WO2015049801A1 - Système de guidage de passagers et procédé de guidage de passagers - Google Patents

Système de guidage de passagers et procédé de guidage de passagers Download PDF

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Publication number
WO2015049801A1
WO2015049801A1 PCT/JP2013/077154 JP2013077154W WO2015049801A1 WO 2015049801 A1 WO2015049801 A1 WO 2015049801A1 JP 2013077154 W JP2013077154 W JP 2013077154W WO 2015049801 A1 WO2015049801 A1 WO 2015049801A1
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Prior art keywords
accident
user
data
route
time
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PCT/JP2013/077154
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English (en)
Japanese (ja)
Inventor
修平 古谷
理恵子 大塚
鈴木　敬
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株式会社日立製作所
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Priority to JP2015540355A priority Critical patent/JP6258952B2/ja
Priority to SG11201602577XA priority patent/SG11201602577XA/en
Priority to PCT/JP2013/077154 priority patent/WO2015049801A1/fr
Publication of WO2015049801A1 publication Critical patent/WO2015049801A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40—Business processes related to the transportation industry
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem

Definitions

  • the present invention uses traffic IC card data to extract passengers affected by transportation obstacles and distribute processed information for each user, thereby prompting passengers to reduce congestion at the time of transportation obstacles It is related with the calculation method and system which implement
  • Patent Document 1 discloses a system in which accident information and the like are distributed to a user when a transportation failure occurs on a travel route registered in advance by the user. Yes.
  • the present invention has been made in view of the above, and the user can know a detour route suitable for himself / herself at the time of transportation trouble without taking time and trouble, and the railway operator can avoid congestion at the time of transportation trouble.
  • the purpose is to avoid.
  • a passenger guidance system is a passenger guidance system that guides a user who travels a route using an IC card, and uses the transportation date and time.
  • an action pattern extraction unit that outputs the user's action pattern based on the movement log data in which the user's movement history including the route is recorded, a use date and time included in the action pattern, and an accident occurrence Based on the accident information data including the section, the accident occurrence time, and the operation resumption time, among the users, the user includes the accident occurrence section in the route and includes the accident occurrence time in the use date and time.
  • a passenger extracting unit for obtaining a detour route of the user, Out of the users to whom the information distribution data has been distributed based on the distribution unit that transmits the information distribution data including the detour route to the issued user terminal, and the movement log data and the detour route, It is configured as a passenger guidance system comprising: an action determination unit that determines whether or not the vehicle has traveled by the detour route from time to time and records the result in an accident pattern data.
  • the present invention is grasped as a passenger guidance method performed in the above passenger guidance system.
  • the user can know a detour route suitable for himself / herself at the time of transportation failure without trouble, and the railway operator can avoid congestion at the time of transportation failure.
  • 1 is a basic configuration diagram of an entire system for implementing the present invention. It is a figure explaining the structure of the record which stores the utilization log
  • Embodiments of a passenger guidance system and a passenger guidance method according to the present invention will be described in detail with reference to FIGS.
  • FIG. 1 is a diagram for explaining the flow of this system.
  • the system generates movement log data / purchase log data (101) when a transaction (100) such as movement or purchase based on traffic IC card data is performed.
  • Movement log data / purchase log data (hereinafter, these may be collectively referred to as movement / purchase log data) is a history of when a user moves using a transportation IC card or purchases an article. Data to be retained.
  • movement log data / purchase log data (hereinafter, these may be collectively referred to as movement / purchase log data) is a history of when a user moves using a transportation IC card or purchases an article. Data to be retained.
  • a case where an article is purchased as an application of a traffic IC card other than when the user moves is described as an example.
  • the user receives a service or charges, etc. The same can be applied to the case where the user performs various actions other than movement.
  • the movement log data / purchase log data may be generated sequentially by the system in accordance with the update of the traffic IC card data, or may be generated by batch processing at a constant cycle.
  • the process flow of this system is roughly divided into three types: before the accident (120), during the accident (130), and after the accident (140).
  • this system Before the accident occurs (120), this system generates behavior pattern data by extracting typical travel routes and time zones of passengers from travel log data and purchase log data (121).
  • the behavior pattern data is data in which the user's past behavior is recorded, such as when the user has used the transportation IC card in the past to move or purchase an article.
  • this system calculates the congestion rate by estimating the number of passengers from the movement log data before the accident occurs (120) (122) and stores it in the database.
  • the system registers the traffic IC card ID and mail address information (123), and generates registrant data (124). The user registered in this registrant data becomes the user of this system.
  • the system acquires behavior pattern data and accident information (131), and extracts affected passengers from the movement log data / purchase log data (132).
  • Accident information is data that records information on railway operators and accidents that occurred.
  • the detour route information is delivered to the affected passenger by referring to the registrant data (134).
  • the detour route information is information in which a detour route obtained by this system from past actions of each user is recorded.
  • the congestion rate of the detour route and the behavior pattern data at the time of the accident are generated (125), and information corresponding to the behavior pattern at the time of the accident of each passenger is attached from these information.
  • the behavior pattern data at the time of the accident is data in which the behavior pattern of the user at the time of the past accident is recorded.
  • the system estimates the behavior of the user after the accident from the movement log data / purchase log data (141), and updates the behavior pattern data at the time of the accident (142). By updating the behavior pattern data at the time of the accident, it becomes possible to distribute the information appropriately for the congestion rate and the user with high accuracy at the time of information distribution.
  • FIG. 2 is an overall configuration diagram of the system.
  • Passengers (200) who use transportation use a traffic IC card (201) or a portable terminal (204) having an equivalent function, and pass through a ticket gate or a reading terminal (202) installed in the vehicle.
  • the data acquired from the traffic IC card (201) and portable terminal (204) by those ticket gates and in-vehicle terminals are transmitted via the network (207) to the server group (210) managed by the respective traffic operators. Is done.
  • This system (208) includes a data server (210), a calculation server (230), and an information distribution server (250), and is configured by a traffic IC card (201) or a portable terminal (equivalent to an equivalent function). 204) is used to perform analysis processing.
  • the data server (210), the calculation server (230), and the information distribution server (250) will be described as a server group. However, all may be executed by one server, or a plurality of servers. It is also possible to configure so that the functions of the server group can be executed in parallel.
