Operation plan making device, operation plan making method, vehicle distribution management device and storage medium

Abstract

The invention provides an operation plan making device and making method, a vehicle distribution management device and a storage medium which can cope with changing conditions all the time. An operation plan making device is provided with: an acquisition unit that acquires an energy functional expression defined as the sum of objective functions relating to an operation plan of a vehicle; and a calculation unit that calculates, as an optimal solution, an operation plan in which an energy function is minimized, the objective functions including: one or more first objective functions obtained on the basis of whether or not a constraint condition is established; and one or more second objective functions for evaluating the degree of achievement of the target phenomenon, the constraint condition including that the destination of the vehicle is one, and the energy functional expression is a functional expression for obtaining a weighted sum of the one or more first objective functions and the one or more second objective functions. The weights given to the one or more first objective functions are greater than the weights given to the one or more second objective functions so that the operation plan for which the constraint conditions are not satisfied is not selected.

Description

Technical Field

[0001] The present invention relates to a operation plan making device, a vehicle allocation management device, an operation plan making method, and a storage medium. Background Art

[0002] Conventionally, there has been an invention of a device that formulates a logistics vehicle allocation as a multi-objective optimization problem and applies an annealing method to search for an optimal vehicle allocation and delivery order (for example, refer to Patent Document 1 below).

[0003] Patent Document 1: Japanese Patent No. 2816802 Summary of the Invention

[0004] The conventional technology can be applied when the delivery items and available trucks are defined in advance, and there are cases where it is impossible to respond to the constantly changing situation according to the vehicle allocation requests of customers.

[0005] The solution of the present invention is completed in consideration of such a situation, and one of the purposes is to provide an operation plan making device, a vehicle allocation management device, an operation plan making method, and a storage medium that can respond to the constantly changing situation.

[0006] In order to solve the above problems, the present invention adopts the following solutions.

[0007] (1): An operation plan making device according to one aspect of the present invention formulates operation plans for a plurality of vehicles in a service where a vehicle transports passengers from a boarding position to an alighting position. The operation plan making device includes: an acquisition unit that acquires an energy function formula defined as the sum of objective functions related to the operation plan of the vehicle; and a calculation unit that calculates an operation plan that minimizes the value of the energy function formula as an optimal solution. The objective functions include: one or more first objective functions obtained based on the establishment or non-establishment of constraint conditions; and one or more second objective functions for evaluating the achievement degree of a target phenomenon. The constraint conditions include that the destination of the vehicle is one place. The energy function formula is a function formula for obtaining a weighted sum of the one or more first objective functions and the one or more second objective functions, and the weight given to the one or more first objective functions is larger than the weight given to the one or more second objective functions to such an extent that an operation plan in which the constraint conditions are not satisfied is not selected.

[0008] (2): Based on the solution in (1) above, it may also be that the operation plan specifies which vehicle goes to which boarding position and which vehicle goes to which vehicle base for a given boarding request.

[0009] (3): Based on the solution in (2) above, it may also be that the operation plan further specifies the configuration of one or more of the vehicle bases.

[0010] (4): Based on the solution in (1) above, it may also be that the target phenomenon includes giving priority to the passengers with longer waiting times and going to pick up more passengers.

[0011] (5): Based on the solution in (1) above, it may also be that the target phenomenon includes shortening the total time required until reaching the boarding position when going to pick up the passengers.

[0012] (6): Based on the solution in (3) above, it may also be that the target phenomenon includes arranging more of the vehicles in the vehicle bases near the places where the appearance frequency of the passengers is higher.

[0013] (7): Based on the solution in (2) above, it may also be that the target phenomenon includes shortening the total time required until the vehicle reaches the vehicle base.

[0014] (8): The vehicle allocation management device according to one aspect of the present invention includes: the operation plan formulation device of the solution in (1) above; and a plan instruction unit that sends at least the operation plan calculated by the calculation unit to the vehicle.

[0015] (9): The operation plan formulation method according to one aspect of the present invention is executed using a computer and formulates operation plans for a plurality of vehicles in the service of transporting passengers from the boarding position to the alighting position. The operation plan formulation method includes: a process of obtaining an energy function formula defined as the sum of objective functions related to the operation plan of the vehicle; and a process of calculating the operation plan that minimizes the value of the energy function formula as the optimal solution. The objective functions include: one or more first objective functions obtained based on the establishment or non-establishment of constraint conditions; and one or more second objective functions for evaluating the degree of achievement of the target phenomenon. The constraint conditions include that the destination of the vehicle is one place. The energy function formula is a function formula for obtaining the weighted sum of the one or more first objective functions and the one or more second objective functions, and the weight given to the one or more first objective functions is larger than the weight given to the one or more second objective functions to such an extent that an operation plan where the constraint condition is not satisfied is not selected.

