JP2016143245A - Server device and reservation acceptance method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve operation efficiency of a vehicle of a car-sharing system.SOLUTION: A server device includes: use record acquisition means that acquires use record, which is data including a place of departure, a place of arrival, and power consumption, for a user moving with an electric vehicle in the past; reservation information acquisition means which acquires first trip which is a section between the place of departure and the place of arrival, from a reservation applicant; first estimation means which estimates first power consumption required for a vehicle to be leased to travel the first trip, on the basis of the use record; second estimation means that estimates second trip including one or more sections where the vehicle travels after the vehicle is returned, on the basis of the use record; second estimation means which estimates second power consumption required for the vehicle to travel the second trip, on the basis of the use record; and lease determination means which determines whether or not the vehicle can be leased to the user, on the basis of the current power remaining in a battery of the vehicle and the first and second power consumption.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a technique for determining whether or not an electric vehicle can be rented.

In recent years, car sharing in which an automobile is shared by a plurality of users has become widespread. In recent years, electric vehicles have been gradually spread, and the operation of electric vehicles has begun in car sharing.
When an electric vehicle is shared among a plurality of users, charging timing becomes a problem. In general car sharing, when the fuel in the vehicle decreases, the user replenishes himself to the gas station. Become.
That is, when unplanned operation is performed, the battery runs out (hereinafter referred to as power shortage) during traveling, and the subsequent vehicle operation may become impossible. Therefore, it is being considered that car sharing companies provide a mechanism that prevents electric shortages during lending.

As an invention related to this, there is a travelable distance estimation system described in Patent Document 1. The system obtains the starting point and the destination, estimates the travel route of the vehicle, obtains the power consumption defined for each road link, and based on the current remaining battery level, Is estimated.
By applying this system to a car sharing system, for example, “If it is difficult to reach the specified destination with the current battery level, the vehicle will not be rented”, “To reach the specified destination It is possible to search for a vehicle that can be used and present it to the user.

JP 2006-115623 A

Since charging facilities for electric vehicles are expensive to install, in some car sharing systems that operate electric vehicles, not all stations are equipped with charging facilities. In addition, if an electric vehicle with no remaining battery charge is returned to a station without a charging facility, there is a risk of running out of electricity in the next rental.
In order to deal with this problem, for example, it is necessary to set a threshold value for the remaining battery level that permits lending to a certain level so that the remaining battery level does not become too low when returning.

  However, when the threshold value of the remaining battery level that permits lending is uniformly set, a case where efficient vehicle operation cannot be performed occurs. For example, if it is predicted that the remaining battery capacity will be reduced upon arrival, it may be determined that the rental is not possible even if there is a charging facility at the destination station. Further, even when there are many charging facilities around the destination station and there is a high possibility that charging will be performed in the next and subsequent rentals, it may be determined that the rental is not possible.

The present invention has been made in consideration of the above-described problems, and an object of the present invention is to improve the operational efficiency of a vehicle in a server device that accepts reservations for an electric vehicle operated in a car sharing system.

The server device according to the present invention includes:
A server device that accepts a reservation for an electric vehicle operated in a car sharing system, and is a usage history that is data including a departure place, an arrival place, and power consumption when the user has moved in the past by an electric vehicle. Use history acquisition means for acquiring a reservation information acquisition means for acquiring a first trip that is a section connecting a first station that is a departure place and a second station that is an arrival place from a reservation applicant. And based on the usage history, first prediction means for predicting the first power consumption required for the vehicle to be rented to travel the first trip, on the basis of the usage history, After the vehicle is returned, second prediction means for predicting a second power consumption that is the amount of power consumed until the vehicle becomes chargeable, and a current battery remaining amount of the vehicle Vehicle information acquisition means to be obtained, lending determination means for deciding whether or not to lend a vehicle to a user based on the remaining battery level, the first power consumption, and the second power consumption. It is characterized by that.