  • the data server (210) records user data read by an IC card reader terminal (not shown) installed in a ticket gate (202) or a store in a database (211) in the server.
  • the data to be collected and stored includes traffic IC card data (212) and basic master data (213) such as stations, bus stops, and routes.
  • traffic IC card data (212) and basic master data (213) such as stations, bus stops, and routes.
  • movement / purchase log data (214) obtained by processing the traffic IC card data (212), and behavior pattern data (215) that is typical movement data of a user generated by totaling and analyzing the movement log data. Is stored.
  • accident pattern data (217) analyzed for each card ID from accident information data (216) input by a railway operator or the like, and travel / purchase log data (214). ) Is included.
  • an accident behavior pattern table (218) in which the accident behavior patterns are classified in advance. Furthermore, information distribution data (219) for storing information distribution contents to the user of this system is stored. Furthermore, the user's traffic IC card data (212) and the registrant data (220) including the traffic IC card ID and mail address for sending information to the user are stored.
  • each of the above-described data is described as being stored in the database (211) in the HDD (Hard Disk Drive).
  • the data is stored in a CD-ROM drive or flash memory, and is read and written by this system.
  • various programs and various data may be divided and recorded in a plurality of recording devices. The same applies to the calculation server (230) and information distribution server (250) described below.
  • the calculation server (230) is a process for generating a travel / purchase log from the data stored in the data server (210), a process for estimating a traffic congestion rate, a process for extracting a behavior pattern of a user's travel route, Mainly performs the process of extracting passengers affected by transportation obstacles and the process of determining behavior after an accident.
  • the calculation server (230) mainly includes a network interface (I / F (A)) (231), a CPU (232), a memory (232), and a storage unit (239).
  • the network interface (I / F (A)) (231) is an interface for connecting to a network.
  • the database (239) includes a travel / purchase log generation program (234), a congestion rate estimation program (235), an action pattern extraction program (236), an affected passenger extraction program (237), and an accident determination program.
  • a program group such as (238), and calculation processing results such as passenger data (241) affected by the transportation obstacle generated by the extraction program of the affected passengers are stored.
  • each program group When each program group is executed, data to be analyzed is read from the data server (210), temporarily stored in the memory (233), and each program (234, 235, 236) is stored in the CPU (232). 237, 238) are read into the memory and executed to implement various functions.
  • the execution timing of these programs may be performed, for example, every time new data is added to the request timing or the data server (210), or automatically as a batch process at a predetermined time every day. Processing may be performed.
  • the program (234, 235, 236, 237, 238) may process only newly added difference data.
  • the information distribution server (250) includes a network interface (I / F (B)) (251), a CPU (253), a memory (254), and a database (252).
  • the network interface (I / F (B)) (251) is an interface for connecting to a network.
  • the database (252) records various programs and various data. Similar to the calculation server (230), the CPU (253) reads various programs (simulation program (255), display screen generation program (256)) stored in the recording device (252) into the memory (254). Various functions are realized by executing them.
  • the generated detour route information, congestion rate, simulation result, and other information are distributed to the operator (272) via the interface (I / F (C)) (258) and the network (270).
  • the interface (I / F (C)) (258) and the network (270).
  • detour route information and the like can be distributed to the user (281) via the network (273), and can be acquired by an information terminal (282) such as a portable terminal.
  • FIG. 3 is a diagram showing an example of the traffic IC card data (212) stored in the data server (210).
  • the traffic IC card data (212) includes a log ID (301) for identifying a history of travel and purchase, a card ID (302) for identifying a traffic IC card, and a user.
  • Station / bus stop ID (303) for identifying the station or bus stop where the reading terminal that has passed (entered or exited) is installed, use that indicates the date and time when the transportation was started at the departure point, or the date and time of purchase
  • the use type (305) for identifying the type of processing at the reading terminal used
  • the traffic IC card data Information such as a purchase place ID (306), a payment amount (307) when moving or purchasing goods, and the like.
  • a user enters the premises of the station “10001” at 12:00 on January 1, 2009 using a traffic IC card identified by the card ID “1234567” and is 200 yen.
  • the traffic system IC card data (212) stores the specific contents when the user acts using the traffic system IC card in association with each other.
  • FIG. 4 is a diagram showing examples of types of master data (213) stored in the data server (210) and respective data structures.
  • the master data (213) includes a station / bus stop master (410) for identifying stations and bus stops, and a route master (420) for identifying routes of transportation such as railways and buses. ),
  • a timetable master (430) which is master data of a timetable of transportation such as railways and buses, a route master (440) indicating a route from the departure point to the arrival point, and a transportation IC card
  • a purchase place master (460) indicating the place where goods are purchased or service is provided is included.
  • Master data other than the purchase place master (460) is master data related to transportation operations.
  • the station / bus stop master (410) includes a station / bus stop ID (411), a station / bus stop name (412) identified by the ID, and a company (usually of the route) Information such as (owning company) (413), station / bus stop location (414), and latitude / longitude information (415) of the location are stored in association with each other.
  • the location of the station A owned by the owning company “XX” is “XX city XX city,...”, And its latitude and longitude are “139.XXX, 34.XXX”. It is shown that.
  • the station A is identified by the station / bus stop ID “10001”.
  • the route master (420) includes the route ID (421), the route name (422) of the route, the name of the operating company (423) that operates the route, the train operated, Information such as the route type (424) indicating the type of bus and the allowable number of passengers (425) of the train of the route type are stored in association with each other.
  • the route of each stop of the X-ray identified by the route ID “200001” is operated by the operating company “XX”, and a railway ordinary train that can ride up to 500 people is operated. Yes.
  • the timetable master (430) includes a route ID (431), a station / bus stop ID (432), an order (433) indicating the stop station / bus stop on the route, and a time (434) from the station / bus stop. ),
  • the time of arrival at the station / bus stop (435), the required time from the starting point of the route (436), and the like are stored in association with each other.
  • the route identified by the route ID “2002” includes the trains in the order from the station identified by the station / bus stop ID “10001” to the station identified by the next station / bus stop ID “10002”. Indicates that the bus is operating. Further, the time required is 10 minutes, and the arrival time is 12:10. Since the first record is the first station / bus stop, the same departure time as the next record is stored.