[0016] (10):A computer-readable non-transitory storage medium according to one aspect of the present invention stores a program for formulating operation plans for a plurality of vehicles in a service of transporting passengers from a boarding position to an alighting position by a vehicle. The program causes a computer to execute: a process of obtaining an energy function formula defined as a sum of objective functions related to the operation plans of the vehicles; and a process of calculating an operation plan that minimizes the value of the energy function formula as an optimal solution. The objective functions include: one or more first objective functions obtained based on the establishment or non-establishment of constraint conditions; and one or more second objective functions for evaluating the achievement degree of a target phenomenon. The constraint conditions include that the destination of the vehicle is one place. The energy function formula is a function formula for obtaining a weighted sum of the one or more first objective functions and the one or more second objective functions, and the weight given to the one or more first objective functions is larger than the weight given to the one or more second objective functions to such an extent that an operation plan in which the constraint conditions are not satisfied is not selected.

[0017] According to the aspects (1) to (10), it is possible to cope with situations that change moment by moment. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 FIG. is an example of an operation scenario that is an object of processing by the operation plan formulation device.

[0019] Figure 2 FIG. is a structural diagram of the operation plan formulation device 100.

[0020] Figure 3 FIG. is a structural diagram of the vehicle allocation management device 50. DETAILED DESCRIPTION OF THE INVENTION

[0021] Hereinafter, embodiments of the operation plan formulation device, vehicle allocation management device, operation plan formulation method, and storage medium of the present invention will be described with reference to the drawings.

[0022] Figure 1This is a diagram showing an example of an operation scenario for which the operation plan creation device is the processing target. In this operation scenario, at an arbitrary location (boarding position P1) in a specific closed area, passenger 20 uses a terminal device such as a smartphone to send a ride request and receives a transportation service. Vehicle 10 stands by at vehicle base 30 when not in use for transportation, and when receiving an instruction, goes to boarding position P1, picks up passenger 20, and moves to alighting position P2. Alternatively, the operation plan creation device may use as the processing target an operation scenario in which vehicle base 30 is not set (for example, vehicle 10 continuously moves like a moving taxi). In this case, the sum (Σ) on the left side of target phenomena 3 and 4 and constraint condition 1 described later can be omitted and the mathematical formula can be appropriately modified. In the figure, 40 is a road. The ride request is sent to the vehicle allocation management device (which may be the same device as operation plan creation device 100 described later or another device) via a communication network, and according to the operation plan created by operation plan creation device 100, the vehicle allocation management device sends an instruction to pick up the vehicle to vehicle 10, or an instruction to return to vehicle base 30, etc., thereby realizing the transportation service for passengers by vehicle 10. Vehicle 10 is, for example, a single-passenger autonomous vehicle, but is not limited thereto, and may be a manned vehicle or a vehicle capable of carrying multiple passengers. The operation scenario may also be a public transportation scenario, or a scenario that restricts traffic participants such as a golf course, an orchard, or a hospital. Hereinafter, in this area, the road structure, the distribution P(S k ), the distribution P(O l ) of alighting positions, and the appearance frequency (ride request sending frequency per unit time) λ of passenger 20 are assumed to be known. The boarding position P1 and the ride request sending position may be the same or different.

[0023] Figure 2It is a structural diagram of the operation plan formulation device 100. The operation plan formulation device 100 includes, for example, an acquisition unit 110, a calculation unit 120, and a storage unit 150. The acquisition unit 110 includes a field information acquisition unit 112 and a mathematical formula definition acquisition unit 114. Components other than the storage unit 150 are implemented, for example, by a hardware processor such as a CPU (Central Processing Unit) executing a program (software). Some or all of these components can be implemented by hardware (including circuitry such as LSI (Large Scale Integration), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array), GPU (Graphics Processing Unit), SOC (System On Chip)), or can be implemented by the cooperation of software and hardware. The program can be pre-stored in a storage device such as an HDD (Hard Disk Drive) or a flash memory (a storage device with a non-transitory storage medium), or can be stored in a removable storage medium such as a DVD or a CD-ROM (a non-transitory storage medium), and installed by mounting the storage medium on a drive device. The storage unit 150 is an HDD, a flash memory, a RAM (Random Access Memory), etc., and stores information such as field information 152 and definition formula information 154.

