Boarding guidance planning device and boarding guidance planning method

Abstract

To provide a boarding guidance planning device and a boarding guidance planning method capable of improving the prevention degree of exceeding getting-on / off time of passengers with respect to a train.SOLUTION: The-number-of-passengers getting off prediction means predicts the number of passengers getting off a train at each door based on the number of passengers getting on / off in the past, the actual value of train passengers, and the number of passengers getting off predicted from the related parameters considered to be a variable factor of the number of passengers getting on / off. Measuring means measures distribution of passengers on a platform where a train stops. The-number-of-passengers getting on calculation means calculates the number of passengers getting on who get on the train at each door based on the measured distribution of passengers. Generating means generates getting-on guidance planning information to guide the passengers on the platform reflecting the predicted number of passengers getting off and the predicted number of passengers getting on. Output means outputs the getting-on guidance planning information.SELECTED DRAWING: Figure 10

Description

[Technical Field]

[0001] The present disclosure relates to a passenger guidance planning device and a passenger guidance planning method. [Background technology]

[0002] Patent Document 1 describes a door-by-door boarding guidance planning device that guides passengers on station platforms. This door-by-door boarding guidance planning device estimates the disembarking times for each door at a stop station and the distribution of passengers inside the car after disembarking based on information from mobile devices carried by passengers inside the car. Furthermore, the door-by-door boarding guidance planning device calculates the number of people that can be allowed to board at a stop station based on this distribution. Then, there is a door-by-door boarding guidance planning device that guides passengers based on this number of people (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-178923 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the door-by-door boarding guidance planning device described in Patent Document 1 calculates the planned number of passengers for each door, and therefore may not be able to contribute much to preventing boarding and alighting times from exceeding the limit.

[0005] An object of the present invention is to provide a passenger guidance planning device and a passenger guidance planning method that can improve the degree to which passengers are prevented from exceeding their boarding and disembarking times on trains. [Means for solving the problem]

[0006] The passenger guidance planning device based on the present disclosure includes an alighting number prediction means for predicting the number of passengers who will alight at each door based on the actual measured values ​​of the past number of passengers boarding and alighting and the number of passengers in the vehicle and the number of passengers alighting predicted from related parameters that are considered to be factors that cause fluctuations in the number of passengers boarding and alighting; a measurement means for measuring the distribution of passengers on the platform where the vehicle stops; a passenger number calculation means for calculating the number of passengers boarding the vehicle at each door based on the measured distribution of passengers; a creation means for creating passenger guidance plan information for guiding passengers on the platform by reflecting the predicted number of passengers alighting and the calculated number of passengers; and an output means for outputting the passenger guidance plan information.

[0007] In the boarding guidance planning method according to the present disclosure, a computer predicts the number of people getting off at each door based on the actual measurements of the number of people getting on and off in the past and the number of people in the vehicle, and the number of people getting off predicted from related parameters that are thought to be factors that cause fluctuations in the number of people getting on and off; measures the distribution of people on the platform where the vehicle stops; calculates the number of people getting on at each door who will board the vehicle based on the measured distribution of people; creates boarding guidance plan information for guiding passengers on the platform by reflecting the predicted number of people getting off and the calculated number of people getting on, and outputs the boarding guidance plan information.

[0008] The boarding guidance planning program based on the present disclosure causes a computer to execute an alighting number prediction process that predicts the number of passengers who will alight at each door based on the actual measured values ​​of the past number of passengers boarding and alighting and the number of passengers in the vehicle and the number of passengers predicted from related parameters that are considered to be factors that cause fluctuations in the number of passengers boarding and alighting; a measurement process that measures the distribution of passengers on the platform where the vehicle stops; a passenger number calculation process that calculates the number of passengers boarding the vehicle at each door based on the measured distribution of passengers; a creation process that creates boarding guidance plan information that guides passengers on the platform by reflecting the predicted number of passengers alighting and the calculated number of passengers; and an output process that outputs the boarding guidance plan information. [Effects of the Invention]

[0009] According to the present invention, it is possible to improve the degree of prevention of excessive boarding and disembarking times of passengers on trains. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 2 is a block diagram illustrating a configuration example of a boarding guidance planning device. [Figure 2] 10 is a flowchart showing the operation of the boarding guidance planning device. [Figure 3] 10A and 10B are explanatory diagrams showing specific examples of measuring the number of passengers distribution and predicting the number of passengers at each door. [Figure 4] FIG. 10 is an explanatory diagram showing a process for creating boarding guidance plan information. [Figure 5] FIG. 10 is an explanatory diagram showing a process for creating boarding guidance plan information. [Figure 6] FIG. 10 is an explanatory diagram showing a process for creating boarding guidance plan information. [Figure 7] FIG. 10 is an explanatory diagram showing a process for creating boarding guidance plan information. [Figure 8] FIG. 10 is an explanatory diagram showing a process for creating boarding guidance plan information. [Figure 9] FIG. 1 is a block diagram illustrating an example of a computer having a CPU. [Figure 10] FIG. 1 is a block diagram showing an overview of a boarding guidance planning device. DETAILED DESCRIPTION OF THE INVENTION

[0011] FIG. 1 is a block diagram showing an example of the configuration of an embodiment of a passenger guidance planning device.

