Patent Publication Number: US-2018032920-A1

Title: Vehicle management system for vehicle-sharing service

Description:
CROSS REFERENCE TO RELATED APPLICATION 
     The present application is based on and claims the benefit of priority of Japanese Patent Application No. 2016-147231, filed on Jul. 27, 2016, the disclosure of which is incorporated herein by reference. 
     TECHNICAL FIELD 
     The present disclosure generally relates to a vehicle management system of a vehicle-sharing service. 
     BACKGROUND INFORMATION 
     A vehicle-sharing service is a service for renting a vehicle to a user on demand, for example, in response to a user request. The service area of the vehicle-sharing service where the vehicle is rented is defined by a plurality of stations from which the vehicle is rented, or to which the vehicle is returned. Each of the plurality of stations has a stock of vehicles available for renting. In one form of the vehicle-sharing service, the user reserves (i.e., makes a reservation for) a vehicle via the Internet. The user then picks up the reserved vehicle at one of the plurality of stations designated during the vehicle reservation process. 
     The patent document 1 listed below discloses a management system for a car-sharing service renting electric vehicles. Such a system organizes and operates the rental service based on the electrical charge rate of each vehicle, i.e. basing vehicle rental availability on the electrical charge level of charging electric vehicles. 
     (Patent document 1) Japanese Patent Laid-Open No. 2014-41475 
     As disclosed in patent document 1, when the user makes a reservation, the reservation result may be presented to the user in response to a reservation operation. The reservation result in this case includes, for example, information regarding whether a reservation is accepted, as well as other information for the reserved vehicle. Vehicle allocation information may be presented to the user after updating the management system based on the new reservation by the user and the pending reservations of other users. 
     However, as the car-sharing service expands to cover a larger service area with a larger vehicle fleet, updates to the management system may take longer to process. In addition, the information collected and used to update the management system (e.g., utility costs associated with charging an electric vehicle, vehicle transfer operation costs (i.e., personnel expenses/labor cost for relocating a vehicle) may also increase, leading to far greater processing time for management system updates. Accordingly, the turn-around time from a user entering a reservation to the system displaying the reservation result may take too much time. 
     SUMMARY 
     It is an object of the present disclosure to provide a vehicle management system for a vehicle-sharing service that reduces operating costs by optimizing vehicle allocation during a reservation process while quickly responding to and displaying a reservation result to a user. 
     In an aspect of the present disclosure, the vehicle management system for managing a vehicle-sharing service of one or more vehicles at one or more vehicle service stations includes: a reservation request input device configured to receive a vehicle reservation from an external computing device; a reservation processor configured to allocate a vehicle to the vehicle reservation request; a result transmitter configured to transmit a reservation result including a rental start time of the vehicle reservation to the external computing device; and a cost calculator configured to calculate an operation cost of the vehicle-sharing service, wherein the reservation processor is further configured to perform either a simple process or the simple process and an optimization process, for a vehicle allocation, wherein the simple process allocates the vehicle within a first processing time by either omitting a calculation of the operation cost by the cost calculator or simplifying the calculation of the operation cost by the cost calculator, and the optimization process allocates the vehicle within a second processing time using the cost calculator to calculate the operation cost based on a given condition to minimize the operation cost, and wherein the first processing time is shorter than the second processing time. 
     The vehicle management system performs the simple process for the vehicle allocation upon receiving an input of a new vehicle reservation from the user via the external computing device, and a reservation result including an allocation of a rental vehicle to the vehicle reservation request, processed using the simple process, is transmitted back to the external computing device for display to the user. The simple process is a process that is simpler and takes less time than vehicle allocation by the optimization process. For example, the simple process allocates a vacant vehicle to the vehicle reservation on a first-come, first-serve basis. Therefore, the reservation result is quickly transmitted back to the user with little or no wait time after the reservation operation by the user. The reservation result transmitted back to the user may simply be information about the validity of the reservation (i.e., whether the vehicle reservation has been accepted or declined), or may include information about the allocated vehicle (i.e., specifying an identity of the reserved vehicle). 
     For the new reservation, if the duration of time between the completion of the simple process and the rental start time is equal to or greater than a threshold value, the reservation processor performs the optimization process to update the vehicle allocation to the new vehicle reservation. In such manner, the operating costs of the vehicle management system are minimized for given conditions by changing the allocation of the vehicle(s) to the vehicle reservations. 
     The threshold value may be set to define a period of time that is longer than a processing time of the optimization process, which makes it possible to finish the optimization process before the rental start time for the reserved vehicle (i.e., before the use start time). Note that if the vehicle allocation is changed by the optimization process, the change of the vehicle allocation may be transmitted to the user in advance, i.e., prior to the use of the reserved vehicle, or the change of the vehicle allocation may be transmitted to the user, for example, at the rental vehicle pick up location, i.e. when the user visits the service station to pick up the reserved vehicle. 
     As described above, the vehicle management system may perform a two-part process, i.e., a simple, abbreviated process for a vehicle allocation in a shorter processing time, and a longer optimization process for a vehicle allocation that minimizes the operation costs of the vehicle-sharing service. In such manner, while the response (i.e., the reservation result) using the simple process is quickly transmitted back to the user, the service cost is efficiently minimized using the optimization process by reducing the operating costs of the vehicle allocation. 
     The present disclosure reduces the costs of a vehicle-sharing service by optimizing the vehicle allocation to the vehicle reservations and also provides a quick response to the user by quickly presenting the reservation result to the user in response to the user&#39;s reservation of a vehicle. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Objects, features, and advantages of the present disclosure will become more apparent from the following detailed description made with reference to the accompanying drawings, in which: 
         FIG. 1  illustrates a management system for a vehicle-sharing service and example infrastructure managed by the system; 
         FIG. 2  illustrates a block diagram of the management system in  FIG. 1 ; 
         FIG. 3  illustrates a timing diagram of a service provision period and an off-service period of the vehicle-sharing service; 
         FIG. 4  illustrates a timing diagram for the electric charging of an electric vehicle; 
         FIG. 5  illustrates a timing diagram of a reservation process performed by the management system; 
         FIG. 6  illustrates another timing diagram of a reservation process performed by the management system; 
         FIG. 7  illustrates another timing diagram of a reservation process performed by the management system; 
         FIG. 8  illustrates another timing diagram of a reservation process performed by the management system; 
         FIG. 9  illustrates a flowchart of a process performed by the management system; and 
         FIG. 10  illustrates a flowchart of another process performed by the management system. 
     
