Delivery plan generating device

Abstract

To provide a delivery plan generating device capable of utilizing an electric vehicle with the performance thereof being taken into consideration.SOLUTION: A plurality of vehicles 10 include: a vehicle 10a that travels by using a battery 11; and a vehicle 10b that travels by using an engine which is a different power source from the battery 11. A processor decides a delivery route of the vehicle 10a and that of the vehicle 10b in such a way that a delivery area A1 is preferentially allocated to the vehicle 10a when the maximum hill-climbing inclination amount of the delivery area A1 is smaller than the maximum hill-climbing inclination amount of a delivery area A3.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] The present disclosure relates to a delivery plan generation device.

Background Art

[0002] International Publication No. 2020 / 090252 (Patent Document 1) discloses a delivery plan generation method for calculating a travelable distance of an electric vehicle based on vehicle information of the electric vehicle for delivering goods and the SOC (State Of Charge) of a secondary battery mounted on the electric vehicle, and generating a delivery plan for the goods using the delivery destination information and the travelable distance of the goods.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] It is assumed that a delivery plan is made not only for electric vehicles as described above but also for vehicles equipped with engines. It is assumed that an electric vehicle has a greater vehicle weight than an engine vehicle of the same class, and there may be a problem that its climbing performance is inferior to that of an engine vehicle. Therefore, when making a delivery plan, it is desirable to consider the climbing situation on the delivery route.

[0005] However, the delivery plan generation method disclosed in Patent Document 1 does not consider a delivery plan that takes into account the performance difference between an electric vehicle and an engine vehicle.

[0006] The present disclosure has been made to solve the above problems, and an object of the present disclosure is to provide a delivery plan generation device that can utilize an electric vehicle based on the performance of the vehicle.

Means for Solving the Problems

[0007] The delivery plan generation device of the present disclosure is a device that generates delivery plans for a plurality of vehicles that deliver packages. The delivery plan generation device includes a processor and a memory that stores programs executable by the processor. The plurality of vehicles includes a first vehicle that travels using an electric motor and a second vehicle that travels using a power source different from the electric motor. When the maximum uphill gradient of the first delivery route is smaller than the maximum uphill gradient of the second delivery route, the processor determines the delivery routes of the first vehicle and the second vehicle such that the first delivery route is preferentially assigned to the first vehicle. According to such a configuration, the first vehicle that travels using an electric motor, for which a poor uphill performance may be assumed, is preferentially assigned to a delivery route with a small maximum uphill gradient, so that the electric vehicle can be utilized in consideration of the performance of the vehicle.

Advantages of the Invention

[0008] According to the present disclosure, an electric vehicle can be utilized in consideration of the performance of the vehicle.

Brief Description of the Drawings

[0009]

Figure 1

Figure 2

Figure 3

Embodiments for Carrying Out the Invention

[0010] Embodiments of the present disclosure will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals and their description will not be repeated.

[0011] FIG. 1 is a diagram schematically showing the overall configuration of the delivery plan generation system 1. The delivery plan generation system 1 includes a plurality of vehicles 10 for delivering packages and a delivery plan generation device 100. The vehicle 10 and the delivery plan generation device 100 can communicate with each other via a communication network.

[0012] The delivery plan generation device 100 is a device that generates delivery plans for a plurality of vehicles 10. The delivery plan generation device 100 performs a process of determining a delivery vehicle from among a plurality of vehicles 10 owned by the delivery company for each of a plurality of delivery areas (delivery routes) managed by the delivery company. The plurality of vehicles 10 includes vehicles with vehicle numbers 1 to 8 (hereinafter also referred to as vehicle [1] to vehicle [8]). The vehicle 10a shown in FIG. 1 is vehicle [1], the vehicle 10b is vehicle [5], and the vehicle 10c is vehicle [8].

