Information processing method, information processing device, and information processing program

Abstract

The server acquires a departure point of the electric vehicle and a current remaining power amount of a storage battery provided in the electric vehicle, estimates a power consumption amount when the electric vehicle moves from the departure point to each of a plurality of grid regions obtained by dividing the map, and determines a power consumption amount of the electric vehicle on the basis of the current remaining power amount and the power consumption amount. The amount of power remaining after movement when the electric vehicle moves from the departure point to each of the plurality of mesh regions is calculated, and an image is generated in which the color or brightness in a rendering region formed by connecting representative points of the four mesh regions changes in stages in accordance with the amount of power remaining after movement. Information obtained by superimposing the generated image on a map is output.

Description

Technical Field

[0001] The present disclosure relates to a technology for presenting a drivable range of an electric vehicle. Background Art

[0002] For example, the image processing device of Patent Document 1 screens and deletes regions that are unnecessary for display from a reachable range divided into a plurality of regions, and displays only regions having a predetermined number, area, perimeter, and shape.

[0003] In addition, for example, the display device of patent document 2 obtains the position of the vehicle at a given timing and the remaining capacity of the battery carried by the vehicle, refers to the readable map information that defines a given grid, and sets the object grids to be processed in sequence based on the position of the vehicle, calculates the power consumption level of the set object grid based on the power consumption information that affects the power consumption required for the driving of the grid obtained from the inside and / or outside of the vehicle, and determines whether the vehicle can travel in the object grid based on the calculated power consumption level of the object grid and the remaining capacity of the battery of the vehicle or the drivable distance corresponding to the remaining capacity of the battery, and displays the object grid that is determined to be drivable by the vehicle as a drivable range.

[0004] However, in the above-mentioned conventional technology, it is difficult to finely display the drivable range of the electric vehicle, and further improvement is required.

[0005] Prior Art Literature

[0006] Patent Literature

[0007] Patent Document 1: Japanese Patent No. 5916862

[0008] Patent Document 2: Japanese Patent No. 5544983 Summary of the invention

[0009] The present disclosure has been made to solve the above-mentioned problems, and an object of the present disclosure is to provide a technology capable of finely displaying the drivable range of an electric vehicle.

[0010] The information processing method disclosed herein is an information processing method in a computer, which obtains a departure point of an electric mobile body and a current remaining power amount of a battery possessed by the electric mobile body; estimates the power consumption amount of the electric mobile body when it moves from the departure point to a plurality of grid areas obtained by dividing a map; calculates the remaining power amount of the electric mobile body after moving from the departure point to the plurality of grid areas based on the current remaining power amount and the consumed power amount; determines a plurality of grid areas where the remaining power amount after the movement is above a threshold as a plurality of reachable grid areas; generates a gradient image in which the color or brightness within a drawing area formed by connecting the center points of four reachable grid areas among the plurality of reachable grid areas changes in stages according to the remaining power amount after the movement; generates the gradient image for all of the plurality of reachable grid areas; and outputs information obtained by superimposing the generated gradient image on a map.

[0011] According to the present disclosure, the drivable range of the electric vehicle can be displayed in detail. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 1 is a diagram showing the overall configuration of the drivable range presentation system in the first embodiment of the present disclosure.

[0013] Figure 2 This is a diagram showing an example of the configuration of a server in Embodiment 1 of the present disclosure.

[0014] Figure 3 This is a diagram showing an example of correction ratio information stored in the correction ratio storage unit in the first embodiment.

[0015] Figure 4 This is a schematic diagram for explaining the relationship between the mesh area and the representative points in the first embodiment.

[0016] Figure 5 This is a schematic diagram for explaining the estimation of the power consumption amount by the power consumption estimating unit in the first embodiment.

[0017] Figure 6 This is a diagram showing an example of a gradation image generated by the gradation image generating unit in the first embodiment.

[0018] Figure 7 It is shown based on Figure 6 FIG. 1 is a diagram showing an example of multiple gradient images generated by the center points of each of the multiple reachable grid areas.

[0019] Figure 8This is a flowchart for explaining the process of generating the power consumption DB of the server in the first embodiment.

[0020] Fig. 9 This is a first flowchart for explaining the drivable range presentation processing of the server in the first embodiment.

[0021] Fig.10 This is a second flowchart for explaining the drivable range presentation processing of the server in the first embodiment.

[0022] Fig.11 This is a diagram showing an example of the drivable range information displayed on the information terminal in the first embodiment.

[0023] Fig.12 This is a diagram showing an example of the configuration of a server in Embodiment 2 of the present disclosure.

[0024] Fig.13 This is a schematic diagram for explaining the estimation of the power consumption amount by the power consumption estimating unit in the second embodiment.

[0025] Fig.14 This is a first flowchart for explaining the drivable range presentation processing of the server in the second embodiment.

[0026] Fig.15 This is a second flowchart for explaining the drivable range presentation processing of the server in the second embodiment. DETAILED DESCRIPTION

[0027] (Knowledge that forms the basis of this disclosure)

[0028] In Patent Document 1, map information is divided into a plurality of regions, and whether a mobile body can reach a certain region is explored for each region. Identification information for identifying whether a mobile body can reach a certain region or cannot reach a certain region is assigned to each region. Based on the region assigned with identification information of reachability, a reachable range of the mobile body is generated. In this case, since whether a mobile body can reach a certain region is explored for each region, only a rough indication of the reachable range of the mobile body can be given. For example, at the boundary between adjacent grids, although there is almost no change in distance, whether or not the mobile body can travel may change greatly.

[0029] In addition, in Patent Document 2, the grids determined to be drivable based on the power consumption level of each grid are displayed as the drivable range. In this case, the drivable range is displayed in grid units, so the drivable range of the vehicle can only be roughly presented.

[0030] In order to solve the above problems, the following technology is disclosed.

[0031] (1) An information processing method according to one aspect of the present disclosure is an information processing method in a computer, comprising obtaining a departure point of an electric vehicle and a current remaining power amount of a battery of the electric vehicle; estimating the power consumption amount of the electric vehicle when moving from the departure point to a plurality of grid areas obtained by dividing a map; calculating the remaining power amount of the electric vehicle after moving from the departure point to the plurality of grid areas based on the current remaining power amount and the consumed power amount; generating an image in which the color or brightness within a drawing area formed by connecting representative points of four grid areas changes stepwise according to the remaining power amount after the movement; and outputting information obtained by superimposing the generated image on a map.

[0032] According to this configuration, an image is generated in which the color or brightness in a drawing area formed by connecting representative points of four grid areas changes stepwise according to the remaining power amount after the movement, and information obtained by superimposing the generated image on a map is output.

[0033] Therefore, the travelable range of the electric vehicle can be displayed in detail by showing an image whose color or brightness changes stepwise according to the remaining power amount of the battery of the electric vehicle after the travel.

[0034] (2) In the information processing method described in (1) above, it may also be that, further, a plurality of grid areas where the remaining power amount after the movement is greater than a threshold value are determined as a plurality of reachable grid areas, and in the generation of the image, a gradient image is generated in which the color or brightness within the drawing area formed by connecting the center points of four reachable grid areas among the plurality of reachable grid areas changes step by step according to the remaining power amount after the movement, the gradient image is generated for all of the plurality of reachable grid areas, and in the output of the information, information obtained by superimposing the generated gradient image on a map is output.

[0035] According to the structure, a plurality of grid areas whose remaining power amount after movement is greater than a threshold value are determined as a plurality of reachable grid areas. A gradient image is generated in which the color or brightness in a drawing area formed by connecting the center points of four reachable grid areas among the plurality of reachable grid areas changes stepwise according to the remaining power amount after movement. A gradient image is generated for all of the plurality of reachable grid areas. Information obtained by superimposing the generated gradient image on a map is output.

[0036] Therefore, the travelable range of the electric vehicle can be displayed in detail by indicating the travelable range of the electric vehicle with a gradation in which the color or brightness changes stepwise according to the remaining power amount of the battery of the electric vehicle after the travel.

[0037] (3) In the information processing method described in (2) above, it may also be that, in the generation of the image, a gradient image is generated in which the color or brightness within the drawing area formed by connecting the center point of one reachable grid area among the multiple reachable grid areas and the three center points of three reachable grid areas surrounding the one reachable grid area changes in stages according to the remaining power of the one reachable grid area and the three reachable grid areas after the movement.

[0038] According to this structure, a gradient image is generated in which the color or brightness within a drawing area formed by connecting the center point of one reachable grid area among a plurality of reachable grid areas and the three center points of three reachable grid areas surrounding the one reachable grid area changes in stages according to the amount of remaining power after the one reachable grid area and the three reachable grid areas move.

[0039] Therefore, a gradation image can be generated with the center point of one reachable mesh area among a plurality of reachable mesh areas as a reference.

[0040] (4) In the information processing method described in any one of the above (1) to (3), it may be that, in the estimation of the power consumption, the power consumption is read out for each of the multiple grid areas from a power consumption storage unit that pre-stores the power consumption when the electric mobile body moves between the multiple grid areas.

[0041] According to this structure, the amount of power consumed by the electric mobile body when it moves between multiple grid areas is pre-stored in the power consumption storage unit. In addition, when estimating the power consumption for each of the multiple grid areas, the power consumption is not calculated by arithmetic processing, but is read from the power consumption storage unit. Therefore, arithmetic processing for calculating the power consumption is not required, and the drivable range of the electric mobile body can be displayed at a high speed.

[0042] (5) In the information processing method described in (4) above, it may also be that, further, a moving path from a grid area serving as a starting point to a grid area serving as an end point among the multiple grid areas is searched, and further, the moving distance of the searched moving path is input into a power consumption estimation model generated by machine learning with the moving distance as an input value and the power consumption as an output value, thereby estimating the power consumption of the electric mobile body when moving between the grid areas, and further, the estimated power consumption, the grid area serving as the starting point, and the grid area serving as the end point are established and stored in the power consumption storage unit in a correspondence.