  • the route master (440) is a route ID (441) for identifying a route from the boarding station or bus stop to the getting off station or bus stop, boarding station / bus stop ID (442), getting off station / bus stop ID (443), and the like. Are stored in association with each other.
  • the route master (440) also has a route ID (444) for the number of transfers from the departure point to the destination, a transfer station / bus stop ID (445), and a transfer station / bus stop ID (446). Finally, information such as the number of boarding routes (447) from the departure point to the destination, the standard time required from the departure point to the destination (448), and the charge (449) are supported. It is remembered. In FIG.
  • the route identified by the route ID “30002” is identified by the boarding station / bus stop identified by the boarding station / bus stop ID “10001” and the departure station / bus stop ID “10031”.
  • change from the departure point to the destination change to the route identified by route ID “20002”, and change to the transfer station / bus stop (transfer station / bus stop ID “10002”). )
  • To the transfer station / bus stop transfer station / bus stop ID “20004”.
  • the remaining four transfers are made to arrive at the destination.
  • the standard required time from the starting point to the destination on this route is 42 minutes, and the charge is 520 yen.
  • the purchase place master (460) includes a purchase place ID (461) indicating a place where the purchase of goods and provision of services are received, the store name (462) of the store at the place, the location (463) of the store, Information such as the latitude / longitude of the location (464) and the store type (465) such as a convenience store or vending machine is stored in association with each other.
  • a purchase place ID 461 indicating a place where the purchase of goods and provision of services are received
  • the store name (462) of the store at the place the location (463) of the store, Information such as the latitude / longitude of the location (464) and the store type (465) such as a convenience store or vending machine is stored in association with each other.
  • the location of the store “XX Mart” identified by the purchase place ID “50001” is “XX prefecture XX city...”
  • the latitude and longitude thereof are “140.XXX, 35”. .XXX ".
  • this store indicates that it is
  • FIG. 5 is a diagram showing an example of the data structure of the behavior pattern table (218) at the time of an accident stored in the data server (210).
  • the behavior pattern table (450) at the time of an accident is moved using a behavior pattern ID (451) at the time of an accident, a detour route according to distribution information described later, or a detour according to distribution information.
  • a behavior pattern ID 451
  • a detour route according to distribution information described later
  • a detour according to distribution information.
  • FIG. 5 shows that, for example, when the user takes an action to move using the detour route distributed by the distribution information, the action pattern ID “1” at the time of the accident is identified. Further, the distribution information is compared with the movement / purchase log data (214), and if the detour path included in the distribution information is recorded in the log data, it is determined that the user has used the detour path. Which indicates that.
  • the departure and arrival locations of the movement / purchase log data (214) do not continue, it is determined that the user has changed at a station on the way, and other transportation means (for example, because the train was used) If there is, it is determined that an action using a bus, a taxi, or another railway company) is taken (behavior pattern ID “3” at the time of the accident). If there is a log, it is determined that the user has purchased a product or the like at a store outside the station and waited after eating and drinking (action pattern IDs “4” and “5” at the time of the accident). Further, if it is neither of these, it is determined that it is determined that the station is on standby as it is (action pattern ID “6” at the time of an accident).
  • FIG. 6 is a diagram showing an example of the data structure of the movement / purchase log data (214) stored in the data server (210).
  • the movement / purchase log data (214) includes movement log data (510) and purchase log data (530).
  • the travel log data (510) includes a log ID (511) for identifying the travel log, a card ID (512) of the user who has moved, a boarding date (513) indicating the date and time when the transportation method is started at the departure point, and arrival Alighting date and time (514) indicating the date and time when the use of the means of transportation was terminated at the point, a boarding station / bus stop ID (515) at which the user got on the boarding date, and a getting off station / bus stop ID at which the user got off (516) and the payment amount (517) is included.
  • the boarding station Information such as the bus stop ID (521) and the getting-off station / bus stop ID (522) is stored in association with each other.
  • a user of a traffic card identified by the card ID “1234567” gets on from the station / bus stop identified by “90001” at 12:30 on August 26, 2013, and the same day At 13:25, it got off at the station / bus stop identified by “90002”, indicating that 200 yen was withdrawn from the traffic IC card of the user.
  • the purchase log data (530) includes a log ID (531) for identifying a purchase log, a card ID (532) of a user who has purchased, a purchase date and time (533) indicating the date and time of purchase history, and a payment amount (534) at the time of purchase.
  • Information such as a purchase place ID (535) for identifying the purchase place is stored in association with each other.
  • a user of a traffic card identified by a card ID “1234567” makes a purchase at a purchase place identified by “50001” at 12:32 on August 26, 2013, and It shows that 200 yen has been withdrawn from the user's transportation IC card. This indicates that the log ID of this record is “70001B”.
  • the user of the traffic card identified by the card ID “1234567” enters the train (station) from the station / bus stop identified by “90001” and is identified by “50001” two minutes later. It can be seen that goods and the like were purchased and boarded at a purchase place (for example, a convenience store in the station).
  • FIG. 7 is a diagram showing an example of the data structure of registrant data (220) stored in the data server (210).
  • the registrant data (220) includes a registrant ID (601) for identifying a registrant who is a user of the system, and a traffic IC card for identifying the traffic IC card data (212) of the registrant.
  • a card ID (602) and a mail address (603) as a transmission destination for transmitting information in the event of a transportation failure.
  • the card ID (602) of the traffic IC card is used, for example, to extract registrant information from the traffic IC card data (212).
  • the user with the registrant ID “100001” uses the traffic card identified by the traffic card ID “123451” and the mail address is “aaa@abc.com”. ing.
  • Information distribution data to be described later is distributed to this address.
  • FIG. 8 is a diagram showing an example of the data structure of the accident information data (220) stored in the data server (210).
  • the accident information data (220) includes an accident ID (701) for identifying an accident such as a transport fault that has occurred, a route ID (702) where the accident occurred, and an accident occurrence section A that is the starting station / bus stop of the accident section. (703), an accident occurrence section B (704), an accident occurrence time (705), and an operation resumption time (706), which are end stations / bus stops of the accident section, are stored in association with each other.