[0013] Vehicles [1] to [4] (such as vehicle 10a) are electric vehicles that can be charged from a charging facility (EVSE: Electric Vehicle Supply Equipment), are BEVs (Battery Electric Vehicles) that do not have an engine (internal combustion engine) and run using a battery 11. On the other hand, vehicles [5] to [8] (such as vehicles 10b and 10c) are vehicles that run using an engine as a power source different from the battery 11. Here, the battery 11 corresponds to the "motor" according to the present disclosure, the engine corresponds to the "power source different from the motor" according to the present disclosure, the vehicle 10a corresponds to the "first vehicle" according to the present disclosure, and the vehicle 10b corresponds to the "second vehicle" according to the present disclosure.

[0014] Vehicles [1] to [4] are equipped with a battery 11, an ECU (Electronic Control Unit) 12, a drive unit 13, a DCM (Data Communication Module) 14, an HMI (Human Machine Interface) 15, and a navigation device 17 that processes position information detected by GPS. The battery 11 stores electric power used for the running of vehicles such as Vehicle [1]. The battery 11 is composed of, for example, a lithium-ion battery. The drive unit 13 includes a motor generator and an inverter that drives the motor generator using the electric power of the battery 11 and charges the battery 11 with the regenerative electric power generated by the motor generator. The DCM 14 is a module for communicating with an external device via a communication network, transmits data from the ECU 12 to the external device, and passes on data from the external device to the ECU 12. The HMI 15 is provided near the driver's seat of Vehicle [1] or the like, receives information input by the user and outputs it to the ECU 12, or displays or notifies the user of information from the ECU 12 by voice, and is configured to include, for example, a touch panel display.

[0015] On the other hand, Vehicles [5] to [8] are vehicles that run using an engine. Vehicles such as Vehicle [5] may be a hybrid electric vehicle (HEV) or a plug-in hybrid electric vehicle (PHEV).

[0016] The delivery plan generation device 100 includes a CPU 110, a memory 120 that stores programs executable by the CPU 110, a communication unit 130, and a mass storage device 140. The memory 120 includes a RAM (Random Access Memory) and a ROM (Read Only Memory). The communication unit 130 can communicate with an external device via a communication network. The mass storage device 140 is composed of an HDD (Hard Disk Drive) or an SSD (Solid State Drive) etc., and stores programs and data used by the CPU 110. The CPU 110 executes programs stored in the memory 120 or the mass storage device 140. The CPU 110 corresponds to the "processor" according to the present disclosure.

[0017] FIG. 2 is a diagram for explaining the assignment of delivery routes. The mass storage device 140 stores delivery area information 90, vehicle information 91, vehicle type information 92, and assignment information 93.

[0018] The delivery area information 90 stores the maximum gradient (also referred to as the "maximum uphill gradient amount") of each delivery area (delivery route). When vehicle 10 (any one of vehicles [1] to [8]) is assigned to a delivery area, vehicle 10 travels on a defined delivery route within the assigned delivery area to perform delivery. The gradient amount that is the largest among the slopes on the delivery route is called the "maximum gradient" or the "maximum uphill gradient amount". There are delivery areas A1 to A6. For example, it is recorded in the delivery area information 90 that the maximum gradient of delivery area A5 is θ[5] degrees, and the maximum gradient of delivery area A3 is θ[3] degrees.

[0019] The vehicle information 91 records the correspondence between the vehicle type and the vehicle number. It is recorded in the vehicle information 91 that the vehicle types of vehicles with vehicle numbers 1 to 4 (vehicles [1] to [4]) are T[1], the vehicle types of vehicles with vehicle numbers 5 and 6 (vehicles [5] and [6]) are T[2], and the vehicle types of vehicles with vehicle numbers 7 and 8 (vehicles [7] and [8]) are T[3]. The vehicle number is assigned in S2 of the flowchart in FIG. 3 described later.

[0020] Vehicle type information 92 records the maximum driving force (unit: N), maximum weight (vehicle weight at maximum load, unit: kg), and limit gradient (unit: degree) for each vehicle type. T[1] is a BEV vehicle. T[2] and T[3] are engine vehicles. For example, for T[1], the maximum driving force is F[1] N, the maximum weight is M[1] kg, and the limit gradient is Θ[1] degrees.