[0043] According to this structure, the power consumption of the electric vehicle when moving between grid areas is estimated by inputting the moving distance of the searched moving path into the power consumption estimation model. Therefore, the power consumption of the electric vehicle when moving between grid areas can be easily estimated using the power consumption estimation model generated in advance by machine learning.

[0044] (6) In the information processing method described in any one of the above (1) to (5), the correction rate can be further read from a correction rate storage unit that pre-stores correction rates corresponding to moving distances and moving body identification information used to identify multiple electric moving bodies, and the read correction rate can be further used to correct the power consumption. The correction rate can also be a value obtained by dividing the power consumption of the electric moving body identified by the moving body identification information when it moves a given moving distance by the average power consumption of multiple electric moving bodies of the same model when they move the same moving distance as the given moving distance.

[0045] According to this configuration, the power consumption estimated based on the vehicle type of the electric vehicle can be corrected to the power consumption corresponding to the electric vehicle identified by the vehicle identification information, and more accurate power consumption can be estimated.

[0046] (7) In the information processing method described in any one of the above (1) to (6), in the estimation of the power consumption, the power consumption of the electric mobile body when moving from a representative point included in the grid area where the departure point is located to a representative point included in each of the multiple grid areas can also be estimated according to each of the multiple grid areas.

[0047] According to this configuration, since the amount of power consumption when the electric vehicle moves between representative points included in a plurality of mesh areas is stored in advance, it is easy to estimate the amount of power consumption.

[0048] (8) In the information processing method described in (7) above, the representative point may be a node on the map that is closest to the center point of the grid area.

[0049] According to this configuration, the representative point is a node on the map that is closest to the center point of the mesh area, and thus a movement path between the representative points can be easily searched.

[0050] (9) In the information processing method described in (2) above, the drawing area may be a rectangle, and in generating the image, a gradient image is generated in which the color or brightness within the drawing area formed by connecting the center point of the first reachable grid area among the multiple reachable grid areas, the center point of the second reachable grid area on the left side of the first reachable grid area, the center point of the third reachable grid area on the upper left side of the first reachable grid area, and the center point of the fourth reachable grid area on the upper side of the first reachable grid area changes in stages according to the remaining power amounts of the first reachable grid area, the second reachable grid area, the third reachable grid area, and the fourth reachable grid area after the movement.

[0051] According to this structure, a rectangular drawing area formed by connecting the center point of the first reachable grid area, the center point of the second reachable grid area, the center point of the third reachable grid area, and the center point of the fourth reachable grid area is represented by a gradient that changes the color or brightness in stages. Therefore, by combining multiple drawing areas, it is possible to cover the entirety of multiple grid areas on the map with a gradient image.

[0052] (10) In the information processing method described in any one of (1) to (9) above, in estimating the power consumption, four representative departure points located around the departure point are determined from representative points included in each of the plurality of grid areas, the plurality of grid areas are divided into four blocks each including the four representative departure points, a first power consumption when moving from the representative departure point to representative points of each of the plurality of grid areas in the same block is estimated for each of the plurality of grid areas, a moving path from the departure point to the representative departure points is searched, and the first power consumption is estimated. The second power consumption of the electric mobile body when moving on the searched moving path is calculated, and the total power consumption obtained by adding the estimated first power consumption and the estimated second power consumption is calculated, and the total power consumption is calculated in the four blocks respectively. In the calculation of the remaining power after the movement, based on the acquired current remaining power and the calculated multiple total power consumptions, the remaining power after the movement of the electric mobile body when moving from the starting point to the multiple grid areas is calculated for each of the multiple grid areas.

[0053] According to this configuration, the total power consumption is calculated by adding the first power consumption when moving from the starting representative point to the representative points of each of the plurality of grid areas in the same block and the second power consumption when the electric moving body moves on the moving path from the starting point to the starting representative point. Therefore, the remaining power after the electric moving body moves from the starting point to the plurality of grid areas can be calculated more accurately.

[0054] In addition, the present disclosure can be implemented not only as an information processing method that performs the above-mentioned characteristic processing, but also as an information processing device or the like having a characteristic structure corresponding to the characteristic processing performed by the information processing method. In addition, it can also be implemented as a computer program that causes a computer to perform the characteristic processing included in such an information processing method. Therefore, in the following other modes, the same effect as the above-mentioned information processing method can also be exerted.

[0055] (11) Another embodiment of the present disclosure relates to an information processing device comprising: an acquisition unit for acquiring a departure point of an electric mobile body and a current remaining power amount of a battery of the electric mobile body; an estimation unit for estimating a power consumption amount of the electric mobile body when moving from the departure point to a plurality of grid areas obtained by dividing a map; a calculation unit for calculating, based on the current remaining power amount and the consumed power amount, the remaining power amount of the electric mobile body after moving from the departure point to the plurality of grid areas; a generation unit for generating an image in which the color or brightness within a drawing area formed by connecting representative points of four of the grid areas changes stepwise according to the remaining power amount after the movement; and an output unit for outputting information obtained by superimposing the generated image on a map.

[0056] (12) Another embodiment of the present disclosure relates to an information processing program that enables a computer to function so as to: obtain a departure point of an electric mobile body and a current remaining power amount of a battery of the electric mobile body; estimate the power consumption amount of the electric mobile body when it moves from the departure point to a plurality of grid areas obtained by dividing a map; calculate the remaining power amount of the electric mobile body after moving from the departure point to the plurality of grid areas based on the current remaining power amount and the consumed power amount; generate an image in which the color or brightness within a drawing area formed by connecting representative points of four of the grid areas changes in stages according to the remaining power amount after the movement; and output information obtained by superimposing the generated image on a map.

[0057] (13) Another embodiment of the present disclosure involves a non-transitory computer-readable recording medium recording an information processing program, wherein the information processing program enables a computer to function so as to: obtain a departure point of an electric mobile body and a current remaining power amount of a battery of the electric mobile body; estimate the power consumption amount of the electric mobile body when it moves from the departure point to a plurality of grid areas obtained by dividing a map; calculate the remaining power amount of the electric mobile body after moving from the departure point to the plurality of grid areas based on the current remaining power amount and the consumed power amount; generate an image in which the color or brightness within a drawing area formed by connecting representative points of four of the grid areas changes in stages according to the remaining power amount after the movement; and output information obtained by superimposing the generated image on a map.

[0058] Hereinafter, an embodiment of the present disclosure will be described with reference to the drawings. In addition, the following embodiment is an example of specificizing the present disclosure, and does not limit the technical scope of the present disclosure.

[0059] (Implementation method 1)

[0060] Figure 1 1 is a diagram showing the overall configuration of the drivable range presentation system in the first embodiment of the present disclosure.

[0061] Figure 1 The illustrated driving range notification system includes an electric vehicle 1 , a server 2 , and an information terminal 3 .

[0062] The electric vehicle 1 is an example of an electric mobile body that moves using a battery mounted thereon. A battery is a secondary battery that can be charged and discharged. The electric vehicle 1 is, for example, an electric car, an electric truck, an electric bus, or an electric two-wheeled vehicle, and moves by supplying the electric power charged into the battery to the motor. The electric vehicle 1 is connected to the server 2 via a network 4 so as to be able to communicate with each other. The electric vehicle 1 periodically sends to the server 2 a vehicle ID for identifying the electric vehicle 1, the current position of the electric vehicle 1, and the current remaining power (remaining capacity) of the battery possessed by the electric vehicle 1. The electric vehicle 1 has a GPS (Global Positioning System) receiver for acquiring position information representing the current position of the electric vehicle 1. In addition, the electric vehicle 1 periodically sends to the server 2 a vehicle ID, a moving distance of a moving path along which the electric vehicle 1 moves, and the amount of power consumed when moving on the moving path.

[0063] In addition, the electric vehicle 1 may also send the altitude difference of the moving path of the electric vehicle 1 and / or the weight of the load when moving on the moving path to the server 2. The altitude difference of the moving path is, for example, the cumulative altitude on the moving path. The cumulative altitude represents the total value of the altitude difference of climbing or descending on the moving path.

[0064] Furthermore, the drivable range presentation system includes not only one electric vehicle 1 but a plurality of electric vehicles 1 .

[0065] The information terminal 3 is, for example, a personal computer, a smart phone, a tablet computer, or a vehicle-mounted terminal, and is operated by a user who uses the electric vehicle 1. The information terminal 3 is connected to the server 2 via a network 4 so as to be able to communicate with each other. The information terminal 3 sends request information for obtaining drivable range information indicating the drivable range of the electric vehicle 1 to the server 2. The request information includes the vehicle ID of the electric vehicle 1. In addition, the information terminal 3 receives the drivable range information of the electric vehicle 1 sent by the server 2. The information terminal 3 displays the received drivable range information.

[0066] The server 2 is, for example, a Web server. The server 2 is an example of an information processing device.

[0067] Figure 2 This is a diagram showing an example of the configuration of the server 2 in Embodiment 1 of the present disclosure.

[0068] Figure 2 The server 2 shown includes a communication unit 21 , a memory 22 , and a processor 23 .

[0069] The communication unit 21 periodically receives the current position and the current remaining power sent by the electric vehicle 1. The communication unit 21 stores the received current position and the current remaining power in the vehicle information storage unit 222 in correspondence with the vehicle ID. In addition, the communication unit 21 periodically receives the vehicle ID, the moving distance of the moving path on which the electric vehicle 1 moves, and the power consumed when moving on the moving path from the electric vehicle 1. The communication unit 21 stores the received moving distance and the power consumed in the vehicle information storage unit 222 in correspondence with the vehicle ID.

