JP2021165958A - Prediction device and prediction method - Google Patents

Abstract

To provide a prediction device for providing appropriate prediction information about supply and demand of alternative transportation means, and to provide a prediction method therefor.SOLUTION: A prediction device according to an embodiment comprises a prediction unit and a provision unit. The prediction unit predicts at least the number of allocatable vehicles as alternative transportation vehicles at an arbitrary time in an arbitrary place, when there is a possibility that an operation plan of public transportation is changed. The provision unit provides a prediction result including the number of allocatable vehicles predicted by the prediction unit, to a device for determining the operation plan.SELECTED DRAWING: Figure 2

Description

The disclosed embodiments relate to predictors and predictors.

Conventionally, a support system for appropriately allocating a taxi based on demand forecast information of a taxi user has been proposed (see, for example, Patent Document 1).

JP-A-2019-091274

However, there is room for further improvement in the prior art in providing appropriate forecast information on the supply and demand of taxis, even when urgent changes may occur in the operation plan of public transportation.

For example, in an emergency such as when a typhoon approaches or an earthquake occurs, the operation plan of public transportation such as railways may be changed. In such a case, for example, if the railway is suspended, people will concentrate on taxis as an alternative means of transportation, but depending on the station where the railway operation is stopped, the number of taxis operating around that station is not sufficient and many. It may lead to a situation where the person is kept waiting for a long time.

It should be noted that such a problem is not limited to taxis, but is a problem common to all vehicles that can be an alternative means of transportation for public transportation.

One aspect of the embodiment is made in view of the above, and an object of the embodiment is to provide a prediction device and a prediction method for providing appropriate prediction information regarding the supply and demand of an alternative transportation vehicle.

The prediction device according to one aspect of the embodiment includes a prediction unit and a providing unit. The forecasting unit predicts the number of alternative transport vehicles that can be dispatched at least at any time at any time when there is a possibility that the operation plan of public transportation will be changed. The providing unit provides a prediction result including the number of vehicles that can be dispatched predicted by the prediction unit to the device that determines the operation plan.

According to one aspect of the embodiment, it is possible to provide a forecasting device and a forecasting method for providing appropriate forecasting information regarding the supply and demand of alternative transportation means.

FIG. 1 is a schematic explanatory view of an example of a prediction method according to an embodiment. FIG. 2 is a block diagram showing a first configuration example of the taxi supply and demand forecasting system according to the embodiment. FIG. 3 is a block diagram showing a second configuration example of the taxi supply and demand forecasting system according to the embodiment. FIG. 4 is a diagram showing an example of station information. FIG. 5 is a diagram showing an example of a prediction request telegram. FIG. 6 is a diagram showing an example of a prediction result telegram. FIG. 7 is a diagram showing an example of a processing sequence of the taxi supply and demand forecasting system according to the embodiment. FIG. 8 is an explanatory diagram of a modified example.

Hereinafter, embodiments of the prediction device and the prediction method disclosed in the present application will be described in detail with reference to the accompanying drawings. The present invention is not limited to the embodiments shown below.

Further, in the following, the public transportation that may cause an urgent change in the operation plan is a railroad, the alternative transportation vehicle of such public transportation is a taxi, and the forecasting device according to the embodiment is a taxi supply / demand forecasting device. The case of 10 will be described as an example.

First, an outline of the prediction method according to the embodiment will be described with reference to FIG. FIG. 1 is a schematic explanatory view of an example of a prediction method according to an embodiment. In FIG. 1, a taxi supply and demand forecasting system 1 to which the forecasting method according to the embodiment is applied will be described as an example.

As shown in FIG. 1, the taxi supply / demand forecasting system 1 according to the embodiment includes a taxi dispatching system 2, a railroad operation system 3, a traffic information providing system 4, a weather information providing system 5, and a taxi supply / demand forecasting device 10. including.

The taxi dispatch system 2 is a system operated by a taxi company or the like, and includes a taxi dispatch management device 20. The railway operation system 3 is a system operated by a railway company or the like, and includes a railway operation management device 30. The traffic information providing system 4 is a system that provides traffic information operated by a public interest corporation, a general business operator, or the like. The meteorological information providing system 5 is a system that provides meteorological information operated by the Japan Meteorological Agency, general businesses, and the like.