[0021] The limit gradient is the maximum gradient amount that vehicle 10 can climb on a slope. The limit gradient is a value determined for each vehicle type of vehicle 10. If the maximum gradient within the delivery area exceeds the limit gradient, it cannot climb the slope, so delivery within the said delivery area cannot be carried out.

[0022] Taking the maximum driving force of vehicle type [i] as F[i], the maximum weight as M[i], the gravitational acceleration as g, and the limit gradient as Θ[i], and considering a safety margin, the equation of motion "maximum driving force F[i] = M[i]g sin Θ[i] + safety margin" holds. From this, the formula "Θ[i] = sin -1 {(F[i] - safety margin) / M[i]g}" is derived. In the present embodiment, it is assumed that F[1] < F[2] < F[3] and Θ[1] < Θ[2] < Θ[3].

[0023] Based on the delivery area information 90, vehicle information 91, and vehicle type information 92, the allocation information 93 records the results of allocating any one of vehicles [1] to [8] to each delivery area. The allocation information 93 records the delivery area No., maximum gradient, delivery area classification, allocated vehicle, and vehicle type of the allocated vehicle corresponding to each delivery area.

[0024] The delivery areas recorded in the delivery area information 90 are sorted in ascending order of the maximum gradient and recorded in the allocation information 93. The maximum gradients are in ascending order of θ[1], θ[2] ··· θ[8]. As a result, the delivery areas are rearranged in the order of A1, A2 ··· A8, and numbers 1 to 8 are assigned as the delivery area No. in ascending order of the maximum gradient and recorded in the allocation information 93.

[0025] Furthermore, for each delivery area, a delivery area classification is determined and recorded in the allocation information 93. The "delivery area classification" is information indicating the vehicle type capable of climbing the steepest slope in the delivery area. By comparing the limit gradient Θ[i] with the maximum gradient θ[j], it is determined what level of vehicle performance or above enables delivery, and this is set as the delivery area classification.

[0026] In the example of FIG. 1, the relationship θ[1] of the maximum gradient in delivery area A1 < Θ[1] of the limit gradient of the BEV vehicle of vehicle type T[1] such as vehicle 10a < θ[3] of the maximum gradient in delivery area A3 < Θ[2] of the limit gradient of the engine vehicle of vehicle type T[2] such as vehicle 10b < θ[6] of the maximum gradient in delivery area A6 < Θ[3] of the limit gradient of the engine vehicle of vehicle type T[3] such as vehicle 10c holds.

[0027] Returning to FIG. 2, for example, if the vehicle type is T[1] or above (T[1] to T[3]), the maximum gradient θ[1] of delivery area A1 can be climbed, so the delivery area classification of delivery area A1 is set as "T[1] or above". Similarly, if the vehicle type is T[2] or above (T[2], T[3]), the maximum gradient θ[3] of delivery area A3 can be climbed, so the delivery area classification of delivery area A3 is set as "T[2] or above".

[0028] When the maximum gradient (maximum uphill gradient amount) of the first delivery route is smaller than the maximum gradient of the second delivery route, the delivery route generation device 100 is configured to determine the delivery routes of the first vehicle that travels using an electric motor and the second vehicle that travels using a power source different from the electric motor such that the first delivery route is preferentially allocated to the first vehicle. The allocated vehicle corresponding to the delivery route is recorded in the allocation information 93. For example, the allocated vehicle for delivery area A1 is vehicle [1] (vehicle No. 1 vehicle) of vehicle type T[1] which is a BEV vehicle. The allocated vehicle for delivery area A3 is vehicle [5] (vehicle type T2: engine vehicle). When determining the allocated vehicle, information such as the number of delivery areas, delivery area No., maximum gradient within the delivery area, number of delivery vehicles, number of delivery vehicle types, vehicle number, maximum driving force, and maximum vehicle weight is used.