[0070] In addition, the communication unit 21 may further receive the altitude difference of the moving path of the electric vehicle 1 and / or the weight of the load when moving on the moving path from the electric vehicle 1. The communication unit 21 may further store the received altitude difference and / or the weight of the load in the vehicle information storage unit 222 in correspondence with the vehicle ID.

[0071] Furthermore, the communication unit 21 receives request information transmitted from the information terminal 3. The request information includes the vehicle ID of the electric vehicle 1. Furthermore, the communication unit 21 transmits the drivable range information indicating the drivable range of the electric vehicle 1 to the information terminal 3.

[0072] The memory 22 is a storage device capable of storing various information, such as a RAM (Random Access Memory), a HDD (Hard Disk Drive), a SSD (Solid State Drive), or a flash memory. The memory 22 implements a map information storage unit 221, a vehicle information storage unit 222, an estimation model storage unit 223, a correction rate storage unit 224, a representative point database (DB) storage unit 225, a power consumption DB storage unit 226, and a post-travel remaining power storage unit 227.

[0073] The processor 23 is, for example, a central processing unit (CPU). The processor 23 implements a log information acquisition unit 201, an estimation model learning unit 202, a correction rate generation unit 203, a power consumption DB generation unit 204, a vehicle information acquisition unit 205, a power consumption estimation unit 206, a power consumption correction unit 207, a remaining power after movement calculation unit 208, a reachable grid area determination unit 209, a gradient image generation unit 210, and an output unit 211.

[0074] In addition, the log information acquisition unit 201 to the output unit 211, the map information storage unit 221 to the remaining power storage unit 227 after the move can also be composed of dedicated hardware circuits. In addition, the log information acquisition unit 201 to the output unit 211, the map information storage unit 221 to the remaining power storage unit 227 after the move can also be distributed in multiple devices.

[0075] The map information storage unit 221 stores map information representing a map divided into a plurality of grid areas in advance. The grid areas are rectangular, for example, square. The length of one side of the grid area is the same as the length of one side at zoom level 16 (about 200 meters).

[0076] The vehicle information storage unit 222 stores the vehicle information corresponding to the vehicle ID, vehicle model, current position of the electric vehicle 1, current remaining power of the electric vehicle 1, and log information of the electric vehicle 1. The log information includes multiple combinations of moving distance and power consumption. In addition, the log information may also include the altitude difference of the moving path and / or the weight of the load of the electric vehicle 1. In addition, the log information may also include other information besides the moving distance, power consumption, altitude difference, and weight of the load.

[0077] The estimation model storage unit 223 stores an estimation model of power consumption generated by machine learning using the travel distance as an input value and the power consumption as an output value.

[0078] When performing machine learning of the power consumption estimation model, the log information acquisition unit 201 acquires the travel distance and the power consumption from the vehicle information storage unit 222 .

[0079] The estimation model learning unit 202 performs machine learning of the power consumption estimation model using the travel distance as an input value and the power consumption corresponding to the travel distance as an output value. In addition, for the learning for generating the power consumption estimation model, it is sufficient to use machine learning such as deep learning using a multi-layer neural network. The estimation model learning unit 202 stores the generated power consumption estimation model in the estimation model storage unit 223.

[0080] In addition, the power consumption estimation model is generated for each model of the electric vehicle 1. The estimation model storage unit 223 stores the power consumption estimation model generated for each model of the electric vehicle 1. The log information acquisition unit 201 acquires multiple combinations of travel distances and power consumption of multiple electric vehicles of the same model from the vehicle information storage unit 222. The estimation model learning unit 202 performs machine learning of the power consumption estimation model for each model, and generates a power consumption estimation model for each model.

[0081] In addition, the estimated model learning unit 202 uses the travel distance as an input value of the power consumption estimation model, but the present disclosure is not particularly limited to this. The estimated model learning unit 202 may also use the travel distance, the altitude difference, and at least one of the weight of the load as an input value of the power consumption estimation model, or may use other geographical feature quantities as input values ​​of the power consumption estimation model.

[0082] The correction rate storage unit 224 stores correction rates associated with travel distances and vehicle IDs for identifying a plurality of electric vehicles in advance. The correction rates are used to correct the power consumption estimated by the power consumption estimating unit 206 according to the model of the electric vehicle according to the individual electric vehicle.

[0083] The correction rate generating unit 203 generates a correction rate obtained by dividing the amount of power consumed by the electric vehicle identified by the vehicle ID when it moves a given moving distance by the average amount of power consumed by multiple electric vehicles of the same vehicle type when they move the same moving distance as the given moving distance. The correction rate generating unit 203 generates the correction rate for each electric vehicle. In addition, the correction rate generating unit 203 generates multiple correction rates corresponding to the moving distance. For example, the correction rate generating unit 203 generates multiple correction rates corresponding to the first moving distance range of 0 kilometers or more and less than 50 kilometers, the second moving distance range of 50 kilometers or more and less than 100 kilometers, and the third moving distance range of 100 kilometers or more and less than 200 kilometers.

[0084] Figure 3 This is a diagram showing an example of correction ratio information stored in the correction ratio storage unit 224 in the first embodiment.

[0085] like Figure 3 As shown, the correction rate storage unit 224 stores the correction rate of the first moving distance range, the correction rate of the second moving distance range, and the correction rate of the third moving distance range for each vehicle ID. For example, the correction rate of the first moving distance range associated with the vehicle ID "0001" is +0.5%, the correction rate of the second moving distance range is +0.4%, and the correction rate of the third moving distance range is +0.3%.

[0086] In the first embodiment, the correction ratio storage unit 224 stores correction ratios corresponding to three moving distance ranges, but the present disclosure is not particularly limited thereto, and correction ratios corresponding to four or more moving distance ranges may be stored.

[0087] In addition, the correction rate storage unit 224 may store correction rates corresponding to a plurality of combinations of moving distance ranges and altitude difference ranges instead of storing correction rates corresponding to moving distance ranges. For example, the altitude difference of the first altitude difference range is greater than -50 meters and less than -10 meters, the altitude difference of the second moving distance range is greater than -10 meters and less than -3 meters, the altitude difference of the third moving distance range is greater than -3 meters and less than +3 meters, the altitude difference of the fourth altitude difference range is greater than +3 meters and less than +10 meters, and the altitude difference of the fifth altitude difference range is greater than +10 meters and less than +50 meters. The correction rate storage unit 224 may also store 15 correction rates corresponding to the combinations of the first to third moving distance ranges and the first to fifth altitude difference ranges.

[0088] The representative point DB storage unit 225 stores a representative point DB in which a grid area ID for identifying a grid area and a position of a representative point in the grid area are associated. A representative point is a node on a map that is closest to the center point of a grid area. Map information is information that represents a map using a plurality of nodes and links connecting the nodes. A node represents a characteristic position on a road, such as a road intersection and a road end point. A link represents a road between nodes. The node closest to the center point of a grid area is set as a representative point.

[0089] In addition, nodes can also be filtered according to the level of the road. For example, nodes above county roads can be set as representative points. This can prevent narrow roads that are not usually used from being set as representative points. As a result, by searching for routes using representative points that are more convenient for users, it is possible to estimate the actual power consumption of roads that are likely to be used in practice.

[0090] The power consumption DB storage unit 226 stores in advance the power consumption when the electric vehicle moves between a plurality of mesh areas.

[0091] The power consumption DB generation unit 204 searches for a moving path from a grid area that is a starting point to a grid area that is an end point among a plurality of grid areas. The power consumption DB generation unit 204 inputs the moving distance of the searched moving path into a power consumption estimation model generated by machine learning with the moving distance as an input value and the power consumption as an output value, thereby estimating the power consumption of the electric vehicle when it moves between grid areas. At this time, the power consumption DB generation unit 204 reads the power consumption estimation model stored in the estimation model storage unit 223, inputs the moving distance of the searched moving path into the power consumption estimation model, and obtains the power consumption output from the power consumption estimation model as an estimation result. The power consumption DB generation unit 204 stores the estimated power consumption, the grid area that is the starting point, and the grid area that is the end point in correspondence with each other in the power consumption DB storage unit 226.

[0092] Figure 4 This is a schematic diagram for explaining the relationship between the mesh area and the representative points in the first embodiment.

[0093] The map 100 is divided into a plurality of rectangular grid areas 101 to 112. A grid area ID for identifying the grid area is assigned to each grid area. For example, a grid area ID such as "00001" is assigned to the grid area 101. Figure 4 In the figure, the black circle represents the center point (center of gravity) of the grid area, and the black square represents the representative point. As mentioned above, the representative point is the node closest to the center point of the grid area. Therefore, the center point of the grid area and the representative point are not necessarily the same.

[0094] The power consumption DB generation unit 204 searches for a moving path from a grid area that is a starting point to a grid area that is an end point among the plurality of grid areas. For example, if the grid area 101 is assumed to be the starting point, the grid areas 102 to 112 are the end points respectively. The power consumption DB generation unit 204 searches for moving paths from the grid area 101 that is the starting point to the plurality of grid areas 102 to 112 that are the end points. At this time, the power consumption DB generation unit 204 searches for moving paths from the representative point of the grid area 101 to the representative points of each of the plurality of grid areas 102 to 112.

[0095] In addition, the moving path from the grid area that becomes the starting point to the grid area that becomes the end point can be calculated using a path search algorithm of the prior art. In the path search algorithm, the moving path with the shortest moving distance or the moving path with the shortest moving time is calculated. The path search algorithm is, for example, the Dijkstra method. The shortest path is, for example, a path with the minimum cost. However, this is an example, and the power consumption DB generation unit 204 can also use an external map API (Application Programming Interface) to calculate the moving path.

[0096] Next, the power consumption DB generator 204 calculates the moving distance of the searched moving path. The length of the moving path can be calculated by summing the lengths of the multiple links constituting the moving path. Next, the power consumption DB generator 204 estimates the power consumption of the electric vehicle when it moves between grid areas by inputting the calculated moving distance of the moving path into a pre-stored power consumption estimation model. The power consumption DB generator 204 estimates the power consumption for all moving paths between the grid area 101 that is the starting point and the multiple grid areas 102 to 112 that are the end points.