[0024] The field information acquisition unit 112 of the acquisition unit 110 acquires road structure, average speed, distribution P(S k ), distribution P(O l ) of the alighting position, and information such as the appearance frequency λ of the passenger 20, etc., which are stored in the storage unit 150 as the field information 152.

[0025] The mathematical formula definition acquisition unit 114 reads out the definition formula information 154 of the storage unit 150 to obtain an energy function formula defined as the sum of objective functions related to the operation plan of the vehicle 10. The objective function can also be set by an operator of the service, etc. In this case, the operation plan formulation device 100 acquires the setting information of the objective function, for example, via an interface operating in an operator terminal device used by the operator of the service. The smaller the value of the objective function (the closer to zero), the more appropriate it indicates.

[0026] The calculation unit 120 calculates the operation plan that minimizes the value of the energy function formula as the optimal solution. The operation plan refers to a plan in which at least the number of vehicles 10 is known, and for the given ride requests, it is specified which vehicle 10 goes to which pick-up location P1 and which vehicle 10 goes to which vehicle base 30 (i.e., the travel destination of the vehicle 10). The operation plan may also specify the configuration of one or more vehicle bases 30. In this case, the vehicle base 30 is not limited to the vehicle base set up along with the construction according to the operation plan, and the operation plan may also specify which of the multiple open spaces that are candidates for the vehicle base 30 in advance is used as the vehicle base 30. Hereinafter, the operation plan is set as a plan that specifies both the travel destination of the vehicle 10 and the configuration of one or more vehicle bases 30. For example, the conceivable operation plans are comprehensively set, the energy function for each operation plan is calculated, and on this basis, the operation plan that minimizes the energy function is calculated as the optimal solution.

[0027] Hereinafter, the objective function will be described. In the following description, the reference numerals 10, 20, and 30 are appropriately omitted. The objective function includes one or more first objective functions obtained based on whether the constraint conditions are satisfied and one or more second objective functions for evaluating the degree of achievement of the target phenomenon. The constraint conditions include, for example, the following two, but may also include other constraint conditions.

[0028] (Constraint condition 1)

[0029] Constraint condition 1 is that "the location where a vehicle goes is one". If this constraint condition is expressed as a first objective function, for example, it becomes the function H of formula (1). A0 . In the formula, i is the identifier of the vehicle, k is the identifier of the passenger, j is the identifier of the vehicle base, and σ vi，bj is a function that becomes 1 when the vehicle i goes to the vehicle base b j and becomes zero otherwise, and σ vi，ck is a function that becomes 1 when the vehicle i goes to the passenger c k and becomes zero otherwise. The function H A0 returns zero if the location where the vehicle i goes is one, and returns a value of 1 or more otherwise.

[0030]

[0031] (Constraint condition 2)

[0032] Constraint condition 2 is that "the vehicle going to one passenger is one". When this constraint condition is expressed as a first objective function, for example, it becomes the function H of formula (2). A1 .

[0033]

[0034] The target phenomena include, for example, the following four, but may also include other constraints.

[0035] (Target Phenomenon 1)

[0036] Target Phenomenon 1 is "giving priority to passengers with longer waiting times and picking up as many passengers as possible". The second objective function corresponding to this target phenomenon becomes, for example, the function H of Equation (3). B0 . In the equation, w ck is the waiting time of passenger ck, and w max is the maximum value of the waiting times of all passengers. w offset is a bias value used to prevent the weight of a passenger with a waiting time of zero from becoming zero. The waiting time is stored, for example, in the storage unit 150 as part of the on-site information 152.

[0037]

[0038] (Target Phenomenon 2)

[0039] Target Phenomenon 2 is "shortening the total required time until arriving at the boarding position when picking up passengers". The second objective function corresponding to this target phenomenon becomes, for example, the function H of Equation (4). B1 . In the equation, t vi，ck is the required time until vehicle i arrives at the boarding position when picking up passenger ck. The time used is calculated by the calculation unit 120 based on the road structure, average speed information, boarding position, and vehicle position included in the on-site information 152.

[0040]

[0041] (Target Phenomenon 3)

[0042] Target Phenomenon 3 is "allocating more vehicles to vehicle bases near places where the appearance frequency of passengers is higher". The second objective function corresponding to this target phenomenon becomes, for example, the function H of Equation (5). B2 .

