Selection device, selection method, and program

Abstract

To provide a selection device etc. capable of selecting an electric vehicle capable of reducing possibility of performing charging in a place where charging is not easy.SOLUTION: A selection device 10 includes: an easiness determination unit 120 for determining easiness of charging of an electric vehicle in a target area including a destination using a relation between a density of a charging port for the electric vehicle, a predicted density of the electric vehicle, and easiness of charging the electric vehicle from density of the charging port in the target area and density of the predicted electric vehicle in the target area; an estimation unit 130 for estimating estimated distance for which a user going from a predetermined departure point to the destination by the electric vehicle causes the electric vehicle to travel without being charged by using the easiness of charging and distance between the departure point and the destination; a selection unit 140 for selecting the electric vehicle capable of traveling the estimated distance from a fully charged state from among available electric vehicles; and an output unit 150 for outputting information on the selected electric vehicle.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] This disclosure relates to a technology for selecting an electric vehicle.

Background Art

[0002] The number of charging ports for power supply to electric vehicles is not necessarily sufficient. Depending on the region, visitors may be made to wait for charging at the available charging ports.

[0003] Patent Document 1 describes a vehicle allocation device that determines an electric vehicle to be allocated based on the charging priority of an area including the user's boarding position or the current position of the electric vehicle, the charging priority of an area including the user's destination, and the remaining battery level of the electric vehicle. The charging priority in Patent Document 1 is an index representing the recommended degree of charging of electric vehicles in an area.

[0004] Patent Document 2 describes a management device that selects an electric vehicle having a charge amount that can reach from a first point to a second point on a route from a departure point to an arrival point from among a group of electric vehicles present at the first point. The first point is a point on the route that is not the arrival point. The second point is a point on the route on the arrival point side to be reached next. The management device sets the recommended degree of the selected electric vehicle based on the shortage of the charge amount of the electric vehicle.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0006] The charging priority described in Patent Document 1 is defined in relation to indicators such as the power supply and demand situation, the density of charging stations, or the utilization rate of renewable energy. However, if the charging priority is defined in relation to the power supply and demand situation or the utilization rate of renewable energy, it does not necessarily mean that there are many available charging stations in areas with a high charging priority. Even when charging priority is defined in relation to the density of charging stations, it is not necessarily true that the number of electric vehicles charging per station will be low in areas with a high density of charging stations. If many users charge their electric vehicles in areas with high charging priority and high charging station density, the number of electric vehicles charging per station may increase in those areas. Thus, charging electric vehicles is not necessarily easy in areas with high charging priority as described in Patent Document 1.

[0007] Furthermore, in the technology described in Patent Document 1, for example, if the charging priority for the area including the current location is low and the charging priority for the area including the destination is high, priority is given to dispatching an electric vehicle with as little battery remaining as possible that is greater than the amount of charge required for travel. Also, if the charging priority for the area including the destination is low, priority is given to dispatching an electric vehicle with as much battery remaining as possible that is greater than the amount of charge required for travel to the destination. Therefore, when using a dispatched electric vehicle, it is not possible to reduce the possibility of having to charge in a location where charging is not easy.

[0008] In the technology described in Patent Document 2, when a user travels from a starting point to a destination using an electric vehicle, it is necessary that multiple electric vehicles that the user can use for transfers are present along the route from the starting point to the destination. However, in the technology described in Patent Document 2, when a user uses only one electric vehicle, the possibility of having to charge it in a location where charging is not easily possible cannot be reduced.

[0009] One of the purposes of this disclosure is to provide a selection device, etc., that allows for the selection of an electric vehicle that can reduce the likelihood of charging in locations where charging is not easy. [Means for solving the problem]

[0010] A selection device according to one aspect of the present disclosure includes: ease determination means for determining the ease of charging electric vehicles in a target area, including a destination, based on the density of charging ports in the target area and the predicted density of electric vehicles in the target area, using the relationship between the density of charging ports for electric vehicles and the predicted density of electric vehicles, and the ease of charging electric vehicles; estimation means for estimating the estimated distance that a user traveling from a departure point to the destination by electric vehicle will travel without charging, using the ease of charging and the distance between a predetermined departure point and the destination; selection means for selecting an electric vehicle capable of traveling the estimated distance from a fully charged state from among available electric vehicles; and output means for outputting information on the selected electric vehicle.

[0011] A selection method according to one aspect of the present disclosure uses the relationship between the density of charging ports for electric vehicles and the predicted density of electric vehicles and the ease of charging electric vehicles to determine the ease of charging electric vehicles in a target area including a destination, based on the density of charging ports in the target area and the predicted density of electric vehicles in the target area, uses the ease of charging and the distance between a predetermined starting point and the destination to estimate the estimated distance that a user traveling from the starting point to the destination by electric vehicle would travel without charging, selects an electric vehicle capable of traveling the estimated distance from a fully charged state from among the available electric vehicles, and outputs information on the selected electric vehicle.

[0012] A program according to one aspect of this disclosure causes a computer to perform the following: an ease determination process that determines the ease of charging an electric vehicle in a target area, including a destination, based on the density of charging ports in the target area and the predicted density of electric vehicles in the target area, using the relationship between the density of charging ports for electric vehicles and the predicted density of electric vehicles, and the ease of charging an electric vehicle; an estimation process that estimates the distance that a user traveling from a starting point to the destination by electric vehicle will travel without charging, using the ease of charging and the distance between a predetermined starting point and the destination; a selection process that selects an electric vehicle capable of traveling the estimated distance from a fully charged state from among available electric vehicles; and an output process that outputs information about the selected electric vehicle. [Effects of the Invention]

[0013] This disclosure has the effect of allowing users to choose electric vehicles that reduce the likelihood of having to charge them in places where charging is not easy. [Brief explanation of the drawing]

[0014] [Figure 1] Figure 1 is a block diagram showing an example of the configuration of a selection device according to the first embodiment of this disclosure. [Figure 2] Figure 2 is a flowchart illustrating an example of the operation of a selection device according to the first embodiment of this disclosure. [Figure 3] Figure 3 is a block diagram showing an example of the configuration of a selection device according to a second embodiment of the present disclosure. [Figure 4] Figure 4 is a flowchart illustrating an example of the operation of a selection device according to a second embodiment of this disclosure. [Figure 5] Figure 5 is a diagram showing an example of a computer hardware configuration that can realize the selection device according to the embodiment of this disclosure. [Modes for carrying out the invention]

[0015] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings.