    
    
     DETAILED DESCRIPTION 
     Hereafter, exemplary embodiments of the present disclosure are described with reference to the accompanying drawings. For the ease of understanding and for the brevity of the description, the same numerals and reference characters are used to represent similar components in the respective drawings. 
     An outline configuration of a vehicle-sharing service using a vehicle management system  100  is described with reference to  FIG. 1 . 
     The vehicle-sharing service (also referred to herein as “service”) is a service that may provide a user with a short-term rental of a vehicle, for example an electric vehicle  30 , after a rental request from the user. 
     The service may use elements such as one or more rental stations  20 , electric vehicles  30 , and the vehicle management system  100  to rent an electric vehicle  30  to a user, shown as components of vehicle sharing system  10 . 
     The station  20  may provide a physical building  220  with a “window” or a “counter” that a user may visit for receiving service. For example, the building  220  can be staffed with a rental attendant that can assist a user with receiving service. Building  220  may also be an unstaffed building with an automated machine or kiosk to provide self-service to a user. Two or more stations  20  may be built in a specific geographic area (e.g., a service area) where the service is offered. For example, a user visits one of the stations  20  and to pick up an electric vehicle  30  to use as a rental vehicle. At or before the end of the rental period, the user then returns the electric vehicle  30  to a station  20  by bringing the vehicle to one of the stations  20 . The station  20  from which a vehicle is borrowed and the station  20  to which the vehicle is returned may be the same station  20 , or may be a different station  20 . The station  20  may also be referred to herein as the service station  20 . 
     According to the present embodiment, prior to receiving a rental vehicle from the service, the user reserves a vehicle  30 . Further, at the time of making a reservation, the user specifies a borrow station  20 , a return station  20 , a rental start time, and a rental finish time. 
     The station  20  may be provided with the building  220 , and parking spaces for the electric vehicles  30  are provided at the station  20 , for example, surrounding the building  220 . 
     The building  220  serves as a facility for providing service to the user and may provide an office for either a user or service personnel to complete work related to the service, for example, paperwork, reservation troubleshooting, and the like. The exemplary number of the stations  20  shown in  FIG. 1  is three, but the number of the stations  20  in the service area may be more than three, or may be less than three. 
     A photovoltaic panel  230  may be disposed on a roof or top part of the building  220 . The photovoltaic panel  230  converts sunlight energy to electric power. The station  20  may supply electric power generated by the photovoltaic panel  230  (i.e., solar-generated electric power) to the electric vehicles  30  parked at station  20  to charge the electric vehicles  30 . 
     The station  20  may also receive electric power, i.e., grid power, from a power grid  11 . The station  20  may also supply the grid power to the electric vehicles  30  to charge the electric vehicles  30 . 
     In the space around the building  220 , parking spaces (not illustrated) may be demarcated by lines painted on the ground. Each of the plurality of parking spaces may have a charger  210 . The charger  210  charges the electric vehicle  30  parked in the parking space, for example, when the vehicle  30  is not in service. That is, the vehicle  30  and the charger  210  are connected by a cable, and an electric power is supplied by the cable from the charger  210  to the vehicle  30  for charging. The electric power supplied for the charging of the vehicle  30  may be a photovoltaic-generated power or power from the grid supply  11 . 
     As shown in  FIG. 1 , each station  20  may have two chargers  210  and two parking spaces. However, the number of the chargers  210  and the parking spaces may vary. For example, the station  20  may have three or more chargers  210 , or may have only one charger  210 . That is, the number of the chargers  210  and parking spaces may vary from station to station. 
     The electric vehicle  30  has a secondary battery, or a storage battery, disposed therein (not illustrated) and uses the electric power stored in the storage battery to drive, i.e. propel, the vehicle. In addition to the above-mentioned storage battery, the electric vehicle  30  is provided with a power converter (not illustrated). 
     The power converter converts the electric power supplied from the charger  210 , and charges the storage battery. At the time of charging, the power converter adjusts the electric power supplied from the charger  210  in a preset range to charge the electric vehicle  30 . 
     Additionally, the electric power may be exchanged, i.e., supplied, from one vehicle  30  to another vehicle  30  parked in the same station  20 . That is, one vehicle  30  in a station  20  may supply, i.e. transfer, the electric power stored in the vehicle&#39;s own storage battery to the storage battery of the other vehicle  30  via the charger  210 , by discharging the electric power from the vehicle&#39;s own storage battery to charge the storage battery in the other vehicle  30 . 
     As discussed above, the electric vehicle  30  may be borrowed from one station  20  and returned to another station  20 , that is, the pick up location at the beginning of the rental period and drop off station  20  at the end of the rental period may not be the same station  20 . However, as contemplated by the embodiments described herein, the vehicle user returns the electric vehicle  30  to one of the stations  20  after use. 
     Therefore, the electric vehicle  30  is either parked in one station  20  or in use (i.e. as a rented vehicle driven by a user) somewhere outside the station  20 , during a service provision period, or in a certain time slot. That is, the electric vehicle  30  is in one of a parking state or use state during the service provision period. 
     The vehicle management system  100  may act as a control device that performs an overall control of the car-sharing system  10 , in order to operate the car-sharing service. The vehicle management system  100  may be configured as a computer system with one or more computers having a CPU, a ROM, a RAM, and the like. In the embodiments described herein, the vehicle management system  100  may utilize both hardware and software to perform functions including, but not limited to, reservation input, reservation allocation, reservation optimization, reservation processing, cost calculation, the transmission of reservation results, and the like. For example, the vehicle management system  100  uses networking hardware such as routers, switches, gateways, bridges, hubs, wired and wireless interface controllers, modems, multiplexers, and the like to transmit and receive vehicle reservation data between computers in the management system  100  and other computers. The management system  100  may be installed in the station  20 , or may be installed in a place other than the station  20 . Further, the management system  100  may be provided as a cooperative system that is implemented by a cooperative operation of many computers and systems, for example, a plurality of computers and systems disposed in a plurality of stations  20 . The vehicle management system  100  may also be configured with one or more servers to provide functionality to a variety of software and hardware clients. For example, the vehicle management system  100  includes one or more specialized servers to provide specific functionality to clients such as a database server, a file server, application server, web server, and the like. 
     The management system  100  operates to receive a vehicle reservation from a user and operates to allocate an electric vehicle  30  to a user&#39;s vehicle reservation. The configuration of the management system  100  is described in the following with reference to  FIG. 2 . 
       FIG. 2  illustrates the management system  100  as functional blocks, including a reservation request input  110 , a reservation result transmitter  120 , a reservation processor  130 , and a cost calculator  140 . Though illustrated as function blocks in  FIG. 2 , each of the reservation request input  110 , the reservation result transmitter  120 , the reservation processor  130 , and the cost calculator  140  includes hardware and software to perform, i.e., execute, the respective functions described below. 
     A user&#39;s computing device  40 , such as a personal computer, may be disposed in a location remote from the management system  100 , such as a user&#39;s house. As used herein, the computing device  40  may also be designated as “the personal computer  40 ,” to distinguish a user&#39;s computing device  40  from the management system  100 . Further, the computing device  40  may also be referred to herein as the external computing device  40  to distinguish that the external computing device is separate from the computers and systems of the management system  100 . 
     A user may use the personal computer  40  to interface with the vehicle management system  100  to reserve a vehicle  30 . The external computing device  40  is not limited to a desktop computer in a user&#39;s home, and may include a computing device  40  at a service facility building  220 , or a mobile terminal such as a smart phone, tablet computer, or the like. 
     The reservation request input  110  communicates with the user&#39;s personal computer  40  via the Internet, together with the result transmitter  120  described in further detail below. 
     The reservation request input  110  receives the vehicle reservation request data via the Internet when a user makes a vehicle reservation from the personal computer  40 . That is, the vehicle reservation request data for an electric vehicle  30  is input from a user&#39;s computing device  40  to the system  100  by the reservation request input  110 . The reservation request data may also be referred to herein as the reservation request, vehicle reservation, or reservation. 