  The usage history acquisition means is means for acquiring data (use history) related to the power consumption when the user of the car sharing system has moved in the past by an electric vehicle. Specifically, the usage history includes information on the departure place, information on the arrival place, and power consumption. The usage history may be stored in a storage device or may be acquired from the outside via a network or the like.

  The reservation information acquisition means is means for acquiring a section (referred to as a first trip) connecting a departure station and an arrival station from a user who desires reservation. The first trip may be acquired by, for example, presenting a list of stations to the user and selecting a departure place and an arrival place.

  The first predicting means is a means for predicting the power consumption (first power consumption) necessary for the vehicle to be rented to travel on the first trip.

  On the other hand, the second predicting means is a means for predicting the amount of power (second power consumption) consumed until the vehicle becomes chargeable after the vehicle is returned. The first and second power consumption amounts can be predicted based on the usage history.

  Further, the lending determination means is a means for determining whether or not the vehicle can be lent based on both the remaining battery amount of the vehicle, the predicted first power consumption amount, and the second power consumption amount. According to this configuration, it is possible to determine whether or not to lend out depending on the risk of power shortage. That is, compared with the case where the threshold value of the battery remaining amount is uniform, the vehicle can be provided to a larger number of users, and the efficiency of vehicle operation can be improved.

  Further, the lending determination means determines whether or not the battery remaining amount of the vehicle to be lent can cover both the first power consumption and the second power consumption without charging. It may be characterized by determining whether or not to lend.

  In this way, if the current remaining battery level of the vehicle cannot cover the predicted first and second power consumption amounts, it is determined that there is a high possibility of power shortage, and lending is rejected. May be. According to such a configuration, the risk of electric shortage can be kept low.

Further, the second station is a station without a charging facility, and the second prediction means is a station with a charging facility after the vehicle is returned based on the usage history. Means for predicting a second trip including one or more sections traveling to a third station, and based on the usage history, the vehicle is required to travel the second trip. And a means for predicting the second power consumption amount.

  The second power consumption varies depending on what route the vehicle takes after reaching the station where the charging facility is located after the vehicle is returned. Therefore, the second trip can be predicted based on the usage history, and the second power consumption can be predicted based on the result.

Further, the second prediction means extracts a plurality of routes connecting the second station and the third station from the usage history, and based on the probability that the second trip takes each route. The second power consumption amount may be predicted.
The second predicting means may predict the second power consumption based on a route having the highest probability that the second trip is taken among the plurality of routes.

  The second power consumption can be predicted based on, for example, the probability of extracting a plurality of routes from the usage history and taking each route. For example, the prediction may be performed based on the route having the highest probability of being selected, or the power consumption amount corresponding to each route may be calculated by using the probability weight. Moreover, you may obtain | require with another method.

In addition, the first prediction unit may acquire a usage history corresponding to the first trip from the usage history acquisition unit, and may predict power consumption using the usage history.
The reservation information acquisition means further acquires information about the driver of the vehicle from the reservation applicant, and the first prediction means prioritizes the usage history corresponding to the driver from the usage history acquisition means. It is good also as a characteristic to acquire.

  The prediction of the first power consumption can be performed by acquiring a usage history corresponding to the first trip. At this time, if there is information related to the driver of the vehicle, it is preferable to preferentially acquire the usage history corresponding to the driver. This is because the amount of electric power required when traveling with an electric vehicle may greatly depend on the driver.

  In addition, this invention can be specified as a server apparatus containing at least one part of the said means. The present invention can also be specified as a reservation receiving method including at least a part of the above processing. The above processes and means can be freely combined and implemented as long as no technical contradiction occurs.

  ADVANTAGE OF THE INVENTION According to this invention, in the server apparatus which receives the reservation of the electric vehicle operated in a car sharing system, the operation efficiency of a vehicle can be improved.