[0097] Next, the power consumption DB generator 204 stores the estimated power consumption, the mesh area ID for identifying the starting mesh area 101 , and the mesh area IDs for identifying the ending mesh areas 102 to 112 in association with each other in the power consumption DB storage 226 .

[0098] Next, the power consumption DB generation unit 204 changes the grid area that is the starting point to another grid area. And the power consumption DB generation unit 204 repeats the above-mentioned process. Thus, the power consumption DB generation unit 204 generates a power consumption DB that associates the estimated power consumption, the grid area ID for identifying the grid area 101 to 112 that is the starting point, and the grid area ID for identifying the grid area 101 to 112 that is the end point.

[0099] In addition, the power consumption DB generating unit 204 may also set the grid area within a given range from the representative point of the grid area serving as the starting point as the grid area serving as the end point. The given range may also be, for example, a circle with the maximum driving distance of the electric vehicle when fully charged as the radius. In this way, the amount of calculation can be reduced by limiting the number of grid areas serving as the end point.

[0100] The vehicle information acquisition unit 205 acquires the departure point of the electric vehicle 1 and the current remaining power of the battery of the electric vehicle 1. When the communication unit 21 receives the request information, the vehicle information acquisition unit 205 acquires the departure point of the electric vehicle 1 corresponding to the vehicle ID included in the request information and the current remaining power of the battery of the electric vehicle 1 from the vehicle information storage unit 222. In addition, the electric vehicle 1 sends the current position and the current remaining power of the battery to the server 2, for example, every 1 minute, and the vehicle information storage unit 222 stores the current position of the electric vehicle 1 and the current remaining power of the battery received every 1 minute. Therefore, the vehicle information acquisition unit 205 acquires the latest position and the latest remaining power of the electric vehicle 1 stored in the vehicle information storage unit 222 as the departure point and the current remaining power of the electric vehicle 1.

[0101] In addition, the vehicle information acquisition unit 205 may also send a request message for the current position and the current remaining power of the battery to the electric vehicle 1 corresponding to the vehicle ID included in the request message when the request message is received by the communication unit 21. If the request message is received, the electric vehicle 1 sends the current position and the current remaining power of the battery to the server 2. The vehicle information acquisition unit 205 acquires the current position and the current remaining power of the electric vehicle 1 received by the communication unit 21 as the departure point and the current remaining power of the electric vehicle 1.

[0102] In addition, the information terminal 3 may also accept the user's input of at least one of the departure point and the current remaining power of the electric vehicle 1. The touch panel of the information terminal 3 may also display a map and accept the input of the departure point of the electric vehicle 1 on the map. In addition, the touch panel of the information terminal 3 may also accept the user's input of the address, place name or facility name of the departure point. The touch panel of the information terminal 3 may also accept the user's input of the current remaining power of the electric vehicle 1. In addition, the touch panel of the information terminal 3 may also display a slide bar and accept the user's input of the current remaining power of the electric vehicle 1 by moving the grip position on the slide bar.

[0103] The information terminal 3 may also send a request message including at least one of the departure point of the electric vehicle 1 and the current remaining power amount input by the user and the vehicle ID to the server 2. When the communication unit 21 receives the request message, the vehicle information acquisition unit 205 may also acquire at least one of the departure point of the electric vehicle 1 and the current remaining power amount included in the request message.

[0104] The departure point of the electric vehicle 1 may be the current position of the information terminal 3 received by the GPS receiver of the information terminal 3. The information terminal 3 may send request information including the current position of the information terminal 3 as the departure point of the electric vehicle 1 to the server 2.

[0105] The power consumption estimation unit 206 estimates the power consumption of the electric vehicle 1 when it moves from the departure point of the electric vehicle 1 to the multiple grid areas obtained by dividing the map. The power consumption estimation unit 206 estimates the power consumption of the electric vehicle 1 when it moves from the departure point of the electric vehicle 1 to the multiple grid areas obtained by dividing the map, for each of the multiple grid areas. The power consumption estimation unit 206 reads the power consumption for each of the multiple grid areas from the power consumption DB storage unit 226 that stores the power consumption of the electric vehicle 1 when it moves between the multiple grid areas in advance. The power consumption estimation unit 206 estimates the power consumption of the electric vehicle 1 when it moves from the representative point included in the grid area where the departure point is located to the representative point included in each of the multiple grid areas, for each of the multiple grid areas.

[0106] Figure 5 Schematic diagram for explaining the estimation of the power consumption amount by the power consumption estimation unit 206 in the first embodiment. Figure 5 In the figure, the black circle represents the center point (center of gravity) of the grid area, and the black square represents the representative point.

[0107] The departure point 141 of the electric vehicle 1 is within the grid area 110. The power consumption estimation unit 206 estimates the power consumption of the electric vehicle 1 when it moves from the representative point included in the grid area 110 where the departure point 141 of the electric vehicle 1 is located to the representative points included in each of the plurality of grid areas 101 to 109, 111, 112, for each of the plurality of grid areas 101 to 109, 111, 112. The power consumption DB storage unit 226 stores in advance the power consumption of the electric vehicle 1 when it moves between the representative points of the plurality of grid areas 101 to 112. Therefore, the power consumption estimation unit 206 reads the power consumption of the electric vehicle 1 when it moves from the representative point included in the grid area 110 where the departure point 141 of the electric vehicle 1 is located to the representative points included in each of the plurality of grid areas 101 to 109, 111, 112 from the power consumption DB storage unit 226. The power consumption estimation unit 206 reads out from the power consumption DB storage unit 226 a plurality of power consumptions associated with the grid area ID of the grid area 110 where the departure point 141 of the electric vehicle 1 is located and the grid area IDs of the plurality of grid areas 101 to 109 , 111 , and 112 other than the grid area 110 .

[0108] The power consumption correction unit 207 reads the correction rate from the correction rate storage unit 224 which pre-stores the correction rate in correspondence with the moving distance and the vehicle ID for identifying a plurality of electric vehicles. The power consumption correction unit 207 uses the read correction rate to correct the power consumption estimated for each of the plurality of grid areas. The correction rate is a value obtained by dividing the power consumption of the electric vehicle 1 identified by the vehicle ID when it moves a given moving distance by the average power consumption of a plurality of electric vehicles of the same vehicle type when they move the same moving distance as the given moving distance.

[0109] The power consumption correction unit 207 reads out the correction rate corresponding to the moving distance between the representative point of the grid area including the departure point and the representative points of other grid areas from the correction rate storage unit 224. For example, when the moving distance between the representative points is 3 kilometers, the power consumption correction unit 207 reads out the correction rate corresponding to the moving distance between the representative points of the grid area including the departure point and the representative points of other grid areas. Figure 3 The correction rate information shown has a correction rate corresponding to the first moving distance range. In addition, the power consumption correction unit 207 may read out the correction rate corresponding to the moving distance between the representative points and the altitude difference instead of the correction rate corresponding to the moving distance between the representative points.

[0110] The power consumption correction unit 207 reads out the correction rate corresponding to the moving distance between the representative point of the grid area including the departure point and the representative points of other grid areas from the correction rate storage unit 224, and multiplies the read correction rate by the power consumption between the representative points, thereby correcting the power consumption. When the correction rate is, for example, +0.5%, the power consumption correction unit 207 multiplies the power consumption by 1.005. In addition, when the correction rate is, for example, -0.5%, the power consumption correction unit 207 multiplies the power consumption by 0.995.

[0111] The remaining power after movement calculation unit 208 calculates the remaining power after movement when the electric vehicle 1 moves from the departure point to the plurality of grid areas, based on the current remaining power acquired by the vehicle information acquisition unit 205 and the power consumption estimated by the power consumption estimation unit 206. The remaining power after movement calculation unit 208 calculates the remaining power after movement when the electric vehicle 1 moves from the departure point to the plurality of grid areas, based on the current remaining power acquired by the vehicle information acquisition unit 205 and the plurality of power consumptions estimated by the power consumption estimation unit 206, for each of the plurality of grid areas. In addition, the remaining power after movement calculation unit 208 calculates the remaining power after movement when the electric vehicle 1 moves from the departure point to the plurality of grid areas, based on the current remaining power acquired by the vehicle information acquisition unit 205 and the plurality of power consumptions corrected by the power consumption correction unit 207, for each of the plurality of grid areas.

[0112] The remaining power calculation unit 208 calculates the remaining power after the electric vehicle 1 moves from the grid area including the departure point to another grid area by subtracting the power consumption corrected by the power consumption correction unit 207 from the current remaining power acquired by the vehicle information acquisition unit 205.

[0113] In addition, in the first embodiment, the grid area does not necessarily include a node, and when the grid area does not include a node, the representative point of the grid area is not set. The remaining power amount calculation unit 208 after movement may also set the remaining power amount after movement of the electric vehicle 1 to 0 when the electric vehicle 1 moves from the grid area including the departure point to the grid area without the representative point.

[0114] In addition, in the first embodiment, the power consumption correction unit 207 uses the correction rate to correct the power consumption estimated for each of the plurality of grid areas, but the present disclosure is not particularly limited thereto. The power consumption correction unit 207 and the correction rate storage unit 224 are not essential structures, and the server 2 may not include the power consumption correction unit 207 and the correction rate storage unit 224.

[0115] The reachable grid area determination unit 209 determines a plurality of grid areas where the remaining power amount after the movement is greater than a threshold as a plurality of reachable grid areas. The reachable grid area determination unit 209 determines a plurality of grid areas where the remaining power amount after the movement is greater than a threshold as a plurality of reachable grid areas. The threshold is, for example, 0 kWh.