[0016] <First Embodiment> First, the first embodiment of the present disclosure will be described in detail with reference to the drawings.

[0017] <Configuration> FIG. 1 is a block diagram showing an example of the configuration of a selection device according to the first embodiment of the present disclosure. In the example shown in FIG. 1, a selection device 10 according to the first embodiment of the present disclosure includes an ease-of-charging determination unit 120, an estimation unit 130, a selection unit 140, and an output unit 150.

[0018] The ease-of-charging determination unit 120 determines the ease of charging electric vehicles in a target area including the destination based on the density of charging ports for electric vehicles in the target area and the predicted density of electric vehicles in the target area. The ease-of-charging determination unit 120 uses the relationship between the density of charging ports and the density of electric vehicles and the ease of charging electric vehicles to determine the ease of charging electric vehicles in the target area. The estimation unit 130 estimates the estimated distance that a user traveling from the starting point to the destination by an electric vehicle can travel the electric vehicle without charging, using the ease of charging and the distance between a predetermined starting point and the destination. The selection unit 140 selects, from among a plurality of available electric vehicles, an electric vehicle capable of traveling the estimated distance from a fully charged state. The output unit 150 outputs information on the selected electric vehicle.

[0019] <Ease-of-Charging Determination Unit 120> The ease determination unit 120 pre-stores the density of charging ports and the predicted density of electric vehicles in multiple regions, including locations that may be designated as destinations. Multiple regions are, for example, sub-regions obtained by dividing an area predetermined by, for example, the administrator, creator, or designer of the selection device, as an area including locations that may be designated as destinations. The area predetermined as an area including locations that may be designated as destinations is a pre-set area including a starting point, a location that may be designated as an arrival point, a location that may be designated as a destination, and roads that may form a route from the starting point to the arrival point via the destination. The area predetermined as an area including locations that may be designated as destinations is, for example, a country, a region (for example, Hokkaido, Tohoku, Hokuriku, Kanto, Tokai, Kinki, Chugoku, Shikoku, Kyushu, etc.), or a prefecture, etc. The area predetermined as an area including locations that may be designated as destinations is not limited to these examples. The area predetermined as containing a place that can be designated as a destination may be, for example, at least a part of an individual region, at least a part of an individual prefecture, or an area that connects them. The area predetermined as containing a place that can be designated as a destination may be determined independently of national and local government boundaries. The subdivided sub-regions may be, for example, a city, town, or village, a part within a city, town, or village, or a sub-region that connects at least one of these. The subdivided sub-regions are not limited to these examples. The subdivided sub-regions may also be determined independently of national and local government boundaries. In this embodiment, a destination is represented by a point indicated, for example, by a value representing latitude and a value representing longitude. The region containing the destination is referred to as the target region. The density of charging ports is the number of charging ports installed in the region per predetermined area. The predicted density of electric vehicles is the number of electric vehicles predicted to be present in the region per predetermined area. The number of electric vehicles predicted to exist within a region is, for example, a statistical value of the number of electric vehicles present in the region during a specified time period (e.g., daytime hours such as 9 a.m. to 5 p.m.). The specified time period is not limited to this example.The predetermined time period may be another predetermined time period. The statistical value of the quantity may be, for example, the maximum value, the average value, the mode value, the median value, or the central value, etc. In this case, the mode value of the quantity may be the mode value of the maximum value or the average value of the quantity for each of the plurality of time periods obtained by dividing the above-mentioned predetermined time period. In this case, the median value of the quantity may be the median value of the maximum value or the average value of the quantity for each of the plurality of time periods obtained by dividing the above-mentioned predetermined time period. In this case, the central value of the quantity may be the central value of the maximum value or the average value of the quantity for each of the plurality of time periods obtained by dividing the above-mentioned predetermined time period. The predicted density of electric vehicles is also referred to as the predicted density of electric vehicles in the description of the embodiments of the present disclosure.

[0020] The ease of charging an electric vehicle may be represented by, for example, the waiting time for the charging order at the charging port. In this case, the ease of charging may be represented by a unit appropriately selected from, for example, seconds, minutes, or hours, etc. The waiting time is, for example, the time from when queuing for charging until starting to charge. The timing of starting to charge may be defined as appropriate. The timing of starting to charge may be, for example, the timing of starting the work for charging. When there is no queue for charging, the waiting time value is zero. The ease of charging an electric vehicle may also be represented by, for example, the sum of the time to search for a charging port and the time to wait in line at the charging port. In the description of the present disclosure, the ease of charging is also referred to as the charging ease.

[0021] The relationship between the density of charging ports and the density of electric vehicles and the waiting time for the charging order at the charging port may be experimentally determined in advance. For example, the range of values that the density of charging ports can take may be divided into a plurality of ranges (hereinafter referred to as the first range). The range of values that the density of electric vehicles can take may also be divided into a plurality of ranges (hereinafter referred to as the second range). Furthermore, for each combination of the first and second ranges, a representative value of the waiting time, determined experimentally, may be associated with it. The representative value is a statistical value such as the mean or mode. The representative value of the waiting time associated with the combination of the first and second ranges is the representative value of the waiting time measured in a situation where the density of charging ports falls within the first range and the density of electric vehicles falls within the second range.

[0022] The ease-of-charging determination unit 120 may use a waiting time associated with a combination of a first range including the charging density of the target area including the destination and a second range including the predicted density of the electric vehicle as a value representing the ease of charging. Note that ease of charging is an index that represents the degree of ease of charging. Ease of charging in this disclosure does not have to be related to the difficulty of the charging operation. Ease of charging in this disclosure may be related to the time from when preparation for charging begins to when the charging operation begins. The start of preparation for charging may be, for example, when one begins to look for a charging port. The start of preparation for charging may be when one begins to join a queue for charging.

