Vehicle allocation management device and vehicle allocation management method

Abstract

To provide a travel route matched with user's taste in consideration of variations of an estimated required time to a destination.SOLUTION: The present invention relates to a vehicle allocation management device for managing vehicle allocation of a vehicle based on a vehicle allocation request. The device comprises a vehicle allocation plan preparation part for preparing a vehicle allocation plan of the vehicle based on a travel route in response to the vehicle allocation request of a user. The vehicle allocation plan preparation part stores travel record information about the allocated vehicle, extracts the vehicle while extracting travel route candidates based on the vehicle allocation request, calculates an effectively estimated required time based on a variation threshold value with respect to a variation degree of a required time for each of the travel route candidates, that is calculated based on the travel record information, determines a variation-allowable degree of the user with respect to the variation degree of a mean estimated required time to a destination indicated by the vehicle allocation request, and determines the travel route from among the travel route candidates, based on the variation-allowable degree and the effectively estimated required time.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to a vehicle allocation management device and a vehicle allocation management method, and more particularly to a vehicle allocation management device and a vehicle allocation management method for appropriately selecting a driving route of a vehicle.

Background Art

[0002] Fleet management is known as a method of managing vehicle allocation so as to improve the convenience of users while increasing the operating rate of vehicles. For example, in response to a user's vehicle allocation request, several driving routes of available vehicles are searched, and a driving route that can efficiently reach the destination is determined from among them.

[0003] For example, Patent Document 1 below discloses a vehicle sharing method and a vehicle sharing system for a shared vehicle capable of making a real-time vehicle sharing request.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, the vehicle allocation system disclosed in Patent Document 1 above does not consider any variation in the estimated required time to the user's destination during vehicle operation. In addition, some users desire that, even if it takes a little longer to reach the destination, the estimated required time presented in the proposed vehicle allocation plan be adhered to as much as possible. Therefore, for such users, when a vehicle is operated on a driving route with a short estimated required time but a large variation in the actual required time, there is a risk of impairing the reliability of the vehicle allocation service due to the uncertainty of the estimated arrival time at the destination.

[0006] Therefore, an object of the present invention is to provide a vehicle dispatching management apparatus and a vehicle dispatching management method that present a driving route suitable for a user's preference in consideration of the degree of variation in the predicted travel time to a destination.

Means for Solving the Problems

[0007] The present invention for solving the above problems is configured to include the following invention-specific matters or technical features.

[0008] According to one aspect of the present invention, there is provided a vehicle dispatching management apparatus that manages the dispatching of vehicles based on a vehicle dispatching request. The vehicle dispatching management apparatus includes a travel performance information database that stores travel performance information of the dispatched vehicles, and a vehicle dispatching plan creation unit that creates a vehicle dispatching plan based on a travel route in response to the vehicle dispatching request for each user. The vehicle dispatching plan creation unit includes a travel route candidate extraction unit that extracts travel route candidates based on the vehicle dispatching request, a candidate vehicle extraction unit that extracts the vehicles based on the vehicle dispatching request, an effective predicted travel time calculation unit that determines a variation threshold for the degree of variation in the travel time for each travel route candidate calculated based on the travel performance information, and calculates an effective predicted travel time based on the variation threshold, a variation tolerance determination unit that determines the user's variation tolerance for the degree of variation in the average predicted travel time to the destination indicated by the vehicle dispatching request, a travel route determination unit that determines the travel route from among the travel route candidates based on the variation tolerance and the effective predicted travel time, and a vehicle dispatching instruction unit that gives a vehicle dispatching instruction to the vehicle based on the vehicle dispatching plan.

[0009] The present invention also exists as a vehicle dispatching management method by a vehicle dispatching management apparatus that manages the dispatching of vehicles in response to a vehicle dispatching request, a computer program for executing the method, and a recording medium that non-temporarily records the program.

[0010] In the present disclosure, the term "system" refers to a collection of a plurality of devices (or functional modules that realize specific functions) logically, and it does not matter whether each device or functional module is in a single housing.

Advantages of the Invention

[0011] According to the present invention, it becomes possible to present a driving route that suits the user's preference in consideration of the degree of variation in the predicted required time to the destination.

[0012] Other technical features, objects, operational effects, and advantages of the present invention will be clarified by the following embodiments described with reference to the attached drawings. The effects described in this specification are merely examples and are not limiting, and there may be other effects.

Brief Description of the Drawings

[0013]

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Embodiments for Carrying Out the Invention

[0014] Hereinafter, embodiments of the present invention will be described with reference to the drawings. However, the embodiments described below are merely examples, and there is no intention to exclude various modifications and applications of technologies not explicitly described below. The present invention can be implemented with various modifications (for example, combining each embodiment) without departing from its gist. Also, in the following description of the drawings, the same or similar parts are denoted by the same or similar reference numerals. The drawings are schematic and do not necessarily match actual dimensions, ratios, etc. There may be parts where the dimensional relationships and ratios are different between the drawings.

[0015] FIG. 1 is a diagram for explaining an example of a vehicle allocation management system according to an embodiment of the present invention. As shown in the figure, the vehicle allocation management system 1 includes a vehicle allocation management device 10, a terminal device 20, and a vehicle V, and these are connected to be mutually communicable via a communication network N. Further, the vehicle allocation management system 1 may be connected to a road traffic information management system 30 that provides various traffic information in real time via the communication network N.

[0016] The vehicle dispatching management system 1 of the present disclosure provides a vehicle dispatching service using a plurality of vehicles V for a certain area, for example. The vehicle dispatching service may be either an "on-demand system" or a "reservation system". The "on-demand vehicle dispatching service" is a service that immediately responds to a vehicle dispatching request from a user and assigns (dispatches) a predetermined vehicle to the user. That is, in the on-demand vehicle dispatching service, there is no vehicle dispatching reservation time specified by the user. Also, "immediately respond" means not only dispatching a vehicle without delay in response to a vehicle dispatching request from a user, but also a concept including a certain range of time that a user can normally tolerate. In contrast, the "reservation-based vehicle dispatching service" is a service that dispatches a vehicle at the vehicle dispatching reservation time or within the time frame specified by the user. The vehicle V may be either a manned vehicle or an unmanned vehicle.

[0017] The vehicle dispatching management device 10 is a computing device that comprehensively manages the vehicle dispatching service by a plurality of vehicles V in the target area of the vehicle dispatching service. The target area may be divided into several areas (sub-areas). The vehicle dispatching management device 10 implements, for example, a vehicle dispatching management server program, and realizes the vehicle dispatching service by executing the vehicle dispatching management server program under the control of a processor.

[0018] The vehicle dispatching management device 10 includes various databases 12 that store and manage the data necessary to realize such a vehicle dispatching service. The database 12 may include, for example, a user information database 12a, a road map information database 12b, a vehicle information database 12c, and a vehicle dispatching plan database 12d (see FIG. 2). The database 12 may be configured as a part of the vehicle dispatching management device 10, or all or part of it may be configured separately from the vehicle dispatching management device 10.

[0019] Generally speaking, the vehicle allocation management device 10 receives vehicle allocation requests from users who wish to be allocated a vehicle for movement by vehicle V or users who wish to have goods delivered, and creates a vehicle allocation plan for candidate vehicles V selected from among a plurality of vehicles V based on the vehicle allocation requests. The vehicle allocation management device 10 determines the vehicle allocation plan for the optimal vehicle V from among the created vehicle allocation plans, and issues a vehicle allocation instruction according to the determined vehicle allocation plan to the vehicle V. The determination of the vehicle allocation plan is made, for example, in response to the user's consent.