The taxi supply / demand forecasting device 10 acquires various information including taxi position information based on a forecast request transmitted from the railway operation management device 30 via a network N such as the Internet or a telephone line network, and at a specific station. It is a device that predicts the number of taxis that can be dispatched at a specific time. Further, the taxi supply and demand forecasting device 10 provides the predicted prediction result to the railway operation management device 30. The forecast results include the number of vehicles that can be dispatched.

The taxi supply and demand forecasting system 1 supports the decision-making of the railway operating system 3 in the event that the railway operating plan may be changed urgently in an emergency such as when a typhoon approaches or an earthquake occurs. It will be useful.

Specifically, as shown in FIG. 1, first, in the railway operation system 3, when there is a possibility that the railway operation plan is changed, the railway operation management device 30 taxi the prediction request via the network N. It is transmitted to the supply and demand forecasting device 10 (step S1).

Such a prediction request includes, for example, one or more candidate stations for suspension of operation when the operation is planned to be stopped, and the stop time of one or more trains that stop at the candidate stations. A specific example of such a prediction request will be described later with reference to FIG.

The taxi supply and demand forecasting device 10 that has received the forecast request acquires various information in response to the forecast request (step S2). The various information includes, for example, taxi position information transmitted from the taxi dispatch system 2 via the network N (step S2-1). Such taxi location information includes at least one of current location information and past location information.

Further, the various information in step S2 includes, for example, traffic information transmitted from the traffic information providing system 4 via the network N, indicating a traffic jam situation or the like (step S2-2). Such traffic information includes at least one of current traffic information and past traffic information.

Further, the various information in step S2 includes, for example, weather information transmitted from the weather information providing system 5 via the network N (step S2-3). Such weather information includes at least one of current weather information and future weather information.

Then, the taxi supply and demand forecasting device 10 predicts the number of taxis that can be dispatched at a specific time at a specific station based on the various acquired information (step S3). Then, the taxi supply and demand forecasting device 10 transmits the forecast result regarding the taxi dispatch including the predicted number of taxi dispatchable vehicles to the railway operation management device 30 (step S4).

Such a prediction result includes a vehicle dispatchable point, an average waiting time, a queue elimination time, and the like at each candidate station. Specific examples of the prediction results will be described later with reference to FIG.

Then, the railway operation management device 30 makes a decision regarding the change of the railway operation plan based on the prediction result acquired from the taxi supply and demand forecasting device 10. For example, the railway operation management device 30 stops the train at the candidate station having the shortest waiting time for a taxi based on the prediction result. The content of the decision is notified to the taxi supply and demand forecasting device 10 and the taxi dispatch management device 20, and for example, the taxi dispatch management device 20 dispatches a taxi according to the content of the notification.

As described above, in the prediction method according to the embodiment, the taxi supply / demand forecasting device 10 predicts the number of taxis that can be dispatched at any time at any candidate station when there is a possibility that the operation plan of the railway may be changed. Then, it was decided to provide the predicted prediction result to the railway operation management device 30 that determines the operation plan.

Therefore, according to the forecasting method according to the embodiment, it is possible to provide appropriate forecasting information regarding the supply and demand of taxis.

Hereinafter, a configuration example of the taxi supply and demand forecasting system 1 to which the forecasting method according to the above-described embodiment is applied will be described more specifically.

FIG. 2 is a block diagram showing a first configuration example of the taxi supply and demand forecasting system 1 according to the embodiment. Further, FIG. 3 is a block diagram showing a second configuration example of the taxi supply and demand forecasting system 1 according to the embodiment. Note that FIGS. 2 and 3 show only the components necessary for explaining the features of the present embodiment, and the description of general components is omitted.

In other words, each component shown in FIGS. 2 and 3 is a functional concept and does not necessarily have to be physically configured as shown. For example, the specific form of distribution / integration of each block is not limited to the one shown in the figure, and all or part of it may be functionally or physically distributed in arbitrary units according to various loads and usage conditions. It can be integrated and configured.

Further, in the description using FIGS. 2 and 3, the description of the components already described may be simplified or omitted.

As described above, as shown in FIG. 2, the taxi supply / demand forecasting system 1 according to the embodiment includes a taxi dispatch system 2, a railway operation system 3, a traffic information providing system 4, a weather information providing system 5, and a taxi. Includes the supply and demand forecasting device 10.

First, the taxi supply and demand forecasting device 10 will be described. The taxi supply and demand forecasting device 10 includes a communication unit 11, a storage unit 12, and a control unit 13.

