Traffic control device, traffic management device, traffic control method, and traffic control program

Abstract

To obtain an operation adjustment device capable of adjusting the increase / decrease of the number of trains in accordance with an actual boarding state of a train.SOLUTION: An operation adjustment device includes: a congestion prediction unit 33 for predicting a future congestion degree for each vehicle based on a boarding rate of passengers for each vehicle constituting a train 10; and an operation adjustment unit 35 for determining whether or not an operation plan of one or more trains 10 in an operation schedule indicating the operation plan of the plurality of trains 10 is to be changed based on a result obtained by comparing the congestion degree predicted by the congestion prediction unit 33 with a predetermined threshold.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a traffic adjustment device, a traffic management device, a traffic adjustment method, and a traffic adjustment program for adjusting train operations. [Background technology]

[0002] Conventionally, when public transportation such as railroads becomes crowded due to an increase in passengers, it takes time for passengers to board and disembark, causing delays and further congestion. For this reason, public transportation predicts travel demand and increases the number of trains when congestion is predicted. For example, Patent Literature 1 discloses a technology that predicts travel demand, calculates the degree of congestion on trains, and controls to increase the number of trains when congestion is predicted, while reducing the number of trains when low travel demand is predicted. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2019-73146 A Summary of the Invention [Problem to be solved by the invention]

[0004] The degree of congestion on a train is not uniform among the cars, and certain cars, for example, cars close to the stairs or ticket gates at the disembarking station, may be crowded. In such a case, even if other cars are empty, if a certain car is crowded, it takes time for passengers to board and disembark from the specific car, which causes train delays. However, according to the above conventional technology, the degree of congestion on a train is evaluated based on the number of passengers relative to the number of passengers that the train can accommodate, so even if a certain car on the train is crowded, if there is room for the occupancy rate of the train as a whole, it is not possible to detect signs of a train delay. This causes a problem of delays in taking measures such as increasing the number of trains.

[0005] The present disclosure has been made in consideration of the above, and aims to provide an operation adjustment device that can adjust the increase or decrease in train service in accordance with the actual passenger status of the train. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the object, the operation adjustment device of the present disclosure includes a congestion prediction unit that predicts the future congestion level of each vehicle based on the passenger occupancy rate of each vehicle in the vehicles constituting the train, and an operation adjustment unit that determines whether or not to change the operation plan of one or more trains in a bus schedule that shows the operation plans of multiple trains including the train, based on a result of comparing the congestion level predicted by the congestion prediction unit with a specified threshold value; A storage unit that stores a train schedule; Equipped The timetable includes a first timetable for a first train that is not normally operated but is subject to an increase in service, a second timetable for a second train that is normally operated but is subject to a reduction in service, and a third timetable for a third train that is not subject to an increase or reduction in service. It is characterized by: Effect of the Invention

[0007] According to the present disclosure, the operation adjustment device has the advantage of being able to adjust the increase or decrease in train service in accordance with the actual passenger status of the train. [Brief description of the drawings]

[0008] [Figure 1] A block diagram showing a configuration example of a traffic control device according to the first embodiment. [Diagram 2] FIG. 1 is a first diagram showing an example of a bus schedule created by a bus schedule creation unit of a traffic control device according to a first embodiment; [Diagram 3] FIG. 2 is a second diagram showing an example of a bus schedule created by the bus schedule creation unit of the traffic control device according to the first embodiment; [Figure 4] FIG. 3 is a third diagram showing an example of a bus schedule created by the bus schedule creation unit of the traffic control device according to the first embodiment; [Diagram 5] FIG. 1 is a diagram showing an example of a timetable corresponding to a bus schedule created by a bus schedule creation unit of a traffic control device according to the first embodiment. [Figure 6] FIG. 1 is a diagram showing an example of a bus schedule stored in a bus schedule database of a traffic control device according to the first embodiment; [Figure 7]FIG. 1 is a diagram showing an example of the congestion degree for each train car stored in a congestion degree database of a traffic control device according to the first embodiment; [Figure 8] FIG. 1 is a diagram showing an example of a vehicle that is a target when the operation adjustment unit of the operation adjustment device according to the first embodiment determines whether to increase or decrease the number of trains. [Figure 9] FIG. 1 is a diagram showing an example of a bus schedule when the operation adjustment unit of the operation adjustment device according to the first embodiment determines to increase or decrease the number of services. [Figure 10] FIG. 1 is a diagram showing changes in passenger occupancy rates that are the basis for generating a passenger occupancy rate model by the operation adjustment unit of the operation adjustment device according to the first embodiment; [Figure 11] FIG. 1 is a first diagram showing a passenger load model generated by a traffic control unit of a traffic control device according to a first embodiment; [Figure 12] FIG. 2 is a second diagram showing a passenger load model generated by the operation adjustment unit of the operation adjustment device according to the first embodiment; [Figure 13] FIG. 1 is a diagram showing an example in which the traffic adjustment unit of the traffic adjustment device according to the first embodiment determines which trains to increase in frequency from among a plurality of candidates. [Figure 14] FIG. 1 is a diagram showing trains that are to be increased or decreased by the operation adjustment unit of the operation adjustment device according to the first embodiment on a train schedule. [Figure 15] FIG. 1 is a diagram showing an example in which the traffic adjustment unit of the traffic adjustment device according to the first embodiment starts the operation of an additional train from the middle of the travel route. [Figure 16] FIG. 1 is a diagram showing an example in which the traffic adjustment unit of the traffic adjustment device according to the first embodiment cancels a train for reduction in service in the middle of a travel route. [Figure 17] A flowchart showing a process in which a traffic control unit of a traffic control device according to the first embodiment determines whether to increase the number of trains or to reduce the number of trains. [Figure 18] A flowchart showing the processing of an increased service mode in the operation adjustment unit of the operation adjustment device according to the first embodiment. [Figure 19] A flowchart showing a process of determining which trains to increase in frequency are to be performed by the traffic control unit of the traffic control device according to the first embodiment. [Figure 20]A flowchart showing a process for determining which trains to reduce in service by the traffic control unit of the traffic control device according to the first embodiment. [Figure 21] A flowchart showing the processing of the reduced service mode in the operation adjustment unit of the operation adjustment device according to the first embodiment [Figure 22] FIG. 1 is a diagram showing an example of the configuration of a processing circuit for implementing the traffic control device according to the first embodiment using a processor and a memory; [Figure 23] FIG. 1 is a diagram showing an example of the configuration of a processing circuit for implementing the traffic control device according to the first embodiment when the processing circuit is configured with dedicated hardware. [Figure 24] A block diagram showing a configuration example of a traffic control device according to a second embodiment. [Diagram 25] A block diagram showing a configuration example of a traffic control device according to a third embodiment. [Figure 26] A block diagram showing a configuration example of a traffic control device according to a fourth embodiment. [Figure 27] FIG. 13 is a diagram showing a change in a train schedule when an increase in the number of trains is determined in the operation adjustment unit of the operation adjustment device according to the fifth embodiment. [Figure 28] A flowchart showing the processing of the increased service mode in the operation adjustment unit of the operation adjustment device according to the fifth embodiment [Figure 29] FIG. 23 is a diagram showing an example in which the operation adjustment unit of the operation adjustment device according to the sixth embodiment determines the type of train to be increased in frequency based on the predicted congestion degree. [Diagram 30] FIG. 23 is a diagram showing an example in which the operation adjustment unit of the operation adjustment device according to the sixth embodiment changes the type of train in operation according to the predicted congestion degree. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, a traffic adjustment device, a traffic management device, a traffic adjustment method, and a traffic adjustment program according to embodiments of the present disclosure will be described in detail with reference to the drawings.