[0023] Furthermore, the relationship between the density of charging ports and the time it takes to find a charging port may also be determined experimentally beforehand. In this case as well, the range of possible values ​​for the density of charging ports may be divided into multiple ranges (hereinafter referred to as the third range). In this case, the multiple third ranges into which the range of possible values ​​for the density of charging ports is divided may coincide with the multiple first ranges described above. For each of the first ranges, a representative value of the time it takes to find a charging port, measured in the area where the density of charging ports falls within the first range, may be associated with that first range. The time it takes to find a charging port may be the time from when you start searching for a charging port until you find one. If there is a queue for charging, the time from when you start searching for a charging port until you find one may be the time from when you start searching for a charging port until you join the queue. If there is no queue for charging, the time from when you start searching for a charging port until you start charging may be the time from when you start searching for a charging port until you start charging.

[0024] In this case, the ease determination unit 120 identifies a waiting time (specifically, a representative value thereof) associated with a combination of a first range including the charging density of the target area including the destination and a second range including the predicted density of electric vehicles. The ease determination unit 120 then identifies a time (specifically, a representative value thereof) for searching for a charging port associated with a third range including the charging density of the target area including the destination. The ease determination unit 120 may use the sum of the time for searching for the identified charging port and the identified waiting time (specifically, the sum of the representative value of the time for searching for the identified charging port and the representative value of the identified waiting time) as a value representing the ease of charging.

[0025] In the above example, a smaller value for ease of charging indicates easier charging. The relationship between the value of ease of charging and the ease of charging may be the reverse of the relationship in the above example. In the following explanation, we will assume that a smaller value for ease of charging indicates easier charging.

[0026] <Estimation part 130> As described above, the estimation unit 130 estimates the distance that a user traveling by electric vehicle from a starting point to a destination will travel without charging, using, for example, the ease of charging and the distance between a predetermined starting point and the destination. The estimation unit 130 estimates the distance that a user will travel without charging the electric vehicle in the target area, for example, if the ease of charging in the target area including the destination does not meet a predetermined standard.

[0027] The user boards a fully charged electric vehicle at the departure point and departs from the departure point towards the destination. The departure point is, for example, the point where an electric vehicle rental company hands over the rental vehicle to the user. The user travels in the electric vehicle from the departure point to the destination and from the destination to the arrival point. The arrival point is, for example, the point where the user returns the electric vehicle. The arrival point may be the same as the departure point. The arrival point may be different from the departure point.

[0028] The distance between a designated starting point and a designated destination is the length of the route taken when traveling by car from the designated starting point to the destination.

[0029] For example, the ease determination unit 120 described above may calculate the distance between a predetermined starting point and a destination using existing technology used in car navigation systems. The estimation unit 130 may receive the distance between a predetermined starting point and a destination from the ease determination unit 120. The estimation unit 130 may calculate the distance between a predetermined starting point and a destination using existing technology used in car navigation systems.

[0030] The method by which the estimation unit 130 estimates the distance will be explained in detail later.

[0031] Furthermore, the estimation unit 130 may use the length of the route from the starting point to the destination via the destination as the estimated distance if the length of the route from the starting point to the destination via the destination is less than or equal to the driving range of at least one of the electric vehicles. The estimation unit 130 may estimate the estimated distance according to the method for estimating the estimated distance if the length of the route from the starting point to the destination via the destination is greater than the driving range of at least one of the electric vehicles. The driving range of an electric vehicle, as described later, represents the driving distance when driving under predetermined conditions, starting with a full charge and continuing until the battery level reaches a predetermined level.

[0032] <Selection section 140> As described above, the selection unit 140 selects an electric vehicle capable of traveling the estimated distance from a fully charged state from among the available electric vehicles. An available electric vehicle is, for example, an electric vehicle that can be lent to a user at the starting point described above. The selection unit 140 selects, for example, an electric vehicle in which the remaining battery charge after starting to drive from a fully charged state and traveling the estimated distance is equal to or greater than a predetermined amount. The selection unit 140 has in advance a relationship between the battery usage and the driving distance for each electric vehicle. The relationship between the battery usage and the driving distance may be expressed, for example, by the driving distance per predetermined amount of battery usage when driving under predetermined conditions. The relationship between the battery usage and the driving distance may be expressed, for example, by the battery usage when driving a predetermined distance under predetermined conditions.

[0033] The selection unit 140 may select multiple electric vehicles. The selection unit 140 may be given other conditions for the electric vehicles. The selection unit 140 may select an electric vehicle that can travel the estimated distance from a fully charged state from among the electric vehicles that meet the given conditions.

[0034] If there are no electric vehicles whose driving range from a full charge is greater than the estimated range, the selection unit 140 may select a predetermined number of electric vehicles, starting with those that have the longest driving range from a full charge.

[0035] <Output section 150> The output unit 150 may output the information of the selected electric vehicle to a terminal device held by the user. The output unit 150 may output the information of the selected electric vehicle to an information processing device managed by the electric vehicle owner (for example, an electric vehicle rental company). The output unit 150 may output the information of the selected electric vehicle to another information processing device or the like.

[0036] <Operation> Next, the operation of the selection device 10 according to the first embodiment of this disclosure will be described.

[0037] Figure 2 is a flowchart showing an example of the operation of the selection device 10 according to the first embodiment of the present disclosure. In the example shown in Figure 2, the ease of charging determination unit 120 determines the ease of charging an electric vehicle in the target area (step S11). Next, the estimation unit 130 estimates the distance that the user can travel without charging the electric vehicle, using the ease of charging in the target area and the distance between the starting point and the destination (step S12). Then, the selection unit 140 selects an electric vehicle that can travel the estimated distance from a fully charged state (step S13). Finally, the output unit 150 outputs information about the selected electric vehicle (step S14).

[0038] <Effects> This embodiment has the effect of allowing the selection of an electric vehicle that can reduce the likelihood of charging in locations where charging is not easy. This is because the estimation unit 130 uses the ease of charging in the target area and the distance between the starting point and the destination to estimate the estimated distance that a user traveling from the starting point to the destination by electric vehicle will need to travel without charging. The selection unit 140 then selects an electric vehicle that can travel the estimated distance from a fully charged state.

[0039] <Method for estimating distance> As described above, the estimation unit 130 estimates the distance that a user traveling by electric vehicle from a starting point to a destination will travel without charging, using, for example, the ease of charging and the distance between a predetermined starting point and the destination. The estimation unit 130 estimates the distance that a user will travel without charging the electric vehicle in the target area, for example, if the ease of charging in the target area including the destination does not meet a predetermined standard.