     The vehicle reservation request data received by the reservation request input  110  is information including the pick up station  20  from which the user borrows the vehicle  30 , the return or drop off station  20  to which the user returns the vehicle  30 , the rental start time and the rental end time. 
     The result transmitter  120  transmits reservation result data for the user&#39;s vehicle reservation request via the Internet to the user (i.e., to the computing device  40 ). As used herein, reservation result data may be used interchangeably with reservation result to describe information transmitted to a user regarding a user&#39;s vehicle reservation in response to a user&#39;s vehicle reservation request. 
     The reservation result data is information which shows whether the vehicle reservation request data received by the reservation request input  110  is accepted or not, that is, whether the electric vehicle  30  is available for rent based on the reservation request made by the user. Further, the reservation result data includes, if the user&#39;s reservation request is accepted, information that identifies the electric vehicle  30  allocated to the user&#39;s vehicle reservation. The information for identifying the allocated electric vehicle  30  may be an individual ID that is assigned to the electric vehicle  30 , for example, vehicle identification number, where an electric vehicle  30  or vehicle parking spot is marked with a number decal/indicia such the vehicle identification number to identify the vehicle to a user and/or service personnel. The individual ID may also include a vehicle description, for example, that the allocated vehicle is a red, 4-door sedan. 
     The reservation result data transmitted from the result transmitter  120  is displayed on a screen of the personal computer  40  in a presentable form to the user, such as text and graphics. That is, when a user performs an operation for making a vehicle reservation, reservation result data is transmitted from the result transmitter  120  back to the external computing device  40 , and the reservation result data is displayed to the user. 
     When the rental start time arrives, the user visits the station  20  specified as the vehicle rental pick up station  20  when the reservation is made, and borrows the electric vehicle  30  designated in the reservation result data. 
     An IC card (i.e., smart card or chip card) may be used to store reservation result data and may be used for unlocking an electric vehicle  30 . 
     When a user makes a vehicle reservation and the vehicle reservation request is not accepted due to too many reservations requests from other users, the result transmitter  120  transmits reservation result data back to the user indicating that the vehicle reservation is declined. 
     Based on the availability of vehicles, the reservation processor  130  allocates an electric vehicle  30  to each of the vehicle reservations request input into vehicle management system  100 . The processing performed by the reservation processor  130  is described in greater detail below. 
     The cost calculator  140  calculates an operating cost for the vehicle-sharing service. The operating costs include, for example, the electricity costs for charging the electric vehicle  30  with the grid power. In other words, the utility costs associated with charging the vehicle  30  with grid power. Further, when a distribution of the electric vehicles  30  has accumulated at one of the plurality of stations  20 , the electric vehicles  30  may have to be relocated, i.e., redistributed and driven/moved to other stations  20  by service staff, and the personnel expenses for moving the electric vehicles  30  to other stations  20  may also be counted as an operating cost. As discussed above, the cost calculator  140  includes hardware and software to perform cost calculation functions. The cost calculator  140  includes hardware to calculate electricity costs such as sensors and interfaces, for example, charge sensors, electric meters, and the like. Further, the cost calculator  140  may include hardware and software to calculate personnel costs, for example, sensors to collect time dock data, a software interface to payroll and accounting software, etc. 
     When the reservation processor  130  allocates an electric vehicle  30  to a vehicle reservation by a user, the above-mentioned operating costs are taken into consideration. Details of the reservation processor  30  are described in greater detail below. 
     With reference to  FIG. 3 , an outline of processing by the vehicle management system  100  that is performed during a service provision period of the vehicle-sharing service is described. 
     The horizontal axis of the timing diagram shown in  FIG. 3  shows a time of a day, i.e., 24 hours as a length from one side to the other. Time TS is a service start time when the vehicle-sharing service is started (i.e. opening hours when vehicle rental operations begin), which may be set as 8:00 a.m. in the present embodiment. Time TE is a service end time when the car-sharing service is finished (i.e. closing hours when vehicle rental operations conclude) for the day, which may be set as 8:00 p.m. in the present embodiment. That is, the service provision period of the car-sharing service is 12 hours from time TS to time TE. The period from time TE to the time of the next TS, for example, the following service day, is an off-service period. The user can make vehicle reservations at any time, that is, while a vehicle  30  is either in the service provision period or in the off-service period. Though an example 12 hour provision period is described, the service provision period may be any number of hours, including a 24 hour period. 
     For example, in case that an operation of the vehicle reservation is performed in the off-service period, which is shown by an arrow AR 0  in  FIG. 3 , the vehicle management system  100  responds in the following manner. 
     When the vehicle reservation is input into the reservation request input  110 , the reservation processor  130  determines whether the vehicle reservation of a subject vehicle  30  is acceptable, and when it is acceptable, the reservation processor  130  allocates the subject electric vehicle  30  to the respective vehicle reservation. 
     The vehicle allocation process for allocating the electric vehicle  30  to the reservation is actually performed as a two-part process. That is, the vehicle allocation is performed either as an abbreviated, “simple” process, or as a longer optimization process. As used herein, the abbreviated process may also be referred to as the simple process to distinguish the abbreviated process from the more process-intensive optimization process. 
     The optimization process performed by the vehicle management system  100  allocates the electric vehicle  30  so that the operating costs calculated by the cost calculator  140  are minimized under a given condition. 
     In performing the optimization process, the reservation processor  130  draws up a charge plan. 
     A charge plan is data in which a charging time slot for each of the electric vehicles  30  is shown as a scheduled data at the station  20 . When a charge plan is made, a vehicle allocation plan is also made, in which vehicle reservations already input into the management system  100  are all listed as data, listing which electric vehicle  30  are assigned to which reservation. 
     Further, a vehicle location plan, that is, a position or location of each of the electric vehicles  30  relative to each of the stations  20 , is also made at the same time, in which the location of each of the electric vehicles  30  in the service provision period is shown as data. 
     The charge plan, the vehicle allocation plan, and the vehicle position plan are all drawn up as a service operation plan of the vehicle-sharing service in a period TM 0  from time TS to time TE. 
     The service operation plan, including the charge plan and the like, is made each time a vehicle reservation is input from a user to the reservation request input and the optimization process is performed in response to such input. 
     That is, the service operation plan for the period from time TS to time TE is updated whenever a vehicle reservation is input into the system  100 . Therefore, the allocation of the electric vehicles  30  to all the vehicle reservations already input to the system  100  is updated and optimized each time a vehicle reservation is input into the system  100 . 
     At time TS, the service provision period is started, and the vehicle-sharing service may be provided. 
     As the users start to use the electric vehicles  30 , the electric vehicles  30  begin to move between the stations  20 . As a result, the number of the electric vehicles  30  stopped/parked at each of the stations  20  (i.e., the number of vehicles in stock at each of the stations  20 ) changes from the number at an initial time state before time TS. 
     For example, at a certain point in time indicated by arrow AR 1  in  FIG. 3 , a new vehicle reservation is made. Such a situation is described in greater detail below. 
     In such case, the same processing as the above is performed. 
     That is, when a new vehicle reservation is input to the reservation request input  110  and the optimization process is performed in response, the reservation processor  130  draws up an updated charge plan, an updated vehicle allocation plan, and an updated vehicle position plan, to reflect any changes to the charge, allocation, or location plans of the service operation plan. 
     These operation plans are drawn up as the service operation plan for a period TM 1  from a current time t when the new vehicle reservation is input to the reservation request input  110  to time TE. 
     The charge plan, the vehicle allocation plan, and the vehicle location plan processes are described in greater detail below. 
     A charge plan is drawn up as data in the following form:
         {p i,j (τ|t)}       