[0012] The boarding guidance planning device 100 of this embodiment outputs boarding guidance plan information for guiding passengers on a platform of a railway station (hereinafter referred to as a station platform or platform).

[0013] As shown in FIG. 1, the passenger guidance planning device 100 includes a passenger number prediction unit 120 that inputs data from a passenger number prediction parameter accumulation unit 110, a platform number distribution measurement unit 130, a next passenger number calculation unit 140, a platform number of passengers information reflection unit 150, and a passenger guidance planning information output unit 160.

[0014] The boarding and alighting passenger count prediction parameter accumulation unit 110 stores prediction source data used to predict the number of passengers alighting from a train (alighting passenger count) and the number of passengers staying in a car before boarding or alighting (car count before boarding or alighting). The prediction source data corresponds to learning data (training data) for learning a prediction model.

[0015] The boarding / alighting number prediction parameter accumulation unit 110 stores data for each station, platform, vehicle, and door as prediction source data. The prediction source data includes the actual measured number of passengers boarding / alighting, the actual measured number of passengers in each vehicle, user demographics (gender, age), date and time, season, weather, information on whether or not there are events in the area around the station, and the distance from the door position to the means of transportation (the means of transportation from the platform to the ticket gate floor, for example, stairs, escalator, elevator). At least a portion of the prediction source data (for example, information on the date and time, season, weather, and whether or not there are events in the area around the station) is considered to be a factor in fluctuations in the number of passengers boarding / alighting. The unit may also store the time required to travel from the door position to the means of transportation (the means of transportation from the platform to the ticket gate floor, for example, stairs, escalator, elevator). The information is learned so that shorter distances and required times from the door position to the means of transportation contribute to an increase in the number of passengers boarding / alighting at each door.

[0016] The prediction source data is collected, for example, every hour and stored in the boarding / alighting number prediction parameter accumulation unit 110. For example, the actual number of boarding / alighting passengers and information on user demographics (gender, age) are collected by performing advanced video analysis on surveillance camera footage installed on the station platform. Information on the date, time, season, and weather is collected, for example, from a weather data API (Application Programming Interface). Information on the presence or absence of events in the area surrounding the station is collected, for example, by the browsing function of a generating AI (Artificial Intelligence). The distance from the door position to the means of transportation (means of transportation from the platform to the ticket gate floor, such as stairs, escalators, and elevators) is collected by having the generating AI acquire a station map. The time required from the door position to the means of transportation (means of transportation from the platform to the ticket gate floor, such as stairs, escalators, and elevators) is collected by measuring the travel time using surveillance camera footage installed on the station platform.

[0017] In this embodiment, the boarding and alighting number of passengers prediction parameter accumulation unit 110 is provided outside the passenger guidance planning device 100, but the present invention is not limited to this and may be included in the passenger guidance planning device 100.

[0018] The passenger number prediction unit 120 predicts the number of passengers who will disembark at each door and the number of passengers in each vehicle before getting on or off, based on the prediction source data stored in the passenger number prediction parameter accumulation unit 110.

[0019] As shown in FIG. 1, the passenger number prediction unit 120 includes a data acquisition unit 121 and a learning unit 122.

[0020] The data acquisition unit 121 acquires the prediction source data from the passenger number prediction parameter accumulation unit 110 .

[0021] The learning unit 122 uses the prediction source data acquired by the data acquisition unit 121 as training data to learn a prediction model that predicts the number of people getting off at each door and the number of people in each vehicle before getting on and off. The learning unit 122 uses the same prediction source data when learning the prediction model that predicts the number of people getting off at each door and when learning the prediction model that predicts the number of people in each vehicle before getting on and off. The learning unit 122 also uses a learning model capable of time series analysis to learn a prediction model that predicts the number of people in each vehicle before getting on and off, using the acquired prediction source data as training data.

[0022] The platform population distribution measurement unit 130 measures the distribution of people on the station platform. The measurement of the population distribution will be described in detail later with reference to FIG.

[0023] The next train passenger number calculation unit 140 calculates the number of passengers at each door based on the number of passengers distribution measured by the platform number of passengers distribution measurement unit 130. Details of the prediction of the number of passengers at each door will be described later with reference to FIG.

