target groups is equal to the number of processing target data. In step S305, the train / bus usage record compilation unit 137 starts the process of repeating steps S306 to S308 for each of the unprocessed processing target data.

[0058] In step S306, the railroad / bus usage record aggregation unit 137 converts the entry station and the exit station into an area ID. Specifically, the railroad / bus usage record aggregation unit 137 refers to the station information 310 and the map information 500, and converts the entry and exit stations of the data to be processed and the entry and exit stations of the corresponding group to be processed into area IDs. In step S307, the railroad / bus usage record tabulation unit 137 tabulates records that match the analysis area. Specifically, the railroad / bus usage record tabulation unit 137 counts the number of records that belong to the processing target group.

[0059] In step S308, the railroad / bus usage record tabulation unit 137 corrects the number of people by the ratio of "total / non-commuter pass." Specifically, first, the railroad / bus usage record tabulation unit 137 multiplies the number counted in step S307 by "multiplication factor A," and sets the result as the "total number of IC card users." Secondly, the railroad and bus usage record aggregation unit 137 adds the total number of IC card users to the total number of people in the processing target data, and sets the result as the "first corrected number of railroad users." Thirdly, the train and bus usage record aggregation unit 137 divides the number of train users after the first correction by the number of train users 708 of the time calculation result 128 (FIG. 9) to obtain the “first correction coefficient”. Fourthly, the rail / bus usage record aggregation unit 137 multiplies the number of non-railroad users 709 of the time calculation result 128 by the "first correction coefficient" to obtain the "number of non-railroad users after first correction." Fifth, the rail / bus usage record aggregation unit 137 updates the number of rail users 708 and the number of non-rail users 709 in the time calculation result 128 with the “first corrected number of rail users” and the “first corrected number of non-rail users”, respectively. After all the repeated processes are completed, the rail / bus usage record aggregation process procedure 137b is terminated. That is, the railroad / bus usage record tabulation unit 137 corrects the number of people who required access time and the number of people who required egress time based on the history of people's actual use of public transportation.

[0060] (Number of people information completion processing procedure) 14 is a flowchart of the number of people information complementation process 138b. Because the movement data 124 does not store all movements of all users, a non-negligible "second discrepancy" occurs between the total number of trip IDs (total number of user IDs) in the movement data 124 and the total number (total number) of users who actually move in the area. Therefore, in order to fill the second discrepancy, the population distribution 510 is used (described in detail later).

[0061] In step S401, the number of people information complementing unit 138 of the calculation server 130 acquires the conditions of the analysis area. Specifically, the number of people information complementing unit 138 acquires the conditions of the analysis area that the condition setting unit 145 acquires in advance from the user (administrator). In step S402, the number of people information complement unit 138 reads the time calculation result 128 (FIG. 9) from the data server 120, and acquires the number of railroad passengers (NP1) of an unprocessed record of the time calculation result 128. The time calculation result 128 here may be the result after the processing procedure of FIG. 13 has been performed or may be the result before the processing procedure has been performed.

[0062] In step S403, the number of passengers information complementing unit 138 reads the train and bus usage history 127 (FIG. 8) from the data server 120. Specifically, first, the number of passengers information complementing unit 138 acquires records that satisfy all of the following conditions from the IC ticket history 600. The attribute in the attribute column 606 matches the attribute in the attribute column 707 of the unprocessed record in step S402. Either the entrance station in the entrance station column 602 or the exit station in the exit station column 603 matches the station ID in the station ID column 703 of an unprocessed record in step S402. The entry time in the entry time column 604 and the exit time in the exit time column 605 match the analysis period in the analysis period column 705 and the time period in the time period column 706 of the unprocessed record in step S402.

[0063] Secondly, the number of passengers information complementing unit 138 acquires records that satisfy all of the following conditions from the ticket gate passage history 610. · The entry / exit station in the entry / exit station column 611 matches the station ID in the station ID column 703 of the unprocessed record in step S402. · The departure time zone in the departure time zone column 613 matches the time zone in the time zone column 706 of the unprocessed record in step S402. Thirdly, the number information complementing unit 138 sets the result of adding the number of records obtained in "the first" of step S403 to the number of people in the records obtained in "the second" of step S403 as "NP2". Fourthly, the number information complementing unit 138 compares NP2 with NP1.

[0064] In step S404, the number information complementing unit 138 determines whether NP1 < NP2. Specifically, when NP1 ≥ NP2 (step S404 "No"), the number information complementing unit 138 proceeds to step S405, and when NP < NP2 (step S "No"), the number information complementing processing procedure 138b ends. In step S405, the number information complementing unit 138 reads the population distribution 510 (Fig. 7) from the data server 120.