  • FIG. 8 for example, at 11:00 on August 26, 2013, an accident occurred between the station A and the station B on the route identified by the route ID “1001”. It shows that 30 minutes are expected.
  • the accident information data (220) is preset by the business operator (272).
  • the accident information data includes the day of the week in order to identify the passengers who are affected by the accident such as a transportation failure using the accident information data (220) and the behavior pattern data (215). Also good.
  • the affected passengers are identified using the time of the accident and the day of the week as keys, so if there are many users who travel daily and there are many routes, the affected passengers can be identified more quickly. can do.
  • FIG. 9 is a diagram showing an example of a data structure of passenger data (218) stored in the data server (210) and affected by the accident.
  • the affected passenger data (218) includes an accident ID (801), a card ID (802), and an expected encounter date and time (805) at which the affected passenger encounters an accident.
  • the boarding station / bus stop ID (807) and the getting-off station / bus stop ID (808) that got off the detour route are stored in association with each other.
  • the user with the card ID “10001” at 11:45 on August 26, 2013 is the boarding station identified by the route “10003” identified by the route ID “3003”. It shows that it is sufficient to use a detour route of getting on at the bus stop and getting off at the getting-off station / bus stop identified by “1101” at 12:00 on the same day.
  • the route ID is included in the passenger data (218) affected by the accident, but actually, the route ID is included as in the case of FIG. 6.
  • FIG. 10 is a diagram showing an example of the data structure of the action pattern data (217) at the time of an accident stored in the data server (210).
  • the action pattern data (217) at the time of an accident includes a card ID (901), an accident ID (902), an action pattern ID at the past accident (903), and a detour route actually used by the user of the card ID at the time of the accident ( 904) are stored in association with each other.
  • the detour route actually used stores the same contents as the movement log data (510) shown in FIG. In FIG. 10, for example, when a user of a traffic IC card identified by the card ID “100001” has encountered an accident identified by the accident ID “20001” in the past, the user is identified by the action pattern ID “1”.
  • the user has detoured and moved by the detour route (904) actually used at the time of the accident (for example, the route shown in FIG. 10.
  • the latest action pattern is Although it is explained on the premise that the user is retained, it may be retained in the history retroactively in order to grasp the characteristics of the user, etc. It is possible to determine whether or not the person is a person who makes a detour, or whether the person tends to wait unfavorably for movement.
  • FIG. 11 is a diagram showing an example of the data structure of the information distribution data (219) stored in the data server (210).
  • the information distribution data (219) includes an accident ID (1001), a registrant ID (1002) of the passenger who distributed the information, a distribution date and time (1003) of this data, and an action pattern ID (1004) of the registrant in the past. ) Are stored in association with each other.
  • the boarding date and time predicted boarding date and time
  • the user whose registrant ID is “100001” indicates the behavior pattern at the time of the accident when the accident identified by the accident ID “20001” occurred in the past, and the detour route similar to FIG. This shows that information such as information was distributed at 11:45 on August 26, 2013.
  • the timing at which this distribution information is actually distributed to the user is appropriately determined by the operator. Specifically, distribution is performed at the timing determined on the screen (FIG. 19) of the operator's operation terminal (271) described later and when the distribution button is pressed. The user can know the detour route suitable for the user by referring to the distribution information.
  • FIG. 12 is a diagram illustrating a processing procedure of processing (log data acquisition processing) in which movement / purchase log data (101) is generated from the traffic system IC card data (100) and stored in the data server (210).
  • processing log data acquisition processing
  • movement / purchase log data (101) is generated from the traffic system IC card data (100) and stored in the data server (210).
  • the storage process in the data server (210) is performed by batch processing once every day at a predetermined time, but the timing can be arbitrarily determined.
  • the movement / purchase log generation program (234) of the calculation server (230) reads the traffic IC card data (212) stored in the data server (210) (processing step 1100).
  • the movement / purchase log generation program (234) sorts the records for each card ID and use / purchase date / time included in the read traffic IC card data (212) (processing step 1101).
  • the movement / purchase log generation program (234) reads the sorted records of the traffic IC card data (212) (processing step 1102), and determines whether or not the usage type of the read record is purchasing (processing). Step 1103).
  • the movement / purchase log generation program (234) determines that the usage type of the read record is not purchase (processing step 1103; No), it further determines whether or not the usage type of the read record is entrance. (Processing Step 1104), and when it is determined that the usage type of the read record is entrance (Processing Step 1104; Yes), the card ID, station / bus stop ID, usage / purchase date and time, payment amount from the record Is acquired (processing step 1105).
  • the transfer / purchase log generation program (234) determines that the usage type of the read record is not entry (processing step 1104; No)
  • the transfer / purchase log generation program (234) determines that the usage type of the read record is exit, and the record The user ID, station / bus stop ID, use / purchase date and time, and payment amount are acquired (processing step 1106).
  • the movement / purchase log generation program determines whether or not the read record is the last record (processing step 1107), and if it is determined that it is not the last record (processing step 1107; No), If it is determined that the read record is the last record (processing step 1107; Yes), the movement / purchase log data (214) is created from the acquired data and stored in the data server (step 1102). Processing step 1108), the processing ends (processing step 1109).
  • the movement / purchase log generation program (234) determines whether the movement is the same user (that is, one movement by a certain user), and the movement / purchase log generation program (234) determines that the movement is a single movement
  • the boarding date and time and the getting off date are recorded in one record.
  • the determination as to whether or not the movement is one time is made, for example, based on whether or not the traffic IC card data with the same card ID is recorded in the time zone before and after the boarding date and time and the date and time of getting off.
  • the previous record with the same card ID is regarded as one movement.
  • log ID is defined so that a record may become unique about each of movement log data and purchase log data.
  • FIG. 13 is a diagram for explaining a processing procedure (behavior pattern estimation processing) of generating behavior pattern data from the movement log data (510) shown in FIG. 6 and storing it in the data server.
  • the behavior pattern extraction program (236) reads the movement log data generated in FIG. 12 (processing step 1200). Next, the behavior pattern extraction program (236) sorts by card ID and boarding time included in the movement log data (processing step 1201), and reads one record of the sorted movement log (processing step 1202). .