[0010] Embodiment 1 FIG. 1 is a block diagram showing a configuration example of a traffic control device 30 according to the first embodiment. The traffic control device 20 includes the traffic control device 30. The traffic control device 30 adjusts the traffic of the train 10, such as increasing the number of trains 10 or decreasing the number of trains 10. The traffic control device 20 manages the traffic of the train 10. The train 10 is an object for which the traffic control device 20 manages the traffic. Note that while the number of trains 10 in FIG. 1 is two, the number of trains 10 for which the traffic control device 20 manages the traffic may be three or more. Also, although the illustration is simplified in FIG. 1, the train 10 is actually composed of a plurality of vehicles. The same applies to the subsequent figures.

[0011] The configuration and operation of the traffic control device 30 will be described. As shown in Fig. 1, the traffic control device 30 includes a traffic schedule creation unit 31, a congestion prediction unit 33, a traffic control unit 35, and a storage unit 37. The storage unit 37 stores a traffic schedule database 32, a congestion degree database 34, and a crew shift database 36. In Fig. 1, "databases" such as the traffic schedule database 32 are written as DB (Data Base). This also applies to the subsequent figures. In Fig. 1, one storage unit 37 stores three databases, but the traffic control device 30 may be configured to have a storage unit for each database.

[0012] The train schedule creation unit 31 creates a train schedule for the train 10. The train schedule creation unit 31 creates a train schedule for the route on which the operation adjustment device 30 adjusts the operation of the train 10. The train schedule includes an upbound train schedule and a downbound train schedule, a weekday train schedule and a holiday train schedule for each route. The train schedule creation unit 31 may create the train schedule automatically, or may create the train schedule by receiving an operation from a person in charge of the railway company. The train schedule created by the train schedule creation unit 31 will be described. FIG. 2 is a first diagram showing an example of a train schedule created by the train schedule creation unit 31 of the operation adjustment device 30 according to the first embodiment. In FIG. 2, the horizontal axis indicates time, and the vertical axis indicates the position of the train 10, such as a station where the train 10 stops. The same applies to the following. The train schedule includes a train schedule for the train 10 that is not normally operated but is subject to an increase in service, a train schedule for the train 10 that is normally operated but is subject to a reduction in service, and a train schedule for the train 10 that is not subject to an increase or reduction in service. A timetable represents the operation of an individual train 10 in the train 10 timetable, and is represented as a graph-like line when the timetable is presented on paper or the like. In the following description, the train 10 that is the subject of an increase in service may be referred to as the first train, and the timetable for the first train may be referred to as the first timetable. The train 10 that is the subject of a reduction in service may be referred to as the second train, and the timetable for the second train may be referred to as the second timetable. The train 10 that is not the subject of an increase or reduction in service may be referred to as the third train, and the timetable for the third train may be referred to as the third timetable. In FIG. 2, the first timetable is referred to as a special timetable, the second timetable is referred to as a regular timetable (possible cancellation), and the third timetable is referred to as a regular timetable. The same applies to the following figures.

[0013] As shown in FIG. 2, in the bus schedule created by the bus schedule creation unit 31, the first train's route is prepared between the routes for the third train. Therefore, it is preferable for the bus schedule creation unit 31 to provide the first train's route in a time period when the intervals between the routes for the third train are wide. The second train is a train 10 that may be suspended. Since the second train is usually scheduled to operate, the bus schedule creation unit 31 creates the bus schedule so that the routes for the second train are not consecutive, for example, by providing one route for the second train for every number of routes for the specified third train.

[0014] The nature of the bus schedule created by the bus schedule creation unit 31 will be described. When the bus schedule created by the bus schedule creation unit 31 is a bus schedule in which the third train is the main train and the first train and the second train are set to a very small extent, the railway company that operates the train 10 can easily operate the train 10 with certainty, and surplus vehicles, personnel, etc. are unlikely to occur. On the other hand, passengers who use the train 10 can easily make plans, but cannot expect a response such as an increase in the number of trains 10 even if the train is crowded. FIG. 3 is a second diagram showing an example of a bus schedule created by the bus schedule creation unit 31 of the operation adjustment device 30 according to the first embodiment. FIG. 3 shows that six of the eight trains 10 are reliably operated.

[0015] Furthermore, when the bus schedule created by the bus schedule creation unit 31 is a bus schedule in which the third train is minimized and the first and second trains are set more frequently, the railway company can more flexibly change the number of trains 10 in operation according to the increase or decrease in passenger demand. On the other hand, passengers can expect an increase in the number of trains 10 when the train is crowded, but it is difficult to plan transfers and the like because there are few trains 10 that are reliably operated. FIG. 4 is a third diagram showing an example of a bus schedule created by the bus schedule creation unit 31 of the traffic adjustment device 30 according to the first embodiment. FIG. 4 shows that only one train 10 out of eight trains 10 is reliably operated.

[0016] In addition, it is common for passengers to search for the departure time of the train 10 that they plan to board in applications on personal computers, smartphones, etc., but if the train 10 that they plan to board is suddenly reduced in service, i.e., suspended, passenger convenience decreases. For this reason, it is preferable to take measures such as setting the train 10 that may be reduced in service, i.e., the second train, to be excluded from the search target of the application. In addition, the operation schedule creation unit 31 can suppress the decrease in passenger convenience by setting the second train to a train 10 that does not have transfers to other trains 10. FIG. 5 is a diagram showing an example of a timetable corresponding to the operation schedule created by the operation schedule creation unit 31 of the operation adjustment device 30 according to the first embodiment. In a timetable displayed at a station, for example, a △ mark is added to the first train and a * mark is added to the second train, so that passengers can be made aware that the operation of the train 10 is fluid.

[0017] The bus schedule database 32 holds the bus schedule created by the bus schedule creation unit 31. That is, the storage unit 37 stores the bus schedule created by the bus schedule creation unit 31. FIG. 6 is a diagram showing an example of a bus schedule held in the bus schedule database 32 of the traffic control device 30 according to the first embodiment. As described above, the bus schedule creation unit 31 creates, for each route, bus schedules for inbound and outbound trips, weekday and holiday trips, and the like, as bus schedules for the routes for which the traffic control device 30 adjusts the operation of the train 10. Therefore, the bus schedule database 32 holds a plurality of bus schedules created by the bus schedule creation unit 31.

[0018] The congestion prediction unit 33 predicts the future congestion level of each vehicle based on the passenger occupancy rate of each vehicle in the vehicles constituting the train 10. First, the congestion prediction unit 33 acquires train data including data on the passenger occupancy rate of each vehicle of the train 10 from each train 10 by wireless communication. The train 10 can estimate the passenger occupancy rate of each vehicle by measuring the weight of the vehicle using a sensor such as a load compensation device. The congestion prediction unit 33 extracts data on the passenger occupancy rate of each vehicle from the train data acquired from each train 10. The congestion prediction unit 33 estimates the current congestion level of each vehicle of the train 10 from the passenger occupancy rate data of each vehicle of the train 10, and further predicts the future congestion level of each vehicle of the train 10.

