Information processing apparatus

Abstract

This invention relates to an information processing apparatus. The objective of this invention is to provide an effective technique for reducing the environmental impact when delivery is shared between electric vehicles and internal combustion engine vehicles. The control unit of the information processing apparatus sets multiple combinations of routes for electric vehicles and internal combustion engine vehicles, assuming that goods are transported to multiple delivery destinations using both electric and internal combustion engine vehicles. The control unit calculates costs corresponding to the transport distance, weight, and CO2 emission rate of the goods for each of the multiple combinations. The control unit generates a delivery plan based on the combination with the lowest calculated cost among the multiple combinations.

Description

Technical Field

[0001] This invention relates to an information processing device. Background Technology

[0002] A route selection system for an electric truck is known, which estimates the variation information of the total load weight during transportation based on transportation weight information including initial weight information of the initial load loaded at the transportation start point and loading and unloading weight information of the goods loaded and unloaded at the cargo loading and unloading point, and selects the optimal route based on the estimated variation information (e.g., see Patent Document 1).

[0003] Patent Document 1: Japanese Patent Application Publication No. 2018-17672 Summary of the Invention

[0004] The purpose of this invention is to provide an effective technology for reducing the environmental impact when electric vehicles and internal combustion engine vehicles share the delivery load.

[0005] This invention can also be viewed as an information processing apparatus for generating delivery plans for distributing goods to multiple delivery destinations. In this case, the information processing apparatus may include a control unit configured to perform the following processing:

[0006] Multiple combinations of routes for electric vehicles and routes for internal combustion engine vehicles are set up under the assumption that electric vehicles and internal combustion engine vehicles share the responsibility of transporting the goods to multiple delivery destinations.

[0007] For each of the aforementioned combinations, calculate the costs corresponding to the transport distance, weight, and CO2 emission rate of the goods; and

[0008] The delivery plan is generated based on the combination with the lowest cost calculated from among the multiple combinations.

[0009] In addition, the present invention can also be regarded as an information processing method in which a computer performs the processing of the above-mentioned information processing device, or as a program for causing a computer to perform the information processing method, or as a non-temporary storage medium for storing the program.

[0010] Invention Effects

[0011] According to the present invention, an effective technology is provided for reducing the environmental impact when electric vehicles and internal combustion engine vehicles share the delivery load. Attached Figure Description

[0012] Figure 1 This is a schematic diagram illustrating an example of a system to which the information processing apparatus of the present invention is applied.

[0013] Figure 2 This is a diagram illustrating an example of vehicle information in an implementation method.

[0014] Figure 3 This is a diagram illustrating an example of delivery destination information in an implementation method.

[0015] Figure 4 This is a diagram illustrating an example of a method for setting up delivery combinations in an implementation scheme.

[0016] Figure 5 This is a flowchart illustrating an example of a processing routine executed in the delivery management device of the implementation method. Detailed Implementation

[0017] During the transition to electrification in the transportation industry, an increase in operators owning both battery electric vehicles (BEVs) and internal combustion engine vehicles is expected. These operators may need to develop delivery plans that distribute goods between electric and internal combustion engine vehicles. In this context, measures to minimize environmental impact are required.

[0018] In contrast, the information processing apparatus of this invention generates a delivery plan for delivering goods to multiple delivery destinations. Specifically, the control unit of the information processing apparatus sets multiple combinations of routes for electric vehicles and routes for internal combustion engine vehicles, assuming that electric vehicles and internal combustion engine vehicles share the responsibility of transporting goods to multiple delivery destinations. The control unit calculates the costs corresponding to the transportation distance of the goods, the weight of the goods, and the CO2 emission rate for each of the multiple combinations. In one example, this cost can be calculated using a modified ton-kilometer method. Then, the control unit generates a delivery plan based on the combination with the lowest calculated cost among the multiple combinations.

[0019] According to the present invention, the environmental impact when electric vehicles and internal combustion engine vehicles share the delivery load can be minimized.