[0065] In step S406, the number information complementing unit 138 corrects the number of people by the ratio of the number of pieces of movement data 124 (Fig. 5) to the number of residents. Specifically, firstly, the number information complementing unit 138 divides the number of residents 512 in the population distribution 510 by the number of records in the movement data 124 for each combination of area and attribute, and sets the result as the "second correction coefficient". Secondly, the number information complementing unit 138 sets the numbers obtained by multiplying the number of railway users 708 and the number of non-railway users 709 in the time calculation result 128 (Fig. 9) by the second correction coefficient as the "second corrected number of railway users" and the "second corrected number of non-railway users", respectively. Third, the number of people information complement unit 138 updates the number of railway users 708 and the number of non-railroad users 709 in the time calculation result 128 (FIG. 9) with the "second corrected number of railway users" and the "second corrected number of non-railroad users", respectively. Then, the number of people information complement processing procedure 138b is terminated. The number of people information complement processing procedure 138b is repeated for all unprocessed records in the time calculation result 128.

[0066] In FIG. 14, if the number of railroad users calculated from the movement data 124 is greater than the number of railroad users calculated from the railroad and bus usage history 127 (the movement data acquired using GPS technology is excessive and unreliable), the number of people information complementing unit 138 executes the correction in step S406. However, in step S404, "Yes" and "No" may be interchanged. In other words, if the movement data acquired using GPS technology is too small and unreliable, the number of people information complementing unit 138 may execute the correction in step S406. That is, the number of people information complementing unit 138 corrects the number of people who required the access time and the number of people who required the egress time based on the population distribution of the area where people live.

[0067] (Condition setting process) FIG. 15 is a flow chart of the condition setting process 145b. In step S1101, the condition setting unit 145 of the information distribution server 140 displays the management screen 1001 on the user terminal device 102 or the administrator terminal device 111. Although this is midway through FIG. 15, the description will now move to FIG.

[0068] (Management screen) Fig. 16 is an example of a management screen 1001. The user (administrator) inputs the departure area, arrival area, analysis period, granularity of time zones, granularity of attributes (age groups), and a threshold value for determining whether to use trains in the condition setting field 1002. Of these, the user may input a different value for the threshold value for determining whether to use trains for each departure area or arrival area. When many stations are concentrated in one area, such as in urban areas, this value will be small.

[0069] The program management field 1003 has a start button 1004, an interrupt button 1005, and a result display button 1006. When the condition setting unit 145 accepts that the user has pressed the start button 1004, each unit 135-138 of the calculation server 130 starts its respective processing. When the condition setting unit 145 accepts that the user has pressed the interrupt button 1005, each unit 135-138 interrupts its respective processing procedure. When the condition setting unit 145 accepts that the user has pressed the result display button 1006, the display screen creation unit 146 of the information distribution server 140 displays the analysis result display screen 1301 (FIG. 18 or FIG. 19) on the user terminal device 102, the administrator terminal device 111, or the conference display. The explanation will return to FIG. 15.

[0070] In step S1102, the condition setting unit 145 acquires conditions such as an analysis area, an analysis period, etc. Specifically, the condition setting unit 145 accepts an input of a departure area, etc. in the condition setting field 1002 of the management screen 1001 by the user. In step S1103, the condition setting unit 145 acquires the analysis process content. Specifically, the condition setting unit 145 accepts the user pressing each of the buttons 1004 to 1006 in the program management column 1003 of the management screen 1001. At this time, the user specifies a processing procedure to be a target such as "start." In step S1104, the condition setting unit 145 instructs each unit to start or stop the corresponding processing procedure, and then ends the condition setting processing procedure 145b.

[0071] (Display screen creation process) FIG. 17 is a flow chart of the display screen creation processing procedure 146b. In step S1201, the display screen creation unit 146 of the information distribution server 140 displays the analysis result display screen 1301 on the user terminal device 102, the conference display 114, or the manager terminal device 111. Although this is midway through Fig. 17, the explanation will now shift to Figs.

[0072] (Analysis results display screen) Figures 18 and 19 are examples of the analysis result display screen 1301. The analysis result display screen 1301 is actually one screen, but because it contains a wealth of display content, it is shown divided into Figures 18 and 19 due to space limitations. The following information is displayed on the analysis result display screen 1301 in Figure 18.

[0073] <1> Departure area, arrival area and analysis period set by the user (same as in Figure 19) The user can reset the analysis period by manipulating the "ALL" field. <2> Histograms showing the distribution of access times and egress times for railway users and non-railway users The user can select a station by operating the "Station: ALL" field. <3> Map of the departure or arrival area Users can select either "access time" or "egress time" and the time period. The direction of the arrows connecting the departure (arrival) area and each station indicates the direction of people flowing at the access (egress), and their thickness indicates the number of people. The departure (arrival) area is divided into square grids. The hatching of the grids indicates whether the number of people at the access (egress) is "more rail users", "more non-rail users", "about the same amount of both", or "no travelers". 4. Pie chart showing attribute ratios The attributes here are a combination of gender and age group.