  • the behavior pattern extraction program (236) acquires the card ID, route ID, boarding station / bus stop ID, getting-off station / bus stop ID, boarding date / time, and boarding date / time included in the record (processing step 1203). Then, the behavior pattern extraction program (236) identifies a record having the same combination of route ID, boarding station / bus stop ID, and getting-off station / bus stop ID for each card ID, and a boarding date / time, getting off date / time, and a calendar (not shown) The average value of the boarding date / time and the getting-off date / time for each day of the week is calculated by comparing with the information (processing step 1204).
  • the average values of the boarding date / time and the getting-off date / time of the plurality of Mondays are calculated and aggregated. Further, when the users with the same card ID are moving on different routes on the same day of the week, they are sequentially added to the record as in the case of the movement log data. Note that the calendar information may be held by the present system, or information that is widely used generally via a network may be read.
  • the behavior pattern extraction program (236) determines whether or not the read record is the last record (processing step 1205), and when the read record is not the last record (processing step 1205; No). Returning to the processing step 1202, the subsequent processing is repeated.
  • the action pattern extraction program (236) reads the card ID, day of the week, boarding date / time, getting-off date / time, boarding station / bus stop ID, getting-off station / Action pattern data in which the bus stop ID and route ID are output is created and stored in the database (211) of the data server (210) (processing step 1206).
  • FIG. 22 is a diagram showing an example of the data structure of the action pattern data (215) stored in the data server (210).
  • the action pattern data (215) includes a card ID (2101), a day of the week (2102), a boarding date and time (2103), a boarding station / bus stop ID (2104), an exit station / bus stop ID (2105), The route ID (2106) and the getting-off station / bus stop ID (2107) are stored in association with each other.
  • the user identified by the card ID “10001” gets on at 07:00 every Monday from the boarding station / bus stop identified by the boarding station / bus stop ID “90001”.
  • the route ID of getting off at the boarding station / bus stop identified by the boarding station / bus stop ID “90001” at 08:00 is moving along the route identified by “30001”.
  • these pieces of information are sequentially added to the record as with the movement log data.
  • a record is generated for each card ID and for each day of the week, and the behavior pattern for each day of the week can be grasped for each user.
  • a process for generating passenger data (241) that is affected by an accident such as a transportation failure will be described.
  • FIG. 14 is a diagram for explaining a processing procedure of processing (passenger data generation processing) in which passenger data (241) affected by the movement log is generated and stored in the storage unit.
  • passenger data 241 affected by the movement log is generated and stored in the storage unit.
  • an accident such as a transportation failure occurs in a certain section of the transportation system, and the accident information data (216) as shown in FIG. 8 is stored in the data server (210) by the operator.
  • the accident information data (216) as shown in FIG. 8 is stored in the data server (210) by the operator.
  • the affected passenger extraction program (237) first reads accident information data (216) and behavior pattern data (215) (processing step 1300). The affected passenger extraction program (237) then sorts by card ID and boarding date and time included in the behavior pattern data (215) (processing step 1301), and records of the sorted behavior pattern data (215) Is read (processing step 1302).
  • the route of the route ID of the behavior pattern is included in the accident section of the accident information data, and the time zone from the boarding date and time to the departure date and time of the behavior pattern data (215) Is included in the time zone from the accident occurrence time to the operation restart time in the accident information data (216) (processing step 1303).
  • the affected passenger extraction program (237) determines that the time zone is included in the time zone from the accident occurrence time to the operation restart time in the accident information data (216) (processing step). 1303; Yes), it is stored in the memory as a passenger affected by the accident (processing step 1304).
  • the affected passenger extraction program (237) determines that the time zone is not included in the time zone from the accident occurrence time to the operation restart time in the accident information data (216) (processing step). 1303; No), it returns to the processing step 1302, and the subsequent processing is repeated.
  • the affected passenger extraction program (237) determines whether or not the read record is the last record (processing step 1305), and determines that the read record is not the last record (processing step). 1305; No), the process returns to the processing step 1302, and the subsequent processing is repeated.
  • the affected passenger extraction program (237) determines that the read record is the last record (processing step 1305; Yes), the accident ID, the card ID, and the expected date and time that the passenger will encounter are calculated.
  • the information stored in the memory is output to the passenger data affected by the (step 1306).
  • the affected passenger extraction program (237) includes the boarding station / bus stop ID and the getting-off station / bus stop ID, the boarding date / time, the getting-off date / time, and the route master (420) acquired from the behavior pattern data (215).
  • the detour route that can be reached by detouring the accident section such as the transportation failure that has occurred, and the expected date and time are calculated.
  • detour route information such as the route ID, boarding date / time, getting-off date / time, boarding station / bus stop ID, getting-off station / bus stop ID, etc. is added.
  • the detour route extends over a plurality of routes, the information is added to the same record as in the case of the behavior pattern table (215).
  • the calculation of the detour route may be performed using the Dijkstra method for the railway / bus route network, or may be performed by another method.
  • the affected passenger extraction program (237) stores the created passenger data (218) affected by the accident in the data server (210).
  • FIG. 15 is a diagram for explaining a processing procedure of processing (congestion rate calculation processing) in which a congestion rate is created from movement log data and stored in the storage unit of the calculation server.
  • This process refers to the movement log data shown in FIG. 6, and the congestion rate in the situation where no accident such as a transport failure has occurred, and the user moves on a normal route without detouring in the situation where the accident has occurred. In this case, the congestion rate is estimated.
  • This processing can be executed at a timing (for example, when an accident occurs or after an accident occurs) appropriately designated by the operator.
  • the congestion rate estimation program (235) first reads movement log data (processing step 1400). As shown in Fig. 6, the travel log data is obtained from the departure point (boarding station / bus stop) to the destination (getting off station / bus stop) and the number of boarding stations / bus stops, getting off stations / bus stops for the number of routes Each information of the boarding date and time and the getting off date and time is included.
  • the congestion rate estimation program (235) divides the movement log data for each transfer and creates divided movement log data (processing step 1401). Then, the congestion rate estimation program (235) sorts the divided movement log data by the boarding date and time and places them in the queue (processing step 1402). Then, the congestion rate estimation program (235) takes out the record with the earliest boarding date and time in the queue (processing step 1403).
  • the congestion rate estimation program (235) specifies routes that can be boarded by referring to the timetable master (430) using the boarding station / bus stop and boarding date and time of the extracted record as keys (processing step 1404).