[0024] The platform passenger count information reflecting unit 150 creates boarding guidance plan information that reflects the number of passengers disembarking at each door predicted by boarding / alighting passenger count predicting unit 120 and the number of passengers boarding at each door calculated by next departure passenger count calculating unit 140. The boarding guidance plan information is information that guides passengers on the train platform from boarding / alighting positions corresponding to doors that are expected to be crowded to boarding / alighting positions corresponding to doors that are expected to be less crowded.

[0025] The boarding guidance plan information output unit 160 outputs the boarding guidance plan information created by the platform number of people information reflecting unit 150. For example, the boarding guidance plan information output unit 160 outputs the boarding guidance plan information to a display device (a display device for passengers, a display device for station staff) provided on the platform, a terminal device carried by a station staff member, or an audio output device (speaker) provided on the platform.

[0026] FIG. 2 is a flowchart showing the operation of the ride guidance planning device 100.

[0027] The data acquisition unit 121 of the passenger guidance planning device 100 acquires the prediction source data from the passenger boarding and alighting number of people prediction parameter accumulation unit 110 (step S112).

[0028] The learning unit 122 of the passenger guidance planning device 100 uses the acquired prediction source data to learn a prediction model that predicts the number of passengers getting off at each door and the number of passengers before getting on and off for each vehicle (step S114).

[0029] The boarding and alighting number of passengers prediction unit 120 of the passenger guidance planning device 100 predicts the number of passengers who will alight at each door and the number of passengers before boarding and alighting for each vehicle based on the prediction model (step S116).

[0030] The platform number of people distribution measuring unit 130 of the passenger guidance planning device 100 measures the number of people distribution for each door position on the platform (step S118).

[0031] The next passenger number calculation unit 140 of the passenger guidance planning device 100 calculates the number of passengers for each door based on the measured number distribution (step S120). Note that the boarding and alighting number prediction unit 120 may also use the actual vehicle number of passengers calculated by the next passenger number calculation unit 140 when predicting the number of passengers who will alight for each door.

[0032] Here, a specific example of measuring the distribution of people on a station platform and predicting the number of people boarding at each door will be explained using Figure 3. Figure 3 is an explanatory diagram showing a specific example of measuring the distribution of people and predicting the number of people boarding at each door. As shown in the figure, boarding positions corresponding to doors A1 to A3 of the train are provided on the station platform.

[0033] First, the on-platform people distribution measurement unit 130 divides the area of ​​the station platform into areas based on the video from the surveillance camera. In the example shown in Fig. 3, the on-platform people distribution measurement unit 130 sets door areas (in the figure, ranges surrounded by rectangles including the boarding positions corresponding to each door; door A1 area to door A3 area) based on the boarding positions corresponding to doors A1 to A3. Next, the on-platform people distribution measurement unit 130 measures the number of people staying in each door area (hereinafter referred to as the number of people within a door area) using a person detection function, thereby measuring the distribution of people on the station platform.

[0034] Next departure passenger number calculation unit 140 then calculates the number of people (those surrounded by a rectangular frame in the drawing) whose moving speed in each door area is equal to or greater than the threshold (hereinafter referred to as the speeding number of people). Next departure passenger number calculation unit 140 calculates the value obtained by subtracting the speeding number of people from the number of people in the door area as the number of passengers at the door corresponding to each door area.

[0035] Returning to the explanation of FIG. 2, after step S120, the platform number of passengers information reflecting unit 150 of the passenger guidance planning device 100 reflects the number of passengers getting off and getting on at each door and the number of passengers before getting on and off for each vehicle in the passenger guidance planning information (step S122).

[0036] The boarding guidance plan information output unit 160 of the boarding guidance planning device 100 outputs the boarding guidance plan information (step S124).

[0037] Next, a specific example of creating boarding guidance plan information will be described with reference to Fig. 4 to Fig. 8. Fig. 4 to Fig. 8 are explanatory diagrams showing the process of creating boarding guidance plan information. Here, an example is taken of creating boarding guidance plan information when a train consisting of three three-door cars (car A to car C) arrives.

[0038] As shown in Fig. 4, vehicle A is provided with doors A1, A2, and A3. Vehicle B is provided with doors B1, B2, and B3. Vehicle C is provided with doors C1, C2, and C3.

[0039] As shown in Fig. 4, the number of passengers before boarding and alighting is associated with each vehicle. Furthermore, the number of passengers alighting, the number of passengers boarding, the alighting time, the boarding time, and the total boarding and alighting time are associated with each door. The number of passengers before boarding and alighting and the number of passengers alighting are stored in a temporary storage unit (not shown) of the passenger guidance planning device 100 when predicted in step S116. The number of passengers alighting is stored in the temporary storage unit when predicted in step S120.