     The above-mentioned “t” is the current time t when a vehicle reservation is input to the reservation request input  110 . The term “τ” represents discrete points of time found in a period from the current time t to time TE, which may be, in other words, a moment with a Step of time period (Δt). 
     Although time τ after lapse of a Step of time period Δt from the current time t is “t+Δt”, it is simplified herein as “t+1,” as shown in  FIG. 3 . 
     Similarly, although time τ after lapse of Δt×2 from the current time t is “t+2Δt”, it is simplified herein as “t+2.” Time τ thereafter may also be represented in similar form. Time τ takes a value from t+1 to TE. 
     The above-mentioned “i” is a variable, identifying each of the stations  20 , by taking an integer value. In the following, for example, the total number of the stations  20  is designated as S, and an individual ID from 1 to S is given to each of the stations  20 . Therefore, the above-mentioned i takes an integer value from 1 to S. 
     The above-mentioned “j” is a variable, identifying each of the electric vehicles  30 , by taking an integer value. In the following, for example, the total number of the electric vehicles  30  is designated as V, and an individual ID from 1 to V is given to each of the electric vehicles  30 . Therefore, the above-mentioned j takes an integer value from 1 to V. 
     The number p i,j (τ|t) is an amount of charge power that is charged to the electric vehicle  30  with an ID of j at time τ, which is after the current time t, at the station  20  with an ID of i. 
     The charge plan {p i,j (τ|t)} is made up of data that shows a summation of the electric power to charge vehicles  30  for all combinations of the variables τ, i, and j. That is, the charge plan {p i,j (τ|t)} is the data related to the schedule forcharging a vehicle  30  at a station  20  in a certain time slot, for each of the vehicles  30  with an ID of 1 to V. 
     The vehicle allocation plan is drawn up as data in the following form:
         {a j,k (t)}       

     In the above expression, “k” is a variable, identifying each of all vehicle reservations, including new vehicle reservations, that are already input to the system  100 . In the following, the total number of vehicle reservations is designated as R, and an individual ID from 1 to R is given to each of the vehicle reservations. Therefore, the above-mentioned k takes an integer value from 1 to R. Note that, since the number R increases as a new vehicle reservation is input, it may more accurately be designated as “R(t)”. 
     The value a j,k (t) is set to 1 when a vehicle reservation of an ID k has an electric vehicle  30  allocated thereto. Other than the above, the value a j,k (t) is set to 0. That is, the value a j,k (t) is either set to 0 or 1, for representing whether an electric vehicle  30  has been allocated or not. Thus, the vehicle allocation plan {a j,k (t)} is made up as the data for representing all allocations of the electric vehicles  30  at the current time t for the combinations of variables j and k. 
     The vehicle location plan is drawn up as data in the following form.
         {x i,j (τ|t)}       

     When an electric vehicle  30  with an ID of j is parked at a station  20  with an ID of i at the time t, the value x i,j (τ|t) is set to 1. Other than the above, the value x i,j (τ|t) is set to 0. 
     The vehicle location plan {x i,j (τ|t)} is made up as the data that shows the value x i,j (τ|t) for all combinations of the variables τ, i, and j. In such manner, the location of an electric vehicle  30  at time τ is represented. 
     The vehicle location plan {x i,j (τ|t)} should represent all vehicle locations, including if a vehicle  30  is parked at a station  20  or if a vehicle  30  is traveling on the road, (i.e., a vehicle not stopped or parked at the station  20 ). Therefore, while a vehicle stopped/parked at a station  20  is represented by the vehicle location plan {x i,j (τ|t)} with the variable “i” indicating a station  20 , a traveling vehicle  30  (not stopped/parked at any station  20 ) is described as stopped/parked at a station  20  with an ID of S+1, to indicate a non-existent station. In other words, a traveling vehicle&#39;s location is shown as S+1 indicating a non-existent station. Therefore, the vehicle position plan {x i,j (τ|t)} has the variable i that takes an integer value from 1 to S+1. 
     The charge plan {p i,j (τ|t)}, the vehicle allocation plan {a j,k (t)}, and the vehicle location plan {x i,j (τ|t)} are respectively calculated as the data which minimizes an operation cost E represented by the following equation (1) on a given condition. 
     That is, each of those plans is drawn up as a result of calculation that minimizes the operation cost E under a given condition. 
     
       
         
           
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     In the equation 1 the first term is 
     
       
         
           
             
               
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               . 
             