It is a system configuration figure of the management server concerning a first embodiment. It is an example of a utilization history table, a vehicle information table, and a station table. It is a figure showing the relationship of several stations. It is a process flowchart of the management server which concerns on 1st embodiment. It is an example of the path | route extraction result in 1st embodiment. It is a process flowchart of the management server which concerns on 2nd embodiment.

(First embodiment)
<System configuration>
The car sharing management system according to the first embodiment will be described with reference to FIG. 1 which is a system configuration diagram. The car sharing management system according to the first embodiment includes a management server 10, a user terminal 20, and a vehicle 30.

  The management server 10 is a server that manages a car sharing system, and is a server that performs reservation reception of vehicle rental, schedule management of a sharing vehicle (electric vehicle, hereinafter simply referred to as vehicle), billing management for a user, and the like. is there. In addition, the management server 10 stores information about the vehicle and a history when the user uses the vehicle, and determines a risk of electric shortage when a new vehicle rental request is received from the user. In addition, it has a function of determining whether or not to lend.

The user terminal 20 is a terminal operated by a user of the car sharing service, and is a personal computer, a mobile phone, a smartphone, or the like. The user terminal 20 can make a reservation for a vehicle by accessing the management server 10.
The vehicle 30 is an electric vehicle to be shared. The vehicle 30 is configured to be able to communicate with the management server 10 by wireless communication. The vehicle 30 may be configured to be able to communicate with the user terminal 20.

  The management server 10 according to the first embodiment includes a communication unit 11, a usage history storage unit 12, a management information storage unit 13, a lending management unit 14, and a power amount prediction unit 15.

  The communication unit 11 is a communication unit for connecting the management server 10 to the user terminal 20 and the vehicle 30 via a network (for example, the Internet or VPN). The communication unit 11 may be a wired network interface or a wireless network interface.

  The usage history storage unit 12 is a means for storing a history (hereinafter referred to as a usage history) when a user has rented a vehicle in a table format. In the usage history table, the user ID, the departure place, the arrival place, the amount of power consumed during the rental, and the like are recorded, and updated when the user returns the vehicle. Details of the usage history table will be described later.

  The management information storage unit 13 is a means for storing current vehicle information (hereinafter, vehicle information) in a table format. In the vehicle information table, the vehicle ID, the current position, the current battery remaining amount, and the like are recorded, and updated when the user returns the vehicle. Details of the vehicle information table will be described later. Hereinafter, the remaining amount level of the battery mounted on the electric vehicle is referred to as SOC (State Of Charge).

  The rental management unit 14 is a means for managing vehicle rental. Specifically, vehicle reservation reception, lending scheduling, notification to the user terminal, transmission of an unlocking signal to the vehicle, billing management of usage charges, and the like are performed. In addition, when accepting a reservation for a vehicle, after obtaining information (reservation request) on the ID, departure location, and destination of the user who wants to lend the vehicle, the departure location is passed through the power amount prediction unit 15 described later Determine whether the section connecting the destination and the destination (first trip) and the section connecting the destination and the charging facility (second trip) can be driven without charging, and use the determination result to make a reservation Determine whether or not.

Based on the reservation request acquired by the lending management unit 14, the stored use history, and the vehicle information, the power amount predicting unit 15 determines the amount of power that will be consumed in the current vehicle lending (first consumption). This is a means for predicting the electric energy. In addition, the power amount prediction unit 15 uses the stored power usage history after the vehicle is returned until the vehicle can be charged (second amount). This is a means for predicting (power consumption).
Each predicted power amount is transmitted to the lending management unit 14 and is used for determining whether reservation is possible.

<Evaluation of occurrence of electric shortage>
Next, the presence / absence determination of the occurrence of power shortage performed by the lending management unit 14 will be described. When the management server 10 according to the present embodiment accepts a reservation for a vehicle from a user, the management server 10 inputs information about the destination, and the vehicle to be rented from the departure point (that is, the current station) to the arrival point ( The amount of power consumed when traveling to the destination station is predicted. Further, the amount of electric power (second electric power consumption) consumed when the vehicle travels from the arrival place to another station having a charging facility is predicted. Then, the risk of power shortage is determined based on whether or not the current battery level of the vehicle can cover both amounts of power, and whether or not reservation is possible is determined.