[0020] The vehicle allocation plan includes a driving route defined from the location where the vehicle V waits (the waiting location serving as the starting point), via several points (boarding and alighting locations (departure and destination)) on the way where the user boards and alights, to the waiting location serving as the end point (not necessarily the same as the first waiting location), and the average value of the estimated required time to each point (hereinafter referred to as "average estimated required time"). If the vehicle V is waiting, the vehicle allocation plan is newly created based on a new vehicle allocation request. On the other hand, if the vehicle V is already carrying a user and in operation, it can be updated based on a new vehicle allocation request. For a vehicle V carrying a user, it may share a ride based on a subsequent user's vehicle allocation request. In the present disclosure, as will be described later, the vehicle allocation management device 10 selects a driving route that conforms to the user's tolerance of variation from among candidates for driving routes with different degrees of variation in the estimated required time (estimated arrival time at the destination) for the vehicle V to reach the destination, and creates a vehicle allocation plan based on this.

[0021] Vehicle V is a vehicle registered in a vehicle information database that is provided for user use. The vehicle type of vehicle V (for example, sedan, minivan, SUV, etc.) is not limited. Vehicle V may be an electric vehicle (EV) powered by an in-vehicle battery. Also, vehicle V may be a fully self-driving autonomous vehicle (driverless vehicle), regardless of the level of automation. Vehicle V is equipped with a control device CTL that controls vehicle V itself or its on-board devices (for example, a navigation device) according to an instruction from the vehicle allocation management device 10 (see Figure 2). The control device CTL of vehicle V acquires, for example, the current position information of vehicle V via a GPS system and transmits this to the vehicle allocation management device 10. Also, the control device CTL receives a vehicle allocation instruction from the vehicle allocation management device 10 and controls the operation of various devices or apparatuses of vehicle V.

[0022] The terminal device 20 is, for example, a computing device for a user who wishes to board to make a vehicle allocation request by operating a user interface. The terminal device 20 is, for example, a smartphone, a tablet computer, a notebook personal computer, a desktop computer, etc., but is not limited thereto. The terminal device 20 implements, for example, a vehicle allocation client program (so-called vehicle allocation app). The terminal device 20 enables a user to use the vehicle allocation service of the vehicle allocation management device 10 by executing the vehicle allocation app under the control of a processor. For example, the user makes a vehicle allocation request from a vehicle allocation request screen (not shown) on the user interface of the terminal device 20, and can make a reservation for boarding vehicle V or a reservation for luggage delivery by accepting the vehicle allocation plan created by the vehicle allocation management device 10 in response thereto. The user may input his / her tolerance for the variation in the average estimated required time at the time of making a vehicle allocation request. Alternatively, the user may input the tolerance in advance during user registration when using the vehicle allocation app.

[0023] The road traffic information management system 30 is an information and communication system that provides road traffic information in real time. For example, the road traffic information management system 30 collects road traffic data from vehicle sensors and cameras installed on roads, and also collects driving data from the control device CTL installed in the vehicle V, and manages road traffic information obtained by integrally processing and editing these data. The edited road traffic information may include, for example, information on traffic stops and detour routes, and the time required between points via a specific route. The road traffic information management system 30 appropriately provides road traffic information to the vehicle allocation management device 10 and the vehicle V.

[0024] FIG. 2 is a block diagram showing an example of a functional configuration model of a vehicle allocation management device according to an embodiment of the present invention. As shown in the figure, the vehicle allocation management device 10 is configured as a functional configuration model including functional configuration elements such as a front-end processing unit 110, a vehicle allocation plan creation unit 120, and a vehicle communication unit 130, for example. Further, as described above, the vehicle allocation management device 10 includes various databases 12. Such a functional configuration model is realized by the vehicle allocation management device 10 executing a vehicle allocation management server program under the control of a processor and cooperating with various hardware resources. The functional configuration model shown here is an example, and all or part of the functions in a certain functional configuration element may be realized by other functional configuration elements. In the figure, for convenience of explanation, the user's terminal device 20 and the control device CTL installed in the vehicle V are also shown.

[0025] The user information database 12a stores information about users (hereinafter referred to as "user information") who use the vehicle allocation service. The user information includes, for example, a user ID and password, personal attribute information (gender, age, presence or absence of children, etc.), and a tolerance for variation. All or part of such user information is registered in the user information database 12a under the control of the vehicle allocation management device 10 by the user inputting predetermined information, for example, at the first startup of the vehicle allocation application.

[0026] The tolerance of variation is a value indicating how much the actual travel time can deviate from the predicted travel time to the destination that the user can tolerate. The tolerance of variation is indicated, for example, on a scale of 0 to 5. For example, a user with a large tolerance of variation can tolerate some delay from the average predicted travel time to the destination, while a user with a small tolerance of variation hopes to strictly adhere to the average predicted travel time to the destination as much as possible. Also, the tolerance of variation may be calculated from the ratio to the average predicted travel time, such as tolerating a delay up to 10% of the average predicted travel time. Further, the tolerance of variation can be calculated or adjusted based on the user's personal attribute information. Additionally, the tolerance of variation can be used to determine whether users can share a ride in the same vehicle V based on ride requests from multiple users.

[0027] Also, the user information may further include travel route selection history information. The travel route selection history information is history information indicating which travel route candidate the user has selected among the travel route candidates proposed in the past. The travel route selection history information is used to determine the user's tolerance of variation. For example, when the user has a tendency to select a travel route candidate with a large degree of variation in the average predicted travel time, the tolerance of variation is set to a relatively large value, while when the user has a tendency to select a travel route candidate with a small degree of variation in the average predicted travel time, the tolerance of variation is set to a relatively small value.

[0028] The road map information database 12b stores information on road maps (hereinafter referred to as "road map information") in the target area of the vehicle dispatching service. The road map information may include information necessary for route search, such as road network information, road attribute information, ground feature information, and environmental information. The road network information is composed of links (road links) and nodes (junction points). The road attribute information includes, for example, traffic regulations such as speed limits, one-way roads, right and left turn prohibitions, parking and stopping prohibitions, and road closures, road types such as local roads and arterial roads (including road widths and traffic lanes), and information on the control of traffic lights at intersections. The ground feature information includes, for example, the situation between buildings and roads (such as sidewalk widths, the presence or absence of pedestrian-vehicle separation zones such as guardrails and plantings, and the degree of visibility). The environmental information includes, for example, the situation of parked and stopped vehicles and pedestrians for each time zone at each location, the frequency of right and left turning vehicles at intersections, the parking and stopping frequency, and the frequency of traffic accidents.

[0029] The vehicle information database 12c stores information on the vehicle V provided for the user's use (vehicle information). The vehicle information includes, for example, vehicle ID, vehicle attributes (vehicle registration number, vehicle type, and maximum number of passengers / maximum load, manned or unmanned, etc.), vehicle performance, other specifications, the current vehicle dispatching plan, the current location, and the current state (service state, remaining battery capacity (endurance), and passengers, etc.). The current location and / or state of the vehicle V can be updated at any time based on the location information transmitted from the vehicle V.

[0030] The vehicle dispatching plan database 12d stores the vehicle dispatching plan of the vehicle V created by the vehicle dispatching management device 10 based on the user's vehicle dispatching request. The vehicle dispatching plan includes the driving route from the starting waiting location through several points to the ending waiting location and the average estimated required time to each destination.