[0020] Hereinafter, specific embodiments of the present invention will be described based on the accompanying drawings. Unless otherwise stated, the hardware structures, module structures, functional structures, etc., described in the following embodiments are not intended to limit the scope of the disclosed technology.

[0021] <Implementation Method>

[0022] In this embodiment, examples of the information processing apparatus according to the present invention applicable to a system using electric vehicles and internal combustion engine vehicles for goods delivery will be described.

[0023] [System Architecture]

[0024] Figure 1This diagram schematically illustrates an example of the general structure of System 1 in this embodiment. System 1 in this embodiment is configured to include one or more electric vehicles 10A, one or more internal combustion engine vehicles 10B, and a delivery management device 20. The one or more electric vehicles 10A, one or more internal combustion engine vehicles 10B, and the delivery management device 20 are interconnected via a network N1. In one example, network N1 may include a world-scale public communication network such as the Internet, i.e., a wide area network (WAN), and / or a wireless communication network such as Wi-Fi (registered trademark).

[0025] One or more electric vehicles 10A and one or more internal combustion engine vehicles 10B are provided at the distribution center of the delivery service provider. Electric vehicle 10A is a battery electric vehicle (BEV) for freight transport, powered by an electric motor, and configured to transmit information such as battery level to the delivery management device 20 via network N1. Internal combustion engine vehicle 10B is an internal combustion engine vehicle (ICEV) for freight transport, powered by an internal combustion engine, and configured to transmit information such as fuel level to the delivery management device 20 via network N1. Furthermore, in the following description, when it is not necessary to distinguish between electric vehicle 10A and internal combustion engine vehicle 10B, both electric vehicle 10A and internal combustion engine vehicle 10B may sometimes be referred to as vehicle 10.

[0026] (Distribution management device)

[0027] The delivery management device 20 in this embodiment is a computer operated by an operator providing goods delivery services or an operator commissioned by that operator, and is an example of the information processing device involved in this invention. Figure 1 As shown, the delivery management device 20 is configured to include a control unit 201, a storage unit 202, an input / output device 203, and a communication I / F 204, etc.

[0028] The control unit 201 executes a dedicated program stored in the storage unit 202 to perform the various functions described later. As one example, the control unit 201 may be configured to include a hardware processor such as a CPU or GPU. As another example, the control unit 201 may also be configured to include RAM, ROM, and cache memory in addition to a hardware processor. Furthermore, some or all of the functions of the delivery management device 20 may be implemented using hardware circuitry such as an ASIC or FPGA.

[0029] Storage unit 202 is configured to include an auxiliary storage device and store various types of information. Additionally, storage unit 202 may be a storage area built into the auxiliary storage device. The information stored in storage unit 202 includes, in addition to the operating system, a dedicated application for generating delivery plans for goods and the data used by that application. Furthermore, the data stored in storage unit 202 includes vehicle information related to both the electric vehicle 10A and the internal combustion engine vehicle 10B, information related to the delivery destination of goods transported from the distribution center (delivery destination information), and map information including road maps of the areas served by the distribution center.

[0030] The input / output device 203 receives input operations from the operator of the delivery management device 20 and provides prompts to the operator. The input / output device 203 is configured to include an input device and an output device. In one example, the input device may include a touch panel or buttons capable of inputting characters or other symbols, and a microphone capable of inputting sound. Furthermore, in one example, the output device may include a display and a speaker.

[0031] Communication I / F 204 includes a communication interface for connecting the delivery management device 20 to the network N1. In one example, communication I / F 204 may include a communication interface for mobile communication (e.g., 3G, LTE, 5G, 6G, etc.). In this embodiment, communication I / F 204 communicates with two or more vehicles 10 via network N1.