[0019] There is no particular limit to the method of predicting the degree of congestion for each vehicle of the future train 10 in the congestion prediction unit 33. For example, the congestion prediction unit 33 may compare the estimated degree of congestion for each vehicle of the current train 10 with the degree of congestion for each vehicle of the past train 10 stored in the congestion database 34, and predict the degree of congestion for each vehicle of the future train 10 from the transition of changes in the degree of congestion, or may predict the degree of congestion for each vehicle of the future train 10 from the estimated degree of congestion for each vehicle of the current train 10 using AI (Artificial Intelligence) or the like. When predicting the degree of congestion for each vehicle of the future train 10, the congestion prediction unit 33 may predict the degree of congestion for each vehicle of the train 10 by using data on the passenger occupancy rate for each vehicle of the train 10 acquired from each train 10, predict the degree of congestion by the passenger occupancy rate for each vehicle relative to the capacity of each vehicle, predict the degree of congestion by the number of passengers boarding each vehicle, predict the degree of congestion by the boarding and alighting time of passengers for each vehicle, predict the degree of congestion by the delay time for each vehicle relative to the specified boarding and alighting time of passengers, or predict the degree of congestion by at least one of these.

[0020] In addition, when predicting the degree of congestion for each car of the train 10 at a certain station, the congestion prediction unit 33 may change the conditions and predict the degree of congestion for each of a plurality of conditions. For example, the congestion prediction unit 33 may predict the degree of congestion for each car of the train 10 at a certain station by the direction of travel, i.e., for each upbound train and downbound train, by day of the week, by weather, i.e., sunny or rainy, by season, i.e., by dividing a year into weeks or months, or by a combination of these. The congestion prediction unit 33 may acquire information on the direction of travel, day of the week, weather, season, etc., for example, from the traffic management device 20, or from a device other than the traffic management device 20, and the method of acquiring each piece of information is not particularly limited.

[0021] The congestion degree database 34 holds the congestion degree of each vehicle of the train 10 estimated by the congestion prediction unit 33. That is, the storage unit 37 stores the congestion degree of each vehicle of the train 10 estimated by the congestion prediction unit 33. FIG. 7 is a diagram showing an example of the congestion degree of each vehicle of the train 10 held in the congestion degree database 34 of the operation coordination device 30 according to the first embodiment. As described above, the congestion prediction unit 33 estimates the congestion degree of each vehicle of the current train 10. Therefore, the congestion degree database 34 holds the result of the congestion degree of each vehicle of the train 10 estimated by the congestion prediction unit 33 in correspondence with the time when the congestion degree was estimated. The congestion degree information held in the congestion degree database 34 represents a past actual value. Note that the congestion prediction unit 33 obtains information such as the direction of travel, the day of the week, the weather, and the season to predict the congestion degree of each vehicle of the train 10, and therefore the congestion degree database 34 may hold the congestion degree of each vehicle of the train 10 estimated by the congestion prediction unit 33 for each type of information. The congestion prediction unit 33 may update the congestion degree information for each car of the train 10 stored in the congestion degree database 34 every time it estimates the congestion degree for each car of the train 10. The congestion degree database 34 may store the passenger occupancy rate data acquired by the congestion prediction unit 33 from the train 10 as is, or may store data averaged over a specified period under the same conditions such as the time of day.

[0022] The crew shift database 36 holds information on the work shifts of crew members such as the driver and conductor of the train 10. That is, the memory unit 37 stores information on the work shifts of crew members such as the driver and conductor of the train 10. When the train 10 is operated by a single driver, the crew shift database 36 only needs to hold information on the work shifts of the driver of the train 10. When the train 10 is operated automatically, the memory unit 37 of the operation coordination device 30 does not need to store the crew shift database 36.

[0023] The operation adjustment unit 35 acquires a train schedule from the train schedule database 32, acquires a predicted congestion level from the congestion prediction unit 33, and acquires a congestion level from the congestion level database 34. Based on a result of comparing the congestion level predicted by the congestion prediction unit 33 with a specified threshold, the operation adjustment unit 35 determines whether or not to change the operation plan of one or more trains 10 in the train schedule showing the operation plans of multiple trains 10 including the target train 10 for which the congestion prediction unit 33 acquired train data. Here, the future congestion level for each vehicle predicted by the congestion prediction unit 33 may not be uniform for each vehicle, but may differ for each vehicle. In general, if congestion on the train 10 causes passengers to take time to board and disembark from the train 10, this causes a delay in the train 10. In other words, if even one of the multiple vehicles constituting the train 10 is crowded and takes time for passengers to board and disembark, this causes a delay in the train 10. Therefore, the operation adjustment unit 35 determines whether to increase or decrease the number of trains 10, focusing on the vehicle, time, station, etc. of the train 10 for which congestion is predicted.

[0024] FIG. 8 is a diagram showing an example of a vehicle that is a target when the operation adjustment unit 35 of the operation adjustment device 30 according to the first embodiment determines whether to increase or decrease the number of trains 10. For example, when a staircase is installed on the front car side of the train 10 shown in FIG. 8 at a station where many passengers get on and off, the congestion prediction unit 33 predicts a congestion degree indicating that the front car of the train 10 will be crowded at the station. Therefore, in the example of FIG. 8, the operation adjustment unit 35 focuses only on the front car of the train 10 and compares the congestion degree of the front car of the train 10 with a specified threshold value to determine whether to increase the number of trains 10. In this way, the operation adjustment unit 35 determines whether to change the operation plan of one or more trains 10 in the operation schedule based on the result of comparing the congestion degree of the car with the highest congestion degree among the congestion degrees of each car of the train 10 predicted by the congestion prediction unit 33 with the threshold value. In addition, if the congestion prediction unit 33 predicts that the congestion level will not be significantly higher in any particular car, at any particular time, or at any particular station of the train 10, and that the congestion will be uniform throughout the train, the operation adjustment unit 35 may determine whether or not to increase the number of trains 10 for all cars, at all times, and at all stations of the train 10.

[0025] The operation adjustment unit 35 determines to increase the number of first trains when the degree of congestion for each car of the train 10 predicted by the congestion prediction unit 33 is equal to or greater than the first threshold for determining whether to increase the number of first trains. At this time, when there are multiple first trains to be increased, the operation adjustment unit 35 selects the first train that can most easily alleviate congestion by increasing the number of trains. Also, when the degree of congestion for each car of the train 10 predicted by the congestion prediction unit 33 is equal to or less than the second threshold for determining whether to reduce the number of second trains, the operation adjustment unit 35 determines to reduce the number of second trains. At this time, when there are multiple second trains to be reduced, the operation adjustment unit 35 selects the second train that can most easily suppress congestion by reducing the number of trains. It should be noted that the first threshold is greater than the second threshold.

[0026] 9 is a diagram showing an example of a train schedule when the operation adjustment unit 35 of the operation adjustment device 30 according to the first embodiment determines to increase or decrease the number of trains. For example, when the congestion prediction unit 33 predicts that a train 10 will be crowded during a certain time period, the operation adjustment unit 35 can alleviate congestion on other trains 10 that were predicted to be crowded by increasing the number of trains 10 for that time period.