[0031] The travel record information database 12e stores information on the past travel history for each vehicle V (hereinafter referred to as "travel record information"). The travel record information includes, for example, for each vehicle V, operation date and time (such as operation start time and end time), travel route, arrival and departure times at each location (such as the destination), travel distance, and various specification information such as fuel consumption (electricity cost). The travel route is composed of, for example, the links and nodes traveled by the vehicle V. In the present disclosure, the travel record information database 12e stores road link required time information indicating the required time for each link created based on the travel record information. The road link required time information is created, for example, by the travel record information management unit 129 described later.

[0032] FIG. 3 is a diagram showing an example of road link required time information in the travel record information database of the vehicle allocation management device according to an embodiment of the present invention. As shown in FIG. 3(a), the road link required time information includes, for each link indicated by an identifier (ID), the average required time and the degree of variation (such as variance or standard deviation) for each date type and time zone. The road link required time information is used to calculate the degree of variation or deviation of the required time to the destination for each candidate for the travel route (hereinafter referred to as "travel route candidate") from the departure place to the destination based on the user's vehicle allocation request. Note that FIG. 3(b) shows the average predicted required time and the degree of variation for each travel route to the departure place and the destination calculated based on FIG. 3(a).

[0033] Returning to FIG. 2, the front-end processing unit 110 performs various processes with the user's terminal device 20. As an example, the front-end processing unit 110 refers to the user information database 12a in accordance with a login request from the vehicle allocation application on the user's terminal device 20 and performs a login authentication process. Further, the front-end processing unit 110 receives a vehicle allocation request from the vehicle allocation application on the user's terminal device 20, delivers this to the vehicle allocation plan creation unit 120, and communicates with the terminal device 20 in order to receive the user's approval or disapproval of the vehicle allocation plan created by the vehicle allocation plan creation unit 120 in response thereto.

[0034] Based on the given vehicle allocation requirements, the vehicle allocation plan creation unit 120 extracts candidate vehicles (candidate vehicle v) from the vehicles V in the target area and tentatively creates the vehicle allocation plan. The tentative vehicle allocation plan may be created for several different driving route candidates (i.e., driving routes). The vehicle allocation plan creation unit 120 proposes the tentative vehicle allocation plan to the user, and upon receiving the user's approval, finalizes it. Then, the vehicle allocation plan creation unit 120 stores the finalized vehicle allocation plan in the vehicle allocation plan database 12d and issues a vehicle allocation instruction to the corresponding vehicle V via the vehicle communication unit 130. Also, when the user selects one of several vehicle allocation plans, the vehicle allocation plan creation unit 120 stores the driving route indicated by the selected vehicle allocation plan in the user information database 12a as driving history information. After completing the vehicle allocation service, the vehicle V that has been allocated based on the vehicle allocation requirements transmits the driving performance information to the vehicle allocation management device 10, and the vehicle allocation plan creation unit 120 stores this in the driving performance information database 12e.

[0035] In the present disclosure, in creating the vehicle allocation plan, the vehicle allocation plan creation unit 120 extracts driving route candidates based on the vehicle allocation requirements, and for each of the driving route candidates, calculates an effective estimated required time (hereinafter referred to as "effective estimated required time") calculated based on the degree of variation in the actual values of the required time indicated by the driving performance information. Then, the vehicle allocation plan creation unit 120 narrows down the driving route candidates according to the user's tolerance of variation and the effective estimated required time.

[0036] The vehicle communication unit 130 exchanges various types of information with the vehicle V via the communication network N. For example, the vehicle communication unit 130 acquires vehicle information including the position information of the vehicle V and delivers it to the vehicle allocation plan creation unit 120, and transmits an operation instruction according to the vehicle allocation plan by the vehicle allocation plan creation unit 120 to the vehicle V. Also, the vehicle communication unit 130 acquires the driving performance information from the vehicle V that has completed the vehicle allocation service and delivers it to the vehicle allocation plan creation unit 120.

[0037] Next, the details of the vehicle allocation plan creation unit 120 will be described. FIG. 4 is a block diagram showing an example of the details of the vehicle allocation plan creation unit of the vehicle allocation management device according to an embodiment of the present invention. In the example shown in the figure, the vehicle allocation plan creation unit 120 includes a vehicle allocation request acquisition unit 1201, a demand calculation unit 1202, a candidate vehicle extraction unit 1203, a travel route candidate extraction unit 1204, an effective estimated required time calculation unit 1205, a variation tolerance determination unit 1206, a travel route determination unit 1207, a vehicle allocation plan proposal unit 1208, a vehicle allocation instruction unit 1209, and a travel performance information management unit 1210.

[0038] The vehicle allocation request acquisition unit 1201 acquires or accepts a vehicle allocation request from the user via the front-end processing unit 110. The time when the vehicle allocation request acquisition unit 1201 acquires the vehicle allocation request is the start time of timing for various limit times (for example, boarding limit time, alighting limit time, etc.). The vehicle allocation request acquisition unit 1201 delivers the acquired vehicle allocation request to each of the demand calculation unit 1202, the candidate vehicle extraction unit 1203, the travel route candidate extraction unit 1204, the variation tolerance determination unit 1206, etc.

[0039] The demand calculation unit 1202 refers to various databases 12, for example, and calculates the current demand and / or the predicted future demand of the vehicle V by the user based on driving performance information and the like, and outputs this as demand information. For example, the current demand may be the number of vehicles V waiting (waiting number) for which no allocation plan has been assigned at the time of receiving the allocation request based on the allocation plan database 12d. Further, the future demand may be the number of vehicles V for which demand is expected at a specific future time or time zone such as 10 minutes later, 20 minutes later, 30 minutes later, and 1 hour later from the reference time (for example, the current time) based on the driving performance information database 12e. As will be described later, for example, when the current and / or future demand is high, the variation threshold is determined to be a value distal from the average predicted required time (see FIG. 5). Thereby, when it is predicted that there will be many allocation requests from the user, a more reliable effective predicted required time based on the variation threshold is calculated so that no delay in the scheduled allocation occurs. Also, the variation threshold can be dynamically determined according to such a future time or time zone of demand prediction. Further, in addition to the driving performance information, the demand calculation unit 1202 may predict the future demand in consideration of environmental factors such as time and seasonal factors and event holding. The demand calculation unit 1202 may include a demand prediction model in which machine learning is performed according to a predetermined machine learning algorithm, using, for example, operation performance information and the like as explanatory variables and the predicted demand as an objective variable. In this way, by using the current and / or future demand, the demand calculation unit 1202 creates a vehicle plan including an optimal driving route, enabling efficient operation of the vehicle V.

[0040] The candidate vehicle extraction unit 1203 extracts one or more vehicles V as candidate vehicles v based on the allocation request. For example, the candidate vehicle extraction unit 1203 extracts, as candidate vehicles v, vehicles V that can be allocated and travel in the vicinity based on the pick-up and drop-off locations (departure and destination) indicated by the allocation request. Also, vehicles V that cannot be allocated to the user within various limit times (for example, boarding limit time, alighting limit time, etc.) from the reception time of the allocation request are excluded.

[0041] The travel route candidate extraction unit 1204 extracts at least one or more travel route candidates based on the vehicle allocation request. Typically, an average estimated required time is associated with the travel route candidates. Alternatively, a required time considering the degree of variation may be associated with the travel route candidates. For example, the travel route candidate extraction unit 1204 extracts travel route candidates by performing a route search while the route search engine refers to the road map information database 12b based on the boarding location and the alighting location indicated by the vehicle allocation request, and calculates the average estimated required time by referring to the travel performance information database 12e.