[0032] (Vehicle Information)

[0033] Here, the vehicle information stored in the storage unit 202 of the delivery management device 20 will be explained. Figure 2 This is a diagram illustrating an example of vehicle information in this embodiment. Figure 2In the example shown, the vehicle information consists of a table with records corresponding to each of all vehicles 10 deployed in the distribution center. Each record corresponding to vehicle 10 has multiple fields, including vehicle ID, type, capacity, consumption rate, and maximum load capacity. The vehicle ID field records the identifier (vehicle ID) of each vehicle 10. The type field records the type of prime mover for each vehicle 10. Specifically, the category field of the record corresponding to electric vehicle 10A records information indicating that the prime mover is an electric motor. Similarly, the category field of the record corresponding to internal combustion engine vehicle 10B records information indicating that the prime mover is an internal combustion engine. The capacity field records the capacity of the drive battery or fuel tank installed in each vehicle 10. Specifically, the capacity field of the record corresponding to electric vehicle 10A records information indicating the capacity (kWh) of the drive battery installed in that electric vehicle 10A. And the capacity field of the record corresponding to internal combustion engine vehicle 10B records information indicating the capacity (L) of the fuel tank installed in that internal combustion engine vehicle 10B. The energy consumption rate field records information indicating the energy consumption rate of each vehicle 10. Specifically, the energy consumption rate field for the record corresponding to electric vehicle 10A records information indicating the electricity consumption rate (km / kWh) of that electric vehicle 10A. Furthermore, the energy consumption rate field for the record corresponding to internal combustion engine vehicle 10B records information indicating the fuel consumption rate (km / L) of that internal combustion engine vehicle 10B. In one example, the information recorded in the energy consumption rate field can be the average of statistically collected past actual values ​​of electricity consumption rate or fuel consumption rate. In another example, the information recorded in the energy consumption rate field can be the minimum value of statistically collected past actual values ​​of electricity consumption rate or fuel consumption rate. The statistically collected past actual values ​​of electricity consumption rate or fuel consumption rate can be the actual values ​​of electricity consumption rate or fuel consumption rate when each vehicle 10 is operating with the same amount of cargo as its maximum load capacity. The maximum load capacity (t) of each vehicle 10 is recorded in the maximum load capacity field.

[0034] (Delivery destination information)

[0035] Next, the delivery destination information stored in the storage unit 202 of the delivery management device 20 will be explained. Figure 3 This is a diagram illustrating an example of delivery destination information in this embodiment. Figure 3In the example shown, the delivery destination information is categorized into multiple tables based on delivery time zones. Each table contains records corresponding to each delivery destination. Each record corresponding to a delivery destination has multiple fields, including delivery destination, location, and quantity of goods. The delivery destination field records the name of each delivery destination. The location field records the location information of each delivery destination. In one example, the information recorded in the location field could be information representing the location (coordinates) on a road map included in the map information of storage unit 202. The quantity of goods field records the total weight (t) of the goods transported to each delivery destination. Additionally, as... Figure 3 The delivery destination information shown is entered by the operator of the delivery management device 20 each time the delivery center receives a delivery request.

[0036] (Generation of delivery plans)

[0037] Next, the generation of the delivery plan based on the delivery management device 20 will be described. In this embodiment, the delivery plan is generated according to the delivery time slot. Specifically, in the delivery management device 20, the control unit 201 accesses the delivery information in the storage unit 202 and determines a table corresponding to the delivery time slots to be targeted. The control unit 201 extracts one or more route candidates for each delivery destination based on the information registered in the determined table and the map information in the storage unit 202. The "route candidate" referred to here is a set of road links connecting the delivery center and the delivery destination. This extraction of route candidates can be performed using known techniques. In one example, the route connecting the delivery center and the delivery destination with the shortest distance (shortest route) and one or more detour routes with a distance longer than the shortest route (excluding detour routes whose distance difference from the shortest route is greater than a threshold (e.g., a few km to about 10 km)) can be extracted as route candidates. However, for delivery destinations that have no routes other than the shortest route, only the shortest route needs to be extracted.