[0074] The analysis result display screen 1301 in FIG. 19 displays the following information: <5> Access and egress timetable This has substantially the same contents as the time calculation result 128 (FIG. 9). The user selects either the access time or the egress time, the station, the user's gender, the user's age group, and the like. 6. Relationship between access time (or egress time) and train / bus usage ratio A vertical dotted line is plotted to indicate the access (or egress) time at which the ratio reaches a given value (eg, 50%). For the explanation, refer back to FIG.

[0075] In step S1202, the display screen creation unit 146 acquires display conditions. The display conditions here include conditions input by the user in the condition setting field 1002 of the management screen 1001, as well as conditions selected on the analysis result display screen 1301. In step S1203, display screen creation unit 146 extracts data that meets the display conditions from time calculation result 128 (FIG. 9). In step S1204, the display screen creation unit 146 collects the extracted data and displays it as the analysis result display screen 1101 on the display device. In step S1205, the display screen creation unit 146 draws a graph and displays it on the analysis result display screen 1301. Thereafter, the display screen creation processing procedure 146b ends.

[0076] The present invention is not limited to the above-described embodiment, but includes various modified examples. For example, the above-described embodiment has been described in detail to easily explain the present invention, and is not necessarily limited to those including all of the configurations described. It is also possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. It is also possible to add, delete, or replace a part of the configuration of each embodiment with another configuration.

[0077] The effects of the travel time analysis system of this embodiment are as follows. (1) The travel time analysis system can calculate agress times and egress times based on people's movement data and the locations where public transportation is used, depending on whether or not public transportation is used. (2) The travel time analysis system may use travel data obtained using satellite positioning system technology such as GPS. (3) The travel time analysis system can calculate access time and the number of people required for access, as well as egress time and the number of people required for egress, for each time period, etc. (4) The travel time analysis system can correct the number of people taking access time, etc. based on the history of public transportation usage. (5) The travel time analysis system can correct the number of people taking time to access a location, etc., based on population distribution. [Explanation of symbols]

[0078] 101 users (railway users, non-railway users, people) 102 User terminal device 103 users (railway users, people) 105 Travel Time Analysis System 123 Station / Route Information 124 Movement Data 125 Railway User Separation Results 126 Maps & Statistics 127 Train and bus history 128 hours calculation result 135 Railway Use Determination Department (Use Determination Department) 136 Access / Egress Time Calculation Unit 137 Railway and bus usage record calculation unit (usage record calculation unit) 138 Number of people information supplement section 145 Condition setting section 146 Display Screen Creation Department 310 Station Information 320 Route Information 500 Map Information 510 Population distribution 600 IC ticket history 610 Ticket gate passing history 1001 Management screen 1301 Analysis result display screen

Claims

1. A travel time analysis system comprising a calculation server and an information distribution server, The calculation server includes: a usage determination unit that separates movement data that stores the positions of people in chronological order into movement data related to people who used public transportation and movement data related to people who did not use public transportation based on the positions of places where public transportation was used; an access / egress time calculation unit that calculates an access time from a departure point in the movement data to a place where public transportation is used, and an egress time from the place where public transportation is used to a destination of the movement data, for each of the presence or absence of use of public transportation; Equipped with The information distribution server includes: a display screen creation unit that displays the calculated access time and egress time on a display device depending on whether or not public transportation is used; A travel time analysis system comprising:

2. The movement data is The information was obtained using satellite positioning technology from a terminal device carried by a person; The travel time analysis system according to claim 1 .

3. The access / egress time calculation unit Calculating a combination of the access time and the number of people who required the access time, and a combination of the egress time and the number of people who required the egress time for each time period, person attribute, or public transportation location; The display screen creation unit Displaying the calculated combinations by time period, person attributes, or public transportation usage location; The travel time analysis system according to claim 1 .

4. a usage record tabulation unit that corrects the number of people who have taken the access time and the number of people who have taken the egress time based on a history of people actually using the public transportation facility; The travel time analysis system according to claim 1 .

5. a number-of-people information complementing unit that corrects the number of people who required the access time and the number of people who required the egress time based on a population distribution of an area where people live; The travel time analysis system according to claim 1 .

6. A travel time analysis method executed in a travel time analysis system including a calculation server and an information distribution server, The usage determination unit of the calculation server A step of separating movement data that stores the positions of people in a time series into movement data related to people who used public transportation and movement data related to people who did not use public transportation based on the positions of places where public transportation was used; The access / egress time calculation unit of the calculation server Calculating an access time from a departure point in the movement data to a location where public transportation is used, and an egress time from the location where public transportation is used to a destination of the movement data, for each of the presence or absence of use of public transportation; A display screen creation unit of the information distribution server, displaying the calculated access time and egress time on a display device according to whether or not public transportation is used; A travel time analysis method comprising:

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