  • the congestion rate estimation program (235) selects the transportation system of the route with the earliest departure time after the boarding date and time among routes that can be boarded.
  • the congestion rate estimation program (235) determines whether or not the number of passengers in the selected transportation system is greater than the number of passengers allowed in the transportation system included in the route master (processing step 1405), and the transportation system included in the route master. If it is determined that there is more than the allowable number of passengers (processing step 1405; Yes), the boarding date and time of the divided movement log data is set to the next departure time stored in the timetable master (430), and the boarding date and time is set. The queue is delayed (processing procedure 1406).
  • the congestion rate estimation program (235) does not exceed the allowable number of passengers in the transportation facility included in the route master (processing step 1405; No)
  • the number of passengers in the transportation facility is increased by one (processing step 1407).
  • the congestion rate estimation program (235) determines whether or not the queue is empty (processing step 1408). If it is determined that the queue is not empty (processing step 1408; No), the processing step Returning to 1403, the subsequent processing is repeated.
  • the congestion rate estimation program (235) divides the number of passengers by the allowable number to obtain the congestion rate at each time, and the calculation server (230 ) In the database (239) (processing procedure 1409).
  • FIG. 16 is a diagram for explaining the processing procedure of the process of predicting the congestion rate at the time of an accident and storing it in the storage unit of the calculation server (congestion rate calculation process at the time of an accident).
  • an accident such as a transportation failure occurs in a certain section of the transportation facility, and the accident information data (216) is transferred to the data server (210) by the operator. Assume that it is in the stored state.
  • the congestion rate estimation program (235) reads passenger data (218) affected by the accident, movement log data, behavior pattern data (217) at the time of the accident, and accident information data (216) (processing step 1500). Then, the congestion rate estimation program (235) calculates the ratio of performing the detour action in the same manner as the behavior pattern ID at the time of the accident that occurred in the past, from the behavior pattern data (217) at the time of the accident. The rate is determined (processing step 1501). For example, in the congestion rate estimation program (235), the record with the card ID of the record whose behavior pattern ID at the past accident is “1” or “2” in the behavior pattern data (217) at the time of the accident is an accident. The ratio included in the passenger data (218) affected by the vehicle is calculated, and the ratio of the passengers who actually detoured among the passengers who had accidents in the past is obtained.
  • the congestion rate estimation program (235) creates new movement log data by combining movement log data and movement pattern data. At this time, if the travel route / time zone is included in the accident section / time zone of the accident information data, a route that bypasses the transportation failure section is calculated, and a new travel log is entered (processing step 1502). In calculating the detour route, the Dijkstra method may be used for the railway / bus route network, or another method may be used.
  • the new travel log includes information on routes, boarding positions, boarding positions, boarding dates, and boarding dates as many as the number of trips from the departure point to the destination. Thereafter, processing similar to that shown in FIG. 15 is performed to calculate the congestion rate at the time of the accident (processing steps 1503 to 1511).
  • FIG. 17 is a diagram for explaining the processing procedure of processing for determining behavior pattern data at the time of an accident from behavior / purchase log data and information distribution data (behavior pattern data creation processing).
  • an accident such as a transportation failure occurs in a certain section of the transportation facility, and the accident information data (216) is sent to the data server (210) by the operator. It is assumed that the accident has converged after being stored.
  • the action determination program (238) at the time of the accident reads the movement / purchase log data (214) and the information distribution data (219) (processing step 1600).
  • the action determination program (238) at the time of the accident extracts the record of the movement / purchase log data (214) of the card ID having the same value as the registrant ID of the information distribution data (219) (processing procedure 1601).
  • the action determination program (238) at the time of an accident selects one registrant ID distributed as information, and records with the same card ID as the registrant ID for the extracted movement / purchase log data (214) record In addition, a record having the same date and time as the date and time recorded in the accident information data (216) is specified, and the specified record path is compared with the record of the information distribution data of the registrant ID. Then, the behavior determination program (238) at the time of the accident refers to the behavior pattern table (218) at the time of the accident and determines which behavior pattern the registrant has taken at the time of the accident (processing procedure 1603).
  • the travel log is a detour route as distributed information
  • it is classified into an action pattern that detours according to the distribution information (action pattern ID “1” at the time of the accident) or immediately after the accident information is distributed
  • action pattern ID “4” at the time of an accident Other behavior patterns are classified in the same way.
  • action pattern determination has not been made for all registrants for whom information has been distributed
  • processing returns to processing step 1602.
  • the behavior pattern of each registrant is output to behavior pattern data (217) at the time of the accident and stored in the data server (processing step 1605). At this time, if an action pattern has already been registered, the action pattern is updated, and the latest action pattern of the registrant is stored.
  • FIG. 18 is an example of a mail screen (1700) for delivering information (transport fault information) to the registrant at the time of transport fault.
  • the screen is composed of a title part (1701) and a text part (1711).
  • the title of the mail is described (1701). This title is predetermined in this system.
  • information on the route and section of an accident such as a transportation failure, information on the time of occurrence, and information on the cause (accident information) is described (1702).
  • the URL of a website explaining the details of the accident (accident details information) may be described (1703).
  • the CPU 253 of the information distribution server 250 refers to the accident information data (216) and outputs the contents as the accident information.
  • the accident detailed information is described in the accident information.
  • a URL for accessing detailed information of the accident on the route for example, the operation resumption time stored in the accident information data (216)
  • the transport failure information includes information on the detour route stored in the information distribution data (219) (1712).
  • the CPU 253 of the information distribution server 250 outputs information on the detour route, it also outputs the congestion rate of each transportation facility at the time of the accident determined in FIG. 16 (1707).
  • the CPU 253 of the information distribution server 250 refers to the affected passenger data (218) shown in FIG. 9, and refers to a certain user's detour route (route from station A to station C) and time ( A time at station A: boarding date and time, a time at station C: date and time of getting off), and a payment amount of 400 yen at that time is output, together with an expected congestion rate of 20%.
  • one detour route is displayed, but actually, a plurality of detour routes are output as candidates.