[0042] The effective estimated required time calculation unit 1205 calculates the degree of variation of the average estimated required time of a travel route including a plurality of links from the departure point to the destination based on the road link required time information in the travel performance information database 12e for each of the extracted travel route candidates, and calculates the effective estimated required time based on the calculated degree of variation. The effective estimated required time is based on the total required time of the links constituting the travel route corresponding to the date and time zone corresponding to the vehicle allocation request. As described above, the effective estimated required time is the required time calculated based on the variation threshold with respect to the degree of variation of the actual value of the required time indicated by the travel performance information. As will be described later, the effective estimated required time calculation unit 1205 determines a variation threshold with respect to the degree of variation according to a predetermined criterion. The effective estimated required time calculation unit 1205 calculates the effective estimated required time by applying the determined variation threshold to the average estimated required time in the travel route candidates calculated by the route search engine.

[0043] FIG. 5 is a diagram for explaining an example of a variation threshold in a vehicle allocation management device according to an embodiment of the present invention. That is, this figure shows the probability distribution of the predicted required time based on the driving performance information for a certain driving route. In the present disclosure, for example, a variation threshold proximal to the average value of the predicted required time is defined as the first variation threshold, and a variation threshold more distal from the average value than the first variation threshold is defined as the second variation threshold. That is, the second variation threshold is a value with a larger distribution range of variations (a value indicating that it is highly probable to fall within that distribution range) than the first variation threshold. |±σ| and |±2σ| in the standard normal distribution are examples of the first variation threshold and the second variation threshold, respectively.

[0044] Returning to FIG. 4, when the effective predicted required time calculation unit 1205 determines that there is a margin for the next vehicle allocation (for example, the movement to the next boarding location) of the candidate vehicle v based on the vehicle allocation plan of the candidate vehicle v, the effective predicted required time calculation unit 1205 may set the first variation threshold proximal to the average value (average predicted required time) as the variation threshold. That is, if there is a margin until the next vehicle allocation for the candidate vehicle v, the degree of freedom in vehicle allocation is high, so the variation threshold can be determined according to other criteria. For example, the effective predicted required time calculation unit 1205 calculates a temporal margin using the average predicted required time for the movement from the user's alighting location to the boarding location of the other user with respect to the boarding time at the next boarding location based on the vehicle allocation requests of other users, and determines whether the calculated margin exceeds a predetermined margin threshold.

[0045] In this case, additionally or alternatively, the effective predicted required time calculation unit 1205 further determines whether the current and / or future demand volume of vehicle V is high based on a predetermined demand threshold, and when it is determined that the current and / or future demand volume is high, the second variation threshold may be set as the variation threshold. This increases the certainty of the effective predicted required time based on the variation threshold.

[0046] In addition, when the effective estimated required time calculation unit 1205 determines that there is no margin for the next vehicle allocation (for example, movement to the pick-up location) of the candidate vehicle v based on the vehicle allocation plan of the candidate vehicle v, or when it determines that there is a margin but the future demand volume is low, it may set a second variation threshold value that is farther from the average value than the first variation threshold value as the variation threshold value. Thereby, the certainty of the effective estimated required time based on the variation threshold value is increased.

[0047] For example, referring to FIG. 3(b), the average estimated required time from the departure place to the destination based on the running performance information of the extracted first running route candidate is 30 minutes, but the degree of variation (standard deviation) is 20 minutes, and the average required time of the extracted second running route candidate is 40 minutes, but the degree of variation is 5 minutes. That is, the first running route candidate has a shorter average estimated required time but a larger degree of variation than the second running route candidate. When the effective estimated required time calculation unit 1205 sets the variation threshold value to, for example, σ according to a predetermined condition, the effective estimated required time of the first running route candidate is calculated to be about 50 minutes, which represents about 68% of the whole, and the effective estimated required time of the second running route candidate is calculated to be about 45 minutes, which represents about 68% of the whole. On the other hand, when the effective estimated required time calculation unit 1205 sets the variation threshold value to, for example, 2σ according to a predetermined standard, the effective estimated required time of the first running route candidate is calculated to be about 50 minutes, which represents about 95% of the whole, and the effective estimated required time of the second running route candidate is calculated to be about 45 minutes, which represents about 95% of the whole.

[0048] Further, the effective expected required time calculation unit 1205 can dynamically set the variation threshold according to a specific future time (for example, 10 minutes later, 20 minutes later, 30 minutes later, 1 hour later, etc. from the current time) or its time zone predicted by the demand calculation unit 1202. For example, the closer the future time for demand prediction is (for example, 10 minutes later), the further the variation threshold is set from the average expected required time (for example, the second variation threshold). Thereby, when the expected demand in the immediate future is high in the vehicle V's vehicle allocation plan, by widening the width of the variation degree of the expected required time, a driving route that can ensure the next vehicle allocation as much as possible will be determined. On the other hand, the further the future time for demand prediction is (for example, 30 minutes later), the closer the variation threshold is set from the average expected required time (for example, the first variation threshold). Thereby, when the expected demand in the immediate future is low, while suppressing the influence on the next vehicle allocation, by narrowing the width of the variation degree of the expected required time, a driving route close to the average expected required time can be determined.

[0049] Furthermore, when the effective expected required time calculation unit 1205 determines that the expected required time to the destination is affected by road traffic information provided from the road traffic information management system 30, environmental factors such as time-based and seasonal factors and / or event holding, the variation threshold may be set closer to the average expected required time. Thereby, even when it is predicted that the traffic flow is affected by sudden factors, by narrowing the width of the variation degree of the expected required time, a driving route close to the expected required time can be determined.

[0050] The variation tolerance determination unit 1206 determines the user's variation tolerance with respect to the degree of variation in the average predicted travel time of the driving route to the destination indicated by the acquired vehicle allocation request. As described above, the variation tolerance is a value indicating how much the user can tolerate the actual travel time with respect to the predicted travel time to the destination. For example, the variation tolerance determination unit 1206 uses the variation tolerance indicated by the vehicle allocation request input by the user. Alternatively, the variation tolerance determination unit 1206 may refer to the user information database 12a and use the variation tolerance of the user information pre-input by the user. Thereby, the variation tolerance input by the user based on his or her preferences can be used.

[0051] In addition, the variation tolerance determination unit 1206 may calculate or adjust the variation tolerance based on the user's personal attribute information indicated by the user information. For example, when the user's personal attribute information indicates that the user is a caregiver with an infant, the variation tolerance determination unit 1206 determines a relatively small value of the variation tolerance. In this way, by determining the variation tolerance according to the user's personal attribute information, it becomes possible to ensure the certainty of the average predicted travel time considering the personal attributes of each user.

[0052] In addition, the variation tolerance determination unit 1206 can determine the variation tolerance based on the driving route selection history information indicated by the user information. For example, when the variation tolerance determination unit 1206 determines, based on the driving route selection history information, that the user has a tendency to select a driving route candidate with a large variation degree of the average predicted required time, the variation tolerance determination unit 1206 determines the variation tolerance to a relatively large value. On the other hand, when the variation tolerance determination unit 1206 determines that the user has a tendency to select a driving route candidate with a small variation degree of the average predicted required time, the variation tolerance determination unit 1206 determines the variation tolerance to a relatively small value. The variation tolerance can be, for example, the average value of the variation degrees of the driving route candidates selected in the past. As a result, it becomes possible to recognize how much variation degree of the average predicted required time the user can tolerate from the driving routes selected in the past.