The communication unit 11 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 11 is connected to the network N by wire or wirelessly, and transmits / receives information to / from the systems 2, 3, 4, and 5 via the network N.

The communication unit 11 can directly send and receive information (current position information, etc.) to and from each taxi included in the taxi dispatch system 2 via a mobile phone line network or the like.

The storage unit 12 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory (Flash Memory), or a storage device such as a hard disk or an optical disk. The history information 12b is stored.

Station information 12a is information about each railway station. Here, an example of station information 12a will be described with reference to FIG. FIG. 4 is a diagram showing an example of station information 12a.

As shown in FIG. 4, the station information 12a includes, for example, a "station name" item, a "dispatchable point" item, an "average traveling time" item, a "connecting transportation" item, and a "taxi occupancy rate" item. including.

The "station name" item stores an identifier of each record in the station information 12a, such as a station name. The "Vehicle dispatchable point" item is an item in which the taxi dispatchable point at each station is stored, and includes the "Average travel time" item. The "average travel time" item stores the average travel time from the station platform to each vehicle dispatchable point. In addition, "BT" in the figure is a bus terminal, and for example, if the bus is not in operation, such a bus terminal can also be a taxi dispatchable point. When the vehicle dispatchable point is BT, the "average travel time" item stores the average travel time from the boarding / alighting place of the bus terminal to each vehicle dispatchable point.

"Connected transportation" stores the transportation connected to each station. The "taxi occupancy rate" item stores the taxi occupancy rate at each station. When the taxi supply and demand forecasting device 10 acquires a forecast request from the railway operation management device 30, the forecasting unit 13b, which will be described later, refers to the station information 12a regarding the information about each candidate station included in the forecast request.

Returning to the description of FIG. The history information 12b is information related to various information in the past prediction process and the history of the prediction result. The prediction unit 13b, which will be described later, refers to the history information 12b when executing the prediction process.

The control unit 13 is a controller, and for example, various programs stored in a storage device inside the taxi supply / demand forecasting device 10 work on the RAM by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. It is realized by executing as an area. Further, the control unit 13 can be realized by, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

The control unit 13 has an acquisition unit 13a, a prediction unit 13b, and a provision unit 13c, and realizes or executes the functions and operations of information processing described below.

The acquisition unit 13a acquires the prediction request transmitted from the railway operation management device 30 via the communication unit 11. Here, an example of the prediction request telegram will be described with reference to FIG. FIG. 5 is a diagram showing an example of a prediction request telegram.

As shown in FIG. 5, the forecast request telegram transmitted from the railway operation management device 30 includes, for example, a "request date and time" item, a "candidate station" item, and a "train information" item. The request date and time is stored in the "request date and time" item. In the "candidate station" item, for example, the identifier of each candidate station whose operation is being considered to be stopped is stored.

The "train information" item is, for example, an item in which information about the train of each train whose operation is being considered to be stopped is stored, for example, a "number" item, a "type" item, a "stop time" item, and ". Includes "current number of passengers" item and "past disembarkation rate" item. The "train information" item may have a "current occupancy rate" item instead of the "current number of passengers" item. Further, the "train information" item may have a "past disembarkation rate" item instead of the "past disembarkation rate" item.

The "number" item stores the identification number of each train. The "type" item stores the type of each train such as "express", "rapid", and "normal". Although not shown, "Shinkansen" and the like may be included. The "stop time" item stores the scheduled stop time at each candidate station of each train. In the "current number of passengers" item, the predicted value of the current number of passengers of each train is stored. Such a predicted value can be calculated based on, for example, the usage status of an IC (Integrated Circuit) card ticket at the starting station and the intermediate station. The "past disembarkation rate" stores the past disembarkation rate at each candidate station of each train.

Returning to the description of FIG. In addition, the acquisition unit 13a acquires various information transmitted from the taxi dispatch management device 20, the traffic information providing system 4, and the weather information providing system 5 in response to the prediction request.

The acquisition unit 13a acquires taxi position information from, for example, the taxi dispatch management device 20. At this time, the acquisition unit 13a acquires the past position information and the current position information of each taxi from, for example, the taxi dispatch management device 20. The past position information can be used for tendency analysis or the like by comparing with the history information 12b. Further, the acquisition unit 13a acquires the current position information directly from, for example, each taxi.