           
         
       
     
     Each term of the equation 1 is described as follows. 
     The value f d (i1,i2,τ) in the first term is a function of the vehicle transfer operation cost (i.e., a vehicle relocation cost) for transferring a vehicle among the stations  20  by a staff member (i.e., not by the rental user). That is, f d (i1,i2,τ) is a cost of a vehicle transfer from a station  20  with an ID of i1 to a station  20  with an ID of i2 at time τ. Note that f d (i1,i2,τ) simply represents a transfer cost (i.e., an amount of money) in the above situation, and does not specify whether such a vehicle transfer is actually performed. Whether the vehicle transfer is actually performed or not is specified by d i1,i2 (τ). 
     The value f d (i1,i2,τ) is a function of τ, because, for example, the transfer cost may vary due to different road congestion conditions in different time slots. Further, the staffs hourly expenses may also change for different time slots, for example, service staff may have higher wages on the weekend or holidays. 
     The value d i1,i2 (τ) in the first term is a function represented by the following equation 2: 
     
       
         
           
             
               
                 
                   
                     
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                     2 
                   
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     On the right side of the equation 2, the term x i1,j (τ) takes a value of 1 when a vehicle  30  with an ID of j is parked at a station  20  with an ID of i1 at time τ. Further, the term x i2,j (τ+1) takes a value of 1 when the vehicle  30  with an ID of j (i.e., the same vehicle  30 ) is parked at a station  20  with an ID of i2 at time τ+1 (after lapse of time Δt from time τ). 
     Therefore, the value of d i1,i2 (τ) represented by the equation 2 is equal to 1 when a vehicle  30  with an ID of j is transferred from a station  20  with an ID of i1 to a station  20  with an ID of i2 during the lapse of time Δt from time τ. 
     Based on the above, the first term of the equation 1 represents a vehicle transfer operation cost for a transfer of the vehicle  30  among different stations  20  by a staff of the car-sharing system  10 , for accommodating a vehicle reservation. 
     Before describing the second term and the third term of the equation 1, g i (τ), w i (τ), and l i (τ) are respectively described. 
     The value g i (τ) is a value of the electric power able to be generated (i.e., generatable) by the photovoltaic panels at a station with an ID of i at time τ, and expressed in units of watts (“W”). Hereafter, it is designated as a “generatable power amount g i (τ).” 
     The generatable power amount g i (τ) is the data prepared in advance based on data obtained from weather agencies regarding the forecast of solar radiation amounts expected at each of the stations  20 . In other words, the data is based on solar radiation that each of the stations  20  is expected to receive, based on forecasted weather data. 
     The data of the generatable power amount g i (τ) is generated for each of the stations  20 , i.e., for the station ID from 1 to S, and for each time τ in the period from time TS to time TE. 
     Note that the actual value of the photovoltaic power actually generated at time τ at the station  20  is not necessarily in agreement with the data of the generatable power amount g i (τ). 
     For example, even when a sufficient amount of solar radiation is received by the photovoltaic panel  230  at a station  20 , the generated electric power from the panel  230  cannot be charged to the battery of the vehicle  30  when no electric vehicle  30  is parked at the station  20 . 
     Therefore, the photovoltaic panel  230  may be configured to automatically suppress a power generation amount in such a situation. Thus, the generatable power amount g i (τ) is rather a maximum generatable amount of electric power at the station  20  at time τ. 
     The value w i (τ) is defined as a power amount that is calculated by deducting an actual generated electric power amount at the station  20  with an ID of i from the above-mentioned generatable power amount g i (τ), and expressed in units of watts (W). 
     Such a value w i (τ) may thus be designated as an opportunity-loss power amount w i (τ), i.e., an amount of electric power that may have otherwise been charged to the battery of the electric vehicle  30  at the station  20  but is lost due to the absence of the vehicle  30 , or the like. 
     The value l i (τ) is a value of the grid power that is supplied to a station with an ID of i at time τ, and expressed in units of watts (“W”). In the following, it is designated as the grid power amount l i (τ). 
     The grid power amount l i (τ) is associated with the above-mentioned generatable power amount g i (τ) and the opportunity-loss power amount w i (τ) by the following equation 3: 
     
       
         
           
             
               
                 
                   
                     