[0116] The reachable grid area determination unit 209 stores the grid area ID of the reachable grid area and the remaining power amount after the move in a correspondence with each other in the remaining power amount storage unit 227 after the move. Figure 5 When the reachable grid area is the grid area 101, the reachable grid area determination unit 209 stores the grid area ID of the grid area 101 and the remaining power after moving from the grid area 110 of the departure point 141 to the grid area 101 in correspondence with each other in the after-movement remaining power storage unit 227. For the remaining reachable grid areas, the reachable grid area determination unit 209 also stores the grid area ID of the reachable grid area and the remaining power after moving in correspondence with each other in the after-movement remaining power storage unit 227.

[0117] The post-movement remaining power amount storage unit 227 stores the post-movement remaining power amount in association with the mesh area ID of the reachable mesh area.

[0118] The gradation image generating unit 210 generates an image in which the color or brightness in a drawing area formed by connecting representative points of four mesh areas changes stepwise according to the remaining power amount after the shift.

[0119] The gradient image generation unit 210 generates a gradient image in which the color or brightness in the drawing area formed by connecting the center points of four reachable grid areas among the plurality of reachable grid areas determined by the reachable grid area determination unit 209 changes stepwise according to the remaining power amount after the movement. The gradient image generation unit 210 generates a gradient image in which the color or brightness in the drawing area formed by connecting the center points of four reachable grid areas among the plurality of reachable grid areas determined by the reachable grid area determination unit 209 changes stepwise according to the remaining power amount after the movement of the four reachable grid areas. The gradient image generation unit 210 generates the gradient image for all of the plurality of reachable grid areas.

[0120] That is, the gradient image generating unit 210 generates a gradient image in which the color or brightness within the drawing area formed by connecting the center point of one reachable grid area among the multiple reachable grid areas determined by the reachable grid area determining unit 209 and the three center points of three reachable grid areas surrounding the one reachable grid area changes in stages according to the remaining power amount after the one reachable grid area and the three reachable grid areas move.

[0121] The gradient image generating unit 210 generates a gradient image in which the color or brightness in the drawing area formed by connecting the center point of the first reachable grid area among the plurality of reachable grid areas, the center point of the second reachable grid area on the left side of the first reachable grid area, the center point of the third reachable grid area on the upper left side of the first reachable grid area, and the center point of the fourth reachable grid area on the upper side of the first reachable grid area changes stepwise according to the remaining power amount after the first reachable grid area, the second reachable grid area, the third reachable grid area, and the fourth reachable grid area are moved.

[0122] Figure 6 1 is a diagram showing an example of a gradation image generated by the gradation image generating unit 210 in the first embodiment.

[0123] exist Figure 6 In the example, the reachable mesh area determination unit 209 determines the plurality of mesh areas 101 to 112 as a plurality of reachable mesh areas.

[0124] The gradient image generating unit 210 generates a gradient image 132 in which the color or brightness within a drawing area 131 formed by connecting a center point 121 of a first reachable grid area 106 among a plurality of reachable grid areas 101 to 112, a center point 122 of a second reachable grid area 105 located to the left of the first reachable grid area 106, a center point 123 of a third reachable grid area 101 located to the upper left of the first reachable grid area 106, and a center point 124 of a fourth reachable grid area 102 located to the upper side of the first reachable grid area 106 changes in stages according to the amount of remaining power after the first reachable grid area 106, the second reachable grid area 105, the third reachable grid area 101, and the fourth reachable grid area 102 move.

[0125] Then, the gradation image generating unit 210 generates a gradation image by using the other reachable mesh regions 101 to 105 and 107 to 112 other than the reachable mesh region 106 as first reachable mesh regions.

[0126] In addition, the gradient image generating unit 210 can also generate a gradient image in which the color or brightness within the drawing area formed by connecting the center point of the first reachable grid area 106 among the multiple reachable grid areas 101 to 112, the center point of the fourth reachable grid area 102 located on the upper side of the first reachable grid area 106, the center point of the fifth reachable grid area 103 located on the upper right side of the first reachable grid area 106, and the center point of the sixth reachable grid area 107 located on the right side of the first reachable grid area 106 changes in stages according to the remaining power amount after the first reachable grid area 106, the fourth reachable grid area 102, the fifth reachable grid area 103 and the sixth reachable grid area 107 are moved.

[0127] In addition, the gradient image generating unit 210 can also generate a gradient image in which the color or brightness within the drawing area formed by connecting the center point of the first reachable grid area 106 among multiple reachable grid areas 101 to 112, the center point of the sixth reachable grid area 107 to the right of the first reachable grid area 106, the center point of the seventh reachable grid area 111 to the lower right of the first reachable grid area 106, and the center point of the eighth reachable grid area 110 to the lower side of the first reachable grid area 106 changes in stages according to the remaining power amount after the movement of the first reachable grid area 106, the sixth reachable grid area 107, the seventh reachable grid area 111 and the eighth reachable grid area 110.

[0128] In addition, the gradient image generating unit 210 can also generate a gradient image in which the color or brightness within the drawing area formed by connecting the center point of the first reachable grid area 106 among the multiple reachable grid areas 101 to 112, the center point of the second reachable grid area 105 on the left side of the first reachable grid area 106, the center point of the eighth reachable grid area 110 on the lower side of the first reachable grid area 106, and the center point of the ninth reachable grid area 109 on the lower left side of the first reachable grid area 106 changes in stages according to the remaining power amount after the movement of the first reachable grid area 106, the second reachable grid area 105, the eighth reachable grid area 110 and the ninth reachable grid area 109.

[0129] The gradient image generation unit 210 converts the remaining power after the movement into a drivable probability. The remaining power after the movement of 0 kWh corresponds to a drivable probability of 0%, and the power of the electric vehicle 1 when fully charged corresponds to a drivable probability of 100%. For example, the gradient image generation unit 210 sets the drivable probability of 100% to green, sets the drivable probability of 0% to red, and changes the color between the drivable probability of 100% and 0% in stages. Moreover, the gradient image generation unit 210 changes the color in the drawing area in stages according to the value of the drivable probability of each center point.

[0130] In addition, in the first embodiment, the remaining power is converted into the driving probability, but the present disclosure is not particularly limited to this, and the charging rate may be used instead of the remaining power. The charging rate is SOC (State Of Charge), which is represented by (remaining capacity [Ah] / full charge capacity [Ah]) * 100. For example, the gradient image generation unit 210 may set SOC100% to green and SOC0% to red, and change the color between SOC100% and 0% in stages.

[0131] In addition, instead of using the remaining power, the value of SOC*SOH (State of Health) may be used. SOH is an indicator of the degradation state of the battery, and is represented by (remaining capacity at degradation [Ah] / initial full charge capacity [Ah])*100. For example, the gradient image generation unit 210 may set SOC*SOH100% to green, SOC*SOH0% to red, and change the color between SOC*SOH100% and 0% in stages.

[0132] Furthermore, the gradation image generating unit 210 may assign a color not used for gradation or a color that is the same as the threshold value (0 kwh) to the center point of the mesh region having no representative point.

[0133] Figure 7 It is shown based on Figure 6 The diagram shows an example of a plurality of gradation images generated by the center points of the respective plurality of reachable mesh areas 101 to 112 .

[0134] exist Figure 7 In the gradation image shown, the vicinity of the departure point 141 is drawn in green, and the color changes to red in stages as the remaining power amount after the movement decreases, that is, as the vehicle moves away from the departure point 141 .

[0135] In addition, the gradation image generation unit 210 may change the brightness in the drawing area in stages according to the value of the drivable probability of each center point. In this case, the color in the drawing area is a single color, and the brightness changes in stages.

[0136] The output unit 211 outputs information obtained by superimposing the gradation image generated by the gradation image generating unit 210 on a map. The output unit 211 outputs information obtained by superimposing the gradation image on a map as drivable range information.

[0137] Next, the power consumption DB generation process of the server 2 in the first embodiment will be described.

[0138] Figure 8 This is a flowchart for explaining the power consumption DB generation process of the server 2 in the first embodiment.

[0139] First, in step S1, the power consumption DB generator 204 determines the representative point of each of the plurality of mesh areas. At this time, the power consumption DB generator 204 determines the position of the node closest to the center point of each of the plurality of mesh areas as the position of the representative point of each of the plurality of mesh areas.

[0140] Next, in step S2 , the power consumption DB generation unit 204 stores the plurality of mesh area IDs and the positions of the representative points in association with each other in the power consumption DB storage unit 226 .

[0141] Next, in step S3 , the power consumption DB generator 204 selects a mesh area ID serving as a starting point from among the plurality of mesh area IDs.

[0142] Next, in step S4 , the power consumption DB generator 204 selects a mesh area ID that becomes an end point from among a plurality of mesh area IDs other than the mesh area ID that becomes the start point.

[0143] Next, in step S5 , the power consumption DB generator 204 searches for a moving path from the representative point of the mesh area serving as the starting point to the representative point of the mesh area serving as the end point.

[0144] Next, in step S6 , the power consumption DB generator 204 calculates the travel distance of the searched travel route.

[0145] Next, in step S7 , the power consumption DB generator 204 estimates the power consumption when the electric vehicle 1 moves on the searched travel route by inputting the calculated travel distance into the power consumption estimation model.

[0146] Next, in step S8 , the power consumption DB generation unit 204 associates the mesh area ID of the start point, the mesh area ID of the end point, and the estimated power consumption and stores them in the power consumption DB storage unit 226 .

[0147] Next, in step S9, the power consumption DB generator 204 determines whether all the mesh area IDs that are the end points have been selected. In other words, the power consumption DB generator 204 determines whether all the mesh area IDs other than the start point have been selected as the mesh area IDs that are the end points.