[0040] When creating the boarding guidance plan information, the platform number of people information reflecting unit 150 of the boarding guidance planning device 100 divides the number of people getting off by 2 and stores the result as the alighting time in the temporary storage unit. Also, the platform number of people information reflecting unit 150 of the boarding guidance planning device 100 divides the number of people getting on by 2 and stores the result as the boarding time in the temporary storage unit. Here, "2" is set as the value to be divided from the number of people getting on and off when calculating the boarding and alighting time. This is because it is assumed that two people get on and off at each door per second. Also, the platform number of people information reflecting unit 150 of the boarding guidance planning device 100 stores a value calculated by adding the alighting time and the boarding time in the temporary storage unit as the total boarding and alighting time.

[0041] Note that a value other than "2" may be set as the value by which the number of passengers getting on and off is divided when calculating the boarding and alighting time. Furthermore, the value by which the number of passengers getting on and alighting is divided when calculating the boarding and alighting time may be changed based on the user demographic information of the prediction source data. For example, if the prediction source data includes information indicating that there are many older passengers, the platform user number information reflecting unit 150 of the passenger guidance planning device 100 may store the value obtained by dividing the number of passengers by 1 as the boarding time in the temporary storage unit, assuming that one person gets on and alights per second at each door.

[0042] Furthermore, in step S122, the platform number of passengers information reflecting unit 150 of the passenger guidance planning device 100 compares the total boarding / alighting time with the allowable stopping time. The allowable stopping time is the time allowed for stopping at each stop station (estimated stopping time). The allowable stopping time is a time that is set in advance for each train. The allowable stopping time is stored, for example, in a memory unit (not shown) of the passenger guidance planning device 100. The allowable stopping time may be acquired from an external device (for example, an external device including the boarding / alighting number of passengers prediction parameter accumulating unit 110). Here, a case where the allowable stopping time is set to 30.0 seconds is taken as an example. In the example shown in FIG. 4, the total boarding / alighting time at doors A1, B1, and C3 exceeds the allowable stopping time (30.0 seconds).

[0043] In step S122, the platform number-of-persons information reflecting unit 150 of the passenger guidance planning device 100 calculates the allowable boarding time by subtracting the disembarking time from the allowable stop time (30.0 seconds), as shown in FIG. 5, and stores the calculated value in the temporary storage unit. Then, the platform number-of-persons information reflecting unit 150 of the passenger guidance planning device 100 calculates the allowable number of passengers by multiplying the allowable boarding time by 2, and stores the calculated value in the temporary storage unit. Here, "2" is set as the value by which the allowable boarding time is multiplied when calculating the allowable number of passengers. This is because it is assumed that two passengers get on and off per door per second.

[0044] Note that a value other than "2" may be set as the value by which the allowable boarding time is multiplied when the allowable number of passengers is calculated. Furthermore, the value by which the allowable boarding time is multiplied when the allowable number of passengers is calculated may vary based on user demographic information in the prediction source data. For example, if the prediction source data includes information indicating that there are many older passengers, the platform number-of-passengers information reflecting unit 150 of the passenger guidance planning device 100 may calculate the allowable number of passengers by multiplying the allowable boarding time by 1, assuming that one person gets on and off per second at each door, and store the calculated number of passengers in the temporary storage unit.

[0045] In step S122, the platform occupancy information reflecting unit 150 of the passenger guidance planning device 100 compares the number of passengers with the allowable number of passengers. For doors where the number of passengers is greater than the allowable number of passengers, it is predicted that boarding and alighting will require a time that exceeds the allowable stopping time. For example, as shown in FIG. 5, door A1 is predicted to require an excess time for 10 passengers to board. door B1 is predicted to require an excess time for 2 passengers to board. door C3 is predicted to require an excess time for 7 passengers to board.

[0046] Furthermore, doors where the allowable number of passengers is greater than the number of passengers are expected to complete boarding and alighting within the allowable stopping time and have room for further passenger increases. Therefore, in step S122, the platform occupancy information reflecting unit 150 of the passenger guidance planning device 100 assigns priorities as guidance destinations so that doors with a large difference between the number of passengers and the allowable number of passengers (doors with a large margin for passenger numbers) can be guided first. In FIG. 6, the priorities as guidance destinations are indicated by circled numbers. For example, door A2, which has a margin for passengers of 16, has the highest priority as a guidance destination. Door B3, which has a margin for passengers of 15, has the second highest priority as a guidance destination. Door A3, which has a margin for passengers of 14, has the third highest priority as a guidance destination. In this way, the platform occupancy information reflecting unit 150 of the passenger guidance planning device 100 creates passenger guidance plan information that guides passengers to doors A2, B3, and A3, which have a margin for passengers. Then, the boarding guidance plan information output unit 160 of the boarding guidance planning device 100 outputs the created boarding guidance plan information to an output destination device.