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                       i 
                     
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     For example, in a time slot in which the generatable power amount g i (τ) takes a relatively small value, the value of the grid power amount l i (τ) is adjusted so that the charging is performable as planned according to the charge plan {p i,j (τ|t)}. As a result, the value of the opportunity-loss power amount w i (τ) in the given time slot becomes 0 (i.e., decreases to 0). 
     In a time slot in which the generatable power amount g i (τ) takes a relatively large value and the need for the charging is relatively low, the grid power amount l i (τ) becomes zero and the opportunity-loss power amount w i (τ) takes a value that is greater than zero. 
     In the calculation for minimizing the operation cost E with the equation 1, in order to perform the charging according to the charge plan {p i,j (τ|t)} using as much electric power supplied from the photovoltaic as possible, the value of the grid power amount l i (τ) is suitably adjusted for each of the time τ. 
     The value f w (τ) in the second term of the equation 1 converts a photovoltaic electric power in a unit of 1 watt-hour into a monetary value. 
     The value f w (τ) may be described as a function of price, for example, in an instance where electric power generated by photovoltaic panels  230  is sold to a grid-power company at time τ. 
     The second term of the equation 1 is equivalent to an integration value over the period of time after the current time t of a product of a summation of the opportunity-loss power amounts w i (τ) of all the stations  20  multiplied by the value f w (τ) described above. 
     That is, the second term represents a value of loss, or the amount of money, of the opportunity-loss power amount w i (τ) for the remaining service provision period. 
     The value f l (τ) in the third term of the equation 1 converts a grid power in a unit of 1 watt-hour into the amount of money for valuation. 
     The value f l (τ) corresponds to a selling price for selling generated power to a grid-power company. 
     The third term of the equation 1 is equivalent to an integration value over the period of time after the current time t of a product of a summation of the grid power amount l i (τ) of all the stations  20  multiplied by the value f l (τ) described above. 
     That is, the value of the third term represents a monetary cost or a “grid-charge cost”, i.e., the cost to charge each of the electric vehicles  30  using grid power for the remaining service provision period of the day. 
     In the optimization process, the operation cost E, that is a sum of the first, second and third terms, described above, is minimized by suitably generating the charge plan {p i,j (τ|t)}, the vehicle allocation plan {a j,k (τ)}, and the vehicle position plan {x i,j (τ|t)}. These plans are made according to the calculation of the reservation processor  130 , based on the calculation of the operation cost E by the cost calculator  140 . 
     In the course of the calculation for minimizing the operation cost E, various initial conditions and various restrictions are considered. That is, the minimization calculation is performed under the plurality of conditions. 
     The initial conditions may be, for example, set as the current position of each of the electric vehicles  30 . The initial condition of the vehicle position corresponds to each of the values of the vehicle position plan {x i,j (τ|t)} at the time of τ=0. 
     The amount of charged electricity (SOC: State of Charge) for each of the storage batteries in each of the electric vehicles  30  at the current time (τ=0), may also be set up as the initial condition. 
     The information regarding the initial SOC may be obtainable, for example, via the communication between the electric vehicle  30  and the charger  210 . As described above, the cost calculator  140  includes hardware and software to perform its given cost calculation function. For example, the cost calculator includes communication hardware to communicate with either the electric vehicle  30  or charger  210  to obtain SOC data. 
     As an exemplary restriction condition (‘restriction’), the value of SOC at time TE for each of the storage batteries carried in each of the electric vehicles is set. 
     That is, a target value of SOC (i.e., the amount of stored electric power) at the end time of the service provision period may be set up as a restriction. While it may be desirable to have the SOC value at the end of the service provision period set as a “larger-the-better,” or maximum value, this may not always be the case. For example, if the target SOC value is set to 100% uniformly for all batteries, setting the target SOC to this value may raise the opportunity-loss power amount w i (τ) of the next day. Therefore, it is not necessarily desirable to set the SOC value to a “larger-the-better” or maximum value. That is, the target SOC value at the end of the service provision period, for example, may be set uniformly to 50%. However, the target SOC value may be set based on other factors such as weather. For example, the target SOC may be set to 30% during clear, sunny days, and 80% during rainy days. 
     By setting the above restrictions, the reservation processor  130  makes the charge plan {p i,j (τ|t)} and the like for controlling the SOC of each of the electric vehicles  30  to match the target SOC value at the end of the service provision period of the vehicle-sharing service. 
     As another exemplary restriction condition, a usage amount (i.e., decrease) of stored electric power during period (Δt) of vehicle travel is set individually for respective electric vehicles  30 . 
     Other exemplary restrictions include, setting individual upper limits and lower limits of SOC for respective electric vehicles  30  operated by the service. In such manner, the reservation processor  130  makes the charge plan {p i,j (τ|t)} and the like based on an assumed condition that the SOC of the electric vehicle  30  in the service operation is kept within a range between a lower limit and an upper limit. 
       FIG. 4  shows an example of transition of SOC upper/lower limit values serving as the restrictions, by a line L 1  and a line L 2 . In the example of  FIG. 4 , the upper limit of SOC is set up as 100% uniformly, and that value does not change. 
     On the other hand, the lower limit of SOC is set up to temporarily increase in a period from time T 10  to time T 20 . 
     For example, where a time slot for vehicle reservation is in high demand, or where the system predicts an increase in the renting of vehicles  30 , it may be desirable to raise the lower limit of SOC temporarily in such a time slot. In such manner, the system prevents the electric vehicle  30  from running out of stored electrical power during operation. Note that the example shown in  FIG. 4  is but one example case, and other conditions may also be set by the system. For example, the upper limit of SOC may vary as a function of time, similar to the lower limit, as described above. 
     The upper limit and the lower limit of charging power during the charging of the electric vehicle  30  may additionally be set as the restrictions. 
     Additionally, during the exchange of power between electric vehicles  30  (i.e., electric power from one vehicle  30  used to charge another electric vehicle  30 ), the upper limit lower limits of electric power discharge from the electric vehicle  30  may be set as a restriction. 
     Note that when performing the calculation for minimizing the operation cost E, other additional real world restrictions may apply. For example, the number of the electric vehicles  30  allocated to one vehicle reservation is set to 1. 
     As mentioned above, the operation cost E, calculated by the cost calculator  140  in the optimization process, may be minimized by the vehicle allocation plan {a j,k (t)} generated under given conditions (e.g., under the initial condition and restrictions), and as a result of such plan, an allocation of an electric vehicle  30  to a vehicle reservation is performed. 
     The optimization process is performed, as described above, by taking various conditions into consideration, such as a position, an amount of stored electric power, etc., of each the electric vehicles  30  in service. 
     Therefore, when the scale of service becomes large, the processing time for the optimization process may increase, for example, taking 15 minutes or more. In such case, it is not practical to keep a user waiting for long periods during the vehicle reservation process, while the optimization process is carried out. 
     Therefore, the reservation processor  130  is configured for performing a simple, abbreviated processing (used herein as “simple” or “abbreviated” process) in addition to the above-mentioned optimization process. The abbreviated process is a process that allocates the electric vehicle  30  in a shorter period of time than the optimization process, by omitting or simplifying the calculation of the operation cost E by the cost calculator  140 . 
     An example of the simple process may be processing that allocates a “vacant” electric vehicle  30  to the vehicle reservation on a first-come, first-serve basis, without taking the operation cost E into consideration. 
     In such case, since the calculation of the operation cost E shown in equation 1 is omitted, the calculation load is made lighter and the allocation of the electric vehicle  30  to a vehicle reservation request is processed in a shorter period of time. 