[0029] For example, when the maximum uphill gradient Θ[1] of the delivery area A1 is smaller than the maximum uphill gradient Θ[3] of the delivery area A3, the delivery route planning device 100 determines the delivery routes of the vehicle [1] and the vehicle [5] so that the delivery area A1 is preferentially assigned to the vehicle [1]. Since Θ[1] < Θ[3], the vehicle [1] (BEV) is assigned to the delivery area A1, and the vehicle [3] (engine) is assigned to the delivery area A3. The delivery area A1 corresponds to the "first delivery route" according to the present disclosure, and the delivery area A3 corresponds to the "second delivery route" according to the present disclosure.

[0030] FIG. 3 is a flowchart showing the processing procedure of the processing executed by the generation system. Hereinafter, in S1 to S8, the maximum gradient that can be climbed is calculated. First, in S1, the delivery route planning device 100 sorts the vehicle type information 92 in ascending order of the maximum driving force. In S2, the delivery route planning device 100 assigns vehicle numbers in ascending order (refer to the vehicle information 91).

[0031] In S3, the delivery route planning device 100 sets the loop variable i = 1 for delivery area classification. In S4, as a loop determination, the delivery route planning device 100 determines whether i ≤ the number of delivery vehicle types N (= 3). If the delivery route planning device 100 determines YES in S4, the process proceeds to S5. On the other hand, if the delivery route planning device 100 determines NO in S4, the process proceeds to S9.

[0032] In S5, the delivery route planning device 100 refers to the maximum driving force F[i]. In S6, the delivery route planning device 100 refers to the maximum weight M[i]. In S7, the delivery route planning device 100 calculates the maximum gradient Θ[i] using the formula Θ[i] = sin -1 {(F - safety margin) / Mg} (refer to the vehicle type information 92). In S8, as loop processing, the delivery route planning device 100 sets i = i + 1 and returns the process to S4. By this loop, the maximum gradients of the vehicle types T[1] to T[3] are calculated.

[0033] Hereinafter, in S9 to S20, delivery area classification is performed. In S9, the delivery plan generation device 100 sorts the delivery area information 90 in ascending order of the gradient within the area. In S10, the delivery plan generation device 100 assigns delivery area numbers in ascending order of the gradient (refer to the allocation information 93). In S11, the delivery plan generation device 100 sets the loop variable j for delivery area setting to 1. In S12, as a loop determination, the delivery plan generation device 100 determines whether j ≤ the number of delivery areas M (= 6). In S12, if the determination is YES, the process proceeds to S13. On the other hand, in S12, if the determination is NO, this process ends. As a result, for delivery areas A1 to A6, delivery area classification and vehicle allocation are performed.

[0034] In S13, the delivery plan generation device 100 refers to the maximum gradient θ[j] within the delivery area. In S14, the delivery plan generation device 100 sets the variable i for area classification to 1. In S15, as a loop determination, the delivery plan generation device 100 determines whether i ≤ the number of delivery vehicle types N. In S15, if the determination is YES, the process proceeds to S16. On the other hand, in S15, if the determination is NO, the process proceeds to S21. Through this loop, for each delivery area, the vehicle types capable of climbing the maximum gradient are determined.

[0035] The delivery plan generation device 100 determines whether i = 1 in S16. When the delivery plan generation device 100 makes a YES determination in S16, it determines whether θ[j] < Θ[i] in S17. When the delivery plan generation device 100 makes a YES determination in S17, in S20, the delivery area classification[j] is set to vehicle type T[i] or higher. For example, when i = 1 and j = 1, since θ[1] of delivery area A1 < the limit gradient Θ[1] of vehicle type T[1], the delivery area classification[1] of delivery area A1 is set to vehicle type T[1] or higher (see Figures 1 and 2). On the other hand, when the delivery plan generation device 100 makes a NO determination in S16, it determines whether Θ[i - 1] < θ[j] < Θ[i] in S18. When the delivery plan generation device 100 makes a YES determination in S18, in S20, the delivery area classification[j] is set to vehicle type T[i] or higher. For example, when i = 2 and j = 3, since the limit gradient Θ[1] of vehicle type T[1] < the maximum gradient θ[3] of delivery area A3 < the limit gradient Θ[2] of vehicle type T[2], the delivery area classification[3] of delivery area A3 is set to vehicle type T[2] or higher (see Figures 1 and 2).