[0047] For example, the passenger display device to which the boarding guidance plan information is output displays a message such as "Please move to doors A2, B3, A3." The speaker to which the boarding guidance plan information is output outputs a voice message such as "Please move to doors A2, B3, A3." The terminal device and the station staff display device to which the boarding guidance plan information is output displays a message such as "Please guide passengers to doors A2, B3, A3."

[0048] After the passenger guidance plan information is created and output, the passenger guidance planning device 100 performs the processes of steps S118 to S122 again after a predetermined period of time has elapsed, thereby predicting the boarding and alighting times again. Then, in step S122, the platform number-of-passengers information reflecting unit 150 of the passenger guidance planning device 100 again compares the total boarding and alighting time with the allowable stopping time. In the example shown in Fig. 7, the total boarding and alighting time at all doors is less than the allowable stopping time.

[0049] In step S122, the platform occupancy information reflecting unit 150 of the passenger guidance planning device 100 calculates the number of passengers in a vehicle after boarding and alighting, and compares the calculated number of passengers in a vehicle after boarding and alighting with the allowable number of passengers in a vehicle. The number of passengers in a vehicle after boarding and alighting is the number of passengers remaining in a vehicle after boarding and alighting. Specifically, the platform occupancy information reflecting unit 150 calculates (predicts) the number of passengers in a vehicle after boarding and alighting by subtracting the number of passengers alighting at each door from the number of passengers in a vehicle before boarding and alighting, and then adding the number of passengers boarding and alighting at each door. The allowable number of passengers in a vehicle is the number of passengers allowed to remain in a vehicle, and is a number that is predetermined for each vehicle. The allowable number of passengers in a vehicle is stored, for example, in a storage unit (not shown) of the passenger guidance planning device 100. The allowable number of passengers in a vehicle may be acquired from an external device (for example, an external device including the boarding and alighting number of passengers prediction parameter accumulating unit 110). Here, 100 passengers is set as the allowable number of passengers in a vehicle. In the example shown in FIG. 7, the number of passengers in a vehicle after boarding and alighting in vehicle A and vehicle B exceeds the allowable number of passengers in a vehicle (100 passengers). The platform occupancy information reflecting unit 150 of the passenger guidance planning device 100 creates passenger guidance plan information for guiding passengers to vehicle C, which has an available number of passengers. Then, the passenger guidance plan information output unit 160 of the passenger guidance planning device 100 outputs the created passenger guidance plan information to an output destination device.

[0050] For example, the passenger display device to which the boarding guidance plan information is output displays a message such as "Please move to car C." The speaker to which the boarding guidance plan information is output outputs a voice message such as "Please move to car C." The terminal device and the station staff display device to which the boarding guidance plan information is output displays a message such as "Please guide passengers to car C."

[0051] After the boarding guidance plan information for guiding passengers to vehicle C is created and output, the boarding guidance planning device 100 performs the processes of steps S118 to S122 again after a predetermined period of time has elapsed, thereby predicting the boarding and alighting times again. Then, in step S122, the platform number of passengers information reflecting unit 150 of the boarding guidance planning device 100 again compares the total boarding and alighting time with the allowable stopping time, and the number of passengers in the vehicle after boarding and alighting with the allowable number of passengers in the vehicle. In the example shown in FIG. 8, the total boarding and alighting time at all doors is less than the allowable stopping time, and the number of passengers in the vehicle after boarding and alighting is less than the allowable number of passengers in the vehicle for all vehicles. Therefore, the boarding guidance planning device 100 does not output the boarding guidance plan information.

[0052] The following describes a specific example of the hardware configuration of the passenger guidance planning device 100. Fig. 9 is an explanatory diagram showing an example of the hardware configuration of the passenger guidance planning device according to the present invention.

[0053] The passenger guidance planning device shown in FIG. 9 includes a CPU (Central Processing Unit) 1000, a main memory unit 1001, and an auxiliary memory unit 1002.

[0054] The passenger guidance planning device is realized by software when a CPU 1000 shown in FIG. 9 executes a program that provides the functions of each component.

[0055] That is, the CPU 1000 loads the program stored in the auxiliary storage unit 1002 into the main storage unit 1001, executes it, and controls the operation of the boarding guidance planning device, thereby realizing each function by software.

[0056] The main memory unit 1001 is used as a data working area and a data temporary saving area, and is, for example, a RAM (Random Access Memory).

[0057] The auxiliary storage unit 1002 is a non-transitory tangible storage medium, such as a magnetic disk, a magneto-optical disk, a CD-ROM (Compact Disk Read Only Memory), a DVD-ROM (Digital Versatile Disk Read Only Memory), or a semiconductor memory.