Before describing the method for predicting the power consumption, the usage history table and the vehicle information table will be described first.
FIG. 2A is an example of a usage history table stored in the usage history storage unit 12. The usage history table records user and vehicle IDs, rental and return locations (stations), rental and return times, and SOCs at the time of rental and return. In addition, the power (Wh) consumed by one lending is recorded. The usage history table is updated each time the vehicle is returned to the station. Note that the power consumption is calculated from the SOC at the time of lending, the SOC at the time of return, and the capacity (described later) of the battery of the vehicle. Moreover, the information regarding SOC is acquired from the vehicle 30 by wireless communication.

  FIG. 2B is an example of a vehicle information table stored in the management information storage unit 13. In the vehicle information table, vehicle ID, current position, current SOC, and battery capacity (Wh) are recorded. The vehicle information table is updated every time the vehicle is returned to the station. In addition, the information regarding SOC is acquired by radio | wireless communication from the vehicle 30, and the information regarding battery capacity is defined in advance.

A method for predicting the power consumption will be described.
When receiving the reservation request from the user, the management server according to the present embodiment first predicts the first power consumption by the following two methods using the request contents and the two tables described above. To do. The reservation request includes at least three pieces of information: a user ID for identifying the driver, a departure place (station that rents the vehicle), and a destination (station that returns the vehicle).

<< Method 1 >>
When the driver included in the reservation request (hereinafter, the user driving the target vehicle is referred to as the driver) uses the same section as the requested section (hereinafter, the reserved section), that is, When there is a past usage history that the driver has traveled in the reserved section, the power consumption amount in the current travel is predicted using the power consumption amount recorded in the usage history.
Specifically, a record that is the driver's own usage history and records the same section as the current reservation is extracted from the usage history table. When the number of acquired records is equal to or greater than a predetermined threshold (for example, 5 records), an average value of the power consumption recorded in the plurality of records is obtained and set as the first power consumption.
According to the method 1, since the power consumption is predicted based on the usage history of the driver, the power consumption according to the individual tendency can be obtained.

<< Method 2 >>
In Method 1, the usage history of the driver himself / herself is extracted from the past usage history, and the power consumption is predicted. However, if the driver does not have a sufficient number of histories using the same section, a highly reliable predicted value cannot be obtained. Therefore, in Method 1, when the necessary number of records for calculation cannot be acquired more than the necessary number (for example, 5 records), the narrowing down by the driver is removed and the history of other users using the target reserved section is used. The power consumption is predicted by the same method.
Specifically, all the records corresponding to the reserved section are extracted, and an average value of the power consumption amounts recorded in the plurality of records is calculated as the first power consumption amount.
In this example, the average value of the power consumption is obtained, but a median value or a mode value may be used. Further, an assumed error may be added. Such an error may be a fixed value or may be obtained based on a standard deviation or the like.

By predicting the first power consumption amount by such a method, it is possible to determine whether or not the vehicle to be rented can reach the destination.
However, if there is no charging facility at the station where the vehicle is returned, there is a risk that a power shortage will occur in subsequent lending.

  A specific example will be described. FIG. 3 is a diagram illustrating a station that lends and returns a vehicle and a route (link) between the stations. Hereinafter, the stations are represented by letters A to D. A station indicated by a solid line represents a station having a charging facility, and a station indicated by a dotted line represents a station having no charging facility.

Here, it is assumed that the vehicle is in station A and the user desires use up to station B. As shown in FIG. 3, there is no charging facility at station B.
In other words, when considering the risk of electric shortage, it is necessary to determine whether or not the vehicle can arrive at station A or station D after the vehicle arrives at station B when accepting the reservation.