[0148] Here, when it is determined that not all of the grid area IDs that are the end points have been selected (No in step S9), the process returns to step S4, and the power consumption DB generation unit 204 selects a grid area ID that has not been selected as the grid area ID that is the end point from among a plurality of other grid area IDs other than the grid area ID that is the starting point.

[0149] On the other hand, when it is determined that all the grid area IDs that are the end points are selected (Yes in step S9), in step S10, the power consumption DB generating unit 204 determines whether all the grid area IDs that are the start points are selected. That is, the power consumption DB generating unit 204 determines whether all the grid area IDs that are the start points are selected.

[0150] Here, when it is determined that not all of the starting mesh area IDs have been selected (No in step S10 ), the process returns to step S3 , and the power consumption DB generator 204 selects other mesh area IDs that have not been selected as the starting mesh area IDs from among the plurality of mesh area IDs.

[0151] On the other hand, when it is determined that all the mesh area IDs serving as the starting point are selected (YES in step S10 ), the power consumption DB creation process ends.

[0152] Next, the drivable range presentation process performed by the server 2 in the first embodiment will be described.

[0153] Fig. 9 is a first flowchart for explaining the drivable range notification process of the server 2 in the first embodiment. Fig.10 This is a second flowchart for explaining the drivable range presentation process of the server 2 in the first embodiment.

[0154] First, in step S21 , the communication unit 21 receives request information for requesting the drivable range information indicating the drivable range of the electric vehicle 1 from the information terminal 3 .

[0155] Next, in step S22 , the vehicle information acquisition unit 205 acquires the departure point of the electric vehicle 1 identified by the vehicle ID included in the request information and the current remaining power amount of the battery included in the electric vehicle 1 from the vehicle information storage unit 222 .

[0156] Next, in step S23 , the power consumption estimation unit 206 specifies the mesh area ID of the mesh area including the departure point.

[0157] Next, in step S24 , the power consumption estimation unit 206 reads out one power consumption from the power consumption DB storage unit 226 , from a plurality of power consumptions associated with the mesh area ID of the mesh area including the departure point and the mesh area IDs of a plurality of other mesh areas.

[0158] Next, in step S25, the power consumption correction unit 207 corrects the power consumption read by the power consumption estimation unit 206. At this time, the power consumption correction unit 207 reads out the correction rate corresponding to the moving distance between the representative point of the grid area including the departure point and the representative points of other grid areas from the correction rate storage unit 224, and multiplies the read correction rate by the power consumption, thereby correcting the power consumption.

[0159] Next, in step S26, the remaining power after movement calculation unit 208 subtracts the power consumption corrected by the power consumption correction unit 207 from the current remaining power acquired by the vehicle information acquisition unit 205, thereby calculating the remaining power after movement of the electric vehicle 1 when it moves from the grid area including the departure point to another grid area.

[0160] Next, in step S27 , the reachable mesh area determination unit 209 determines whether the calculated remaining power amount after the movement is equal to or greater than a threshold value.

[0161] Here, when it is determined that the remaining power amount after the movement is not equal to or greater than the threshold value (No in step S27 ), the process proceeds to step S29 .

[0162] On the other hand, when it is determined that the remaining power after the move is above the threshold (yes in step S27), in step S28, the reachable grid area determination unit 209 determines the grid area where the remaining power after the move is above the threshold as a reachable grid area, and establishes a correspondence between the grid area ID of the reachable grid area and the remaining power after the move and stores them in the remaining power after the move storage unit 227.

[0163] Next, in step S29 , the power consumption estimating unit 206 determines whether all power consumptions associated with the mesh area ID of the mesh area including the departure point and the mesh area IDs of a plurality of other mesh areas have been read.

[0164] Here, when it is determined that not all power consumption has been read out (No in step S29), the process returns to step S24, and the power consumption estimation unit 206 reads out other power consumption from the power consumption DB storage unit 226, from a plurality of power consumptions corresponding to the grid area ID of the grid area including the departure point and the grid area IDs of a plurality of other grid areas.

[0165] On the other hand, when it is determined that all the power consumption has been read out (yes in step S29 ), in step S30 , the gradient image generating unit 210 selects the grid area ID of one reachable grid area from among the multiple reachable grid areas determined by the reachable grid area determining unit 209 .

[0166] Next, in step S31, the gradient image generating unit 210 reads out, from the remaining power after movement storage unit 227, the remaining power after movement corresponding to the grid area ID of the selected one reachable grid area, and three remaining power after movement corresponding to the three grid area IDs of the three reachable grid areas surrounding the one reachable grid area.

[0167] More specifically, the gradient image generating unit 210 reads out, from the moved remaining power amount storage unit 227, the remaining power amount after movement corresponding to the grid area ID of the first reachable grid area selected from the multiple reachable grid areas, the remaining power amount after movement corresponding to the grid area ID of the second reachable grid area located on the left side of the first reachable grid area, the remaining power amount after movement corresponding to the grid area ID of the third reachable grid area located on the upper left side of the first reachable grid area, and the remaining power amount after movement corresponding to the grid area ID of the fourth reachable grid area located on the upper side of the first reachable grid area.

[0168] In addition, when there is no reachable grid area on the right side of the selected first reachable grid area, the gradient image generating unit 210 reads out from the moved remaining power amount storage unit 227 the remaining power amount after movement corresponding to the grid area ID of the selected first reachable grid area, the remaining power amount after movement corresponding to the grid area ID of the grid area on the right side of the first reachable grid area, the remaining power amount after movement corresponding to the grid area ID of the grid area on the upper right side of the first reachable grid area, and the remaining power amount after movement corresponding to the grid area ID of the grid area on the upper side of the first reachable grid area.

[0169] In addition, when there is no reachable grid area below the selected first reachable grid area, the gradient image generating unit 210 reads out from the moved remaining power amount storage unit 227 the remaining power amount after movement corresponding to the grid area ID of the selected first reachable grid area, the remaining power amount after movement corresponding to the grid area ID of the grid area on the left side of the first reachable grid area, the remaining power amount after movement corresponding to the grid area ID of the grid area on the lower left side of the first reachable grid area, and the remaining power amount after movement corresponding to the grid area ID of the grid area on the lower side of the first reachable grid area.

[0170] In addition, when there is no reachable grid area on the right side of the selected first reachable grid area and there is no reachable grid area on the bottom side of the selected first reachable grid area, the gradient image generating unit 210 reads out from the moved remaining power amount storage unit 227 the remaining power amount after movement corresponding to the grid area ID of the selected first reachable grid area, the remaining power amount after movement corresponding to the grid area ID of the grid area on the right side of the first reachable grid area, the remaining power amount after movement corresponding to the grid area ID of the grid area on the lower right side of the first reachable grid area, and the remaining power amount after movement corresponding to the grid area ID of the grid area on the bottom side of the first reachable grid area.

[0171] Thus, the remaining power amount after the movement of the grid areas located on the right side, the bottom side, and the lower right side of the plurality of reachable grid areas can be acquired.

[0172] Next, in step S32, the gradient image generating unit 210 generates a gradient image in which the color or brightness within the drawing area formed by connecting the center point of a selected reachable grid area and the three center points of three reachable grid areas surrounding the one reachable grid area changes in stages according to the remaining power amount after the one reachable grid area and the three reachable grid areas are moved.

[0173] More specifically, the gradient image generating unit 210 generates a gradient image in which the color or brightness within a drawing area formed by connecting the center point of a selected first reachable grid area among a plurality of reachable grid areas, the center point of a second reachable grid area on the left side of the first reachable grid area, the center point of a third reachable grid area on the upper left side of the first reachable grid area, and the center point of a fourth reachable grid area on the upper side of the first reachable grid area changes in stages according to the amount of remaining power after movement of the first reachable grid area, the second reachable grid area, the third reachable grid area, and the fourth reachable grid area.

[0174] In addition, when there is no reachable grid area to the right of the selected first reachable grid area, the gradient image generating unit 210 generates a gradient image in which the color or brightness within the drawing area formed by connecting the center point of the selected first reachable grid area, the center point of the grid area to the right of the first reachable grid area, the center point of the grid area to the upper right of the first reachable grid area, and the center point of the grid area to the upper side of the first reachable grid area changes in stages according to the remaining power amount after the movement of the first reachable grid area and the three grid areas.

[0175] In addition, when there is no reachable grid area below the selected first reachable grid area, the gradient image generating unit 210 generates a gradient image in which the color or brightness within the drawing area formed by connecting the center point of the selected first reachable grid area, the center point of the grid area to the left of the first reachable grid area, the center point of the grid area to the lower left of the first reachable grid area, and the center point of the grid area below the first reachable grid area changes in stages according to the remaining power amount after the first reachable grid area and the three grid areas are moved.

[0176] In addition, when there is no reachable grid area to the right of the selected first reachable grid area and there is no reachable grid area to the bottom of the selected first reachable grid area, the gradient image generating unit 210 generates a gradient image in which the color or brightness within the drawing area formed by connecting the center point of the selected first reachable grid area, the center point of the grid area to the right of the first reachable grid area, the center point of the grid area to the lower right of the first reachable grid area, and the center point of the grid area to the bottom of the first reachable grid area changes in stages according to the remaining power amount after the movement of the first reachable grid area and the three grid areas.

[0177] Thus, the gradation image is also generated on the right side, the bottom side, and the lower right side of the plurality of reachable mesh areas, and thus it is possible to prevent the right side, the bottom side, and the lower right side of the gradation image from being lost.

[0178] Next, in step S33 , the gradation image generating unit 210 determines whether all of the mesh area IDs of the plurality of reachable mesh areas have been selected.

[0179] Here, when it is determined that not all of the grid area IDs of the multiple reachable grid areas have been selected (No in step S33), the process returns to step S30, and the gradient image generating unit 210 selects the grid area IDs of other reachable grid areas among the multiple reachable grid areas determined by the reachable grid area determining unit 209.