[0058] In the embodiment of the passenger guidance planning device 100, the auxiliary memory unit 1002 stores programs for realizing the boarding and alighting number prediction unit 120 (data acquisition unit 121, learning unit 122), the number of passengers distribution measurement unit 130 on the platform, the next passenger number calculation unit 140, the platform number of passengers information reflection unit 150, and the passenger guidance planning information output unit 160.

[0059] The signal processing system 100 may be implemented with a circuit including hardware components such as an LSI (Large Scale Integration) that implements the functions shown in FIG.

[0060] Next, an outline of the present invention will be described. Fig. 10 is a block diagram showing an outline of a passenger guidance planning device according to the present invention. The passenger guidance planning device 10 according to the present invention comprises a passenger number prediction means 11 (e.g., a passenger number prediction unit 120) for predicting the number of passengers who will alight at each door based on the past number of passengers boarding and alighting (e.g., included in the prediction source data), the actual number of passengers in the vehicle (e.g., calculated by a next departure passenger number calculation unit 140), and the number of passengers who alight predicted from related parameters (e.g., included in the prediction source data) that are considered to be factors that cause fluctuations in the number of passengers boarding and alighting, and a measurement means 12 for measuring the number of passengers on the platform where the vehicle stops. (e.g., platform number of people distribution measurement unit 130), passenger number calculation means 13 (e.g., next departure passenger number calculation unit 140) that calculates the number of passengers for each door boarding the vehicle based on the measured number of people distribution, creation means 14 (e.g., platform number of people information reflection unit 150) that creates boarding guidance plan information to guide passengers on the platform by reflecting the predicted number of people disembarking and the calculated number of people boarding, and output means 15 (e.g., boarding guidance plan information output unit 160) that outputs the boarding guidance plan information.

[0061] Such an arrangement may improve the degree of prevention of excessive passenger boarding and disembarking times on trains.

[0062] In addition, the creation means 14 may predict the boarding and alighting time required for boarding and alighting at each door based on the predicted number of disembarking passengers and the calculated number of passengers boarding, and create boarding guidance plan information that guides passengers on the platform from a boarding position at a door with a long predicted boarding and alighting time to a boarding position at a door with a short predicted boarding and alighting time.

[0063] Such a configuration can help reduce passenger travel times.

[0064] In addition, the creation means 14 may create boarding guidance plan information that guides passengers on the platform from a boarding position at a door where the predicted boarding and alighting time exceeds the allowable train stopping time to a boarding position at a door where the predicted boarding and alighting time does not exceed the allowable train stopping time.

[0065] Such a configuration can reduce the number of doors where the boarding time exceeds the train's allowable stopping time.

[0066] In addition, the alighting number prediction means 11 may predict the number of passengers remaining in each vehicle before boarding or alighting, based on information indicating the number of passengers remaining in the vehicle before boarding or alighting in the past, and the creation means 14 may create boarding guidance plan information that guides passengers on the platform from a boarding position of a vehicle where the predicted number of passengers remaining in the vehicle before boarding or alighting exceeds the allowable number of passengers, to a boarding position of a vehicle where the predicted number of passengers remaining in the vehicle before boarding or alighting does not exceed the allowable number of passengers.

[0067] Such a configuration can improve the degree to which passengers are prevented from exceeding the allowable number of passengers in a train after boarding and disembarking, while also preventing excessive boarding and disembarking times for passengers on trains.

[0068] Furthermore, the measuring means 12 may measure the number of passengers staying in each section on the platform corresponding to the boarding position of the door, excluding passengers whose moving speed is equal to or greater than a threshold.

[0069] Such a configuration makes it possible to count the number of people excluding passengers who are on the platform but do not board the train, thereby improving measurement accuracy.

[0070] A part or all of the above-described embodiments can be described as, but not limited to, the following supplementary notes.

[0071] (Appendix 1) A means for predicting the number of passengers getting off at each door based on the actual measured values ​​of the number of passengers getting on and off in the past and the number of passengers in the vehicle, and the number of passengers getting off predicted from related parameters (e.g., prediction source data) that are considered to be factors that cause fluctuations in the number of passengers getting on and off; A measuring means for measuring the distribution of people on the platform where the vehicle stops; a passenger number calculation means for calculating the number of passengers entering the vehicle at each door based on the measured passenger number distribution; a creating means for creating boarding guidance plan information for guiding passengers on the platform by reflecting the predicted number of passengers getting off and the calculated number of passengers getting on; and an output means for outputting the boarding guidance plan information. Ride guidance planning device.

[0072] (Note 2) The creating means predicts the boarding and alighting time required for each door based on the predicted number of alighting passengers and the calculated number of boarding passengers, and creates the boarding guidance plan information for guiding passengers on the platform from a boarding position at a door where the predicted boarding and alighting time is long to a boarding position at a door where the predicted boarding and alighting time is short. Attachment 1. A boarding guidance planning device.