  Therefore, in this embodiment, after the target vehicle is returned based on the usage history, the amount of power consumption (second power consumption) required until the vehicle reaches a station with a charging facility is predicted. Then, whether or not to lend is determined based on whether or not the vehicle can cover both the first power consumption and the second power consumption.

<Process flowchart>
Specific processing performed by the server device according to the present embodiment will be described with reference to FIG. 4 which is a processing flowchart. The process illustrated in FIG. 4 is started when the management server 10 receives a vehicle reservation request from the user terminal 20.

First, in step S11, the lending management unit 14 acquires a reservation request. The reservation request is information transmitted from the user terminal 20 and is information including a driver's user ID, departure place, destination, use start time, return time, and the like. In this embodiment, it is assumed that there are a plurality of stations, and the IDs of the stations are designated as the departure point and the destination.
Information about the user ID, the departure place, and the destination is transmitted to the power amount prediction unit 15.

Steps S12 to S15 are processes for predicting the first power consumption.
In step S12, a record is extracted from the usage history table using the driver's user ID, departure place (lending station ID), and destination (return station ID) as keys.
Next, in step S13, it is determined whether or not the number of extracted records is greater than a predetermined threshold. As a result, when it is determined that the number is large, the process proceeds to step S14. When it is determined that the number is small, the process proceeds to step S15.

In step S14, a plurality of power consumption amounts recorded in the record extracted in step S12 are acquired, and the first power consumption amount is calculated by taking an average value.
On the other hand, in step S15, in a state where the user ID is removed from the search key, the corresponding record (that is, the record in which the pair of the departure place and the destination matches) is extracted again from the use history table. Then, a plurality of power consumption amounts recorded in the extracted record are acquired, and the first power consumption amount is calculated by taking an average value.
The predicted first power consumption is transmitted to the lending management unit 14.

Steps S16 to S18 are processes for predicting the second power consumption.
In step S16, a route (second trip) that can be taken after the target vehicle is returned is extracted. Specifically, a plurality of routes starting from the destination included in the reservation request and ending at any other station with the charging facility are extracted from the usage history table. Here, as shown in FIG. 5, a total of four routes are extracted: a route of B → C → A, a route of B → A, a route of B → C → D, and a route of B → D. Shall.
The extraction is performed, for example, by sequentially referencing the usage history from one month ago to the present, and acquiring a route starting from station B and ending with a station with another charging facility. Note that the extraction period may be other than this.
In the present embodiment, the presence / absence of a charging facility for each station is stored in the management information storage unit 13 in the format shown in FIG.

  Next, in step S17, based on the extracted plurality of routes, a route that most likely causes the target vehicle to travel after returning is determined. In the example of FIG. 5, since the number of cases that have taken the route of B → C → D is the largest, it is determined that the possibility of taking the route after return is the highest.

Next, in step S18, the power consumption corresponding to the route determined in step S17 is calculated. Specifically, the amount of power consumption for each section is predicted by the same method as the first power consumption amount, and the total is obtained. However, since it is impossible to predict who the driver of the second trip will be, prediction is performed without using information about the driver.
The total obtained here is the second power consumption amount.

In step S19, the rental management unit 14 determines whether the vehicle can be rented based on the reservation request and the predicted power consumption. For example, if the requested rental location is station A, the SOC of the vehicle parked at station A is obtained from the vehicle information table, and the predicted first and second power consumption amounts can be consumed without charging. It is determined whether or not. Here, when it is determined that consumption is possible, a reservation process for lending is started.
If it is determined that the vehicle cannot be consumed, a notification that the vehicle cannot be rented is generated and transmitted to the user terminal 20. The case where the predicted power consumption cannot be consumed is, for example, the case where it is determined that the predicted power consumption cannot be covered by the current SOC of the vehicle (a case where the predicted power consumption is below a predetermined threshold when returned). Included).