[0180] On the other hand, when it is determined that all the grid area IDs of the plurality of reachable grid areas are selected (Yes in step S33), in step S34, the output unit 211 outputs the drivable range information obtained by superimposing the gradient image generated by the gradient image generating unit 210 on the map to the communication unit 21. The gradient image has a given transparency. The given transparency is, for example, 50%. Thus, the map under the gradient image can be visually confirmed.

[0181] Next, in step S35, the communication unit 21 transmits the drivable range information to the information terminal 3. The information terminal 3 displays the received drivable range information.

[0182] Fig.11 This is a diagram showing an example of the drivable range information displayed on the information terminal 3 in the first embodiment.

[0183] The display unit of the information terminal 3 displays Fig.11 The drivable range information 301 is shown. The drivable range information 301 includes a map image 311, a gradient image 312 superimposed on the map image 311, a departure point icon 313 indicating the departure point of the electric vehicle 1, and a color bar 314 indicating the correspondence between the drivable probability and the color. The gradient image 312 is, for example, semi-transparent, and the map image 311 under the gradient image 312 is displayed so as to be visually confirmed. Since the drivable range of the electric vehicle 1 is displayed in a gradient manner, the user can obtain a more detailed drivable range of the electric vehicle 1 by observing the drivable range information 301.

[0184] In this way, multiple grid areas in which the remaining power amount after movement is greater than the threshold value among the multiple grid areas are determined as multiple reachable grid areas. A gradient image is generated in which the color or brightness in the drawing area formed by connecting the center point of one reachable grid area among the multiple reachable grid areas and the three center points of three reachable grid areas around the one reachable grid area changes in stages according to the remaining power amount after movement of the one reachable grid area and the three reachable grid areas. A gradient image is generated for all of the multiple reachable grid areas. The drivable range information obtained by superimposing the generated gradient image on the map is output.

[0185] Therefore, the travelable range of the electric vehicle 1 can be indicated by a gradation in which the color or brightness changes stepwise according to the remaining power amount of the battery of the electric vehicle 1 after the movement, so that the travelable range of the electric vehicle 1 can be displayed in detail.

[0186] (Implementation method 2)

[0187] In the above-mentioned first embodiment, the power consumption between the representative point of the grid area including the departure point of the electric vehicle 1 and the representative points of other grid areas is estimated. In this case, the distance between the departure point and the representative point is not considered, and the power consumption when moving from the departure point to the representative point is not considered. In contrast, in the second embodiment, the first power consumption between the departure representative point around the departure point of the electric vehicle 1 and the representative points of other grid areas is estimated, and the second power consumption between the departure point of the electric vehicle 1 and the departure representative point is estimated, and the total power consumption obtained by adding the first power consumption and the second power consumption is calculated. Thus, the distance between the departure point and the representative point (departure representative point) is considered, and the power consumption when moving from the departure point to the representative point (departure representative point) is considered.

[0188] Fig.12 This is a diagram showing an example of the configuration of a server 2A in Embodiment 2 of the present disclosure.

[0189] Fig.12 The server 2A shown in the figure includes a communication unit 21, a memory 22, and a processor 23A. In the second embodiment, the same components as those in the first embodiment are denoted by the same reference numerals, and description thereof will be omitted.

[0190] The processor 23A is, for example, a CPU. The processor 23A implements the log information acquisition unit 201, the estimation model learning unit 202, the correction rate generation unit 203, the power consumption DB generation unit 204, the vehicle information acquisition unit 205, the power consumption estimation unit 206A, the power consumption correction unit 207, the remaining power after movement calculation unit 208A, the reachable grid area determination unit 209, the gradient image generation unit 210, and the output unit 211.

[0191] The power consumption estimation unit 206A determines four representative departure points that are located around the departure point among the representative points included in each of the multiple grid areas. The power consumption estimation unit 206A divides the multiple grid areas into four blocks each including the four representative departure points. The power consumption estimation unit 206A estimates the first power consumption when moving from the departure representative point to the representative points of each of the multiple grid areas in the same block according to each of the multiple grid areas. The power consumption estimation unit 206A searches for a moving path from the departure point to the representative departure point. The power consumption estimation unit 206A estimates the second power consumption when the electric vehicle 1 moves on the searched moving path. The power consumption estimation unit 206A calculates the total power consumption obtained by adding the estimated first power consumption and the estimated second power consumption. The power consumption estimation unit 206A calculates the total power consumption in each of the four blocks.

[0192] Fig.13 Schematic diagram for explaining the estimation of the power consumption amount by the power consumption estimation unit 206A in the second embodiment. Fig.13 In the figure, the black circle represents the center point (center of gravity) of the grid area, and the black square represents the representative point.

[0193] The power consumption estimation unit 206A determines four representative departure points 161, 162, 163, and 164 located around the departure point 141 among the representative points included in each of the plurality of grid areas. At this time, the power consumption estimation unit 206A determines the four representative departure points 161, 162, 163, and 164 in order from near to far from the departure point 141.

[0194] Next, the power consumption estimation unit 206A divides the plurality of grid areas 101 to 116 into four blocks 151, 152, 153, and 154, each including four representative departure points 161, 162, 163, and 164. For example, the first block 151 including the representative departure point 161 is composed of the plurality of grid areas 109, 110, 113, and 114. In addition, the second block 152 including the representative departure point 162 is composed of the plurality of grid areas 101, 102, 105, and 106. In addition, the third block 153 including the representative departure point 163 is composed of the plurality of grid areas 103, 104, 107, and 108. In addition, the fourth block 154 including the representative departure point 164 is composed of the plurality of grid areas 111, 112, 115, and 116.

[0195] The plurality of grid areas 101 to 116 are allocated as a first block 151 , a second block 152 located above the first block 151 , a third block 153 located to the upper right of the first block, and a fourth block located to the right of the first block.

[0196] Next, the power consumption estimating unit 206A estimates the first power consumption when moving from the starting representative point 161 of the first block 151 to the representative points of the plurality of mesh areas 109 , 113 , 114 in the first block 151 for each of the plurality of mesh areas 109 , 113 , 114 .

[0197] Next, the power consumption estimation unit 206A searches for a movement route from the departure point 141 to the representative departure point 161 .

[0198] Next, the power consumption estimation unit 206A estimates the second power consumption when the electric vehicle 1 moves on the searched moving path. At this time, the power consumption estimation unit 206A calculates the moving distance of the searched moving path. In addition, the power consumption estimation unit 206A estimates the second power consumption when the electric vehicle 1 moves on the searched moving path by inputting the calculated moving distance of the moving path into a pre-stored power consumption estimation model.

[0199] Next, the power consumption estimation unit 206A calculates a total power consumption obtained by adding the first power consumption estimated for each of the plurality of grid areas 109, 113, and 114 to the second power consumption estimated. That is, the power consumption estimation unit 206A calculates a total power consumption obtained by adding the first power consumption when moving from the representative departure point 161 to the representative point in the grid area 109 and the second power consumption when moving from the departure point 141 to the representative departure point 161. Furthermore, the power consumption estimation unit 206A calculates a total power consumption obtained by adding the first power consumption when moving from the representative departure point 161 to the representative point in the grid area 113 and the second power consumption when moving from the departure point 141 to the representative departure point 161. Furthermore, the power consumption estimation unit 206A calculates a total power consumption obtained by adding a first power consumption when moving from the representative departure point 161 to a representative point in the grid area 114 and a second power consumption when moving from the departure point 141 to the representative departure point 161. The power consumption estimation unit 206A calculates the total power consumption for all grid areas in the first block 151.

[0200] Furthermore, the power consumption estimation unit 206A calculates the total power consumption in each of the second block 152 to the fourth block 154 other than the first block 151 .

[0201] The remaining power after movement calculation unit 208A calculates the remaining power after movement when the electric vehicle 1 moves from the departure point to the plurality of grid areas respectively, based on the current remaining power acquired by the vehicle information acquisition unit 205 and the plurality of total power consumptions estimated by the power consumption estimation unit 206A. In addition, the remaining power after movement calculation unit 208A calculates the remaining power after movement when the electric vehicle 1 moves from the departure point to the plurality of grid areas respectively, based on the current remaining power acquired by the vehicle information acquisition unit 205 and the plurality of total power consumptions corrected by the power consumption correction unit 207, for each of the plurality of grid areas.

[0202] The remaining power calculation unit 208A calculates the remaining power after the electric vehicle 1 moves from the grid area including the departure point to another grid area by subtracting multiple total power consumption amounts corrected by the power consumption correction unit 207 from the current remaining power acquired by the vehicle information acquisition unit 205.

[0203] Next, the drivable range presentation process of the server 2A in the second embodiment will be described.

[0204] Fig.14 is a first flowchart for explaining the drivable range presentation processing of the server 2A in the second embodiment. Fig.15 This is a second flowchart for explaining the drivable range presentation process of the server 2A in the second embodiment.

[0205] In addition, the processing of step S41 to step S42 is the same as Fig. 9 The processing of step S21 to step S22 is the same, so the description is omitted.

[0206] Next, in step S43, the power consumption estimation unit 206A specifies four representative departure points that are located around the departure point among the representative points included in each of the plurality of mesh areas.

[0207] Next, in step S44 , the power consumption estimation unit 206A divides the plurality of mesh areas into four blocks each including four representative departure points.

[0208] Next, in step S45, the power consumption estimation unit 206A selects one block from among the four divided blocks.

[0209] Next, in step S46, the power consumption estimation unit 206A reads out one power consumption as the first power consumption from the power consumption DB storage unit 226, from a plurality of power consumptions corresponding to the grid area ID of the grid area including the representative departure point and the grid area IDs of a plurality of other grid areas in the same block.

[0210] Next, in step S47, the power consumption estimation unit 206A searches for a movement route from the departure point to the representative departure point.