[0027] At this time, the operation adjustment unit 35 generates a passenger load model for each station and each car of the train 10 in order to confirm the effect of increasing or decreasing the number of trains. When generating a passenger load model, the operation adjustment unit 35 uses data on the passenger load of each car when the door of the train 10 is open at the target station. FIG. 10 is a diagram showing a change in passenger load that is the basis for the operation adjustment unit 35 of the operation adjustment device 30 according to the first embodiment to generate a passenger load model. The period from when the door of the train 10 opens to when the passenger load is at its lowest at the target station is the passenger disembarking time, and the period from when the passenger load is at its lowest to when the door of the train 10 closes is the boarding time. The passenger load model represents the increase or decrease in the passenger load of each car of the train 10 at each station, but may be converted into the number of passengers boarding and alighting to form a passenger load model. In this case, the number of passengers boarding and alighting is not the number actually counted, but can be estimated from the relationship between the vehicle weight measured as described above and the average weight of passengers. The operation adjustment unit 35 can generate an occupancy rate model by using congestion degree information or occupancy rate data stored in the congestion degree database 34 for conditions such as the congestion degree predicted by the congestion prediction unit 33 and the direction of travel, day of the week, weather, season, etc.

[0028] FIG. 11 is a first diagram showing a passenger load factor model generated by the operation adjustment unit 35 of the operation adjustment device 30 according to the first embodiment. FIG. 11 shows a passenger load factor model generated by the operation adjustment unit 35 according to an increase in the passenger load factor. By increasing the frequency of a certain train 10, the operation adjustment unit 35 can reduce the number of passengers who board the increased train 10 and the number of passengers who board the train 10 that runs after the increased train 10. On the other hand, by reducing the frequency of a certain train 10, the operation adjustment unit 35 increases the number of passengers who could not board the reduced train 10 and the number of passengers who board the train 10 that runs after the reduced train 10.

[0029] FIG. 12 is a second diagram showing a passenger load factor model generated by the operation adjustment unit 35 of the operation adjustment device 30 according to the first embodiment. FIG. 12 shows a passenger load factor model generated by the operation adjustment unit 35 according to the amount of reduction in the passenger load factor. By increasing the frequency of a certain train 10, the operation adjustment unit 35 can reduce the number of passengers who board the increased train 10 and the number of passengers who get off the train 10 that runs after the increased train 10. On the other hand, by reducing the frequency of a certain train 10, the operation adjustment unit 35 increases the number of passengers who could not board the reduced train 10 and the number of passengers who get off the train 10 that runs after the reduced train 10.

[0030] Based on the passenger load factor model shown in FIG. 11 and FIG. 12, when the number of trains 10 is to be increased, the operation adjustment unit 35 determines the number of trains 10 to be increased depending on how much the increase or decrease in the passenger load factor of the train 10 following the train 10 to be increased can be improved. Also, based on the passenger load factor model shown in FIG. 11 and FIG. 12, when the number of trains 10 is to be reduced, the operation adjustment unit 35 determines the number of trains 10 to be reduced depending on how much the deterioration of the increase or decrease in the passenger load factor of the train 10 following the train 10 to be reduced can be suppressed. Note that the operation adjustment unit 35 does not need to generate both of the passenger load factor models shown in FIG. 11 and FIG. 12, and may generate only one of them as long as the fluctuation of the passenger load factor can be grasped. Also, the operation adjustment unit 35 can generate the passenger load factor model by using the congestion degree information or passenger load factor data held in the congestion degree database 34, but when the congestion degree prediction accuracy in the congestion prediction unit 33 is high, the passenger load factor model may be generated using the congestion degree predicted by the congestion prediction unit 33.

[0031] FIG. 13 is a diagram showing an example when the operation adjustment unit 35 of the operation adjustment device 30 according to the first embodiment determines the train 10 to be increased from among multiple candidates. As shown in FIG. 13, when there are three trains 10 that can be increased in number, the operation adjustment unit 35 selects the train 10 that can be increased in number to obtain the most effect. In the example of FIG. 13, among trains 1, 2, and 3, train 3 has the largest boarding and alighting numbers, and there is no significant difference between trains 1 and 2 in boarding and alighting numbers. Therefore, in order to disperse passengers on train 3, the operation adjustment unit 35 selects candidate train 10 b as the train 10 to be increased in number. At this time, the operation adjustment unit 35 may select the train 10 for increasing the number of trains that can obtain the most effect by using a prescribed evaluation function together with the passenger load model. The evaluation function may include, but is not limited to, a function that selects an additional train 10 that minimizes the probability that the total number of passengers boarding and alighting at each station during a time period when congestion is predicted exceeds a specified threshold, or a function that selects an additional train 10 that minimizes the maximum number of passengers boarding and alighting at each station during a time period when congestion is predicted, etc.

[0032] Here, if the train 10 is not an unmanned train and requires a driver, the driver is required to operate the train 10. The increase in the number of trains 10 can be handled by reserving a driver in advance in anticipation of an increase in the number of trains 10, but if the number of trains 10 is not increased, the reserved driver may end his / her duties without driving, which is not efficient for the railway company. Therefore, the operation adjustment unit 35 acquires crew shift information from the crew shift database 36, and reduces the number of trains 10 that were scheduled to be driven by a driver who can drive the increased number of trains 10, i.e., the second train, thereby securing a driver for the increased number of trains 10. FIG. 14 is a diagram showing trains 10 that are to be increased and reduced by the operation adjustment unit 35 of the operation adjustment device 30 according to the first embodiment on a train schedule. In the example of FIG. 14, when the operation coordination unit 35 needs to reduce the number of trains 10 in order to secure a driver when increasing the number of trains 10, the operation coordination unit 35 determines that driver B, who is able to drive the increased train 10, will reduce the number of trains 10 that were scheduled to be driven. The operation coordination unit 35 determines that driver A, who is unable to drive the increased train 10, will drive the train 10 according to the train schedule. In this way, when it is necessary to reduce the number of trains of a second train in order to increase the number of trains of a first train, the operation coordination unit 35 selects the first train and the second train based on the shift information of the crew members.

[0033] In the above description, the operation adjustment unit 35 of the operation adjustment device 30 starts the operation of the train 10 from the beginning according to the schedule specified in the operation diagram when the number of trains is increased, and suspends the operation of the train 10 from the beginning according to the schedule specified in the operation diagram when the number of trains is reduced, but this is not limited to the above. For example, if a station where the additional train 10 can wait is located on the operation route, the operation adjustment unit 35 may start the operation of the additional train 10 from that station. FIG. 15 is a diagram showing an example in which the operation adjustment unit 35 of the operation adjustment device 30 according to the first embodiment starts the operation of the additional train 10 from the middle of the operation route. The operation adjustment unit 35 increases the number of trains 10 that run ahead of the train 10 that has started to become crowded. This allows the operation adjustment unit 35 to reduce the number of passengers getting on and off the train 10 at the station where the additional train 10 starts operating, thereby alleviating congestion. In this way, when the number of trains of the first train is increased, the operation adjustment unit 35 can determine that the first train starts operating from an intermediate station.