As described above, in the first embodiment, the power consumption necessary for traveling in the reserved section is predicted using the past usage history. Accordingly, it is possible to determine in advance the danger of electric shortage and determine whether or not to lend. Further, when predicting the power consumption amount, priority can be given to the driver's own history, so that more accurate prediction can be performed.
In addition, because the amount of power consumed from when the vehicle is returned to when it can be recharged is further predicted, it is determined whether or not it can be rented out, preventing the occurrence of power shortage and the vehicle being unable to rent It is possible to achieve both prevention of opportunity loss due to

Note that the threshold used in step S13 may be set based on actual results, or may be automatically set based on a value obtained by data mining or the like.
Further, in step S14, a record in which both the driver and the trip are the same is extracted and determined. However, if the power consumption amount can be predicted based on the usage history of the driver himself, another method is used. May be.

Further, in this embodiment, in step S17, the route having the highest possibility of traveling by the vehicle is determined based on the number of cases extracted for each route, but other criteria are used as long as the route is based on the usage history. Thus, a route that is most likely to travel by the vehicle may be determined.
Also, the route need not necessarily be narrowed down to one. For example, weighting may be performed according to the probability of taking each route, and the calculated power consumption may be set as the second power consumption.
In this embodiment, the route is extracted by tracking the position of the vehicle in chronological order. However, the probability for each route is obtained based on the probability that the vehicle at one station will move to another station next. May be.

(Second embodiment)
In the first embodiment, when a sufficient number of histories cannot be acquired in step S13, the limitation by the user ID is canceled and prediction is performed. However, since the power consumption required when driving an electric vehicle varies greatly depending on the individual difference of the driver, the actual power consumption required for some drivers is far from the predicted value. There is a case.
For example, even when driving in the same section, if a certain driver tends to drive at a higher speed than other drivers, the power consumption rate (hereinafter referred to as power consumption) deteriorates, so that other drivers More power is required than Even when traveling in the same section, if a certain driver tends to take a detour on his own, he / she consumes more electric power than other drivers.

In the second embodiment, in order to cope with such a tendency for each individual, a tendency regarding power consumption for each driver is acquired, and a prediction result is corrected.
Since the system configuration of the management server according to the second embodiment is the same as that of the first embodiment, a description thereof will be omitted, and only differences in processing will be described.

FIG. 6 is a flowchart showing details of the process in step S15 in the second embodiment.
First, in step S151, all records whose reserved sections match and whose user ID does not match the driver are extracted from the use history table, and an average value of power consumption is calculated.
Next, in step S152, a record in which the reserved section matches and the user ID matches the driver is extracted from the use history table, and the average value of the power consumption is calculated.
Next, in step S153, the average value obtained in step S152 is divided by the average value obtained in step S151 to obtain a correction coefficient.
Finally, in step S154, the average value obtained in step S151 is multiplied by the correction coefficient to obtain the first power consumption amount.

  As described above, in the second embodiment, the ratio of the power consumption with other users traveling in the same reserved section is calculated, and the predicted power consumption is corrected using the ratio. Thereby, the tendency regarding the power consumption for each driver can be reflected, and the prediction accuracy of the first power consumption can be improved.

In the present embodiment, only records corresponding to the same reserved section are extracted, but the calculation may be performed using data other than the corresponding section. In this case, the correction coefficient may be calculated for each section by the process described above, and an average of the plurality of correction coefficients may be further acquired.
If the number of records obtained in step S152 is smaller than the predetermined number, the calculation of the correction coefficient may be omitted and the process may be continued.

(Modification)
The above embodiment is merely an example, and the present invention can be implemented with appropriate modifications within a range not departing from the gist thereof.
For example, the usage history used for prediction may be narrowed down using conditions other than those described in each embodiment. For example, an upper limit may be set on the number of records used for power consumption prediction, and records may be extracted with priorities. For example, if there is a record corresponding to the driver in step S15, the record may be extracted with priority, or a more recent usage history may be prioritized.