[0040] The estimation unit 130 may estimate the distance an electric vehicle can travel without charging, using the ease of charging in each region through which the route from the starting point to the destination via the destination passes, so that the user can refrain from charging in regions where the ease of charging does not meet a predetermined standard. In this case, for example, the ease determination unit 120 may derive a route from the starting point to the destination via the destination using an existing method used in a car navigation system. The ease determination unit 120 may then identify the regions through which the derived route passes. The ease determination unit 120 may further determine the ease of charging in the identified regions. If the route includes roads such as expressways, the ease determination unit 120 may set the ease of charging in the parts of such roads in the route other than where charging ports exist to a predetermined value as the maximum value of the ease of charging. The aforementioned expressways and other roads are roads where entry is not possible at parts other than the entrance and exit is not possible at parts other than the exit, and where charging ports do not exist except at specific locations (such as service areas).

[0041] Generally, there are fewer charging ports for electric vehicles compared to gas stations. Therefore, it's not possible to charge an electric vehicle just anywhere. As a result, rental companies that lend out electric vehicles often do not require the vehicle to be fully charged upon return. Users who rent electric vehicles often do not charge them unless they need to before returning the vehicle. Also, when users rent electric vehicles for sightseeing or other purposes, they may obtain information about charging ports near their destination. However, they may not thoroughly check information about charging ports along the route between their departure point and destination (or between their destination and arrival point). Furthermore, while users may visit various places by electric vehicle near their destination, they tend to stick to their route between the departure point and destination, and between their destination and arrival point, except when stopping at facilities adjacent to the route such as restaurants or service areas. In the following, it is assumed that users will not charge their electric vehicles if they can reach their destination without charging, and if they cannot reach their destination without charging, they will charge in the target area if charging is easy in that area. Furthermore, it is assumed that if users cannot reach their destination without charging, and charging is not easy in the target area, they will charge in any area along the route from the departure point to the destination via the destination. In addition, it is assumed that users will charge when departing from the destination towards the destination if they choose to charge in the target area.

[0042] The following section describes specific examples of methods for estimating distance. Note that the methods for estimating distance are not limited to the examples below.

[0043] <Example 1> If the departure point and arrival point are the same location, and the outward and return journeys follow the same route, the estimation unit 130 may estimate the distance as follows, for example.

[0044] The estimation unit 130 determines the estimated distance to be the sum of the distance from the starting point to the destination and a predetermined additional distance if the ease of charging in the target area including the destination is less than the charging acceptance threshold (i.e., the ease of charging is easier than the ease indicated by the charging acceptance threshold). The additional distance may be, for example, a distance predetermined as the distance traveled by the electric vehicle other than the route taken by the user from the starting point to the destination via the destination. The charging ease threshold may represent, for example, the charging ease value at which a predetermined percentage or more of all survey participants felt a negative impression of charging the electric vehicle. The charging ease threshold may also be a value statistically derived from the survey results. The charging ease threshold may also be a value determined by other methods. The estimation unit 130 determines that if the ease of charging in the target area including the destination is equal to or greater than the charging acceptance threshold (i.e., the ease of charging is not as easy as indicated by the charging acceptance threshold), the estimated distance is the sum of twice the distance from the starting point to the destination and a predetermined additional distance.

[0045] <Example 2> If the starting point and the destination are not necessarily the same place, and if the route from the starting point to the destination is different from the route from the destination to the destination, the estimation unit 130 may estimate the distance as follows, for example.

[0046] The estimation unit 130 selects the larger of the distance from the starting point to the destination and the distance from the destination to the arrival point. If the distance from the starting point to the destination and the distance from the destination to the arrival point are the same, the estimation unit 130 uses the distance from the starting point to the destination (i.e., the distance from the destination to the arrival point) as the selected distance.

[0047] If the ease of charging in the target area including the destination is less than the charging acceptance threshold, the estimation unit 130 may use the sum of the selected distance and a predetermined additional distance as the estimated distance. If the ease of charging in the target area including the destination is greater than the charging acceptance threshold, the estimation unit 130 may use the sum of the distance from the departure point to the destination, the distance from the destination to the arrival point, and a predetermined additional distance as the estimated distance.

[0048] <Example 3> If the departure point and destination point are the same, and the outward and return journeys follow the same route, the estimation unit 130 may estimate the distance as follows, for example. In the following explanation, the route from the departure point to the destination point via the destination will be referred to as the travel route.

[0049] For example, the ease of charging determination unit 120 derives a route from the starting point to the destination using existing technology, such as that used in car navigation systems. The ease of charging determination unit 120 determines the charging ease of an area that includes at least a portion of the route between the starting point and the destination.

[0050] If the ease of charging in the target area including the destination is less than the charging tolerance threshold, the estimation unit 130 may estimate the estimated distance in the same way as the estimation unit 130 in Example 1. If the ease of charging in the target area including the destination is equal to or greater than the charging tolerance threshold, the estimation unit 130 selects the area closest to the target area from among the areas that include at least a part of the driving route and where the ease of charging is less than the charging tolerance threshold. The estimation unit 130 may then use the sum of the distance from the starting point to the destination, the distance from the destination to the selected area, and a predetermined additional distance as the estimated distance. The distance from the destination to the selected area may be, for example, the distance between the destination and the furthest point from the destination in the portion of the route from the destination back to the starting point that is included in the selected area. The distance from the destination to the selected area may be determined by other methods. These distances along the route may be calculated, for example, by the ease determination unit 120.

[0051] <Example 4> If the starting point and the destination point are different locations, the estimation unit 130 may estimate the distance as follows, for example.

[0052] For example, the ease of charging determination unit 120 uses existing technology, such as that used in car navigation systems, to derive a driving route from the starting point to the destination via the destination. The ease of charging determination unit 120 further identifies intermediate points along the driving route. The ease of charging determination unit 120 identifies the charging ease of a region that includes at least a portion of the route between the starting point and the destination.

[0053] If the ease of charging in the target area including the destination is less than the charging tolerance threshold, the estimation unit 130 may estimate the estimated distance in the same way as the estimation unit 130 in Example 2. If the ease of charging in the target area including the destination is equal to or greater than the charging tolerance threshold, the estimation unit 130 estimates the estimated distance as follows.