[0053] The travel route determination unit 1207 determines one or more travel routes to be presented to the user from among the travel route candidates based on the variation tolerance with respect to the variation degree of the average predicted travel time and the effective predicted travel time. That is, first, for each travel route candidate, the travel route determination unit 1207 refers to the travel performance information database 12e to obtain the variation degree of the average predicted travel time. Alternatively, the travel route determination unit 1207 may calculate the variation degree of the average predicted travel time based on the difference between the average predicted travel time and the effective predicted travel time. For example, if the difference between the average predicted travel time and the effective predicted travel time is small, the variation degree is small; if the difference between the average predicted travel time and the effective predicted travel time is large, the variation degree of the average predicted travel time is large. Thus, the variation degree of the average predicted travel time for each travel route candidate can be calculated. Also, the travel route determination unit 1207 compares the travel route candidates and narrows down the travel route candidates by excluding the travel route candidates whose average predicted travel time and effective predicted travel time are both larger than others. That is, the travel route determination unit 1207 narrows down to the travel routes with at least one of the average predicted travel time and the effective predicted travel time being small. This makes the selection of travel route candidates more efficient. Subsequently, the travel route determination unit 1207 determines, from among the narrowed-down travel route candidates, those that conform to the user's variation tolerance as the travel routes. More specifically, the travel route determination unit 1207 applies the variation tolerance based on the average predicted travel time of each travel route candidate, and determines the travel route candidates whose predicted travel time corresponding to the variation tolerance falls within the effective predicted travel time as the travel routes to be finally presented to the user. If there are multiple travel route candidates that conform to the variation tolerance, the travel route determination unit 1207 may select the travel route candidate with the minimum effective predicted travel time as the travel route, or may determine the travel route candidate with a small effective predicted travel time as the travel route according to other conditions such as the vehicle V's cruising range and the vehicle allocation plan. Alternatively, the travel route determination unit 1207 may determine all or some of the multiple travel route candidates that conform to the variation tolerance as the multiple travel routes to be presented to the user.In this case, for example, an effective estimated required time may be associated with each of a plurality of driving routes, and each driving route may be visually distinguished and displayed in the order of being recommended according to the effective estimated required time. As a result, it becomes easier for the user to select a driving route, and it is possible to collect driving route selection history information based on the driving route finally selected by the user, and it becomes possible to obtain the user's preference for the tolerance of variation.

[0054] Further, when the tolerance of variation is smaller than the first allowable threshold, the driving route determination unit 1207 may determine a driving route candidate with a smaller degree of variation in the average estimated required time as the driving route. Further, when the tolerance of variation is larger than the second allowable threshold, the driving route determination unit 1207 may determine a driving route candidate with a larger degree of variation in the average estimated required time as the driving route. The second allowable threshold is a value that is the same as or larger than the first allowable threshold. As a result, it becomes possible to select an appropriate driving route candidate according to the user's preference for the degree of variation in the average estimated required time and propose this to the user as the driving route.

[0055] When the driving route is determined in this way, the vehicle allocation plan creation unit 120 creates a vehicle allocation plan for the candidate vehicle v based on the driving route. Note that when there are a plurality of determined driving routes, the vehicle allocation plan creation unit 120 creates a vehicle allocation plan based on each driving route. In this case, the vehicle allocation plan creation unit 120 may create a vehicle allocation plan so that each driving route is visually distinguished and displayed in the order of being recommended according to the effective estimated required time.

[0056] The vehicle allocation plan creation unit 120 may create a vehicle allocation plan so that users share a single vehicle V based on vehicle allocation requests from a plurality of users. For example, the vehicle allocation plan creation unit 120 determines whether such a user sharing is successful when, after one user makes a vehicle allocation request, another user makes a vehicle allocation request within a predetermined time, or when another user makes a vehicle allocation request while the vehicle V is being allocated to the vehicle allocation request of one user and is traveling on the driving route to the destination.

[0057] More specifically, when the tolerance of each user is greater than a predetermined carpooling reference value, the vehicle allocation plan creation unit 120 allows carpooling with other users in the vehicle V allocated to one user. Therefore, when the vehicle allocation plan creation unit 120 receives a vehicle allocation request from another user, it determines whether carpooling between users can be established. As a result, carpooling between users with a large tolerance can be promoted in the vehicle V, and the vehicle allocation efficiency can be improved. Alternatively, when the difference between the tolerance of one user and the tolerance of another user is equal to or less than a predetermined value, the vehicle allocation plan creation unit 120 allows carpooling with other users in the vehicle V allocated to one user, and based on the vehicle allocation request of the other user, a vehicle allocation plan may be created so that the user and other users can carpool in the vehicle allocated to the user. As a result, carpooling between users with similar preferences for the degree of variation in the average expected travel time is promoted.

[0058] In addition, when at least a part of the driving route of the vehicle V for one user overlaps with the driving route candidate of the vehicle V for another user, the vehicle allocation plan creation unit 120 can create a vehicle allocation plan so that one user and another user can carpool. As a result, it is not necessary to change the driving route of a user that has already been determined, and it is possible to prevent the convenience of the user from being excessively impaired.

[0059] The vehicle allocation plan proposal unit 1208 proposes the vehicle allocation plan created based on the determined driving route to the user, and when receiving the user's acceptance of this, determines the vehicle allocation plan. That is, the vehicle allocation plan proposal unit 1208 transmits the vehicle allocation plan of the candidate vehicle v to the user's terminal device 20 via the front-end processing unit 110, and displays the vehicle allocation plan on the user interface of the terminal device 20. The user makes a commitment or rejection to the vehicle allocation plan, and in response to this, the terminal device 20 transmits a notification of the commitment or rejection. When the vehicle allocation plan proposal unit 127 receives the user's acceptance notification via the front-end processing unit 110, it determines the vehicle allocation plan.

[0060] In addition, when there are vehicle allocation plans based on each of a plurality of driving routes, the vehicle allocation plan proposal unit 1208 can present them to the user in a selectable manner. For example, the vehicle allocation plan can be presented to the user such that each driving route is visually distinguished and displayed in the order recommended according to the effective estimated required time. This makes it easier for the user to select a driving route. The vehicle allocation plan proposal unit 1208 stores the driving route indicated by the vehicle allocation plan determined according to the user's approval notice in the user information database 12a as the user's driving route selection history information.

[0061] In addition, when there is a shared ride among users in the vehicle V, the vehicle allocation plan proposal unit 1208 proposes a vehicle allocation plan to each user and similarly requests the approval of each user. For example, when the vehicle V has already been allocated to a previous user, the vehicle allocation plan proposal unit 1208 proposes a vehicle allocation plan for the shared ride in the vehicle V based on the vehicle allocation request of a subsequent user and requests the approval of the subsequent user.

[0062] The vehicle allocation instruction unit 1209 gives a vehicle allocation instruction to the corresponding vehicle V according to the determined vehicle allocation plan. The control device CTL of the vehicle V that has received the operation instruction displays the driving route according to the vehicle allocation plan on, for example, the user interface by means of the navigation function. Alternatively, in the case of a driverless vehicle, the control device CTL determines a detailed actual driving route according to the driving route of the vehicle allocation plan and performs control so that autonomous driving is performed along the actual driving route.