[0034] In addition, for example, when there is a train 10 that can be transferred from the train 10 to be reduced, the operation adjustment unit 35 may suspend the reduced train 10 at a station where the transfer is possible. FIG. 16 is a diagram showing an example in which the operation adjustment unit 35 of the operation adjustment device 30 according to the first embodiment suspends the reduced train 10 in the middle of the operation route. For a train 10 that runs after the train 10 whose congestion has started to ease, if there is a train 10 that runs at a nearby time and transfer to the train 10 is easy, the operation adjustment unit 35 may reduce the service, i.e., suspend the train 10 in the section beyond the station where the transfer is possible. The train 10 that runs at a nearby time may be a train 10 that runs on the same line, or a train 10 that runs directly from another line. In this way, the operation adjustment unit 35 can reduce the number of trains 10 in operation in the section where congestion is eased, and prevent the transportation capacity of the train 10 from becoming excessive. In this way, when reducing the service of the second train, the operation adjustment unit 35 can determine to operate the second train to an intermediate station and then suspend operation.

[0035] The operation of the operation adjustment unit 35 will be described using a flowchart. FIG. 17 is a flowchart showing the process of the operation adjustment unit 35 of the operation adjustment device 30 according to the first embodiment determining whether to increase the number of trains 10 or reduce the number of trains 10. When the congestion degree predicted by the congestion prediction unit 33 is equal to or greater than the first threshold (step S101: Yes), the operation adjustment unit 35 shifts to an increase in trains mode (step S102). When the congestion degree predicted by the congestion prediction unit 33 is less than the first threshold (step S101: No) and less than a second threshold smaller than the first threshold (step S103: Yes), the operation adjustment unit 35 shifts to a reduction in trains mode (step S104). When the congestion degree predicted by the congestion prediction unit 33 is less than the first threshold (step S101: No) and is equal to or greater than the second threshold smaller than the first threshold (step S103: No), the operation adjustment unit 35 ends the operation. The operation adjustment unit 35 periodically and repeatedly executes the operation of the flowchart shown in FIG.

[0036] FIG. 18 is a flowchart showing the processing of the increased service mode in the operation adjustment unit 35 of the operation adjustment device 30 according to the first embodiment. The flowchart shown in FIG. 18 shows the details of the processing of the increased service mode in step S102 of the flowchart shown in FIG. 17. The operation adjustment unit 35 determines the number of trains 10 to be increased (step S201). The operation adjustment unit 35 refers to the crew shift database 36, and if the train configuration and crew are secured for the train 10 for which the increased service has been determined (step S202: Yes), changes the operation schedule (step S203), confirms the changes (step S204), and ends the processing of the increased service mode. The operation adjustment unit 35 refers to the crew shift database 36, and if the train configuration and crew are not secured for the train 10 for which the increased service has been determined (step S202: No), determines whether there is a train 10 that can be reduced (step S205). If there is a train 10 that can be reduced (step S205: Yes), the operation adjustment unit 35 determines which train 10 to reduce (step S206). The operation adjustment unit 35 changes the train schedule (step S203), confirms the changes (step S204), and ends the processing in the increased service mode. If there is no train 10 that can be reduced (step S205: No), the operation adjustment unit 35 ends the processing in the increased service mode without increasing the number of trains 10.

[0037] FIG. 19 is a flowchart showing the process of determining the train 10 to be increased by the operation adjustment unit 35 of the operation adjustment device 30 according to the first embodiment. The flowchart shown in FIG. 19 shows details of the process of determining the train 10 to be increased in step S201 of the flowchart shown in FIG. 18. When there are multiple trains 10 that are candidates for increasing the number of trains, the operation adjustment unit 35 selects one of the trains 10 that are candidates for increasing the number of trains (step S301). The operation adjustment unit 35 evaluates the case where the selected train 10 that is a candidate for increasing the number of trains is actually increased using a passenger load model, an evaluation function, and the like (step S302). When there are multiple trains 10 that are candidates for increasing the number of trains and there is a train 10 that is a candidate for increasing the number of trains that has not been selected (step S303: No), the operation adjustment unit 35 returns to step S301 and selects one of the trains 10 that are candidates for increasing the number of trains that has not been selected. The operation adjustment unit 35 repeats the above process, and when all candidate trains 10 for increasing service have been selected (step S303: Yes), selects the optimal train 10 based on the evaluation results of each candidate train 10 for increasing service (step S304). As described above, the optimal train 10 is the train 10 that can most effectively alleviate congestion on other trains 10 by increasing the service.

[0038] FIG. 20 is a flowchart showing the process of the operation adjustment unit 35 of the operation adjustment device 30 according to the first embodiment to determine the train 10 to be reduced. The flowchart shown in FIG. 20 shows details of the process of determining the train 10 to be reduced in step S206 of the flowchart shown in FIG. 18. When there are multiple trains 10 that are candidates for reduction, the operation adjustment unit 35 selects one of the trains 10 that are candidates for reduction (step S401). The operation adjustment unit 35 evaluates the case where the selected train 10 that is a candidate for reduction is actually reduced using a passenger load model, an evaluation function, and the like (step S402). When there are multiple trains 10 that are candidates for reduction and there is a train 10 that is a candidate for reduction that has not been selected (step S403: No), the operation adjustment unit 35 returns to step S401 and selects one of the trains 10 that are candidates for reduction that have not been selected. The operation adjustment unit 35 repeats the above process, and when all trains 10 that are candidates for reduction have been selected (step S403: Yes), selects the optimal train 10 based on the evaluation results of each train 10 that is a candidate for reduction (step S404). As described above, the optimal train 10 is the train 10 that can most effectively prevent an increase in congestion on other trains 10 by reducing the service.

[0039] FIG. 21 is a flowchart showing the processing of the reduced service mode in the operation adjustment unit 35 of the operation adjustment device 30 according to the first embodiment. The flowchart shown in FIG. 21 shows details of the processing of the reduced service mode in step S104 of the flowchart shown in FIG. 17. If there is a train 10 that can be reduced (step S501: Yes), the operation adjustment unit 35 determines the train 10 to be reduced (step S502). The operation adjustment unit 35 changes the operation schedule (step S503), confirms the changes (step S504), and ends the processing of the reduced service mode. If there is no train 10 that can be reduced (step S501: No), the operation adjustment unit 35 ends the processing of the reduced service mode without reducing the number of trains 10. The processing of determining the train 10 to be reduced in step S502 is the same as the processing of step S206 of the flowchart shown in FIG. 18, that is, the processing of the flowchart shown in FIG. 20.

[0040] In the first embodiment, the traffic management device 20 is configured to include the traffic adjustment device 30. Therefore, when the traffic adjustment device 30 has the same or similar configuration as the traffic schedule creation unit 31, the traffic schedule database 32 stored in the storage unit 37, the driver shift database 36 stored in the storage unit 37, and the like, the traffic management device 20 may use the configuration of the traffic adjustment device 30 to simplify the configuration.

[0041] Next, the hardware configuration of the traffic control device 30 according to the first embodiment will be described. In the traffic control device 30, the storage unit 37 is a memory. The traffic diagram creation unit 31, the congestion prediction unit 33, and the traffic control unit 35 are realized by processing circuits. The processing circuit may be a memory that stores a program and a processor that executes the program stored in the memory, or may be dedicated hardware. The processing circuit is also called a control circuit.