[0038] If more than one route candidate is extracted for each delivery destination, the control unit 201 of the delivery management device 20 calculates the cost of each route candidate. In this embodiment, the cost is a value that serves as an indicator of the environmental impact caused by the transportation of goods. In one example, the cost can be calculated based on a modified ton-kilometer method using parameters such as the distance (km) of each route candidate, the weight (t) of the goods transported by the vehicle 10 along each route candidate, and the CO2 emission rate of each vehicle 10. Alternatively, the cost of each route candidate can also be calculated using methods other than the modified ton-kilometer method (e.g., the existing ton-kilometer method).

[0039] In this embodiment, for each route candidate, two costs are calculated: the cost assuming electric vehicle 10A travels on each route candidate, and the cost assuming internal combustion engine vehicle 10B travels on each route candidate. However, for route candidates where the distance between the distribution center and the delivery destination exceeds the driving range of either electric vehicle 10A or internal combustion engine vehicle 10B, the cost is calculated only for either electric vehicle 10A or internal combustion engine vehicle 10B.

[0040] Furthermore, the control unit 201 of the delivery management device 20 sets multiple combinations for situations where delivery to multiple destinations is shared by electric vehicle 10A and internal combustion engine vehicle 10B; that is, combinations of route candidates for electric vehicle 10A and route candidates for internal combustion engine vehicle 10B. Here, refer to... Figure 4 An example of a method for setting the above combinations will be explained. Figure 4 In the example shown, one electric vehicle 10A (hereinafter, sometimes referred to as "target electric vehicle 10A") and one internal combustion engine vehicle 10B (hereinafter, sometimes referred to as "target internal combustion engine vehicle 10B") are used to deliver goods to two destinations, delivery destination A and delivery destination B. The total weight of the goods transported to delivery destination A is 2t, and the total weight of the goods transported to delivery destination B is 3t. Furthermore, the only route candidate for delivery destination A is route R1, while the two route candidates for delivery destination B are routes R2 and R3. Additionally, the target electric vehicle 10A and the target internal combustion engine vehicle 10B are selected from vehicles 10 that do not have a set operating schedule during the delivery period. The method for selecting the target electric vehicle 10A and the target internal combustion engine vehicle 10B can be appropriately determined according to the implementation method. As an example, the electric vehicle 10A with the most remaining battery capacity and the internal combustion engine vehicle 10B with the most remaining fuel capacity may also be selected from the vehicles 10 that do not have a set operating schedule during the delivery period.

[0041] If extract Figure 4 For routes R1-R3 illustrated, the control unit 201 of the delivery management device 20 calculates the distance of each route. Specifically, the control unit 201 accesses the delivery destination information in the storage unit 202 and extracts the location information of delivery destination A and delivery destination B. Based on the location information of delivery destination A and delivery destination B and the map information in the storage unit 202, the control unit 201 calculates the distance of each of routes R1-R3. Figure 4 In the example shown, the distance of route R1 is 35km, the distance of route R2 is 38km, and the distance of route R3 is 42km.

[0042] Furthermore, the control unit 201 of the delivery management device 20 communicates with the electric vehicle 10A and the internal combustion engine vehicle 10B responsible for this delivery via communication I / F 204, thereby obtaining the remaining battery power of the target electric vehicle 10A and the remaining fuel power of the target internal combustion engine vehicle 10B. The control unit 201 accesses the vehicle information in the storage unit 202 and extracts the energy consumption rate of the target electric vehicle 10A and the fuel consumption rate of the target internal combustion engine vehicle 10B. The control unit 201 calculates the driving range of the target electric vehicle 10A based on the remaining battery power and energy consumption rate of the target electric vehicle 10A. Similarly, the control unit 201 calculates the driving range of the target internal combustion engine vehicle 10B based on the remaining fuel power and fuel consumption rate of the target internal combustion engine vehicle 10B. Figure 4 In the example shown, the remaining battery capacity and energy consumption rate of the target electric vehicle 10A are 20 kWh and 4 km / kWh, respectively. Therefore, the driving range of the target electric vehicle 10A is approximately 80 km. Furthermore, the remaining fuel capacity and fuel consumption rate of the target internal combustion engine vehicle 10B are 30 L and 6 km / L, respectively. Therefore, the driving range of the target internal combustion engine vehicle 10B is approximately 180 km.