[0063] When the driving performance information management unit 1210 acquires the driving performance information transmitted from the vehicle V that has completed the vehicle allocation service according to the vehicle allocation plan via the vehicle communication unit 130, it stores this in the driving performance information database 12e. In addition, the driving performance information management unit 1210 creates road link required time information including the degree of variation as shown in FIG. 3 based on the acquired driving performance information. For example, the driving performance information management unit 129 calculates the degree of variation in the required time for each road link based on the road link required time information including the required time corresponding to the date type and time zone of each road link based on the acquired driving performance information.

[0064] FIG. 6 is a sequence chart for explaining the outline of a vehicle dispatching service in a vehicle dispatching management system according to an embodiment of the present invention.

[0065] First, the vehicle V transmits its own position information acquired from the GPS system to the vehicle dispatching management device 10 at a predetermined timing (S601). Note that the acquisition and transmission of the position information by the vehicle V are performed periodically or in response to a transmission request from the vehicle dispatching management device 10. Thereby, the vehicle dispatching management device 10 acquires the position information transmitted from the vehicle V (S602).

[0066] On the other hand, a user who wants to use the vehicle dispatching service executes a vehicle dispatching application installed in the terminal device 20 and inputs necessary information for a vehicle dispatching request to a vehicle dispatching request screen displayed on the user interface. Thereby, the terminal device 20 transmits the vehicle dispatching request to the vehicle dispatching management device 10 (S603). For example, a user who wishes to board inputs a boarding location, a disembarking location, the number of passengers, a tolerance, etc. The boarding location and the disembarking location can be selected from, for example, a geographical map displayed by the vehicle dispatching application. Further, the boarding location (loading location) may be, for example, the current position acquired by a GPS function mounted on the user's smartphone.

[0067] When the vehicle dispatching management device 10 receives a vehicle dispatching request from the terminal device 20 (S604), it determines a driving route from among the driving route candidates based on the user's tolerance and the effective estimated required time for the received vehicle dispatching request, and creates a vehicle dispatching plan for the vehicle V (candidate vehicle v) (S605). That is, the vehicle dispatching management device 10 calculates the degree of variation of the average estimated required time based on the difference between the average estimated required time and the effective estimated required time for each driving route candidate. Subsequently, the vehicle dispatching management device 10 determines at least one that conforms to the user's tolerance as the driving route from among the narrowed-down driving route candidates. The vehicle dispatching management device 10 transmits the content of the created vehicle dispatching plan to the terminal device 20 in order to propose this to the user. The vehicle dispatching plan may include a plurality of visually distinguishable driving routes.

[0068] When the terminal device 20 receives the content of the vehicle allocation plan, it displays this on the user interface as a vehicle allocation plan proposal screen, and prompts the user for acceptance or rejection (approval or disapproval) of the proposed vehicle allocation plan (S606). When the user inputs approval or disapproval with respect to the vehicle allocation plan proposal screen, in response to this, the terminal device 20 transmits an approval or disapproval notice to the vehicle allocation management device 10 (S607), and the vehicle allocation management device 10 receives the approval or disapproval notice transmitted from the terminal device 20 (S608). For example, when the approval or disapproval notice indicates acceptance of the vehicle allocation plan, the vehicle allocation management device 10 determines the vehicle allocation plan of vehicle V according to the vehicle allocation plan, transmits a confirmation notice of the vehicle reservation to the terminal device 20, and transmits a vehicle allocation instruction according to the vehicle allocation plan to vehicle V (S609).

[0069] When the terminal device 20 receives the confirmation notice of the vehicle reservation, it displays this on the user interface to notify the user that the vehicle reservation has been confirmed (S610). On the other hand, when vehicle V receives the vehicle allocation instruction, in order to navigate the driver, for example, it displays a driving route according to the vehicle allocation plan indicated by the vehicle allocation instruction on the navigation screen (S611). Although not shown in the figure, vehicle V for which the vehicle allocation service according to the vehicle allocation plan has ended transmits the driving performance information to the vehicle allocation management device 10. The vehicle allocation management device 10 stores the driving performance information received from vehicle V in the driving performance information database 12e and updates the road link required time information.

[0070] FIGS. 7 to 9 are flowcharts for explaining an example of vehicle allocation management processing by a vehicle allocation management device according to an embodiment of the present invention. Such processing is realized by the vehicle allocation management device executing a vehicle allocation management server program under the control of a processor in cooperation with various hardware resources.

[0071] As shown in FIG. 7, the vehicle allocation management device 10 waits until there is a new vehicle allocation request from the user (S701). On the other hand, for example, a user who wishes to board operates a vehicle allocation application on the user interface of the terminal device 20 to input a vehicle allocation request. In this example, the vehicle allocation request includes the tolerance of variation input by the user. When there is a vehicle allocation request from the user (Yes in S701), the vehicle allocation management device 10 refers to the road map information database 12b based on the vehicle allocation request and determines the departure place and the destination (departure place) (S702).

[0072] Next, the vehicle allocation management device 10 refers to the road map information database 12b based on the determined departure place and extracts one or more driving route candidates (S703). That is, each driving route candidate has the same departure place, but the roads (links) in the middle are different. An average estimated required time is associated with each driving route candidate.

[0073] Next, the vehicle allocation management device 10 extracts one or more candidate vehicles v according to the departure place and the driving route candidates (S704). For example, the vehicle allocation management device 10 extracts the vehicle V waiting in the vicinity of the departure place or moving as the candidate vehicle v.

[0074] Next, the vehicle allocation management device 10 refers to the driving performance information database 12e for the extracted driving route candidates and calculates the effective estimated required time (S705). When calculating the effective estimated required time, the vehicle allocation management device 10 determines a variation threshold according to a predetermined condition. The details of the calculation process of the effective estimated required time will be described later.

[0075] Next, the vehicle allocation management device 10 determines the optimal one as the driving route from among the driving route candidates based on the user's tolerance of variation with respect to the variation degree of the average estimated required time of the driving route candidates and the effective estimated required time (S706). The details of the driving route determination process will be described later.

[0076] Subsequently, the vehicle allocation management device 10 creates or updates a vehicle allocation plan based on the determined driving route (S707). That is, the vehicle allocation management device 10 determines a vehicle V to be assigned to the determined driving route from among the candidate vehicles v. For example, the vehicle allocation management device 10 excludes candidate vehicles v in which the waiting time of the user who made a new vehicle allocation request exceeds the vehicle allocation delay limit time. Also, although not shown, the vehicle allocation management device 10 may create a vehicle allocation plan such that users share a single vehicle V based on vehicle allocation requests from multiple users. For example, when another user makes a vehicle allocation request within a predetermined time after one user makes a vehicle allocation request, or when another user makes a vehicle allocation request while vehicle V is being allocated to the vehicle allocation request of one user and is traveling on the driving route to the destination, the vehicle allocation plan creation unit 120 determines whether such user sharing is possible.

[0077] Next, the vehicle allocation management device 10 proposes the content of the created / updated vehicle allocation plan to the user (S708). That is, the vehicle allocation management device 10 transmits the content of the created / updated vehicle allocation plan to the terminal device 20, and in response, the terminal device 20 displays the content on the user interface and prompts the user to accept or reject the proposed vehicle allocation plan.

[0078] The vehicle allocation management device 10 determines whether it has received acceptance from the user for the proposed vehicle allocation plan (S709). If the vehicle allocation management device 10 has received acceptance from the user for the proposed vehicle allocation plan (Yes in S709), the vehicle allocation management device 10 finalizes the current vehicle allocation plan (S710). The vehicle allocation management device 10 stores the finalized vehicle allocation plan in the vehicle allocation plan database 12d. Subsequently, the vehicle allocation management device 10 transmits a confirmation notice of the vehicle allocation reservation to the terminal device 20 and transmits a vehicle allocation instruction based on the vehicle allocation plan to vehicle V (S711).