[0054] If the ease of charging in the area including the intermediate point is less than the charging tolerance threshold, the estimation unit 130 may use the sum of the distance from the starting point to the intermediate point and a predetermined additional distance as the estimated distance. If the charging accessibility of the area including the intermediate point is equal to or greater than the charging acceptance threshold, the area closest to the intermediate point is identified within the area that includes at least a portion of the route between the destination and the arrival point. The area closest to the intermediate point is, for example, the area with the shortest distance between the point closest to the intermediate point on the driving route included in the area and the intermediate point. The estimation unit 130 selects the larger of the distance from the departure point to the selected area and the distance from the selected area to the arrival point. The distance between the starting point and the selected region may be, for example, the distance between the starting point and the point furthest from the starting point within the portion of the route from the starting point to the destination that is included in the selected region. The distance from the selected region to the destination may be the distance from the point furthest from the destination within the portion of the route from the starting point to the destination that is included in the selected region. These distances along the route may be calculated, for example, by the ease determination unit 120. The estimation unit 130 may use the sum of the selected distance and a predetermined additional distance as the estimated distance.

[0055] <Second Embodiment> A second embodiment of this disclosure will be described below.

[0056] Figure 3 is a block diagram showing an example of the configuration of a selection device 100 according to a second embodiment of the present disclosure. In the example shown in Figure 3, the selection device 100 includes a destination information receiving unit 110, an ease determination unit 120, an estimation unit 130, a selection unit 140, an output unit 150, a regional information storage unit 160, a vehicle information storage unit 170, and a vehicle information update unit 180. The ease determination unit 120, estimation unit 130, selection unit 140, and output unit 150 of this embodiment each have the same functions as the ease determination unit 120, estimation unit 130, selection unit 140, and output unit 150 of the first embodiment. The ease determination unit 120, estimation unit 130, selection unit 140, and output unit 150 of this embodiment each operate in the same manner as the ease determination unit 120, estimation unit 130, selection unit 140, and output unit 150 of the first embodiment.

[0057] <Destination information receiving unit 110> The destination information receiving unit 110 receives information that specifies a destination. The information representing the destination may be information that represents a city, town, or village. The information specifying the destination may be information that represents a district within a city, town, or village. The information specifying the destination may be a combination of latitude and longitude values. The information specifying the destination is configured to represent a region or point that is included in one of several pre-set regions described later. If the information specifying the destination represents an area with a certain area (for example, a city, town, or village, or a district, etc.), the destination information receiving unit 110 identifies a representative point of the area designated as the destination, which is the point that represents the destination. The representative point of the area designated as the destination may be predetermined.

[0058] The destination information receiving unit 110 sends information representing the destination (i.e., information identifying the location representing the destination) to the ease determination unit 120.

[0059] <Regional Information Storage Unit 160> The regional information storage unit 160 stores information on the density of charging ports for each of a set of pre-configured regions. The regional information storage unit 160 also stores information on the density of electric vehicles for each of a set of pre-configured regions. The information on the density of charging ports and the information on the density of electric vehicles may be stored in the regional information storage unit 160 in advance.

[0060] <Easiness determination unit 120> The ease of charging determination unit 120 receives destination information from the destination information receiving unit 110. The ease of charging determination unit 120 identifies a region (i.e., the target region) from among a plurality of pre-set regions that includes the destination indicated by the destination information received. Information on the plurality of pre-set regions is provided to the selection device 100 in advance. Each part of the selection device 100 is configured to be able to use the provided information on the plurality of pre-set regions. The ease of charging determination unit 120 reads information on the density of charging ports in the target region and information on the density of electric vehicles in the target region from the region information storage unit 160. Similar to the ease of charging determination unit 120 in the first embodiment, the ease of charging determination unit 120 uses the information on the density of charging ports in the target region and the information on the density of electric vehicles in the target region, read from the region information storage unit 160, to determine the ease of charging in the target region (i.e., charging ease).

[0061] The ease of charging determination unit 120 sends the determined ease of charging of the target area to the estimation unit 130.

[0062] <Estimation part 130> The estimation unit 130 receives the charging ease of the target area from the ease of charging determination unit 120.

[0063] Similar to the estimation unit 130 of the first embodiment, the estimation unit 130 uses the ease of charging and the distance between a predetermined starting point and destination to estimate the distance that a user traveling by electric vehicle from a starting point to a destination will be able to travel without charging the electric vehicle.

[0064] The estimation unit 130 sends the estimated distance (specifically, information on the estimated distance) to the selection unit 140.

[0065] <Vehicle Information Storage Unit 170> The vehicle information storage unit 170 stores information on multiple electric vehicles (hereinafter referred to as vehicle information). The vehicle information of an electric vehicle includes, for example, information on the distance traveled when the electric vehicle starts driving with a full charge and drives under predetermined conditions until the battery level reaches a predetermined level. In this disclosure, the distance traveled when the electric vehicle starts driving with a full charge and drives under predetermined conditions until the battery level reaches a predetermined level is referred to as the driving distance. The predetermined battery level may be expressed as a percentage of the battery's current capacity. The predetermined battery level may also be expressed as a percentage of the battery's capacity when new.

[0066] The vehicle information storage unit 170 stores the driving range of the electric vehicle when the battery was new, the current state of the electric vehicle's battery, and the latest driving range. The battery state may be expressed as the ratio of the current battery capacity to the capacity of the new battery. The electric vehicle's battery state is measured, for example, at predetermined intervals. The electric vehicle's battery state obtained through measurement is then stored in the vehicle information storage unit 170, for example, by the administrator of the selection device 100.