[0042] FIG. 22 is a diagram showing an example of the configuration of the processing circuit 90 in the case where the processing circuit for realizing the traffic control device 30 according to the first embodiment is realized by a processor 91 and a memory 92. The processing circuit 90 shown in FIG. 22 is a control circuit and includes a processor 91 and a memory 92. When the processing circuit 90 is configured with the processor 91 and the memory 92, each function of the processing circuit 90 is realized by software, firmware, or a combination of software and firmware. The software or firmware is described as a program and stored in the memory 92. In the processing circuit 90, each function is realized by the processor 91 reading and executing the program stored in the memory 92. That is, the processing circuit 90 includes a memory 92 for storing a program that results in the processing of the traffic control device 30 being executed. This program can also be said to be a program for causing the traffic control device 30 to execute each function realized by the processing circuit 90. This program may be provided by a storage medium in which the program is stored, or may be provided by other means such as a communication medium.

[0043] The above program can also be said to be a program that causes the operation coordination device 30 to execute a congestion prediction step in which the congestion prediction unit 33 predicts the future degree of congestion in each car based on the passenger occupancy rate in each car that constitutes the train 10, and an operation coordination step in which the operation coordination unit 35 determines whether to change the operation plan of one or more trains 10 in a train schedule that shows the operation plans of multiple trains 10 including train 10, based on the result of comparing the congestion degree predicted by the congestion prediction unit 33 with a specified threshold.

[0044] Here, the processor 91 is, for example, a CPU (Central Processing Unit), a processing device, an arithmetic device, a microprocessor, a microcomputer, or a DSP (Digital Signal Processor), etc. Also, the memory 92 is, for example, a non-volatile or volatile semiconductor memory such as a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, an EPROM (Erasable Programmable ROM), an EEPROM (Electrically EPROM), a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, or a DVD (Digital Versatile Disc), etc.

[0045] FIG. 23 is a diagram showing an example of the configuration of the processing circuit 93 when the processing circuit for realizing the traffic control device 30 according to the first embodiment is configured with dedicated hardware. The processing circuit 93 shown in FIG. 23 corresponds to, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a combination of these. The processing circuit 93 may be partially realized with dedicated hardware and partially realized with software or firmware. In this way, the processing circuit 93 can realize each of the above-mentioned functions by dedicated hardware, software, firmware, or a combination of these.

[0046] As described above, according to this embodiment, the traffic control device 30 predicts the future congestion level of each vehicle based on the passenger occupancy rate of each vehicle constituting the train 10, and based on the result of comparing the predicted congestion level with a specified threshold, determines whether or not to change the operation plan of one or more trains 10 in the bus schedule showing the operation plans of multiple trains 10 including the train 10 whose congestion level has been predicted. This allows the traffic control device 30 to adjust the increase or decrease in the number of trains 10 in accordance with the actual passenger occupancy status of the trains 10.

[0047] Embodiment 2 In the first embodiment, the traffic management device 20 is configured to include the traffic adjustment device 30. In the second embodiment, a case in which the traffic adjustment device 30 is located outside the traffic management device will be described.

[0048] FIG. 24 is a block diagram showing a configuration example of the traffic control device 30 according to the second embodiment. Unlike the first embodiment, the traffic control device 30 is located outside the traffic control device 20a. The traffic control device 20a acquires train data including data on the occupancy rate of each car of the train 10 from each train 10 by wireless communication. The traffic control device 20a transmits the acquired train data to the traffic control device 30. The communication between the traffic control device 20a and the traffic control device 30 may be wired communication or wireless communication. The traffic control device 30 acquires train data including data on the occupancy rate of each car of the train 10 from each train 10 via the traffic control device 20a. In the second embodiment, the operation after the traffic control device 30 acquires the train data is the same as the operation of the traffic control device 30 in the first embodiment. Therefore, a detailed description of the operation of the traffic control device 30 in the second embodiment will be omitted.

[0049] The configuration of the first embodiment is, for example, intended for a case where a railway company newly purchases a traffic management device 20. On the other hand, the configuration of the second embodiment is, for example, intended for a case where a railway company continues to use an existing traffic management device 20a, and additionally introduces a traffic control device 30. In the second embodiment, the traffic control device 30 only needs to acquire train data from the traffic management device 20a, and therefore the communication function of the congestion prediction unit 33 can be simplified compared to the first embodiment in which train data is acquired directly from the train 10 by wireless communication.

[0050] Embodiment 3 In the third embodiment, a case will be described in which the traffic control device 30 acquires train data including data on the occupancy rate of each car of the train 10 from each train 10 via the cloud.

[0051] FIG. 25 is a block diagram showing a configuration example of the traffic control device 30 according to the third embodiment. The data collection device 41 acquires train data including data on the occupancy rate of each car of the train 10 from each train 10 by wireless communication. The data collection device 41 transmits the acquired train data to the traffic control device 30. The communication between the data collection device 41 and the traffic control device 30 may be wired communication or wireless communication. In the third embodiment, the traffic control device 30 acquires train data including data on the occupancy rate of each car of the train 10 from each train 10 via the data collection device 41 installed in the cloud 40. The operation of the traffic control device 30 after acquiring the train data in the third embodiment is the same as the operation of the traffic control device 30 in the first embodiment. Therefore, a detailed description of the operation of the traffic control device 30 in the third embodiment will be omitted.

[0052] The configuration of the third embodiment assumes that the railway company is already equipped with a data collection device 41 capable of collecting train data from trains 10. In the third embodiment, the traffic control device 30 only needs to acquire train data from the data collection device 41 via a network owned by the railway company, and therefore the communication function of the congestion prediction unit 33 can be simplified compared to the first embodiment in which train data is acquired directly from the trains 10 via wireless communication.

[0053] Embodiment 4 In the fourth embodiment, a case will be described in which the traffic control device 30 acquires train data including data on the occupancy rate of each car of the train 10 from each train 10 via the cloud 40 and the traffic management device 20a.

[0054] FIG. 26 is a block diagram showing a configuration example of the traffic control device 30 according to the fourth embodiment. The fourth embodiment is a combination of the configurations of the second embodiment and the third embodiment. The data collection device 41 acquires train data including data on the occupancy rate of each car of the train 10 from each train 10 by wireless communication. The data collection device 41 transmits the acquired train data to the traffic control device 20a. The communication between the data collection device 41 and the traffic control device 20a may be wired communication or wireless communication. The traffic control device 20a transmits the acquired train data to the traffic control device 30. The communication between the traffic control device 20a and the traffic control device 30 may be wired communication or wireless communication. In the fourth embodiment, the traffic control device 30 acquires train data including data on the occupancy rate of each car of the train 10 from each train 10 via the data collection device 41 installed in the cloud 40 and the traffic control device 20a. The operation after the traffic control device 30 acquires the train data in the fourth embodiment is the same as the operation of the traffic control device 30 in the first embodiment. Therefore, a detailed description of the operation of the traffic adjustment device 30 in the fourth embodiment will be omitted.

[0055] The configuration of the fourth embodiment assumes that the railway company is already equipped with a data collection device 41 capable of collecting train data from trains 10, and an operation management device 20a. In the fourth embodiment, the operation coordination device 30 only needs to acquire train data from the operation management device 20a via a network owned by the railway company, and therefore the communication function of the congestion prediction unit 33 can be simplified compared to the first embodiment in which train data is acquired directly from trains 10 by wireless communication.