[0079] On the other hand, when the vehicle allocation management device 10 receives a rejection (refusal) from the user with respect to the proposed vehicle allocation plan (No in S709), it cancels the current vehicle allocation plan based on the vehicle allocation request of the user (S712). In this case, the vehicle allocation management device 10 returns the temporarily reserved vehicle allocation plan used for recreating the vehicle allocation plan to the original reserved vehicle allocation plan. If the user desires another vehicle allocation service, a new vehicle allocation request will be made.

[0080] Next, the calculation process of the effective estimated required time in the vehicle allocation management device 10 will be described with reference to FIG. 8. That is, FIG. 8 is a flowchart showing the details of the calculation process (S705) of the effective estimated required time shown in FIG. 7.

[0081] As shown in the figure, based on the vehicle allocation plan of the candidate vehicle v, the vehicle allocation management device 10 determines whether there is a margin for the next vehicle allocation of the candidate vehicle v (for example, the movement to the next boarding or alighting location) (S801). For example, the vehicle allocation management device 10 calculates the time margin by applying the average estimated required time for the movement from the user's alighting location to the boarding location of another user with respect to the boarding time at the next boarding location based on the vehicle allocation requests of other users, and determines whether the calculated margin exceeds a predetermined margin tolerance value.

[0082] When the vehicle allocation management device 10 determines that there is a margin for the next vehicle allocation of the candidate vehicle v (Yes in S801), subsequently, the vehicle allocation management device 10 determines whether the future demand forecast is high based on the demand information with reference to a predetermined demand threshold (S802). For example, the vehicle allocation management device 10 refers to the driving performance information database 12e, etc., calculates the future demand amount indicated by the expected amount of the user's vehicle allocation requests with respect to the number of vehicles V available for vehicle allocation in a certain future time period, and determines whether the calculated future demand amount exceeds a predetermined demand threshold. In this example, the vehicle allocation management device 10 makes a determination based on the future demand forecast, but it is not limited to this, and a determination may also be made based on the current demand.

[0083] When the vehicle allocation management device 10 determines that the future demand forecast is not high (No in S802), the vehicle allocation management device 10 sets the variation threshold to the first variation threshold (S803). As described above, the first variation threshold is a value closer to the average predicted required time (average value) than the second variation threshold. Therefore, by selecting the first variation threshold closer to the average predicted required time as the variation threshold, it is expected that a driving route with less variation in the required time will be selected. That is, when there is a margin in the vehicle allocation plan for the vehicle V and / or when the future demand forecast is low, a driving route will be determined such that the actual required time of the vehicle V matches the average predicted required time as much as possible.

[0084] On the other hand, when the vehicle allocation management device 10 determines that the future demand forecast is high (Yes in S802), the vehicle allocation management device 10 sets the variation threshold to the second variation threshold (S804). As described above, the second variation threshold is a value farther from the average value than the first variation threshold. Therefore, by selecting the second variation threshold farther from the average predicted required time as the variation threshold, it is expected that a driving route with a larger variation in the required time will be selected. That is, when there is a margin in the vehicle allocation plan for the vehicle V but the future demand forecast is high, a driving route will be determined that widens the range of variation in the predicted required time to ensure the next vehicle allocation as much as possible.

[0085] Also, when the vehicle allocation management device 10 determines that there is no margin for the next vehicle allocation of the candidate vehicle v (No in S801), the vehicle allocation management device 10 sets the variation threshold to the second variation threshold (S804). Therefore, by selecting the second variation threshold farther from the average value as the variation threshold, it is expected that a driving route with a larger variation in the required time will be selected. That is, when there is no margin in the vehicle allocation plan for the vehicle V, a driving route will be determined that widens the range of variation in the predicted required time to ensure the next vehicle allocation as much as possible.

[0086] Then, the vehicle allocation management device 10 calculates the effective estimated required time by applying it to the average estimated required time in the driving route candidates calculated by the route search engine based on the set variation threshold (S805).

[0087] Next, the determination process of the driving route based on the tolerance in the vehicle allocation management device 10 will be described with reference to FIG. 9. That is, FIG. 9 is a flowchart showing the details of the determination process (S706) of the driving route based on the tolerance shown in FIG. 7.

[0088] As shown in the figure, the vehicle allocation management device 10 excludes those in which both the average estimated required time and the effective estimated required time among the extracted driving route candidates are larger than those of other driving route candidates (S901). Next, the vehicle allocation management device 10 determines whether there is a driving route candidate that satisfies the tolerance (S902). When the vehicle allocation management device 10 determines that there is a driving route candidate that satisfies the tolerance (Yes in S902), the vehicle allocation management device 10 determines, as the driving route for presenting to the user, the one with the smaller effective estimated required time among the driving route candidates that satisfy the tolerance (S903).

[0089] For example, assume that the vehicle allocation management device 10 has acquired data showing graphs of probability density functions based on the driving performance information as shown in Fig. 10(a) for the driving route candidates R1 to R3. Here, for the driving route candidates R1 to R3, let their average values (average expected travel times) be T1_ave to T3_ave respectively, and assume that the effective expected travel times when the variation threshold 2σ is used are T1_2σ to T3_2σ respectively. That is, in the graph of the probability density function shown in Fig. (a), the narrower the distribution width of the variation (for example, the smaller the difference between the average expected travel time and the effective expected travel time), the smaller the degree of variation of the average expected travel time. The vehicle allocation management device 10 first excludes, for such driving route candidates R1 to R3, those for which both the average expected travel time and the effective expected travel time are greater than those of other driving route candidates. That is, in this example, the driving route candidate R3 is excluded, and the selection is narrowed down to the driving route candidates R1 and R2 (see Fig. (b) of the same figure).

[0090] Subsequently, the vehicle allocation management device 10 determines, for the driving route candidates R1 and R2, a driving route that conforms to the user's tolerance for variation as the driving route. For example, as shown in Fig. (b) of the same figure, the vehicle allocation management device 10 applies the tolerance for variation based on the average expected travel times T1_ave and T2_ave of the driving route candidates R1 and R2 and compares them with the effective expected travel times T1_2σ and T2_2σ. In this example, since the effective expected travel time T1_2σ of the driving route candidate R1 exceeds the expected travel time corresponding to the tolerance for variation, while the effective expected travel time T2_2σ of the driving route candidate R2 is within the expected travel time corresponding to the tolerance for variation, the vehicle allocation management device 10 determines the driving route candidate R2 as the driving route to be presented to the user.

[0091] Further, for example, when the user's tolerance for variation is less than the first allowable threshold, the vehicle allocation management device 10 may determine the driving route candidate R2 with a smaller variation degree of the average predicted travel time as the driving route. In contrast, when the user's tolerance for variation is greater than the second allowable threshold, the vehicle allocation management device 10 may determine the driving route candidate R1 with a larger variation degree of the average predicted travel time as the driving route. In addition, when there are multiple driving route candidates that meet the tolerance for variation, typically, the driving route candidate with a smaller average predicted travel time is determined as the driving route to be presented to the user.

[0092] On the other hand, when the vehicle allocation management device 10 determines that there is no driving route candidate that satisfies the tolerance for variation (No in S902), the vehicle allocation management device 10 determines, as the driving route for presenting to the user, the one with a smaller average predicted travel time among the existing driving route candidates (S904).