  • the CPU 253 of the information distribution server 250 may describe the URL of the website for re-searching so that the detour route can be re-searched (1708). For example, when the CPU 253 of the information distribution server 250 accepts the click of the URL described above, the CPU 253 activates the display screen generation program (256), and displays the detour route re-search screen (2000) shown in FIG. (282) is displayed on the display unit.
  • FIG. 21 is a screen example of a website for re-searching for a detour route.
  • the detour route re-search screen (2000) has an input screen for a departure point (2001) and a destination (2002).
  • the display screen generation program (256) refers to the action pattern data (215) shown in FIG. 22 with the registrant ID of the user as a key at the input location of the departure place and the destination, and the same card ID.
  • the boarding station / bus stop and the getting-off station / bus stop included in this record may be entered or displayed in advance.
  • the detour route re-search screen (2000) has a departure time input field (2003), and when the search start button (2004) is pressed, the search is started.
  • a plurality of routes may be displayed with reference to the action pattern data (215) shown in FIG. 22 (2013, 2014).
  • information on departure time and arrival time (2005), information on charges (2006), number of transfers (2007), congestion rate (2007), and the like are displayed.
  • the button (2013) is pressed, a specific route included in the behavior pattern data (215) shown in FIG. 22 may be displayed.
  • the display screen generation program (256) may additionally display information other than the detour route according to the behavior type estimated from the behavior pattern data (217) at the time of the accident of the registrant (1709). .
  • the display screen generation program (256) may additionally display information other than the detour route according to the behavior type estimated from the behavior pattern data (217) at the time of the accident of the registrant (1709).
  • the URL or telephone number of the taxi company near the station is placed, or the mobile terminal (282) If it has a GPS function, the URL or telephone number of the nearest taxi company may be included.
  • the display screen generation program (256) displays the route from the current value or target value to the departure point in the same format as the detour route in the case of an action pattern that stops moving and returns to the departure point. good. Furthermore, if there is a purchase history near the station, the display screen generation program (256) may put the store information by accessing the website of the company that operates the store. Further, the display screen generation program (256) allows the user to change the action type by himself or herself by accessing the action pattern table at the time of the accident shown in FIG. A URL may be described (1710).
  • FIG. 19 shows an example of a screen for a business operator managing a system such as a railway business operator to determine the number of persons to be delivered.
  • the display screen generation program (256) may refer to the accident information data (216) and display the section and time of the transport fault on the screen (1801) as in the case of the transport fault information shown in FIG. 1802). Further, the display screen generation program (256) refers to the affected passenger data (218) shown in FIG. 9, counts the card ID for each accident ID, and displays the number of affected persons and the number of affected passengers on the screen. The number of users registered in this system (number of registered users) is counted with reference to the registered user data (220) shown in FIG. 7 and displayed on the screen. (1804).
  • the display screen generation program (256) when the accident information data (216) and each item value displayed on this screen are stored in the data server (210) as a history, the accident date and time (1806) at that time ), Accident route (1807), time interval (1808), distribution number (1809) indicating the number of registered users of the system, etc., display past history that occurred on the same route and time zone, and select past operation history The same operation may be automatically performed (1805). Further, when the operation history (1805) is displayed, the congestion rate shown in FIG. 15 is calculated at the timing when the accident occurs and at the timing when the accident occurs and converges, and the effect on the congestion rate (from the ratio of these values ( How much congestion has been reduced) may be obtained and displayed on the screen together with the information described above (1810). In this case, the effect is also stored in the history in association with each information described above.
  • the display screen generation program (256) may accept the set value.
  • the distribution condition setting when the user's address is stored in the registrant data (220), or from the history stored in the movement / purchase log data (214), the boarding station / bus stop or the getting-off station / bus stop The map information (not shown) may be matched, and the distribution area of the information distribution data (219) may be determined on another screen.
  • the display screen generation program (256) may set conditions such as a congestion rate reduction target, and distribute it to registrants who meet the conditions. For example, the display screen generation program (256) uses the congestion rate when the number of distributions is one (that is, the number of people who may bypass the route using this system), and the congestion when the number of distributions is two.
  • the traffic congestion rate calculation processing shown in FIG. 16 is executed by gradually increasing the rate and the number of distributions to obtain the congestion rate in each case, and the total congestion rate is determined as a target congestion rate (for example, When the congestion rate reaches a value that is reduced by 15%), the information distribution data (219) may be distributed to registrants calculated so far (for example, 1000 out of 3000 people). .
  • the display screen generation program (256) may display the expected congestion rate as to how much the congestion rate is reduced (1813). ).
  • the display screen generation program (256) refers to the action data (217) at the time of the accident shown in FIG. 10, and is the same card as the card ID of the registrant's transportation IC card included in the information distribution data (219).
  • the records of ID count the number of records whose behavior pattern ID at the time of the past accident is “1”, and calculate the expected congestion rate (the reduced congestion rate) of the accident occurring at that time, It may be displayed on the screen.
  • the display screen generation program (256) accepts pressing of the distribution button (1814) and distributes information distribution data (219). Alternatively, if it is determined that the provider does not need distribution, the display screen generation program (256) may accept the pressing of the non-distribution button (1815) and decide not to distribute.
  • FIG. 20 shows an example of a screen on which a business operator managing a system such as a railway business operator sees a simulation result of the flow of transportation and passengers.
  • a simulation screen (1900) showing the flow of passengers, transportation obstacle information (1901, 1902), mail distribution number (1903), detour route usage rate (1904), number of passengers affected by transportation obstacles (1907) It is displayed.
  • the transportation failure information (1901, 1902) and the number of mail delivery (1903) are the same as the transportation failure section and time (1801, 1802) and the delivery number (1811) shown in FIG.
  • the ratio of the number of users (for example, behavior pattern IDs “1” and “2” at the time of past accidents) using the detour route is
  • the display screen generation program (256) picks up a user randomly (or for each route or region) from the behavior data (217) at the time of the accident, and the user takes a detour route.
  • the movement of the entire user when moved by may be displayed on the screen.
  • a detour route extending to the lower right is displayed with respect to the route in the upper right direction in the figure.
  • This screen shows that a train or bus (1909) is moving between a station or a bus stop (1908).
  • the display screen generation program (256) may display the simulation result by thickening the detour path on the screen or changing the color as the number of users picked up increases.