[0067] <Vehicle Information Update Section 180> When the battery status of an electric vehicle, stored in the vehicle information storage unit 170, is updated, the vehicle information update unit 180 updates the latest driving range of the electric vehicle using the driving range when the battery was new and the battery status. Specifically, the vehicle information update unit 180 calculates, for example, the amount of battery power required to travel the driving range when the battery was new. The amount of battery power required to travel the driving range when the battery was new is the difference between the capacity of the new battery and the predetermined remaining capacity of the battery. The difference between the capacity of the new battery and the predetermined remaining capacity of the battery, that is, the amount of battery power required to travel the driving range when the battery was new, can also be rephrased as the usable capacity of the new battery. The vehicle information update unit 180 further calculates the amount of battery power that can be used from full charge to a predetermined remaining capacity (hereinafter also referred to as the latest usable capacity) in the updated battery state. The amount of battery usage (i.e., the latest usable capacity) that can be used from a full charge to a predetermined remaining capacity is the difference between the battery capacity when fully charged and the battery's predetermined remaining capacity in the updated battery state. The vehicle information update unit 180 then calculates the latest driving range of the electric vehicle using the driving range when the battery was new, the usable capacity of the new battery, and the calculated latest usable capacity. For example, the vehicle information update unit 180 calculates the latest driving range of the electric vehicle by multiplying the driving range when the battery was new by the ratio of the calculated latest usable capacity to the usable capacity of the new battery. In the above calculations, the vehicle information update unit 180 may use the value of the ratio to the battery capacity when new as the value of the battery capacity, battery usage, battery remaining capacity, etc.

[0068] The vehicle information update unit 180 stores the calculated latest remaining driving range of the electric vehicle in the vehicle information storage unit 170.

[0069] <Selection section 140> The selection unit 140 receives the estimated distance (specifically, information on the estimated distance) from the estimation unit 130. The selection unit 140 selects an electric vehicle from among the electric vehicles whose vehicle information is stored in the vehicle information storage unit 170, in which the most recent remaining driving range is equal to or greater than the estimated distance.

[0070] The selection unit 140 sends information about the selected electric vehicle to the output unit 150.

[0071] <Output section 150> The output unit 150 receives information about the selected electric vehicle from the selection unit 140. The output unit 150 outputs information about the selected electric vehicle, similar to the output unit 150 of the first embodiment.

[0072] <Operation> Next, the operation of the selection device 100 according to the second embodiment of this disclosure will be described in detail with reference to the drawings.

[0073] Figure 4 is a flowchart showing an example of the operation of the selection device 100 according to the second embodiment of the present disclosure. In the example shown in Figure 4, the destination information receiving unit 110 receives information specifying the destination (step S101). The ease of charging determination unit 120 determines the ease of charging the electric vehicle in the target area (step S102). Next, the estimation unit 130 estimates the estimated distance that the user will travel without charging the electric vehicle, using the ease of charging in the target area and the distance between the starting point and the destination (step S103). Then, the selection unit 140 selects an electric vehicle that can travel the estimated distance from a fully charged state (step S104). Then, the output unit 150 outputs information about the selected electric vehicle (step S105).

[0074] <Effects> The embodiment described above has the same effects as the first embodiment. The reason for this is the same as the reason for the effects of the first embodiment.

[0075] <First modified example of the second embodiment> The destination information receiving unit 110 may receive destination information for multiple destinations that the train will pass through between the departure point and the arrival point.

[0076] In this case, the ease of charging determination unit 120 determines the ease of charging for each of the target areas that include any of the multiple destinations.

[0077] In this case, for example, the ease determination unit 120 derives the route distance between the starting point and the destination for each of the multiple destinations using one of the existing methods used in car navigation systems. The ease determination unit 120 similarly derives the route distance between the destination and the arrival point for each of the multiple destinations.

[0078] The following section describes specific examples of methods for estimating distance. Note that the methods for estimating distance are not limited to the examples below.

[0079] <Example 5> The estimation unit 130 identifies a target area that includes any of several destinations, where the ease of charging is less than the allowable charging threshold. From the destinations included in the target area where the ease of charging is less than the allowable charging threshold, it identifies the destination closest to the midpoint of the route between the departure point and the arrival point. The estimation unit 130 selects the larger of the distance between the departure point and the identified destination, and the distance between the identified destination and the departure point. The estimation unit 130 may use the sum of the selected distance and a predetermined additional distance as the estimated distance.

[0080] The estimation unit 130, if the charging ease of all target areas including any of the multiple destinations is greater than or equal to the charging tolerance threshold, extracts areas that include at least a portion of the route between the departure point and the destination point and whose charging ease is less than the charging tolerance threshold. The estimation unit 130 identifies the area among the extracted areas that is closest to the midpoint of the route between the departure point and the destination point. The estimation unit 130 selects the larger of the distance between the departure point and the identified area and the distance between the identified area and the destination point. The estimation unit 130 may use the sum of the selected distance and a predetermined additional distance as the estimated distance.

[0081] <Second modified example of the second embodiment> The ease of charging determination unit 120 may determine the ease of charging for each region that includes at least a portion of the route from the starting point to the destination via the destination.

[0082] The output unit 150 may output the charging ease for each region that includes at least a portion of the route from the starting point to the destination via the destination. The output unit 150 may also output information representing regions where the charging ease is less than the charging tolerance threshold, among the regions that include at least a portion of the route from the starting point to the destination via the destination.

[0083] <Third modified example of the second embodiment> The density of electric vehicles may be determined for each time period and stored in the regional information storage unit 160.

[0084] The destination information receiving unit 110 may receive the scheduled departure time of the user from the departure point and the scheduled arrival time of the user from the destination point.

[0085] The ease of use determination unit 120 may use a method used in car navigation systems to calculate the time from when the user departs from the starting point until they pass through multiple points on the route from the starting point to the destination. The ease of use determination unit 120 may further calculate the time at which the user passes through points on the route from the starting point to the destination, based on the scheduled time when the user departs from the starting point.

[0086] The ease of use determination unit 120 may use a method used in car navigation systems to calculate the time it takes for the user to reach multiple points on the route from the destination to the destination, including the destination. The ease of use determination unit 120 may further calculate the departure time from the destination to the destination from the time it takes to reach points on the route from the destination to the destination, including the destination, and the estimated time of arrival at the destination.

[0087] The aforementioned locations may be set to include locations used to calculate the distance between the starting point or destination and the region.