[0093] As described above, according to the present embodiment, it becomes possible to present a driving route that suits the user's preference in consideration of the variation degree of the predicted travel time to the destination. In particular, according to the present embodiment, based on the user's tolerance for variation and the effective predicted travel time, the driving route is selected from among the extracted driving route candidates, so that it becomes possible to create a vehicle allocation plan based on the optimal driving route that suits the user's preference.

[0094] Each of the above embodiments is an exemplification for explaining the present invention, and is not intended to limit the present invention only to these embodiments. The present invention can be implemented in various forms without departing from its gist.

[0095] For example, in the method disclosed in this specification, steps, operations, or functions may be performed in parallel or in a different order, as long as the results do not conflict. The described steps, operations, and functions are provided as mere examples, and some of the steps, operations, and functions may be omitted, combined with each other to form one, or other steps, operations, or functions may be added, without departing from the gist of the invention.

[0096] In addition, although various embodiments are disclosed in this specification, specific features (technical matters) in one embodiment can be added to other embodiments while appropriately improving them, or replaced with specific features in other embodiments, and such forms are also included in the gist of the present invention.

Explanation of Reference Numerals

[0097] 1…Vehicle Allocation Management System 10…Vehicle Allocation Management Device 110…Front-End Processing Unit 120…Vehicle Allocation Plan Creation Unit 1201…Vehicle Allocation Requirement Acquisition Unit 1202…Demand Calculation Unit 1203…Candidate Vehicle Extraction Unit 1204…Travel Route Candidate Extraction Unit 1205…Effective Estimated Required Time Calculation Unit 1206…Variation Tolerance Determination Unit 1207…Travel Route Determination Unit 1208…Vehicle Allocation Plan Proposal Unit 1209…Vehicle Allocation Instruction Unit 1210…Travel Performance Information Management Unit 130…Vehicle Communication Unit 12…Database 12a…User Information Database 12b…Road Map Information Database 12c…Vehicle Information Database 12d…Vehicle Allocation Plan Database 12e…Travel Performance Information Database 20…Terminal Device 30… Road traffic information management system N… Communication network V… Vehicle CTL… Control device

Claims

1. A vehicle allocation management device that manages the allocation of vehicles based on allocation requests, comprising: A driving performance information database that stores the driving performance information of the allocated vehicles; An allocation plan creation unit that creates an allocation plan for the vehicles based on the driving route in response to the allocation requests of each user. The allocation plan creation unit includes: A driving route candidate extraction unit that extracts driving route candidates based on the allocation request; A candidate vehicle extraction unit that extracts the vehicles based on the allocation request; An effective estimated required time calculation unit that determines a variation threshold for the variation degree of the required time for each driving route candidate calculated based on the driving performance information, and calculates an effective estimated required time based on the variation threshold; A variation tolerance determination unit that determines the user's variation tolerance for the variation degree of the average estimated required time to the destination indicated by the allocation request; A driving route determination unit that determines the driving route from among the driving route candidates based on the variation tolerance and the effective estimated required time; An allocation instruction unit that gives an allocation instruction to the vehicle based on the allocation plan. The vehicle allocation management device.

2. The variation tolerance determination unit determines the variation tolerance based on the allocation request. The vehicle allocation management device according to Claim 1.

3. It further includes a user information database that manages the user information of the user, The user information includes the variation tolerance input by the user, The variation tolerance determination unit determines the variation tolerance based on the user information. The vehicle allocation management device according to Claim 1.

4. The variation tolerance determination unit determines the variation tolerance based on the personal attribute information of the user indicated by the user information. The vehicle allocation management device according to Claim 3.

5. It further includes an allocation plan proposal unit for presenting an allocation plan based on at least one of the driving routes to the user. The vehicle allocation management device according to Claim 3.

6. The user information includes driving route selection history information indicating the history information of the driving routes previously selected by the user from among the at least one driving route, The variation tolerance determination unit determines the user's variation tolerance based on the driving route selection history information. The vehicle allocation management device according to Claim 5.

7. The variation tolerance determination unit determines the variation tolerance based on the degree of variation in the average predicted required time of the driving route indicated by the driving route selection history information. The vehicle allocation management device according to claim 6.

8. When the variation tolerance is smaller than a first allowable threshold value, the driving route determination unit determines, as the driving route, the driving route candidate with a smaller degree of variation in the average predicted required time. The vehicle allocation management device according to claim 1.

9. When the variation tolerance is larger than a second allowable threshold value, the driving route determination unit determines, as the driving route, the driving route candidate with a larger degree of variation in the average predicted required time. The vehicle allocation management device according to claim 1.

10. When the variation tolerance is larger than the shared use reference value, the vehicle allocation plan creation unit allows sharing between the user and other users in the vehicle allocated to the user. The vehicle allocation management device according to claim 1.

11. When the difference between the variation tolerance of the user and the variation tolerance of the other user is equal to or less than a predetermined value, the vehicle allocation plan creation unit creates the vehicle allocation plan such that the user and the other user share the vehicle allocated to the user based on the vehicle allocation request of the other user. The vehicle allocation management device according to claim 10.

12. When at least a part of the driving route of the vehicle for the user overlaps with the driving route candidate based on the variation tolerance of the other user, the vehicle allocation plan is created such that the user and the other user share the vehicle. The vehicle allocation management device according to claim 10.

13. The driving route candidate extraction unit calculates the average predicted required time of the extracted driving route candidate. The driving route determination unit calculates the degree of variation in the average predicted required time based on the difference between the average predicted required time and the effective predicted required time. The vehicle allocation management device according to claim 1.

14. The driving route determination unit narrows down the driving route candidates by excluding the driving route candidates among the extracted driving route candidates where both the average predicted required time and the effective predicted required time are larger than others. The vehicle allocation management device according to claim 1.

15. A vehicle allocation management method for managing the allocation of vehicles based on vehicle allocation requests, comprising: acquiring driving performance information of the allocated vehicle; responding to the vehicle allocation requests of each user, creating a vehicle allocation plan based on a driving route, and creating the vehicle allocation plan includes extracting candidate driving routes based on the vehicle allocation requests, extracting the vehicle based on the vehicle allocation requests, determining a variation threshold for the degree of variation in the required time for each candidate driving route calculated based on the driving performance information, calculating an effective estimated required time based on the variation threshold, determining the user's tolerance for variation in the degree of variation in the average estimated required time to the destination indicated by the vehicle allocation request, determining the driving route from among the candidate driving routes based on the tolerance for variation and the effective estimated required time, performing a vehicle allocation instruction to the vehicle based on the vehicle allocation plan, and a vehicle allocation management method.

16. A computer program for causing a computing device to execute a method for managing vehicle allocation in response to a user's vehicle allocation request under the control of a processor, the method includes acquiring driving performance information of the allocated vehicle, responding to the vehicle allocation requests of each user, creating a vehicle allocation plan based on a driving route, and creating the vehicle allocation plan includes extracting candidate driving routes based on the vehicle allocation requests, extracting the vehicle based on the vehicle allocation requests, determining a variation threshold for the degree of variation in the required time for each candidate driving route calculated based on the driving performance information, calculating an effective estimated required time based on the variation threshold, determining the user's tolerance for variation in the degree of variation in the average estimated required time to the destination indicated by the vehicle allocation request, determining the driving route from among the candidate driving routes based on the tolerance for variation and the effective estimated required time, performing a vehicle allocation instruction to the vehicle based on the vehicle allocation plan, and a computer program.

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