[0036] When the delivery plan generation device 100 makes a NO determination in S17 or S18, in S19, as loop processing, i = i + 1 and the process returns to S15. Thereby, sequential determination is made for vehicle types T[1] to T[3]. The delivery plan generation device 100 sets the delivery area classification[j] to vehicle type T[N + 1] in S21. In this case, it means that there is no vehicle (vehicle type) that can make the delivery.

[0037] Thereafter, in S22 and 23, vehicle allocation for each delivery area is performed. The delivery plan generation device 100 allocates in ascending order of the smallest maximum driving force F among the vehicle types that can climb slopes in S22. The delivery plan generation device 100 sets j = j + 1 as loop processing and returns the process to S12 in S23. Thereby, processing is performed for each of delivery areas A1 to A6.

[0038] For example, as shown in FIGS. 2 and 3, for delivery area A1, among vehicle types T[1] or above that can climb slopes, vehicle [1] of the BEV vehicle with the smallest maximum driving force F is allocated. Alternatively, in S22, it may be allocated in ascending order of the minimum gradient Θ among vehicle types that can climb slopes. Also, for delivery area A3, among vehicle types T[2] or above that can climb slopes, vehicle [5] of the engine vehicle with the smallest maximum driving force F is allocated. Further, for delivery area A5, among vehicle types T[2] or above that can climb slopes, vehicle [7] of the engine vehicle with the smallest maximum driving force F is allocated. Here, since all vehicles 10 of vehicle type T[2] have been allocated, vehicle [7] is selected from among vehicles 10 of vehicle type T[3].

[0039] In this way, when the maximum gradient of delivery area A1 is smaller than that of delivery area A3, for example, the delivery planning device 100 determines the delivery routes of vehicle 10a (BEV vehicle [1]) and vehicle 10b (engine vehicle [5]) so that delivery area A1 is preferentially allocated to vehicle 10a. When using an electric vehicle as a delivery vehicle, compared with an engine vehicle, the vehicle weight is heavier and the slope climbing performance may be inferior. In this case, depending on the gradient of the slope road in the delivery area, it may not be able to climb the slope and may cause problems in delivery. Also, when making a delivery plan, there is a possibility that an electric vehicle may be allocated to an area where slope climbing is impossible. At the time of delivery planning, it is configured to appropriately allocate electric vehicles and engine vehicles according to the gradient of the delivery area, and by preferentially allocating electric vehicles, for which inferior slope climbing performance is assumed, to delivery routes with a small maximum slope climbing amount, electric vehicles can be utilized based on the performance of the vehicles.

[0040] The embodiments disclosed this time should be considered to be illustrative in all respects and not restrictive. The scope of the present disclosure is indicated by the claims rather than the description of the above-described embodiments, and is intended to include all modifications within the meaning and scope equivalent to the claims.

Explanation of Reference Numerals

[0041] 1 Generation system, 10, 10a to 10c Vehicles, 11 Battery, 12 ECU, 13 Drive unit, 14 DCM, 15 HMI, 17 Navigation device, 90 Delivery area information, 91 Vehicle information, 92 Vehicle type information, 93 Allocation information, 100 Generation device, 110 CPU, 120 Memory, 130 Communication unit, 140 Mass storage device.

Claims

Claim 1 A delivery plan generation device that generates delivery plans for a plurality of vehicles for delivering goods, a processor, and a memory that stores a program executable by the processor, wherein the plurality of vehicles includes a first vehicle that travels using an electric motor and a second vehicle that travels using a power source different from the electric motor, and the processor determines delivery routes for the first vehicle and the second vehicle such that when the maximum uphill gradient of a first delivery route is smaller than the maximum uphill gradient of a second delivery route, the first delivery route is preferentially assigned to the first vehicle. A delivery plan generation device.

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