[0043] Here, when delivering goods to destination A using route R1, a range of over 70km is required to travel to and from route R. In contrast, both the target electric vehicle 10A and the target internal combustion engine vehicle 10B have a range of over 70km, thus enabling them to deliver goods to destination A using route R1.

[0044] Furthermore, when delivering goods to destination B using route R2, a range of over 76km is required to travel to and from destination B via route R2. In contrast, both the target electric vehicle 10A and the target internal combustion engine vehicle 10B have a range of over 76km, thus enabling them to deliver goods to destination B using route R2.

[0045] Furthermore, when delivering goods to destination B using route R3, a range of at least 84 km is required for a round trip on route R3. In comparison, the target internal combustion engine vehicle 10B has a range of at least 84 km, while the target electric vehicle 10A has a range of less than 84 km. Therefore, delivery to destination B using route R3 can only be carried out by the target internal combustion engine vehicle 10B. Therefore, in Figure 4 In the example shown, the control unit 201 calculates the costs corresponding to the target electric vehicle 10A and the target internal combustion engine vehicle 10B for routes R1 and R2, and only calculates the cost corresponding to the target internal combustion engine vehicle 10B for route R3.

[0046] Next, the control unit 201 of the delivery management device 20 sets the combination of vehicle and route candidates (hereinafter, sometimes referred to as "delivery combination") in the case where delivery to delivery destination A and delivery destination B are shared by the target electric vehicle 10A and the target internal combustion engine vehicle 10B. Figure 4 In the example shown, the electric vehicle 10A cannot perform delivery to the delivery destination B using route R3, so the following 3 delivery combinations are extracted.

[0047] (Combination A) Route R1: Electric vehicle 10A; Route R2: Internal combustion engine vehicle 10B

[0048] (Combination B) Route R1: Target internal combustion engine vehicle 10B; Route R2: Target electric vehicle 10A

[0049] (Combination C) Route R1: Electric vehicle 10A; Route R3: Internal combustion engine vehicle 10B

[0050] If multiple delivery combinations are set, the control unit 201 of the delivery management device 20 calculates the total cost of each of the multiple delivery combinations. Here, if the cost of the target electric vehicle 10A round trip route R1 is set as Cst1, the cost of the target electric vehicle 10A round trip route R2 is set as Cst2, the cost of the target internal combustion engine vehicle 10B round trip route R1 is set as Cst3, the cost of the target internal combustion engine vehicle 10B round trip route R2 is set as Cst4, and the cost of the target internal combustion engine vehicle 10B round trip route R3 is set as Cst5, then the costs of combination A, combination B, and combination C are as follows.

[0051] (Cost of combination A) = Cst1 + Cst4

[0052] (Cost of combination B) = Cst3 + Cst2

[0053] (Cost of combination C) = Cst1 + Cst5

[0054] If the total cost of each of the multiple delivery combinations is calculated, the control unit 201 of the delivery management device 20 determines the delivery combination with the lowest total cost among the multiple delivery combinations. Then, the control unit 201 generates a delivery plan corresponding to the delivery combination with the lowest total cost. As an example, among the above three delivery combinations, if combination A has the lowest total cost, a delivery plan is generated that includes a timetable for the target electric vehicle 10A to deliver goods to the delivery destination A using route R1 and a timetable for the target internal combustion engine vehicle 10B to deliver goods to the delivery destination B using route R2. The generated delivery plan can be displayed to the operator through the input / output device 203 of the delivery management device 20, or it can be sent to the terminal used by the driver of the target electric vehicle 10A and the target internal combustion engine vehicle 10B.

[0055] (Processing flow)

[0056] Here, based on Figure 5 The process flow executed in the delivery management device 20 in this embodiment will be explained. Figure 5 This is a flowchart illustrating the processing routines executed in the delivery management device 20 at a predetermined cycle (e.g., every day). Regarding... Figure 5 The processing of steps S101 to S110 in the processing routine is performed for delivery of all delivery time slots.