In addition, the acquisition unit 13a acquires traffic information from the traffic information providing system 4, including the traffic information around each candidate station included in the prediction request and the congestion status of the arrival route to each candidate station. In addition, the acquisition unit 13a acquires the current weather information and future weather information around each candidate station included in the prediction request from the weather information providing system 5.

The prediction unit 13b predicts the number of vehicles that can be dispatched at a specific time at each vehicle dispatchable point of each candidate station based on various information, station information 12a, and history information 12b acquired by the acquisition unit 13a. The "specific time" referred to here may be, for example, the stop time of each train, or the average travel time of the above-mentioned station information 12a to each dispatchable point is added to the stop time of each train. It may be the time.

Further, the prediction unit 13b predicts the number of vehicles that can be dispatched based on the position information of the taxi among the various information acquired by the acquisition unit 13a. The taxi location information is at least one of the current and past minutes. The prediction unit 13b can predict the number of vehicles that can be dispatched based only on the past position information by the above-mentioned tendency analysis or the like.

Further, the prediction unit 13b predicts whether or not the vehicle can be dispatched at each normal vehicle dispatchable point based on the traffic information and the weather information among the various information acquired by the acquisition unit 13a. Then, the prediction unit 13b notifies the providing unit 13c of the predicted prediction result.

The providing unit 13c generates a prediction result telegram based on the prediction result notified by the prediction unit 13b, and transmits it to the railway operation management device 30 via the communication unit 11. Here, an example of the prediction result telegram will be described with reference to FIG. FIG. 6 is a diagram showing an example of a prediction result telegram.

As shown in FIG. 6, the prediction result telegram transmitted to the railway operation management device 30 includes, for example, a "response date and time" item, a "candidate station" item, a "train information" item, and a "vehicle allocation prediction information" item. including. The response date and time is stored in the "response date and time" item. The "candidate station" item corresponds to the same item in the forecast request telegram described above. The "train information" item corresponds to the "number" item, "type" item, and "stop time" item of the forecast request telegram described above.

The "vehicle allocation prediction information" item is an item in which the prediction result predicted by the prediction unit 13b is stored. For example, the "possible point" item, the "possible number of vehicles" item, the "average waiting time" item, and the "matrix" item. Includes "Resolution time" item.

The "possible point" item corresponds to the "possible point" item of the station information 12a described above. In the "possible number" item, the number of taxis that can be dispatched at each dispatchable point of each candidate station predicted by the prediction unit 13b is stored. The "average waiting time" item stores the average waiting time when using a taxi, which is predicted by the prediction unit 13b. The "matrix clearing time" item stores the taxi queue clearing time predicted by the prediction unit 13b.

For the average waiting time and the queue elimination time, for example, the number of passengers getting off at each candidate station is calculated from the "current number of passengers" and "past disembarkation rate" included in the above-mentioned forecast request, and the number of disembarking people and the above-mentioned number of getting off are described above. It is possible to make a prediction based on the taxi occupancy rate of the station information 12a and the predicted number of trains that can be dispatched.

In the case of the example of FIG. 6, for "A station", each train specified in the forecast request can be dispatched at the "north exit" and "south exit", and the number of trains that can be dispatched, the average waiting time, and so on. It can be seen that the queue cancellation time and the like are notified. In addition, it can be seen that taxis cannot be dispatched to "BT" because the bus is in operation.

Further, regarding "B station", for example, based on traffic information and weather information, it can be seen that there is no vehicle dispatchable point because it is "difficult to dispatch due to flooding in front of the station". When the prediction result of the example of FIG. 6 is received, the railway operation management device 30 should exclude the B station from the candidate stations, for example, and at least 40 minutes when each train is stopped for the A station. You can see that the taxi queue can be eliminated. That is, the railway operation management device 30 can make a decision regarding the change of the railway operation plan based on the prediction result.

Next, a configuration example of the taxi dispatch management device 20 will be described. As shown in FIG. 3, the taxi dispatch management device 20 includes a communication unit 21, a storage unit 22, and a control unit 23.

Like the communication unit 11, the communication unit 21 is realized by, for example, a NIC or the like. The communication unit 21 is connected to the network N by wire or wirelessly, and communicates with the taxi supply and demand forecasting device 10 and the railway operation management device 30 via the network N.

The communication unit 21 can also send and receive information by voice call to and from each taxi, for example, via the taxi radio.

Similar to the storage unit 12, the storage unit 22 is realized by, for example, a semiconductor memory element such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk. In the example of FIG. 3, the storage unit 22 stores the history information 22a.