[0088] The ease determination unit 120 uses the density of electric vehicles in the target area as the density of electric vehicles during the time period that includes the time calculated as the departure time from the destination to the arrival point. The ease determination unit 120 uses the density of electric vehicles in areas other than the target area, which include at least a portion of the route from the starting point to the destination via the destination, as the density of electric vehicles in the time period including the time of passing through a point included in that area. If the area consists of multiple points for which the time of passing has been calculated, one point may be selected in a predetermined manner, and the time of passing through the selected point may be used as the time of passing through the area including that point. In this case, the method of selecting one point from multiple points may be, for example, selecting the point closest to the starting point. In this case, the method of selecting one point from multiple points may be, for example, selecting the point furthest from the starting point. In this case, the method of selecting one point from multiple points may be, for example, the point closest to the midpoint of the portion of the travel route that is included in the area containing those multiple points. In this case, the method of selecting one point from multiple points may be any other method. <Other Embodiments> A selection device according to the embodiments of this disclosure can be implemented by a computer including a memory loaded with a program read from a storage medium and a processor that executes the program. A selection device according to the embodiments of this disclosure can be implemented by dedicated hardware. A selection device according to the embodiments of this disclosure can be implemented by a combination of the aforementioned computer and dedicated hardware.

[0089] Figure 5 is a diagram showing an example of the hardware configuration of a computer 1000 that can realize a selection device according to the embodiment of this disclosure. In the example shown in Figure 5, the computer 1000 includes a processor 1001, a memory 1002, a storage device 1003, and an I / O (Input / Output) interface 1004. The computer 1000 can also access a storage medium 1005. The memory 1002 and the storage device 1003 are, for example, storage devices such as RAM (Random Access Memory) and hard disks. The storage medium 1005 is, for example, a storage device such as RAM and hard disks, ROM (Read Only Memory), and a portable storage medium. The storage device 1003 may also be the storage medium 1005. The processor 1001 can read and write data and programs to the memory 1002 and the storage device 1003. The processor 1001 can access, for example, other information processing devices and terminal devices via the I / O interface 1004. The processor 1001 can access the storage medium 1005. The storage medium 1005 stores a program that causes the computer 1000 to operate as a selection device according to the embodiment of this disclosure.

[0090] The processor 1001 loads into the memory 1002 a program stored in the storage medium 1005 that causes the computer 1000 to operate as a selection device according to the embodiment of this disclosure. The processor 1001 then executes the program loaded into the memory 1002, causing the computer 1000 to operate as a selection device according to the embodiment of this disclosure.

[0091] The destination information receiving unit 110, the ease of use determination unit 120, the estimation unit 130, the selection unit 140, the output unit 150, and the vehicle information update unit 180 can be implemented, for example, by a processor 1001 that executes a program loaded into memory 1002. The regional information storage unit 160 and the vehicle information storage unit 170 can be implemented by a storage device 1003 such as memory 1002 or a hard disk drive included in the computer 1000. Alternatively, some or all of the destination information receiving unit 110, the ease of use determination unit 120, the estimation unit 130, the selection unit 140, the output unit 150, the regional information storage unit 160, the vehicle information storage unit 170, and the vehicle information update unit 180 can be implemented by dedicated circuits that realize the functions of each unit.

[0092] Furthermore, some or all of the above embodiments may also be described as follows, but are not limited to the following.

[0093] (Note 1) An ease determination means for determining the ease of charging electric vehicles in a target area, including the destination, based on the density of charging ports in the target area and the predicted density of electric vehicles in the target area, using the relationship between the density of charging ports for electric vehicles, the density of electric vehicles, and the ease of charging electric vehicles in the target area. An estimation means for estimating the estimated distance that a user traveling by electric vehicle from the starting point to the destination will travel without charging, using the ease of charging and the distance between a predetermined starting point and the destination, A selection means for selecting an electric vehicle capable of traveling the estimated distance from a fully charged state from among available electric vehicles, An output means for outputting information about the selected electric vehicle, A selection device equipped with the following features.

[0094] (Note 2) The ease of charging determination means further determines the ease of charging in a region that includes at least a part of the route, among a plurality of regions into which the area including the route from the departure point to the destination via the destination is divided, The estimation means estimates the estimated distance based on the ease of charging in the area, which includes at least a portion of the route from the departure point to the destination via the destination. The selection device described in Appendix 1.

[0095] (Note 3) The ease determination means estimates the waiting time at the charging port as the ease of charging. The selection device described in Appendix 1 or 2.

[0096] (Note 4) The ease of charging determination means estimates the sum of the time spent searching for a charging port and the time spent waiting in line at a charging port as the ease of charging. The selection device described in Appendix 1 or 2.

[0097] (Note 5) A vehicle information update means estimates the driving range of the electric vehicle based on an index indicating the size of the electric vehicle's battery capacity relative to the battery's capacity when new, and the distance the electric vehicle can travel from a fully charged state when the battery is new. Furthermore, The selection means selects the electric vehicle using the driving range of each of the plurality of available electric vehicles. The selection device described in Appendix 1 or 2.

[0098] (Note 6) A destination information receiving means that receives information specifying the destination, An output means for outputting information about the selected electric vehicle, A selection device as described in Appendix 1 or 2, further comprising:

[0099] (Note 7) Using the relationship between the density of charging ports for electric vehicles, the density of electric vehicles, and the ease of charging electric vehicles, the ease of charging electric vehicles in a target area, including the destination, is determined from the density of charging ports in the target area and the predicted density of electric vehicles in the target area. Using the ease of charging and the distance between a predetermined starting point and the destination, the estimated distance that a user traveling from the starting point to the destination by electric vehicle would travel without charging is estimated. From a fully charged state, an electric vehicle capable of traveling the estimated distance is selected from among the available electric vehicles. Outputs information about the selected electric vehicle. Selection method.

[0100] (Note 8) The ease of charging is further determined for a region that includes at least a part of the route, among a plurality of regions into which the area including the route from the departure point to the destination via the destination is divided, The estimated distance is estimated based on the ease of charging in the area, which includes at least a portion of the route from the departure point to the destination via the destination. The selection method is as described in Appendix 7.

[0101] (Note 9) The ease of charging is estimated by estimating the waiting time at the charging port. The selection method described in Appendix 7 or 8.

[0102] (Note 10) The ease of charging is estimated by the sum of the time spent searching for a charging port and the time spent waiting in line at the charging port. The selection method described in Appendix 7 or 8.