[0073] (Supplementary Note 3) The creating means creates the boarding guidance plan information for guiding passengers on the platform from a boarding position of a door where the predicted boarding / alighting time exceeds the allowable stopping time of the train to a boarding position of a door where the predicted boarding / alighting time does not exceed the allowable stopping time of the train. Attachment 2: A boarding guidance planning device.

[0074] (Supplementary Note 4) The alighting number prediction means predicts the number of people before getting on or off for each vehicle staying in the vehicle before getting on or off based on information indicating the number of people before getting on or off who stayed in the vehicle before getting on or off in the past, The creating means creates the boarding guidance plan information for guiding passengers on the platform from a boarding position of a vehicle where the predicted number of passengers before boarding / alighting exceeds the allowable number of passengers to a boarding position of a vehicle where the predicted number of passengers before boarding / alighting does not exceed the allowable number of passengers. Attachment 3: A boarding guidance planning device.

[0075] (Note 5) The measuring means measures the number of people staying in each area on the platform corresponding to the boarding position of the door, excluding people whose moving speed is equal to or greater than a threshold. 5. A passenger guidance planning device according to any one of appendices 1 to 4.

[0076] (Appendix 6) The computer The number of passengers getting off at each door is predicted based on the past measured number of passengers getting on and off and the number of passengers in the vehicle, and the number of passengers getting off predicted from related parameters that are considered to be factors that cause fluctuations in the number of passengers getting on and off; Measure the distribution of people on the platform where the train stops, Based on the measured number of passengers distribution, the number of passengers entering each door of the vehicle is calculated, Create boarding guidance plan information for guiding passengers on the platform by reflecting the predicted number of passengers getting off and the calculated number of passengers getting on. Output the boarding guidance plan information Boarding guidance planning method.

[0077] (Appendix 7) The computer predicts the boarding and alighting time required for each door based on the predicted number of alighting passengers and the calculated number of boarding passengers, and creates the boarding guidance plan information to guide passengers on the platform from the boarding position of the door with the longest predicted boarding and alighting time to the boarding position of the door with the shortest predicted boarding and alighting time. The boarding guidance planning method described in Appendix 6.

[0078] (Appendix 8) The computer creates the boarding guidance plan information to guide passengers on the platform from a boarding position at a door where the expected boarding / alighting time exceeds the allowable train stopping time to a boarding position at a door where the expected boarding / alighting time does not exceed the allowable train stopping time. The boarding guidance planning method described in Appendix 7.

[0079] (Appendix 9) The computer predicts the number of passengers in each vehicle before getting on or off based on information indicating the number of passengers in each vehicle before getting on or off in the past, The creating means creates the boarding guidance plan information for guiding passengers on the platform from a boarding position of a vehicle where the predicted number of passengers before boarding / alighting exceeds the allowable number of passengers to a boarding position of a vehicle where the predicted number of passengers before boarding / alighting does not exceed the allowable number of passengers. The boarding guidance planning method described in Appendix 8.

[0080] (Appendix 10) The computer counts the number of people in each area on the platform corresponding to the boarding position of the door, excluding people whose movement speed is above a threshold. 10. A boarding guidance planning method according to any one of appendices 6 to 9.

[0081] (Appendix 11) To the computer, a process of predicting the number of passengers who will get off at each door based on the actual measurements of the number of passengers getting on and off in the past and the number of passengers in the vehicle, and the number of passengers who will get off predicted from related parameters that are considered to be factors that cause fluctuations in the number of passengers getting on and off; A measurement process for measuring the distribution of people on the platform where the train stops; a passenger number calculation process for calculating the number of passengers entering the vehicle at each door based on the measured passenger number distribution; a creation process for creating boarding guidance plan information for guiding passengers on the platform by reflecting the predicted number of passengers getting off and the calculated number of passengers getting on; an output process for outputting the boarding guidance plan information; A passenger guidance planning program to execute the above.

[0082] (Appendix 12) To the computer, In the creation process, the boarding and alighting time required for boarding and alighting at each door is predicted based on the predicted number of alighting passengers and the calculated number of boarding passengers, and the boarding guidance plan information is created to guide passengers on the platform from a boarding position at a door where the predicted boarding and alighting time is long to a boarding position at a door where the predicted boarding and alighting time is short. The boarding guidance planning program described in Appendix 11.

[0083] (Appendix 13) To the computer, In the creation process, the boarding guidance plan information is created to guide passengers on the platform from a boarding position of a door where the expected boarding / alighting time exceeds the allowable stopping time of the train to a boarding position of a door where the expected boarding / alighting time does not exceed the allowable stopping time of the train. The boarding guidance planning program described in Appendix 12.