[0211] Next, in step S48 , the power consumption estimating unit 206A estimates the second power consumption when the electric vehicle 1 moves on the searched travel route.

[0212] Next, in step S49, the power consumption estimation unit 206A calculates a total power consumption amount by adding the read first power consumption amount and the estimated second power consumption amount.

[0213] Next, in step S50, the power consumption correction unit 207 corrects the total power consumption calculated by the power consumption estimation unit 206A. At this time, the power consumption correction unit 207 reads out the correction rate corresponding to the moving distance between the departure point and the representative points of other grid areas from the correction rate storage unit 224, and multiplies the read correction rate by the total power consumption, thereby correcting the total power consumption.

[0214] Next, in step S51, the remaining power after movement calculation unit 208A calculates the remaining power after movement of the electric vehicle 1 when it moves from the starting point to another grid area by subtracting the total power consumption corrected by the power consumption correction unit 207 from the current remaining power acquired by the vehicle information acquisition unit 205.

[0215] In addition, the processing of steps S52 to S53 is the same as Fig. 9 The processing of step S27 to step S28 is the same, so the description is omitted.

[0216] Next, in step S54 , the power consumption estimating unit 206A determines whether all power consumptions associated with the mesh area ID of the mesh area including the representative departure point and the mesh area IDs of a plurality of other mesh areas have been read.

[0217] Here, when it is determined that not all power consumption has been read out (No in step S54), the process returns to step S46, and the power consumption estimation unit 206A reads out other power consumption as the first power consumption from the power consumption DB storage unit 226, from the multiple power consumptions corresponding to the grid area ID of the grid area including the representative departure point and the grid area IDs of multiple other grid areas in the same block.

[0218] On the other hand, when it is determined that all the power consumption amounts have been read (YES in step S54 ), in step S55 , the power consumption estimating unit 206A determines whether all of the four blocks have been selected.

[0219] Here, when it is determined that not all of the four blocks have been selected (No in step S55 ), the process returns to step S45 , and the power consumption estimation unit 206A selects the other unselected blocks among the four divided blocks.

[0220] On the other hand, when it is determined that all four blocks are selected (yes in step S55 ), in step S56 , the gradation image generating unit 210 selects the grid area ID of one reachable grid area among the plurality of reachable grid areas determined by the reachable grid area determining unit 209 .

[0221] In addition, the processing of steps S56 to S61 is the same as Fig.10 The processing of step S30 to step S35 is the same, so the description is omitted.

[0222] In addition, in each of the above-mentioned embodiments, each component may also be constituted by dedicated hardware, or implemented by executing a software program suitable for each component. Each component may also be implemented by a program execution unit such as a CPU or a processor reading and executing a software program recorded on a recording medium such as a hard disk or a semiconductor memory. In addition, the program may also be transferred by recording it on a recording medium, or by transferring the program via a network, so that the program is implemented by another independent computer system.

[0223] Part or all of the functions of the device involved in the embodiments of the present disclosure are typically implemented as LSI (Large Scale Integration) as an integrated circuit. They can be monolithic individually or in a manner that includes part or all of them. In addition, integrated circuitization is not limited to LSI, and can also be implemented by a dedicated circuit or a general-purpose processor. It is also possible to use an FPGA (Field Programmable Gate Array) that can be programmed after LSI manufacturing, or a reconfigurable processor that can reconfigure the connection and setting of the circuit unit inside the LSI.

[0224] Furthermore, a part or all of the functions of the apparatus according to the embodiment of the present disclosure may be realized by executing a program by a processor such as a CPU.

[0225] In addition, all the numbers used in the above description are exemplified in order to specifically describe the present disclosure, and the present disclosure is not limited to the exemplified numbers.

[0226] In addition, the order in which the steps shown in the above flowchart are executed is used as an example to specifically explain the order of the present disclosure, and the order other than the above may be used within the scope of obtaining the same effect. In addition, part of the above steps may also be executed simultaneously (in parallel) with other steps.

[0227] Industrial Applicability

[0228] The technology according to the present disclosure can display the drivable range of an electric vehicle in detail, and is therefore useful as a technology for presenting the drivable range of an electric vehicle.

Claims

1. An information processing method is an information processing method in a computer. Acquiring a departure point of the electric vehicle and a current remaining amount of power of a storage battery of the electric vehicle; estimating the amount of power consumed by the electric mobile object when the electric mobile object moves from the departure point to each of a plurality of mesh areas obtained by dividing the map; calculating, based on the current remaining power amount and the consumed power amount, the remaining power amount after the electric moving object moves from the starting point to the plurality of grid areas respectively; generating an image in which the color or brightness within a drawing area formed by connecting the representative points of the four grid areas changes stepwise according to the remaining power amount after the movement; Information obtained by superimposing the generated image on a map is output.

2. The information processing method according to claim 1, wherein: Further, a plurality of grid areas where the remaining power amount after the movement is greater than a threshold value are determined as a plurality of reachable grid areas, In the generation of said image: generating a gradient image in which the color or brightness in a drawing area formed by connecting the center points of four reachable grid areas among the plurality of reachable grid areas changes stepwise according to the remaining power amount after the movement, generating the gradient image for all of the plurality of reachable grid areas, In the output of the information, information obtained by superimposing the generated gradation image on a map is output.

3. The information processing method according to claim 2, wherein: In the generation of the image, the gradient image is generated so that the color or brightness within the drawing area formed by connecting the center point of one reachable grid area among the multiple reachable grid areas and the three center points of three reachable grid areas surrounding the one reachable grid area changes in stages according to the remaining power amount after the movement of the one reachable grid area and the three reachable grid areas.

4. The information processing method according to claim 1, wherein: In the estimation of the power consumption, the power consumption is read out for each of the plurality of grid areas from a power consumption storage unit that stores in advance the power consumption when the electric vehicle moves between the plurality of grid areas.

5. The information processing method according to claim 4, wherein: Further, searching for a moving path from a grid area that becomes a starting point to a grid area that becomes an end point among the plurality of grid areas, Furthermore, the moving distance of the searched moving path is input into a power consumption estimation model generated by machine learning with the moving distance as an input value and the power consumption as an output value, thereby estimating the power consumption of the electric mobile body when it moves between the grid areas. Furthermore, the estimated power consumption amount, the mesh area serving as a start point, and the mesh area serving as an end point are stored in the power consumption amount storage unit in association with each other.

6. The information processing method according to claim 1, wherein: Furthermore, the correction ratio is read out from a correction ratio storage unit that stores correction ratios in association with movement distances and moving body identification information for identifying a plurality of electric moving bodies. Further, the power consumption is corrected using the correction rate read out, The correction rate is a value obtained by dividing the amount of power consumed by the electric vehicle identified by the vehicle identification information when it moves a given distance by an average of the amounts of power consumed by a plurality of electric vehicles of the same vehicle type when they move the same distance as the given distance.

7. The information processing method according to claim 1, wherein: In estimating the power consumption, the power consumption of the electric vehicle when moving from a representative point included in the grid area where the departure point is located to a representative point included in each of the plurality of grid areas is estimated for each of the plurality of grid areas.

8. The information processing method according to claim 7, wherein: The representative point is a node on the map that is closest to the center point of the grid area.

9. The information processing method according to claim 2, wherein: The drawing area is a rectangle. In the generation of the image, the gradient image is generated so that the color or brightness within the drawing area formed by connecting the center point of the first reachable grid area among the multiple reachable grid areas, the center point of the second reachable grid area on the left side of the first reachable grid area, the center point of the third reachable grid area on the upper left side of the first reachable grid area, and the center point of the fourth reachable grid area on the upper side of the first reachable grid area changes in stages according to the remaining power amount after the movement of the first reachable grid area, the second reachable grid area, the third reachable grid area, and the fourth reachable grid area.

10. The information processing method according to claim 1, wherein: In the estimation of the power consumption, four representative departure points located around the departure point are determined among the representative points included in each of the plurality of grid areas, the plurality of grid areas are divided into four blocks each including the four representative departure points, a first power consumption when moving from the representative departure point to each of the representative points of the plurality of grid areas in the same block is estimated for each of the plurality of grid areas, a moving path from the departure point to the representative departure point is searched, a second power consumption when the electric mobile body moves on the searched moving path is estimated, a total power consumption is calculated by adding the estimated first power consumption and the estimated second power consumption, and the total power consumption is calculated in each of the four blocks, In the calculation of the remaining power after the movement, based on the acquired current remaining power and the calculated multiple total power consumption, the remaining power after the movement of the electric mobile body when it moves from the starting point to the multiple grid areas respectively is calculated according to each of the multiple grid areas.

11. An information processing device comprising: an acquisition unit that acquires a departure point of the electric mobile body and a current remaining power amount of a storage battery included in the electric mobile body; an estimating unit that estimates the amount of power consumed when the electric mobile body moves from the departure point to each of a plurality of mesh areas obtained by dividing the map; A calculation unit that calculates the remaining power amount after the electric moving body moves from the departure point to each of the plurality of grid areas based on the current remaining power amount and the consumed power amount; A generating unit generating an image in which the color or brightness in a drawing area formed by connecting the representative points of the four mesh areas changes stepwise according to the remaining power amount after the movement; and The output unit outputs information obtained by superimposing the generated image on a map.

12. An information processing program that enables a computer to function so that: Acquiring a departure point of the electric vehicle and a current remaining amount of power of a storage battery of the electric vehicle; estimating the amount of power consumed by the electric mobile object when the electric mobile object moves from the departure point to each of a plurality of mesh areas obtained by dividing the map; calculating, based on the current remaining power amount and the consumed power amount, the remaining power amount after the electric moving object moves from the starting point to the plurality of grid areas respectively; generating an image in which the color or brightness within a drawing area formed by connecting the representative points of the four grid areas changes stepwise according to the remaining power amount after the movement; Information obtained by superimposing the generated image on a map is output.

Images