The history information 22a is information related to the history such as the position information of the past taxi and the dispatch information of the past taxi.

The control unit 23 is a controller like the control unit 13, and for example, various programs stored in the storage device inside the taxi dispatch management device 20 are executed by the CPU, MPU, or the like using the RAM as a work area. Is realized by. Further, the control unit 23 can be realized by, for example, an integrated circuit such as an ASIC or FPGA.

The control unit 23 has an acquisition unit 23a, a provision unit 23b, and an instruction unit 23c, and realizes or executes an information processing function or operation described below.

The acquisition unit 23a acquires a position information request based on the prediction request from the taxi supply and demand forecasting device 10. In addition, the acquisition unit 23a acquires the prediction result predicted by the taxi supply and demand forecasting device 10 from the taxi supply and demand forecasting device 10. In addition, the acquisition unit 23a acquires the decision result regarding the change of the railway operation plan from the railway operation management device 30.

The providing unit 23b transmits the current position information and the past position information of each taxi to the taxi supply and demand forecasting device 10 via the communication unit 21 based on the position information request from the taxi supply and demand forecasting device 10.

The instruction unit 23c prepares a taxi dispatch instruction based on the prediction result of the taxi supply and demand forecasting device 10. In addition, the instruction unit 23c instructs the taxi to be dispatched based on the determination result from the railway operation management device 30.

Next, a configuration example of the railway operation management device 30 will be described. As shown in FIG. 3, the railway operation management device 30 includes a communication unit 31, a storage unit 32, and a control unit 33.

The communication unit 31 is realized by, for example, a NIC or the like, similarly to the communication units 11 and 21. The communication unit 31 is connected to the network N by wire or wirelessly, and communicates with the taxi supply and demand forecasting device 10 and the taxi dispatch management device 20 via the network N.

Similar to the storage units 12 and 22, the storage unit 32 is realized by, for example, a semiconductor memory element such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk. In the example of FIG. 3, the storage unit 32 stores the alarm information 32a. do.

The warning information 32a is information related to a disaster warning issued, for example, regarding weather, an earthquake, or the like. The alarm information 32a is updated in real time.

The control unit 33 is a controller like the control units 13 and 23. For example, various programs stored in the storage device inside the railway operation management device 30 are executed by the CPU, MPU, or the like using the RAM as a work area. It is realized by. Further, the control unit 33 can be realized by, for example, an integrated circuit such as an ASIC or FPGA.

The control unit 33 has an acquisition unit 33a, a request unit 33b, and a determination unit 33c, and realizes or executes an information processing function or operation described below.

The acquisition unit 33a acquires information on a disaster warning in real time from a weather information providing system 5 or the like (not shown) and stores it in the warning information 32a. Further, the acquisition unit 33a can also acquire traffic information in real time from the traffic information providing system 4 (not shown). Further, when the acquisition unit 33a transmits the taxi to the taxi supply and demand forecasting device 10, the acquisition unit 33a acquires the prediction result in response to the forecast request from the taxi supply and demand forecasting device 10.

The requesting unit 33b generates the above-mentioned forecast request telegram based on the warning information 32a, the traffic information, and the like, and transmits the forecast request telegram to the taxi supply and demand forecasting device 10 via the communication unit 31.

The decision unit 33c makes a decision regarding the change of the railway operation plan based on the prediction result of the taxi supply and demand forecasting device 10 in response to the forecast request transmitted by the requesting unit 33b. In addition, the decision unit 33c changes the operation plan of the railway according to the decision contents.

Further, the determination unit 33c transmits the determination result to the taxi supply and demand forecasting device 10 and the taxi dispatch management device 20 via the communication unit 31.

Next, the processing procedure executed by the taxi supply and demand forecasting system 1 according to the embodiment will be described with reference to FIG. 7. FIG. 7 is a diagram showing an example of a processing sequence executed by the taxi supply and demand forecasting system 1 according to the embodiment.

As shown in FIG. 7, the railway operation management device 30 first transmits a forecast request to the taxi supply and demand forecasting device 10 (step S11). Then, the taxi supply and demand forecasting device 10 receives this and transmits a position information request to the taxi dispatch system 2 (step S12).

The taxi dispatch system 2 receives the position information request and responds the taxi position information to the taxi supply and demand forecasting device 10 (step S13).