[0084] (Appendix 14) To the computer, In the process of predicting the number of passengers getting off, the number of passengers who will be staying in the vehicle before getting on or off in each vehicle is predicted based on information indicating the number of passengers who have stayed in the vehicle before getting on or off in the past; The creating means creates the boarding guidance plan information for guiding passengers on the platform from a boarding position of a vehicle where the predicted number of passengers before boarding / alighting exceeds the allowable number of passengers to a boarding position of a vehicle where the predicted number of passengers before boarding / alighting does not exceed the allowable number of passengers. The boarding guidance planning program described in Appendix 13.

[0085] (Appendix 15) To the computer, In the measurement process, for each area on the platform corresponding to the boarding position of the door, the number of people staying in that area is counted, excluding people whose moving speed is equal to or greater than a threshold. A boarding guidance planning program according to any one of appendices 11 to 14. [Explanation of symbols]

[0086] 10. Ride guidance planning device 11. Prediction of number of passengers getting off 12 Measurement methods 13 Passenger number calculation method 14 Creation Method 15 Output Method 100 Ride guidance planning device 110 Passenger number prediction parameter accumulation unit 120 Passenger Number Prediction Department 121 Data Acquisition Unit 122 Learning Department 130 Platform population distribution measurement unit 140 Next departure passenger number calculation unit 150 Platform number of people information reflection section 160 Boarding guidance plan information output unit 1000 CPU 1001 Main memory 1002 Auxiliary storage

Claims

1. a means for predicting the number of passengers who will get off at each door based on the actual measurements of the number of passengers getting on and off in the past and the number of passengers in the vehicle, and the number of passengers who will get off predicted from related parameters that are considered to be factors that cause fluctuations in the number of passengers getting on and off; A measuring means for measuring the distribution of people on the platform where the vehicle stops; a passenger number calculation means for calculating the number of passengers entering the vehicle at each door based on the measured passenger number distribution; a creating means for creating boarding guidance plan information for guiding passengers on the platform by reflecting the predicted number of passengers getting off and the calculated number of passengers getting on; and an output means for outputting the boarding guidance plan information. Ride guidance planning device.

2. The creating means predicts the boarding and alighting time required for each door based on the predicted number of alighting passengers and the calculated number of boarding passengers, and creates the boarding guidance plan information for guiding passengers on the platform from a boarding position at a door where the predicted boarding and alighting time is long to a boarding position at a door where the predicted boarding and alighting time is short. The passenger guidance planning device according to claim 1.

3. The creating means creates the boarding guidance plan information for guiding passengers on the platform from a boarding position of a door where the predicted boarding / alighting time exceeds the allowable stopping time of the train to a boarding position of a door where the predicted boarding / alighting time does not exceed the allowable stopping time of the train. The boarding guidance planning device according to claim 2.

4. The alighting number prediction means predicts the number of passengers before getting on or off for each vehicle who will be staying in the vehicle before getting on or off based on information indicating the number of passengers before getting on or off who have stayed in the vehicle before getting on or off in the past, The creating means creates the boarding guidance plan information for guiding passengers on the platform from a boarding position of a vehicle where the predicted number of passengers before boarding / alighting exceeds the allowable number of passengers to a boarding position of a vehicle where the predicted number of passengers before boarding / alighting does not exceed the allowable number of passengers. The passenger guidance planning device according to claim 3.

5. The measuring means measures the number of people staying in each area on the platform corresponding to the boarding position of the door, excluding people whose moving speed is equal to or greater than a threshold. The passenger guidance planning device according to any one of claims 1 to 4.

6. The computer The number of passengers getting off at each door is predicted based on the past measured number of passengers getting on and off and the number of passengers in the vehicle, and the number of passengers getting off predicted from related parameters that are considered to be factors that cause fluctuations in the number of passengers getting on and off; Measure the distribution of people on the platform where the train stops, Based on the measured number of passengers distribution, the number of passengers entering each door of the vehicle is calculated, Create boarding guidance plan information for guiding passengers on the platform by reflecting the predicted number of passengers getting off and the calculated number of passengers getting on. Output the boarding guidance plan information Boarding guidance planning method.

7. On the computer, a process of predicting the number of passengers who will get off at each door based on the actual measurements of the number of passengers getting on and off in the past and the number of passengers in the vehicle, and the number of passengers who will get off predicted from related parameters that are considered to be factors that cause fluctuations in the number of passengers getting on and off; A measurement process for measuring the distribution of people on the platform where the train stops; a passenger number calculation process for calculating the number of passengers entering the vehicle at each door based on the measured passenger number distribution; a creation process for creating boarding guidance plan information for guiding passengers on the platform by reflecting the predicted number of passengers getting off and the calculated number of passengers getting on; an output process for outputting the boarding guidance plan information; A passenger guidance planning program to execute the above.

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