     Another example of the simple process omits the first term of the operation cost E in Equation 1, that is, the simple process is carried out without taking the vehicle transfer operation cost, or the vehicle relocation cost into consideration. 
     In such case, since calculation of the operation cost E is simplified, allocation of the electric vehicle  30  takes less time than the allocation time used by the optimization process. 
     An example of the processing performed by the system  100 , when a vehicle reservation is made by a user and the vehicle is allocated to the reservation, is described with reference to a timing diagram in  FIG. 5 . As used in the drawings and description below, a user who makes the vehicle reservation may be designated as “User  1 ”. 
     When a vehicle reservation is input to the reservation request input at time T 110 , the abbreviated process is started at such point in time. In  FIG. 5 , a processing period of the abbreviated process is represented by an arrow AR 10 . As mentioned above, since the abbreviated process completes in a short period of time, the abbreviated process completes at time T 120 , which occurs shortly after time T 110 . 
     The simple process in the present embodiment is processing which allocates a vacant electric vehicle  30  to the vehicle reservation on a first-come, first-serve basis without taking the operation cost E into consideration. Therefore, when a vacant electric vehicle  30  is available for rent, the available electric vehicle  30  is allocated to the vehicle reservation. That is, the allocations of the electric vehicles  30  to the other, prior vehicle reservations are not changed by performing the simple process for the subject vehicle. 
     At time T 120 , i.e., when the abbreviated process is complete, transmission of a reservation result is transmitted to User  1 . As described above, the information that specifies which electric vehicle  30  is allocated to the vehicle reservation is included in the reservation result. 
     After completion of the abbreviated process, the optimization process starts subsequently. In  FIG. 5 , a processing period for the optimization process is represented by an arrow AR 20 . In this example, since User  1  has already received the reservation result at T 120 , and User  1  may not provide any further input into personal computer  40  for the reservation process and may exit any reservation application running on the personal computer  40 . 
     In the example of  FIG. 5 , a rental start time shown in the vehicle reservation is designated as time T 140 . The time from the completion of the simple process at time T 120  to time T 140  is a relatively-long period, that is, longer than the time required for performing the optimization process (i.e., longer than the length of the arrow AR 20 ). Therefore, the optimization process is complete at time T 130  before the rental start time (T 140 ). 
     When the optimization process is complete and the allocation of the electric vehicle  30  to the vehicle reservation is changed at time T 130 , such change of the vehicle reservation is transmitted to the User  1  at time T 130 . 
     The updated reservation result information showing the updated allocation of the electric vehicle  30 , for example, is transmitted from the result transmitter  120  to the personal computer  40  or a portable communication device (i.e. smart phone, tablet, and the like) of User  1 . As described above, the allocation information reservation result may also be considered as “updated by the optimization process.” 
     There may be instances where a period of time from the completion of the simple process to the rental start time is relatively short, and the optimization process cannot be completed within such a period of time. Such an example is shown in  FIG. 6 . 
     In  FIG. 6 , a processing period for the simple process (i.e., a period from time T 110  to time T 120 ) is represented by the arrow AR 10 . 
     As also illustrated in  FIG. 6 , the rental start time is time T 125 , which is earlier than the completion of the optimization process at time T 130 . That is, a period of time from time T 120 , at which the simple process completes, to time T 125 , that is the rental start time, is shorter than a period of time from T 120  to T 130  for the optimization process (i.e., the time from T 120  to T 125  is shorter than the length of the arrow AR 20 ). 
     In such case, the reservation processor  130  does not perform the optimization process, and confirms the vehicle allocation of the electric vehicle made during the simple process is the same as the vehicle allocation as determined by the optimization process, i.e. a final vehicle allocation to the vehicle reservation made by User  1 . 
     The determination of whether to perform the optimization process or not may be made based on a comparison between: (i) a period of time from completion of the simple process to a rental start time; and (ii) a predetermined threshold value. 
     The optimization process is performed when the period of time from completion of the simple process to the rental start time is equal to or greater than the threshold value. The threshold value may be set to define a period of time for the completion of the optimization process, or a period of time of greater duration than the optimization process 
     Another example of the processing performed by system  100 , when a plurality of vehicle reservations are made by a plurality of users and a vehicle is allocated to a reservation, is described with reference to a timing diagram in  FIG. 7 . 
     As shown in  FIG. 7 , User  1  makes a first vehicle reservation at time T 110 , and the abbreviated process associated with the first vehicle reservation is performed from time T 110  to time T 120 , as shown by arrow AR 10 . The rental start time for the vehicle reserved by User  1  is T 140 . 
     At time T 120 , the optimization process of the vehicle reserved by User  1  is started, as shown by arrow AR 20 . 
     With continued reference to the example illustrated in  FIG. 7 , at time T 121 , a point in time after T 120  and before time T 130 , another user, User  2 , makes a second, subsequent vehicle reservation. In such case, the optimization process being performed for the first vehicle reservation made by User  1  is interrupted. Between time T 121  and T 122 , the simple process for the second vehicle reservation made by User  2  is performed, as shown by arrow AR 40 . In such manner, an electric vehicle  30  is allocated to the second vehicle reservation made by User  2 . 
     When the simple process shown by arrow AR 40  is complete at time T 122 , a reservation result includes information showing a vehicle allocation is transmitted to User  2 . 
     A rental start time for the second, subsequent vehicle reservation made by User  2  is at time T 123 . Accordingly, the period of time from the completion of the simple process at time T 122  to the rental start time at T 123  may be shorter than a threshold value. 
     Therefore, the optimization process for the second vehicle reservation made by User  2  is not performed, but the allocation of the electric vehicle  30  to the second vehicle reservation is finalized or fixed, i.e., fixedly determined, at time T 122 . 
     After completion of the simple process for the second vehicle reservation made by User  2 , the interruption of the optimization process for the first vehicle reservation made by User  1  stops, and the optimization process resumes, as shown by arrow AR 30 . 
     A period of time from time T 122 , where the optimization process of the first reservation is resumed, to the rental start time for the first reservation at T 140 , is longer than the period to complete the optimization process for the first reservation, i.e. the period from time T 122  to time T 135 , as shown by arrow AR 30 . Therefore, the optimization process is complete at time T 135  before the rental start time at T 140 . 
     When the optimization process shown by arrow AR 30  is complete, the electric vehicle  30  originally allocated to the first vehicle reservation made by User  1  is changed (for example, allocated to the second vehicle reservation made by User  2 ), and information regarding such change is transmitted to User  1 . 
     Another example of the processing performed by system  100 , when a plurality of vehicle reservations are made by a plurality of users and a vehicle is allocated to a reservation, is described with reference to a timing diagram in  FIG. 8 . In  FIG. 8 , User  1  makes a first vehicle reservation at time T 110 , and the simple process for such reservation is performed in a period of time from time T 110  to time T 120 , as shown by arrow AR 10 . The rental start time for the first vehicle reservation is at time T 140 . Therefore, at time T 120 , the optimization process for the first vehicle reservation is started, as shown by arrow AR 20 . 
     At time T 125 , a point in time after T 120  and before time T 130 , another user, User  2 , makes a second vehicle reservation. 
     The optimization process for the first vehicle reservation made by User  1  is interrupted at time T 125 . 
     After time T 125 , an abbreviated process for the second vehicle reservation made by User  2  is performed, as shown by arrow AR 41  and an electric vehicle  30  is allocated to the second vehicle reservation made by User  2 . 
     When the simple process for the second vehicle reservation is complete at time T 126 , a reservation result including the information regarding vehicle allocation is transmitted to User  2 . 