Further, the traffic information providing system 4 transmits traffic information to the taxi supply and demand forecasting device 10 at any time (step S14). Similarly, the weather information providing system 5 transmits the weather information to the taxi supply and demand forecasting device 10 at any time (step S15).

Similar to steps S14 and S15, the position information in step S13 may be transmitted to the taxi supply and demand forecasting device 10 at any time without being triggered by the position information request in step S12.

Then, the taxi supply / demand forecasting device 10 predicts the number of vehicles that can be dispatched at a specific time at each candidate station based on various information acquired from each of the systems 2, 4 and 5 (step S16), and the forecast result is the railway operation management device 30. (Step S17). Further, the taxi supply and demand forecasting device 10 transmits the forecast result to the taxi dispatch system 2 (step S18).

The railway operation management device 30 determines, for example, an operation stop station based on the acquired prediction result (step S19). Further, the taxi dispatch system 2 prepares, for example, a vehicle dispatch instruction based on the acquired prediction result (step S20).

Further, the railway operation management device 30 transmits the determined decision result to the taxi supply and demand forecasting device 10 and the taxi dispatch system 2, respectively (steps S21 and S22). The taxi dispatch system 2 gives a vehicle dispatch instruction based on the determination result from the railway operation management device 30 (step S23).

Here, FIG. 8 is an explanatory diagram of a modified example. So far, the railway has been taken as an example of public transportation, but as shown in FIG. 8, the above-described embodiment may be applied to the shuttle bus B connecting the airport and the railway station or the like.

In such a case, the number of passengers and the rate of getting off at the station may be obtained from the bus operation management system (not shown), and the number of passengers getting off at the station may be predicted.

As described above, the taxi supply and demand forecasting device 10 (corresponding to an example of the “prediction device”) according to the embodiment includes a forecasting unit 13b and a providing unit 13c. The forecasting unit 13b uses a taxi (an example of an "alternative transport vehicle") at least at any time at any time when there is a possibility that the operation plan of a railway (corresponding to an example of "public transportation") may change. Predict the number of vehicles that can be dispatched. The providing unit 13c provides the railway operation management device 30 (corresponding to an example of the “device for determining the operation plan”) with a prediction result including the number of vehicles that can be dispatched predicted by the prediction unit 13b.

Therefore, according to the taxi supply and demand forecasting device 10 according to the embodiment, it is possible to provide appropriate forecast information regarding the supply and demand of taxi.

In addition, the prediction unit 13b predicts the number of vehicles that can be dispatched based on at least one of the current position information and the past position information of the taxi.

Therefore, according to the taxi supply / demand forecasting device 10 according to the embodiment, it is possible to accurately predict the number of vehicles that can be dispatched based on the current position information of the taxi, the tendency analysis of the past position information, and the like.

In addition, the prediction unit 13b predicts the taxi dispatchable points and the dispatchable number of taxi dispatchable points at a specific time at a specific candidate station designated by the railway operation management device 30.

Therefore, according to the taxi supply and demand forecasting device 10 according to the embodiment, various patterns can be simulated for the change contents of the operation plan determined by the railway operation management device 30, and the number of vehicles that can be dispatched is set for each vehicle dispatchable point of the candidate station. It becomes possible to grasp in detail.

In addition, the prediction unit 13b adds the average travel time from the platform of the specific candidate station or the boarding / alighting place of the bus terminal to the dispatchable point with respect to the stop time of the specific train or bus at the specific candidate station or bus terminal. Predict the number of vehicles that can be dispatched at each vehicle dispatchable point with the specified time as the above-mentioned specific time.

Therefore, according to the taxi supply and demand forecasting device 10 according to the embodiment, it is possible to provide highly accurate forecast information in consideration of the average traveling time to the vehicle dispatchable point for each candidate station or bus terminal.

In addition, the prediction unit 13b predicts whether or not the vehicle can be dispatched and the number of vehicles that can be dispatched at the vehicle dispatchable point based on at least one of the traffic information about the vicinity of the specific candidate station or the bus terminal and the weather information.

Therefore, according to the taxi supply and demand forecasting device 10 according to the embodiment, it is possible to provide detailed and highly accurate forecast information for each candidate station or bus terminal, taking into account the surrounding traffic conditions and weather conditions.

Further, the prediction result includes at least one of the average waiting time of the taxi and the elimination time of the queue, and the prediction unit 13b describes the above based on the number of passengers and the disembarkation rate of the train notified from the railway operation management device 30. Predict the average waiting time and the above resolution time.