[0056] Embodiment 5. In the first embodiment, the traffic control device 30 takes into consideration crew shifts and the like, and when increasing the number of trains 10, reduces the number of trains 10. In this case, there is no need to secure extra train configurations, crew members, etc., but reducing the number of trains reduces convenience for passengers. In the fifth embodiment, the operation of the traffic control device 30 in the case where increasing the number of trains 10 does not involve reducing the number of trains 10 will be described.

[0057] In the fifth embodiment, the configuration of the operation coordination device 30 is the same as that in the first embodiment shown in FIG. 1. In the fifth embodiment, in a situation where several additional trains 10 and crew members are secured, the operation coordination device 30 determines whether to increase the number of trains 10 or reduce the number of trains 10. The additional trains 10 are stored in a storage line at a base station, a garage near a base station, or the like. When the operation coordination device 30 determines to increase the number of trains 10, it sends the additional trains 10 from the station where the additional trains 10 are stored or to the station where the additional trains 10 start operating, and then starts operating the additional trains 10. FIG. 27 is a diagram showing a change in the operation schedule when the operation coordination unit 35 of the operation coordination device 30 according to the fifth embodiment determines to increase the number of trains 10. In the fifth embodiment, when congestion is predicted, the traffic control device 30 increases the number of trains 10 without reducing the number of trains 10 in other time slots, i.e., canceling the trains 10, in order to secure the additional train configurations and crew members. The traffic schedule creation unit 31 of the traffic control device 30 creates a traffic schedule in which several additional trains 10 are reserved in advance and which allows for deadhead operation so that the above-mentioned processing can be performed.

[0058] FIG. 28 is a flowchart showing the processing of the increased service mode in the operation adjustment unit 35 of the operation adjustment device 30 according to the fifth embodiment. The flowchart shown in FIG. 28 shows details of the processing of the increased service mode in step S102 of the flowchart shown in FIG. 17. The operation adjustment unit 35 decides the number of trains 10 to be increased (step S201). The operation adjustment unit 35 refers to the crew shift database 36, and if crew members are secured for the train 10 for which the increased service has been decided (step S601: Yes), it determines whether the train formation is secured (step S602). If the train formation is secured (step S602: Yes), the operation adjustment unit 35 changes the operation schedule (step S203), confirms the changes (step S204), and ends the processing of the increased service mode. If the train configuration is not secured (step S602: No) but the train configuration can be sent forward (step S603: Yes), the operation adjustment unit 35 changes the operation schedule (step S203), confirms the change (step S204), and ends the processing of the increased service mode. The operation adjustment unit 35 refers to the crew shift database 36, and if the crew is not secured for the train 10 for which the increased service has been decided (step S601: No), or if the train configuration cannot be sent forward (step S603: No), determines whether or not there is a train 10 for which the service can be reduced (step S205). If there is a train 10 for which the service can be reduced (step S205: Yes), the operation adjustment unit 35 determines the train 10 to be reduced (step S206). The operation adjustment unit 35 changes the operation schedule (step S203), confirms the change (step S204), and ends the processing of the increased service mode. If there is no train 10 for which the service can be reduced (step S205: No), the operation adjustment unit 35 ends the processing of the service increase mode without increasing the service of the train 10.

[0059] The process of determining which trains 10 to increase in service in step S201 is the same as the process of step S201 in the flowchart shown in Fig. 18, i.e., the process of the flowchart shown in Fig. 19. The process of determining which trains 10 to reduce in step S206 is the same as the process of step S206 in the flowchart shown in Fig. 18, i.e., the process of the flowchart shown in Fig. 20. The operation adjustment unit 35 of the operation adjustment device 30 performs the process of step S205 shown in the flowchart in Fig. 28 when all the trains 10 reserved in advance for increasing the service have been used up.

[0060] In this way, by securing in advance several additional trains 10 and crew members, the operation coordination device 30 can increase the number of trains 10 without reducing the number of trains 10 at other times, i.e., without canceling them.

[0061] Embodiment 6 In the first to fifth embodiments, when the operation of the train 10 is increased, the operation coordination device 30 is assumed to increase the number of trains 10 of the same type as the trains 10 in the preceding and following time slots. In the sixth embodiment, a case will be described in which the operation coordination device 30 changes the type of train 10 to be increased depending on the predicted congestion level.

[0062] In the sixth embodiment, the configuration of the operation adjustment device 30 is the same as that in the first embodiment shown in FIG. 1. In the operation adjustment device 30, the operation adjustment unit 35 may determine to increase the number of trains 10 that stop only at stations with high demand when the future congestion degree of each vehicle of the train 10 predicted by the congestion prediction unit 33 increases significantly only at a certain station, that is, when the demand varies greatly from station to station. FIG. 29 is a diagram showing an example in which the operation adjustment unit 35 of the operation adjustment device 30 according to the sixth embodiment determines the type of train 10 to be increased according to the predicted congestion degree. As shown in FIG. 29, when a large number of people boarding and alighting are predicted at station B and congestion is predicted, the operation adjustment unit 35 determines to increase the number of trains 10 of a type that does not stop at stations A and C, but stops at station B, for example, a rapid train. In this way, the operation adjustment unit 35 can alleviate congestion caused by boarding and alighting of the train 10 at station B.

[0063] In addition, the operation adjustment unit 35 may change the type of the train 10 already in operation when the number of passengers boarding and alighting at station B is predicted to be large and congestion is expected, as described above. FIG. 30 is a diagram showing an example in which the operation adjustment unit 35 of the operation adjustment device 30 according to the sixth embodiment changes the type of the train 10 in operation according to the predicted congestion level. As shown in FIG. 30, when the number of passengers boarding and alighting at station B is predicted to be large and congestion is expected, the operation adjustment unit 35 decides to change the type of the train 10 to a type that does not stop at stations A and C, but stops at station B, for example, a rapid train. In this way, the operation adjustment unit 35 can alleviate congestion at station B due to passengers boarding and alighting the train 10. In addition, the operation schedule creation unit 31 of the operation adjustment device 30 creates a operation schedule that can be selected from multiple types for the operation of one train 10 in advance so that the above-mentioned processing can be performed. In this case, even if a local operation schedule is selected for a certain train 10, a rapid operation schedule cannot be selected for another train 10.

[0064] In this manner, the operation adjustment unit 35 may change the type of the train 10, that is, change the stations at which the train 10 stops, based on the degree of congestion.

[0065] The configurations shown in the above embodiments are merely examples, and may be combined with other known technologies, or the embodiments may be combined with each other. Also, parts of the configurations may be omitted or modified without departing from the spirit of the invention. [Explanation of symbols]

[0066] 10 train, 20, 20a operation management device, 30 operation adjustment device, 31 operation schedule creation unit, 32 operation schedule database, 33 congestion prediction unit, 34 congestion degree database, 35 operation adjustment unit, 36 crew shift database, 37 memory unit, 40 cloud, 41 data collection device.

Claims

1. a congestion prediction unit that predicts a future congestion degree for each vehicle based on a passenger occupancy rate for each vehicle in the train; an operation adjustment unit that determines whether or not to change an operation plan of one or more trains in a train schedule that indicates an operation plan of a plurality of trains including the train, based on a result of comparing the congestion degree predicted by the congestion prediction unit with a specified threshold; A storage unit that stores the train schedule; Equipped with The train schedule includes a first train schedule for a first train, which is not normally operated but is subject to an increase in service, a second train schedule for a second train, which is normally operated but is subject to a reduction in service, and a third train schedule for a third train, which is not subject to an increase or reduction in service. An operation adjustment device characterized by the above.