[0043]

[0044] Here, τ bj is explained. In the following explanation, S k is the appearance position of the k-th passenger (more specifically, the transmission position of the ride request), O l is the l-th disembarkation position, avg_pos is the average position of empty vehicles, and r is the average occupancy rate. When defined in this way, the average vehicle allocation time t j to each vehicle base b bjIt is represented by Equation (6). t bj，ride is the time until vehicle i with a passenger on board reaches vehicle base b j up to that point, and t bj，not_ride is the time until vehicle i without a passenger on board reaches vehicle base b j up to that point. The first term of t bj，ride is the time until vehicle i delivers the passenger on board to the alighting position, and the second term is the time from when the passenger is delivered to the alighting position until reaching vehicle base b j up to that point. t bj，avg_pos is the time from the average position of the empty vehicle to being assigned to vehicle base b j .

[0045]

[0046] When a passenger appears at the appearance position S k , the probability p(x|S) of dispatching a vehicle from position x is obtained using Equation (7) k . t x，Sk is the travel time from position x to the appearance position S k , t bj，Sk is the travel time from vehicle base b j to the appearance position S k , and t = t x，Sk refers to the phenomenon where the vehicle dispatching time from position x to the appearance position becomes t x，Sk . v avg is the average vehicle speed, and t avg is the average waiting time (the time obtained by dividing the total waiting time of passengers within the current observation period by the number of passengers within that observation period). The numerator of the rightmost term in Equation (7) assumes that the probability density of the vehicle dispatching time becoming t xk follows an exponential function, and the denominator of the rightmost term means that the longer the vehicle dispatching time, the farther position x is from the appearance position S k , and the probability density decreases proportionally to the radius for places that are farther away.

[0047]

[0048] Furthermore, by substituting vehicle base b for position x in Equation (7) and substituting it into the middle term of Equation (8), τ is calculated using Equation (9) j . bj .

[0049]

[0050] (Target Phenomenon 4)

[0051] The target phenomenon 4 is "the total of the required times shortened until the vehicle reaches the vehicle base". The second objective function corresponding to this target phenomenon becomes, for example, the function H of Equation (10). B3 .

[0052]

[0053] Using the first objective function and the second objective function exemplified above, the energy function is represented by Equation (11). The calculation unit 120 calculates the energy function for each operation plan, for example, and selects the operation plan with the minimum energy function as the optimal solution. Here, the weights α0 and α1 assigned to one or more first objective functions are larger than the weights β0 to β3 assigned to one or more second objective functions to such an extent that an operation plan for which the constraint condition is not satisfied is not selected. That is, even when all of H B0、 H B1、 H B2、 H B3 become the minimum values that can be conceived, when any one of H A0 and H A1 is not zero, the weights are set so that the energy function does not become the minimum value.

[0054] H = α0H A0 + α1H A1 + β0H B0 + β1H B1 + β2H B2 + β3H B3 …(11)

[0055] By performing processing in this way, it is possible to appropriately perform processing using an optimization device of the annealing method. As a result, it is possible to appropriately (accurately and with low load) generate an operation plan for a vehicle that runs carrying passengers. Since the operation plan is generated based on information on past probabilities (the distribution P(S k ), the distribution P(O l ), and the appearance frequency of the passengers 20 (the ride request transmission frequency per unit time) λ), it is possible to appropriately respond to the situation that changes every moment.

[0056] As described above, the operation plan creation device may also have a structure that forms a vehicle allocation management device together with a plan instruction unit that transmits the operation plan to the vehicle. Figure 3This is a structural diagram of the vehicle allocation management device 50. The vehicle allocation management device 50 includes an operation plan formulation device 100 and a plan instruction unit 60. The plan instruction unit 60 is implemented, for example, by a hardware processor such as a CPU executing a program (software), or can be implemented by hardware such as an LSI, ASIC, FPGA, GPU, or SOC, or can be implemented by the cooperation of software and hardware. The plan instruction unit 60 sends an operation plan to at least the vehicle 10 via the network NW. The network NW is a WAN (Wide Area Network), LAN (Local Area Network), the Internet, a Wi-fi network, a cellular network, etc. If the configuration of the vehicle base 30 is such as "which of the multiple open spaces is to be used as the vehicle base" and the configuration of the vehicle base 30 is transmitted to the vehicle 10, the operation plan is achieved.

[0057] The embodiments described above can be expressed as follows.