[0103] (Note 11) The driving range of the electric vehicle is estimated from an index indicating the size of the battery capacity of the electric vehicle relative to the capacity of the battery when it is new, and the distance the electric vehicle can travel from a fully charged state when the battery is new. The electric vehicle is selected using the driving range of each of the multiple available electric vehicles. The selection method described in Appendix 7 or 8.

[0104] (Note 12) Upon receiving the information specifying the aforementioned destination, An output means for outputting information about the selected electric vehicle, A selection method as described in Appendix 7 or 8, further comprising:

[0105] (Note 13) Using the relationship between the density of charging ports for electric vehicles and the density of electric vehicles, and the ease of charging electric vehicles, an ease determination process is performed to determine the ease of charging electric vehicles in a target area, including the destination, based on the density of charging ports in the target area and the predicted density of electric vehicles in the target area. An estimation process that uses the ease of charging and the distance between a predetermined starting point and the destination to estimate the estimated distance that a user traveling from the starting point to the destination by electric vehicle would travel without charging the electric vehicle, A selection process to select an electric vehicle capable of traveling the estimated distance from a fully charged state from among available electric vehicles, Output processing that outputs information about the selected electric vehicle, A program that causes a computer to execute something.

[0106] (Note 14) The ease of charging determination process further determines the ease of charging in a region that includes at least a part of the route, among a plurality of regions into which the area including the route from the starting point to the destination via the destination is divided, The estimation process estimates the estimated distance based on the ease of charging in the area, which includes at least a portion of the route from the starting point to the destination via the destination. The program described in Appendix 13.

[0107] (Note 15) The ease of charging determination process estimates the waiting time at the charging port as the ease of charging. The program described in Appendix 13 or 14.

[0108] (Note 16) The ease of charging determination process estimates the sum of the time it takes to find a charging port and the time spent waiting in line at the charging port as the ease of charging. The program described in Appendix 13 or 14.

[0109] (Note 17) A vehicle information update process that estimates the driving range of the electric vehicle based on an index indicating the size of the electric vehicle's battery capacity relative to its capacity when new, and the distance the electric vehicle can travel from a fully charged state when the battery is new. Let the computer execute it further, The selection process selects the electric vehicle using the driving range of each of the multiple available electric vehicles. The program described in Appendix 13 or 14.

[0110] (Note 18) A destination information receiving process that receives information specifying the destination, Output processing that outputs information about the selected electric vehicle, A program described in Appendix 13 or 14 that further causes a computer to execute.

[0111] Although the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure can be understood by those skilled in the art within the scope of the present disclosure. [Explanation of symbols]

[0112] 10 Selection device 100 Selection device 110 Destination Information Receiving Section 120 Ease of judgment part 130 Estimation part 140 Selection Section 150 Output section 160 Regional Information Storage Unit 170 Vehicle Information Storage Unit 180 Vehicle Information Update Department 1000 computers 1001 Processor 1002 memory 1003 Storage device 1004 I / O Interface 1005 Storage medium

Claims

1. An ease determination means for determining the ease of charging electric vehicles in a target area, including the destination, based on the density of charging ports in the target area and the predicted density of electric vehicles in the target area, using the relationship between the density of charging ports for electric vehicles, the density of electric vehicles, and the ease of charging electric vehicles in the target area. An estimation means for estimating the estimated distance that a user traveling by electric vehicle from the starting point to the destination will travel without charging, using the ease of charging and the distance between a predetermined starting point and the destination, A selection means for selecting an electric vehicle capable of traveling the estimated distance from a fully charged state from among available electric vehicles, An output means for outputting information about the selected electric vehicle, A selection device equipped with the following features.

2. The ease of charging determination means further determines the ease of charging in a region that includes at least a part of the route, among a plurality of regions into which the area including the route from the departure point to the destination via the destination is divided, The estimation means estimates the estimated distance based on the ease of charging in the area, which includes at least a portion of the route from the departure point to the destination via the destination. The selection device according to claim 1.

3. The ease determination means estimates the waiting time at the charging port as the ease of charging. The selection device according to claim 1 or 2.

4. The ease of charging determination means estimates the sum of the time spent searching for a charging port and the time spent waiting in line at a charging port as the ease of charging. The selection device according to claim 1 or 2.

5. A vehicle information update means estimates the driving range of the electric vehicle based on an index indicating the size of the electric vehicle's battery capacity relative to the battery's capacity when new, and the distance the electric vehicle can travel from a fully charged state when the battery is new. Furthermore, The selection means selects the electric vehicle using the driving range of each of the plurality of available electric vehicles. The selection device according to claim 1 or 2.

6. Using the relationship between the density of charging ports for electric vehicles, the density of electric vehicles, and the ease of charging electric vehicles, the ease of charging electric vehicles in a target area, including the destination, is determined from the density of charging ports in the target area and the predicted density of electric vehicles in the target area. Using the ease of charging and the distance between a predetermined starting point and the destination, the estimated distance that a user traveling from the starting point to the destination by electric vehicle would travel without charging is estimated. From a fully charged state, an electric vehicle capable of traveling the estimated distance is selected from among the available electric vehicles. Outputs information about the selected electric vehicle. Selection method.

7. The ease of charging is further determined for a region that includes at least a part of the route among a plurality of regions into which the area including the route from the departure point to the destination via the destination is divided, The estimated distance is estimated based on the ease of charging in the area, which includes at least a portion of the route from the departure point to the destination via the destination. The selection method according to claim 6.

8. The ease of charging is estimated by estimating the waiting time at the charging port. The selection method according to claim 6 or 7.

9. The ease of charging is estimated by the sum of the time spent searching for a charging port and the time spent waiting in line at the charging port. The selection method according to claim 6 or 7.

10. Using the relationship between the density of charging ports for electric vehicles and the density of electric vehicles, and the ease of charging electric vehicles, an ease determination process is performed to determine the ease of charging electric vehicles in a target area, including the destination, based on the density of charging ports in the target area and the predicted density of electric vehicles in the target area. An estimation process that uses the ease of charging and the distance between a predetermined starting point and the destination to estimate the estimated distance that a user traveling by electric vehicle from the starting point to the destination will travel without charging the electric vehicle, A selection process to select an electric vehicle capable of traveling the estimated distance from a fully charged state from among available electric vehicles, Output processing that outputs information about the selected electric vehicle, A program that causes a computer to execute something.

Images