2. A congestion prediction unit that predicts a future congestion degree for each vehicle based on a passenger occupancy rate for each vehicle constituting a train; an operation adjustment unit that determines whether or not to change an operation plan of one or more trains in a train schedule that indicates an operation plan of a plurality of trains including the train, based on a result of comparing the congestion degree predicted by the congestion prediction unit with a specified threshold; Equipped with The operation coordinating unit changes the stations at which the train stops based on the congestion degree. An operation adjustment device characterized by the above.

3. A storage unit that stores the train schedule; Equipped with The train schedule includes a first train schedule for a first train, which is not normally operated but is subject to an increase in service, a second train schedule for a second train, which is normally operated but is subject to a reduction in service, and a third train schedule for a third train, which is not subject to an increase or reduction in service.

3. The operation adjustment device according to claim 2 .

4. the operation adjustment unit determines to increase the number of services of the first train when the congestion degree is equal to or greater than a first threshold for determining an increase in the number of services of the first train, and determines to reduce the number of services of the second train when the congestion degree is less than a second threshold for determining a decrease in the number of services of the second train.

4. The operation adjustment device according to claim 1 or 3.

5. the operation adjustment unit, when there are a plurality of the first trains, selects the first train that can most easily alleviate congestion by increasing the service, and when there are a plurality of the second trains, selects the second train that can most easily suppress an increase in congestion by reducing the service.

5. The operation adjustment device according to claim 4.

6. When it is necessary to reduce the number of trains of the second train in order to increase the number of trains of the first train, the operation coordination unit selects the first train and the second train based on crew shift information.

6. The operation adjustment device according to claim 5.

7. The operation coordination unit determines that the first train should start operation from an intermediate station when increasing the number of trains of the first train.

7. The operation adjustment device according to claim 5 or 6.

8. When reducing the service of the second train, the operation adjustment unit determines to operate the second train to an intermediate station and then suspend the service.

8. The operation control device according to claim 5, wherein the operation control device is a vehicle operation control device.

9. the operation adjustment unit determines whether to change the operation plan of one or more trains in the train schedule based on a result of comparing the congestion degree of a car with the highest congestion degree among the congestion degrees for the cars of the train predicted by the congestion prediction unit with the threshold value; 9. The operation control device according to claim 1, wherein the operation control device is a vehicle operation control device.

10. the congestion prediction unit predicts the congestion degree based on at least one of a passenger occupancy rate for each vehicle relative to the capacity of each vehicle, the number of passengers in each vehicle, passenger boarding / alighting times for each vehicle, and a delay time for each vehicle relative to a specified passenger boarding / alighting time; 10. The operation control device according to claim 1, wherein the operation control device is a vehicle operation control device.

11. An operation management device comprising the operation adjustment device according to any one of claims 1 to 10.

12. a congestion prediction step of predicting a future congestion degree of each vehicle based on a passenger occupancy rate of each vehicle in the train; an operation adjustment step of determining whether or not to change an operation plan of one or more trains in a train schedule indicating operation plans of a plurality of trains including the train, based on a result of comparing the predicted congestion degree with a specified threshold; Including, The train schedule includes a first train schedule for a first train, which is not normally operated but is subject to an increase in service, a second train schedule for a second train, which is normally operated but is subject to a reduction in service, and a third train schedule for a third train, which is not subject to an increase or reduction in service. A method for adjusting operations.

13. A congestion prediction step of predicting a future congestion degree for each vehicle based on a passenger occupancy rate for each vehicle constituting a train; an operation adjustment step of determining whether or not to change an operation plan of one or more trains in a train schedule indicating operation plans of a plurality of trains including the train, based on a result of comparing the predicted congestion degree with a specified threshold; Including, In the operation adjustment step, the operation adjustment unit changes the stations at which the train stops based on the congestion degree. A method for adjusting operations.

14. The train schedule includes a first train schedule for a first train, which is not normally operated but is subject to an increase in service, a second train schedule for a second train, which is normally operated but is subject to a reduction in service, and a third train schedule for a third train, which is not subject to an increase or reduction in service. The operation adjustment method according to claim 13 .

15. In the operation adjustment step, when the congestion degree is equal to or greater than a first threshold for determining an increase in the service of the first train, the operation adjustment unit determines to increase the service of the first train, and when the congestion degree is less than a second threshold for determining a reduction in the service of the second train, the operation adjustment unit determines to reduce the service of the second train.

15. The operation adjustment method according to claim 12 or 14.

16. In the operation adjustment step, when there are a plurality of the first trains, the operation adjustment unit selects the first train that can most easily alleviate congestion by increasing the service of the first train, and when there are a plurality of the second trains, the operation adjustment unit selects the second train that can most easily suppress an increase in congestion by reducing the service of the second train. The operation coordination method according to claim 15 .

17. In the operation adjustment step, when it is necessary to reduce the number of trains of the second train in order to increase the number of trains of the first train, the operation adjustment unit selects the first train and the second train based on crew shift information. The operation coordination method according to claim 16 .

18. In the operation adjustment step, when the number of trains of the first train is to be increased, the operation adjustment unit determines that the first train is to start operation from an intermediate station.

18. The operation adjustment method according to claim 16 or 17.

19. In the operation adjustment step, when the service of the second train is to be reduced, the operation adjustment unit determines that the second train is to be operated to an intermediate station and then suspended.

19. The operation coordination method according to claim 16, wherein the operation coordination method comprises:

20. In the operation adjustment step, the operation adjustment unit determines whether or not to change the operation plan of one or more trains in the train schedule based on a result of comparing the congestion degree of the car with the highest congestion degree among the congestion degrees for the cars of the train predicted by the congestion prediction unit with the threshold value.

20. The operation coordination method according to claim 12, wherein the operation coordination method comprises:

21. In the congestion prediction step, the congestion prediction unit predicts the congestion degree based on at least one of a passenger occupancy rate relative to the capacity of each vehicle, the number of passengers in each vehicle, passenger boarding and alighting times for each vehicle, and a delay time for each vehicle relative to a specified passenger boarding and alighting time.

21. The operation coordination method according to claim 12, wherein the operation coordination method comprises:

22. a congestion prediction step of predicting a future congestion degree of each vehicle based on a passenger occupancy rate of each vehicle in the train; an operation adjustment step of determining whether or not to change an operation plan of one or more trains in a train schedule indicating operation plans of a plurality of trains including the train, based on a result of comparing the predicted congestion degree with a specified threshold; The computer executes the above. The train schedule includes a first train schedule for a first train, which is not normally operated but is subject to an increase in service, a second train schedule for a second train, which is normally operated but is subject to a reduction in service, and a third train schedule for a third train, which is not subject to an increase or reduction in service. An operation adjustment program characterized by:

23. A congestion prediction step of predicting a future congestion degree for each vehicle constituting a train based on a passenger occupancy rate for each vehicle; an operation adjustment step of determining whether or not to change an operation plan of one or more trains in a train schedule indicating operation plans of a plurality of trains including the train, based on a result of comparing the predicted congestion degree with a specified threshold; The computer executes the above. In the operation adjustment step, the operation adjustment unit changes the stations at which the train stops based on the congestion degree. An operation adjustment program characterized by:

Images