Therefore, according to the taxi supply and demand forecasting device 10 according to the embodiment, it is possible to provide detailed and highly accurate forecast information for each candidate station or bus terminal, taking into account the waiting time and the queue elimination time. In other words, when the railway operation management device 30 makes a decision to change the operation plan, it is possible to provide forecast information having high utility value.

In the above-described embodiment, the case where the alternative transportation vehicle is a taxi is taken as an example, but the present invention is not limited to this, and information on the allocation of the cabin module having accommodation equipment may be predicted. .. This is useful for those who wish to stay after the last train, for example, when the waiting time for a taxi is likely to be longer than one hour. In such a case, the prediction device according to the embodiment functions as an accommodation guidance device.

In the sense that it functions as an accommodation guidance device, when the waiting time is likely to be long, the vacancy rate of accommodation facilities near the candidate station is predicted, and based on the prediction result, the accommodation facility guidance information May be provided.

Further, in the above-described embodiment, the case where the alternative transportation vehicle is a taxi has been given as an example, but the present invention is not limited to this. For example, even when a typhoon is approaching, it is possible that there is almost no effect on the operation of the subway. In this case, the subway may be used as an alternative transportation vehicle. When such a subway is used as an alternative transportation vehicle, public transportation that may cause an urgent change in the operation plan is, for example, a railroad that runs on land.

Further, at least one of the taxi supply and demand forecasting device 10, the taxi dispatch management device 20, and the railway operation management device 30 may be configured as a cloud server that provides a cloud service.

Further effects and variations can be easily derived by those skilled in the art. For this reason, the broader aspects of the invention are not limited to the particular details and representative embodiments expressed and described above. Therefore, various modifications can be made without departing from the spirit or scope of the general concept of the invention as defined by the appended claims and their equivalents.

1 Taxi supply and demand forecasting system 2 Taxi dispatching system 3 Railway operation system 4 Traffic information providing system 5 Meteorological information providing system 10 Taxi supply and demand forecasting device 13a Acquisition unit 13b Prediction unit 13c Providing unit 20 Taxi dispatch management device 23a Acquisition unit 23b Providing unit 23c Instruction Department 30 Railway operation management device 33a Acquisition department 33b Request department 33c Decision department

Claims (8)

A forecasting unit that predicts the number of alternative transport vehicles that can be dispatched at least at any time at any time when there is a possibility that the operation plan of public transportation will change.
A prediction device comprising a providing unit that provides a prediction result including a number of vehicles that can be dispatched predicted by the prediction unit for the device that determines the operation plan. The public transport is a railroad or a bus and the alternative transport vehicle is a taxi.
The prediction unit
The prediction device according to claim 1, wherein the number of vehicles that can be dispatched is predicted based on at least one of the current position information and the past position information of the taxi. The prediction unit
The predictive device according to claim 2, wherein the taxi can be dispatched at a specific time at a specific candidate station designated by the device, and the number of taxi can be dispatched for each dispatchable point. The prediction unit
The specific time obtained by adding the average travel time from the platform of the specific candidate station or the boarding / alighting place of the bus terminal to the dispatchable point to the stop time of the specific train or bus at the specific candidate station or bus terminal. The prediction device according to claim 3, further comprising predicting the number of vehicles that can be dispatched for each vehicle dispatchable point set at the time of. The prediction unit
3. The third aspect of the present invention is to predict whether or not the vehicle can be dispatched at the vehicle dispatchable point and the number of vehicles that can be dispatched based on at least one of the traffic information about the vicinity of the specific candidate station or the bus terminal and the weather information. Or the prediction device according to 4. The prediction result includes at least one of the average waiting time of the taxi and the elimination time of the queue.
The prediction unit
The prediction device according to any one of claims 2 to 5, wherein the average waiting time and the cancellation time are predicted based on the number of passengers and the disembarkation rate of the train notified from the device. The prediction device according to claim 1, wherein the alternative transport vehicle is a cabin module having accommodation-capable equipment. A forecasting process that predicts the number of alternative transport vehicles that can be dispatched at least at any time at any time when there is a possibility that the operation plan of public transportation will change.
A prediction method characterized in that the device for determining an operation plan includes a provision process for providing a prediction result including the number of vehicles that can be dispatched predicted in the prediction process.

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