[0057] In step S101, the control unit 201 of the delivery management device 20 extracts route candidates for the delivery to be targeted. Specifically, the control unit 201 accesses the delivery information in the storage unit 202 and determines a table corresponding to the delivery time slots to be targeted. Based on the information registered in the determined table and the map information in the storage unit 202, the control unit 201 extracts one or more route candidates.

[0058] In step S102, the control unit 201 communicates with the target electric vehicle 10A and the target internal combustion engine vehicle 10B via communication I / F 204, thereby obtaining the remaining battery capacity of the target electric vehicle 10A and the remaining fuel capacity of the target internal combustion engine vehicle 10B.

[0059] In step S103, the control unit 201 calculates the driving range of both the target electric vehicle 10A and the target internal combustion engine vehicle 10B. Specifically, the control unit 201 first accesses the vehicle information in the storage unit 202 to obtain the energy consumption rate of the target electric vehicle 10A and the fuel consumption rate of the target internal combustion engine vehicle 10B. Next, the control unit 201 calculates the driving range of the target electric vehicle 10A based on the remaining battery level obtained in step S102 and the energy consumption rate obtained from the vehicle information. Furthermore, the control unit 201 calculates the driving range of the target internal combustion engine vehicle 10B based on the remaining fuel level obtained in step S102 and the fuel consumption rate obtained from the vehicle information.

[0060] In step S104, the control unit 201 determines the route candidates extracted in step S101 that are excluded from the cost calculation objects for the target electric vehicle 10A and / or the internal combustion engine vehicle 10B. Here, if there is a route candidate extracted in step S101 with a distance longer than the driving range of the target electric vehicle 10A, it is excluded from the cost calculation objects assuming the target electric vehicle 10A travels that route candidate. Furthermore, if there is a route candidate extracted in step S101 with a distance longer than the driving range of the target internal combustion engine vehicle 10B, it is excluded from the cost calculation objects assuming the target internal combustion engine vehicle 10B travels that route candidate.

[0061] In step S105, the control unit 201 calculates the cost (cost of target electric vehicle 10A and cost of target internal combustion engine vehicle 10B) for each of the route candidates not excluded in step S104, based on vehicle type (electric vehicle and internal combustion engine vehicle). In this embodiment, as described above, the cost of each route candidate is calculated using a modified ton-kilometer method, which uses the distance (km) of each route candidate, the weight (t) of the cargo carried by the vehicle 10 when traveling on each route candidate, and the CO2 emission rate of each vehicle 10 as parameters.

[0062] In step S106, the control unit 201 sets the combination of vehicle and route candidates (delivery combination) when the delivery to the delivery destination is shared by the target electric vehicle 10A and the target internal combustion engine vehicle 10B. The delivery combination is set through the aforementioned... Figure 4 The method described in the instructions shall be used to perform the action.

[0063] In step S107, the control unit 201 calculates the total cost for each delivery combination set in step S106 using the cost calculated in step S105. The total cost calculation is performed using the aforementioned... Figure 4 The method described in the instructions shall be used to perform the action.

[0064] In step S108, the control unit 201 determines the delivery combination with the lowest total cost based on the total cost of each delivery combination calculated in step S107.

[0065] In step S109, the control unit 201 generates a delivery plan for the delivery combination determined to have the lowest total cost in step S108. Specifically, the control unit 201 generates a delivery plan that includes the following schedules: a schedule for the electric vehicle 10A to deliver goods to the delivery destination along the route set by the delivery combination; and a schedule for the internal combustion engine vehicle 10B to deliver goods to the delivery destination B along the route set by the delivery combination.

[0066] In step S110, the control unit 201 outputs the delivery plan generated in step S108. This output includes displaying the generated delivery plan to the operator via the input / output device 203 of the delivery management device 20 and / or sending the generated delivery plan to the terminals used by the drivers of the target electric vehicle 10A and the target internal combustion engine vehicle 10B.