In the first embodiment, the route until the target vehicle arrives at a station where the charging facility is located is predicted. However, the charging facility is not necessarily provided in the station. For example, when charging is possible in another facility, a route to the facility may be predicted based on the use history.
In addition, the usage history does not necessarily represent movement between stations as long as it can determine whether or not the charging facility can be reached.

  Further, when conditions differ between the travel related to the usage history and the travel to be predicted, the power consumption amount may be predicted or whether or not the reservation can be determined in consideration of the difference between the conditions. For example, when the degree of congestion on the road, the number of passengers, the total weight of the vehicle, the outside air temperature, and the like are different, there is a possibility that the required power consumption and the travelable distance may vary. In such a case, the process for correcting the change may be executed at an arbitrary timing.

DESCRIPTION OF SYMBOLS 10 Management server 11 Communication part 12 Usage history memory | storage part 13 Management information memory | storage part 14 Lending management part 15 Electric energy prediction part 20 User terminal 30 Vehicle

Claims (8)

A server device that accepts reservations for electric vehicles operated in a car sharing system,
Usage history acquisition means for acquiring a usage history that is data including a departure place, an arrival place, and power consumption when the user has traveled with an electric vehicle in the past,
Reservation information acquisition means for acquiring a first trip that is a section connecting a first station that is a departure point and a second station that is an arrival point from a reservation applicant,
A first predicting means for predicting a first power consumption amount required for the vehicle to be rented to travel on the first trip based on the use history;
A second predicting means for predicting a second power consumption that is an amount of power consumed until the vehicle becomes chargeable after the vehicle is returned based on the usage history;
Vehicle information acquisition means for acquiring a current battery remaining amount of the vehicle;
Lending determination means for deciding whether or not to lend a vehicle to a user based on the battery remaining amount, the first power consumption, and the second power consumption;
A server device. The lending determination means determines whether or not the vehicle can be rented depending on whether or not the remaining battery power of the vehicle to be rented can cover both the first power consumption and the second power consumption without charging. To decide,
The server device according to claim 1. The second station is a station without a charging facility,
The second prediction means includes
Based on the usage history, after the vehicle is returned, the vehicle predicts a second trip including one or more sections that travel to reach a third station that is a station with a charging facility. Means,
Means for predicting a second power consumption amount necessary for the vehicle to travel the second trip based on the usage history,
The server device according to claim 1 or 2. The second predicting means extracts a plurality of routes connecting the second station and the third station from the usage history, and based on a probability that the second trip takes each route. Predicting the power consumption of
The server device according to claim 3. The second predicting means predicts a second power consumption amount based on a route having the highest probability that the second trip takes among the plurality of routes.
The server device according to claim 4. The first prediction unit acquires a usage history corresponding to the first trip from the usage history acquisition unit, and predicts power consumption using the usage history.
The server apparatus in any one of Claim 1 to 5. The reservation information acquisition means further acquires information on the driver of the vehicle from the reservation applicant,
The first predicting unit preferentially acquires a usage history corresponding to the driver from the usage history acquiring unit.
The server device according to claim 6. A reservation accepting method executed by a server device accepting a reservation for an electric vehicle operated in a car sharing system,
A usage history acquisition step of acquiring a usage history that is data including a departure place, an arrival place, and power consumption when the user has traveled with an electric vehicle in the past,
Reservation information acquisition step for acquiring a first trip that is a section connecting a first station that is a departure point and a second station that is an arrival point from a reservation applicant,
Based on the usage history, a first prediction step of predicting a first power consumption required for the vehicle to be rented to travel the first trip;
A second prediction step of predicting a second power consumption amount that is an amount of power consumed until the vehicle is in a chargeable state after the vehicle is returned based on the usage history;
Vehicle information acquisition step of acquiring the current battery remaining amount of the vehicle;
A lending determination step for deciding whether or not to lend a vehicle to a user based on the remaining battery amount, the first power consumption, and the second power consumption;
Including reservations.

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