  • These screens can be operated using an input interface such as a mouse or keyboard. For example, you can zoom in / out with a wheel button or click a station, bus stop, train, or bus with a mouse. The number of waiting persons and the number of passengers may be displayed.
  • the display screen generation program (256) may display a ratio for each action type for which information is distributed (1908).
  • the figure showing the ratio by action type may be displayed as a figure other than a pie chart.
  • the display screen generation program (256) refers to the action data (217) at the time of the accident shown in FIG. 10 using the accident ID as a key when displaying the ratio by type (1907), and the accident at that time
  • the action patterns of the user in are aggregated and displayed on the screen.
  • the above-described processes are performed, and passengers who are affected by the transportation obstacle are estimated by estimating the typical movement route and time zone of the user from the action history of the traffic system IC card data. Identify.
  • information other than the detour behavior performed by the user is learned and distributed to the user, thereby reducing congestion on the detour route.
  • different processing is performed before the occurrence of a transportation failure, during the occurrence of a transportation failure, and after the operation is resumed, using the movement / purchase log data generated from the traffic IC card data.
  • the behavior pattern of the passenger is estimated, and the ID and e-mail address of the traffic IC card data of the system user are registered.
  • passengers affected by the transportation failure are extracted from the accident information and the estimation result of the passenger behavior pattern estimated in advance.
  • information is distributed according to the instructions of the railway operator.
  • the behavior at the time of the accident of the passenger who received the information during the occurrence of the transport failure is analyzed, and the behavior data at the time of the accident is updated. Therefore, the user's labor can be saved by analyzing the behavior pattern of the user from the traffic IC card data and automatically updating the movement route information of the user registered in the system.
  • the concentration of passengers on detour routes is reduced and congestion is reduced. Can be achieved.
  • this invention is not limited to the above-mentioned Example, Various modifications are included.
  • the above-described embodiments have been described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described.
  • a part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment.
  • DESCRIPTION OF SYMBOLS 100 ... Traffic IC card data, 101 ... Movement / purchase log data generation processing, 120 ... Pre-accident processing, 121 ... Behavior pattern estimation processing, 122 ... Congestion rate estimation processing, 123 ... User card ID mail Address information, 124 ... registrant data generation process, 125 ... action list at the time of an accident, 130 ... process during an accident, 131 ... accident information by the operator, 132 ... extraction process for passengers who are subject to transportation failures, 133 ... by the operator Information distribution instruction, 134 ... Information distribution process, 140 ... Process after accident, 141 ... Action estimation process after accident, 142 ... Action list update process at accident, 200 ... User of traffic IC card, 201 ...
  • Traffic System IC card 202 ... Ticket, 203 ... Bus, 204 ... Mobile terminal, 205 ... User, 206 ... Taxi, 207 ... Network, 208 ... Transport Extraction and guidance system of passengers affected by transportation obstacles for mitigating congestion at the time of harm, 210 ... Data server, 211 ... Storage unit, 212 ... Transportation IC card data, 213 ... Master data, 214 ... Moving and purchasing Log data, 215 ... Action pattern data, 216 ... Accident information data, 217 ... Action data at the time of an accident, 218 ... Action pattern table at the time of an accident, 219 ... Information distribution data, 220 ... Registrant data, 230 ... Calculation server, 231 ... Interface, 232 ...

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Abstract

La présente invention a pour objet d'informer un usager, sans le déranger, sur un itinéraire alternatif pouvant lui convenir lorsqu'il y a des perturbations dans les transports ou équivalent ; ainsi, un opérateur ferroviaire peut éviter des encombrements lorsqu'il y a des perturbations dans les transports. L'invention propose un système de guidage de passagers destiné à guider des usagers qui empruntent un itinéraire en utilisant une carte à puce, le système étant pourvu des éléments suivants : une section d'extraction de modèle de comportement qui génère le modèle de comportement d'usagers à partir des données d'un journal de déplacements dans lequel est enregistré l'historique des déplacements des usagers, comprenant la date et l'heure d'utilisation du réseau de transport et l'itinéraire emprunté ; une section de sélection de passagers qui sélectionne des usagers qui seront influencés par un accident en utilisant la date et l'heure d'utilisation et l'itinéraire contenus dans le modèle de comportement et des données d'informations d'accident qui comprennent la zone où l'accident s'est produit et l'heure à laquelle l'accident s'est produit , ainsi que l'heure à laquelle le service sera rétabli, et qui détermine un itinéraire alternatif pour les usagers à l'appui de l'itinéraire des usagers et des informations de service principal du réseau de transport ; une section de diffusion qui transmet, vers un terminal des usagers sélectionnés, des données de diffusion d'informations comprenant un itinéraire alternatif ; et une section de détermination de comportement qui, sur la base des données du journal de déplacements et de l'itinéraire alternatif, détermine si des usagers, parmi les usagers auxquels des données de diffusion d'informations ont été envoyées, se sont déplacés selon l'itinéraire alternatif au moment de l'accident, et qui enregistre ces résultats à titre de données de modèle de déplacement au moment de l'accident.
PCT/JP2013/077154 2013-10-04 2013-10-04 Système de guidage de passagers et procédé de guidage de passagers WO2015049801A1 (fr)

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SG11201602577XA SG11201602577XA (en) 2013-10-04 2013-10-04 Passenger guidance system and passenger guidance method
PCT/JP2013/077154 WO2015049801A1 (fr) 2013-10-04 2013-10-04 Système de guidage de passagers et procédé de guidage de passagers

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Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2017149368A (ja) * 2016-02-26 2017-08-31 株式会社東芝 情報処理装置及び情報処理の方法
WO2019043332A1 (fr) * 2017-09-01 2019-03-07 Mytechtrip Procede de gestion de perturbations de service, plateforme mettant en oeuvre ledit procede et systeme associe
JP2019215629A (ja) * 2018-06-11 2019-12-19 日産自動車株式会社 移送モビリティサービスの提案方法及び移送モビリティサービスの提案装置
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WO2023203841A1 (fr) * 2022-04-18 2023-10-26 株式会社Ｎｔｔドコモ Système d'exploration de taux de changement
WO2023203842A1 (fr) * 2022-04-18 2023-10-26 株式会社Ｎｔｔドコモ Système de recherche de degré d'encombrement

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