[0067] If the generation and output of delivery plans for all deliveries within a specific delivery timeframe are completed, then Control Unit 201 will cease execution. Figure 5 The processing routine.

[0068] According to this embodiment, when electric vehicle 10A and internal combustion engine vehicle 10B share the responsibility of transporting goods to multiple delivery destinations, a delivery plan corresponding to the delivery combination that minimizes the total cost can be generated. As a result, the environmental impact when electric vehicle 10A and internal combustion engine vehicle 10B share the responsibility of transporting goods to multiple delivery destinations can be minimized.

[0069] (Variation example)

[0070] In the foregoing embodiments, an example of generating a delivery plan using the cost based on the modified ton-kilometer method was described. However, a modified cost based on the modified ton-kilometer method can also be used to generate a delivery plan. That is, for route candidates that include uphill sections, a correction can be made by multiplying a first coefficient greater than 1 by the cost calculated using the modified ton-kilometer method; for route candidates that include downhill sections, a correction can be made by multiplying a second coefficient greater than 0 and less than 1 by the cost calculated using the modified ton-kilometer method.

[0071] The first coefficient can be set to a larger value for longer uphill sections with steeper gradients. The second coefficient can be set to a smaller value for longer downhill sections with steeper gradients. Furthermore, the first and second coefficients can be set to different values ​​for the electric vehicle 10A and the internal combustion engine vehicle 10B. In this case, the first coefficient can be set to a value greater for the electric vehicle 10A than that for the internal combustion engine vehicle 10B. And the second coefficient can be set to a value less for the electric vehicle 10A than that for the internal combustion engine vehicle 10B. This is because, compared to the internal combustion engine vehicle 10B, the energy consumption of the electric vehicle 10A varies more significantly due to gradient.

[0072] In this variation, the total cost of each of the multiple delivery combinations is calculated using the cost modified as described above. Then, a delivery plan is generated based on the delivery combination with the minimum total cost. This allows for a more reliable reduction in the environmental impact when electric vehicles 10A and internal combustion engine vehicles 10B share the transportation of goods to multiple delivery destinations.

[0073] <Other>

[0074] The above-described embodiments are merely examples, and the present invention can be implemented with appropriate modifications without departing from its spirit. Furthermore, the present invention can also be implemented by supplying a computer program (information processing program) with functional installation as described in the above embodiments to a computer, which can then read and execute the program using one or more processors. This computer program can be provided to the computer via a non-transitory computer-readable storage medium connectable to the computer's system bus, or it can be provided to the computer via a network.

[0075] Symbol Explanation

[0076] 10A - Electric vehicles, 10B - Internal combustion engine vehicles, 20 - Delivery management device, 201 - Control unit, 202 - Storage unit, 203 - Input / output device, 204 - Communication I / F.

Claims

1. An information processing apparatus that generates a delivery plan for distributing goods to multiple delivery destinations, characterized in that it includes a control unit configured to perform the following processing: Multiple combinations of routes for electric vehicles and routes for internal combustion engine vehicles are set up under the assumption that electric vehicles and internal combustion engine vehicles share the responsibility of transporting the goods to multiple delivery destinations. Calculate the costs corresponding to the transport distance, weight, and CO2 emission rate of the goods for each of the multiple combinations; and The delivery plan is generated based on the combination with the lowest cost calculated from among the multiple combinations.

2. The information processing device according to claim 1, characterized in that, Setting multiple of the aforementioned combinations includes excluding combinations of routes in which at least one of the electric vehicle and the internal combustion engine vehicle travels a distance longer than the vehicle's driving range.

3. The information processing device according to claim 1, characterized in that, The costs of the operation include: When the route included in the combination contains uphill sections, a modification is made in a manner that increases cost compared to the case where it does not contain uphill sections; and If the route included in the combination contains downhill sections, it is modified in a way that reduces costs compared to the case where it does not contain downhill sections.

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