[0058] An operation plan formulation device that formulates operation plans for multiple vehicles in a service where the vehicle transports passengers from a boarding position to an alighting position, wherein

[0059] The operation plan formulation device includes:

[0060] A storage medium that stores computer-readable instructions; and

[0061] A processor connected to the storage medium,

[0062] The processor performs the following processing by executing the computer-readable instructions:

[0063] Obtain an energy function formula defined as the sum of objective functions related to the operation plan of the vehicle; and

[0064] Calculate the operation plan that minimizes the energy function as the optimal solution,

[0065] The objective functions include:

[0066] One or more first objective functions obtained based on the establishment or non-establishment of constraints; and

[0067] One or more second objective functions for evaluating the achievement degree of the target phenomenon,

[0068] The constraints include that the destination of the vehicle is one place,

[0069] The energy function is obtained as a weighted sum of the one or more first objective functions and the one or more second objective functions.

[0070] The weight given to the one or more first objective functions is larger than the weight given to the one or more second objective functions to such an extent that an operation plan for which the constraint condition does not hold is not selected.

[0071] The specific embodiments of the present invention have been described above using the embodiments, but the present invention is in no way limited to such embodiments, and various modifications and substitutions can be made without departing from the gist of the present invention.

Claims

1. An operation plan formulation device that formulates operation plans for a plurality of vehicles in a service where a vehicle transports passengers from a boarding position to an alighting position, wherein the operation plan formulation device includes: an acquisition unit that acquires an energy function formula defined as the sum of objective functions related to the operation plan of the vehicle; and a calculation unit that calculates the operation plan that minimizes the value of the energy function formula as the optimal solution, the objective function includes: one or more first objective functions obtained based on the establishment or non-establishment of constraints; and one or more second objective functions for evaluating the achievement degree of the target phenomenon, the constraint includes that the destination of the vehicle is one place, the energy function formula is a function formula for obtaining the weighted sum of the one or more first objective functions and the one or more second objective functions, the weight assigned to the one or more first objective functions is larger than the weight assigned to the one or more second objective functions to such an extent that an operation plan where the constraint is not established is not selected.

2. The operation plan formulation device according to claim 1, wherein the operation plan specifies which vehicle goes to which boarding position and which vehicle goes to which vehicle base for a given boarding request.

3. The operation plan formulation device according to claim 2, wherein the operation plan also specifies the configuration of one or more of the vehicle bases.

4. The operation plan formulation device according to claim 1, wherein the target phenomenon includes giving priority to passengers with longer waiting times and picking up more passengers.

5. The operation plan formulation device according to claim 1, wherein the target phenomenon includes shortening the total required time until arriving at the boarding position when picking up the passengers.

6. The operation plan formulation device according to claim 3, wherein the target phenomenon includes arranging more vehicles at vehicle bases near places where the appearance frequency of the passengers is higher.

7. The operation plan formulation device according to claim 2, wherein the target phenomenon includes shortening the total required time until the vehicle arrives at the vehicle base.

8. A vehicle allocation management device, wherein the vehicle allocation management device includes: the operation plan formulation device according to claim 1; and a plan instruction unit that sends the operation plan calculated by the calculation unit to at least the vehicle.

9. An operation plan formulation method that is executed using a computer and formulates operation plans for a plurality of vehicles in a service where a vehicle transports passengers from a boarding position to an alighting position, wherein the operation plan formulation method includes: a process of acquiring an energy function formula defined as the sum of objective functions related to the operation plan of the vehicle; and a process of calculating the operation plan that minimizes the value of the energy function formula as the optimal solution, the objective function includes: one or more first objective functions obtained based on the establishment or non-establishment of constraints; and one or more second objective functions for evaluating the achievement degree of the target phenomenon, the constraint includes that the destination of the vehicle is one place, The energy function formula is a formula for obtaining the weighted sum of the one or more first objective functions and the one or more second objective functions. The weight assigned to the one or more first objective functions is greater than the weight assigned to the one or more second objective functions to such an extent that an operation plan for which the constraint condition does not hold is not selected.

10. A storage medium, which is a computer-readable non-transitory storage medium, stores a program for formulating operation plans for a plurality of vehicles in a service of transporting passengers from a boarding position to an alighting position by a vehicle. Among them, The program causes a computer to execute: A process of obtaining an energy function formula defined as the sum of objective functions related to the operation plan of the vehicle; And A process of calculating an operation plan that minimizes the value of the energy function formula as an optimal solution, The objective functions include: One or more first objective functions obtained based on the establishment or non-establishment of constraint conditions; And One or more second objective functions for evaluating the degree of achievement of an objective phenomenon, The constraint condition includes that the destination of the vehicle is one place, The energy function formula is a formula for obtaining the weighted sum of the one or more first objective functions and the one or more second objective functions. The weight assigned to the one or more first objective functions is greater than the weight assigned to the one or more second objective functions to such an extent that an operation plan for which the constraint condition does not hold is not selected.

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