     A rental start time for the second vehicle reservation made by User  2  is at time T 127 . A period of time from the completion of the simple process for the second vehicle reservation at time T 126  to the rental start time at T 127  is shorter than a threshold value. Therefore, the optimization process for the second vehicle reservation made by User  2  is not performed and the allocation of an electric vehicle  30  to the second vehicle reservation is finalized or fixed, i.e., fixedly determined, at time T 126 . 
     The interrupted optimization process for the first reservation made by User  1 , if resumed at time T 126 , will complete at time T 145 , as shown by arrow AR 31 . 
     Accordingly, since the interruption of the optimization processing for the first reservation occurs later in the optimization process, for example as compared to the example illustrated in  FIG. 7 , and the completion time of the simple process for the second reservation occurs at time T 126 , the new completion time for the optimization of the first reservation will be completed at T 145 , a point in time after the desired rental time start T 140  for the first reservation made by User  1 . That is, when it is determined that a duration and a completion of an optimization process resumed after an interruption, for example, the resumed optimization process for the first reservation by User  1 , as shown by arrow AR 31 , will be longer in duration and occur after the desired rental start time, i.e., T 140 , selected by User  1 , the reservation processor  130 , allocates an electric vehicle  30  to the first vehicle reservation immediately following the completion of the simple process for the first reservation, as shown by arrow AR 10 , without performing the optimization process. Such a vehicle allocation is final and conclusive, and the system  100  fixes a vehicle allocation to the first vehicle reservation made by User  1 . 
     As discussed above, for vehicle management system  100 , when a new vehicle reservation is input to the reservation request input  110 , the reservation processor  130  performs the abbreviated process for allocating an electric vehicle to the respective vehicle reservation. Then, the result transmitter  120  transmits the reservation result back to the user. 
     In such case, when a period of time between a user&#39;s reservation of a vehicle and the rental start time of the vehicle reservation is equal to or greater than the predetermined threshold value, the reservation processor  130  performs an optimization process. Thereby, the allocation of an electric vehicle  30  to the vehicle reservation is updated. 
     As described above, the vehicle management system  100  may perform a two-part vehicle allocation, as both a simple process that completes the allocation of the electric vehicle  30  to a vehicle reservation in a short period of time, and as an optimization process in which allocation of the electric vehicle  30  is updated/reconsidered so that an operation cost, E, is minimized. 
     In such manner, the vehicle management system quickly responds to a user who making a vehicle reservation (i.e., quickly transmitting a reservation result), and provides an efficient operation of a vehicle sharing service in a low cost manner. 
     A process performed by the vehicle management system  100 , in response to the reservation request input  110  receiving a vehicle reservation request by a user, is described with reference to  FIG. 9 . 
     Note that, when two or more vehicle reservations are input to the reservation request input  110  by two or more different users at the same time, the process shown in  FIG. 9  is performed concurrently for each of the vehicle reservations. 
     As described herein, a new vehicle reservation triggering the process illustrated in  FIG. 9  may also be designated as a ‘new reservation’ to distinguish the ‘new reservation’ from other vehicle reservations already input into the system  100 , i.e., reservations made prior to the new vehicle reservation. 
     At S 01 , the simple process is performed by the reservation processor  130 . When the simple process is complete, the process proceeds to S 02 . In S 02 , a transmission of the reservation result to the user is performed by the result transmitter  120 . 
     Note, when there are no electric vehicles  30  available to accommodate the new reservation, the reservation result showing such a result is transmitted in S 02 . In such case, the operation system ends the process shown in  FIG. 9  after S 02 . 
     In S 03 , the system determines whether there is time for performing the optimization process. 
     When the system determines in S 03  that the period of time from the completion of the simple process to the rental start time is equal to or greater than a threshold value, (i.e. YES indication), the process proceeds to S 04 . 
     Having proceeded to S 04  means that, as shown in the example of  FIG. 5 , the optimization process may be completed by a rental start time. Therefore, the optimization process is started accordingly. 
     For the optimization process performed after S 04 , the process jumps from connector A in  FIG. 9  to connector A in  FIG. 10 , and returns to connector B in  FIG. 9 , after completing S 15  shown in  FIG. 10 . 
     Prior to describing the process of  FIG. 10 , “a fixed reservation” and “an unfixed reservation” are described. 
     In the vehicle management system  100 , all the inputs of the vehicle reservation are categorized and stored into a memory of system  100  as either a fixed reservation or an unfixed reservation. 
     The fixed reservation is a vehicle reservation where changing the allocation of the electric vehicle  30  to a user is prohibited, for example, due to the short period of time between a user making a vehicle reservation and the vehicle rental start time. In other words, the reservation of a vehicle  30  to a user reservation request is fixed and cannot be changed. 
     The unfixed reservation is a vehicle reservation in which there is extra time available prior to the vehicle rental start time, and the allocation of the electric vehicle  30  to a user may be changed. For example, the time between a user making a vehicle reservation and the vehicle rental start time is long enough to allow the vehicle allocation to the user to be changed. 
     In S 11 , one unfixed reservation is extracted from the prior (i.e., already input before the “new” reservation) vehicle reservations. 
     In S 12 , the system  100  determines whether there is any additional time for performing the optimization process for the unfixed reservation. In such case, when a period of time from the completion of the simple process to the rental start time is equal to or greater than a threshold value, the system  100  determines there is enough time to perform an optimization process. When there is time for the optimization process, the process proceeds to S 14 , without performing S 13 . When there is not enough time to perform the optimization process, the process proceeds to S 13 . 
     When the process proceeds to S 13 , the allocation of the electric vehicle to the corresponding unfixed reservation becomes fixed so that it may not be changed. That is, an unfixed reservation is changed to a fixed reservation at S 13  and the process proceeds to S 14 . 
     In S 14 , the system  100  determines whether processing for all the unfixed reservations after S 12  has been performed. 
     When there are any prior, unfixed reservations which have not yet undergone processing after S 12 , the process returns to S 11  and the next unfixed reservation is extracted and processed, as described by S 11  and S 12 . 
     When processing after S 14  has been performed for all the prior, unfixed reservations, the process proceeds to S 15 . 
     In such manner, by performing processing from S 11  to S 14  for all the unfixed reservations, all the unfixed reservations having no additional spare time to perform an optimization process prior to the rental start time are changed from unfixed reservations to fixed reservations. 
     In S 15 , the operation plan, i.e., the plan made up from the charge plan {p i,j (τ|t)}, the vehicle allocation plan {a j,k (τ)}, and the vehicle position plan {x i,j (τ|t)}, is generated to minimize the operation cost E. 
     Although the method of generating the operation plan and its subcomponents is described above, the operation plan is generated based on an assumption that a part of the vehicle allocation plan {a j,k (t)} corresponding to the fixed reservation will not be changed. 
     That is, among all the vehicle reservations (i.e., more precisely one or more already-input or prior vehicle reservations), the allocation of an electric vehicle  30  is updated by the reservation processor  130  for the prior, unfixed reservation(s), in addition to updating the vehicle allocation to the new, subsequent reservation. 
     Returning to connector B in  FIG. 9 , as shown after S 04 , when the optimization process is started, the process proceeds to S 05 . 
     In S 05 , the system  100  determines whether the optimization process is complete. When the optimization process is complete, the process proceeds to S 06 . 
     In S 06 , the reservation result data updated by the optimization process is transmitted to a user (i.e., transmitted to a user&#39;s personal computer  40  for display to the user) from the result transmitter  120 . 
     When the allocation of the electric vehicle  30  to the new, subsequent reservation is changed, a reservation result is transmitted to the user making the new reservation. 
     When the allocation of the electric vehicles  30  to the vehicle reservations other than the new reservation is changed, i.e. to the prior vehicle reservation requests, a reservation result is also transmitted to the user(s) who made the corresponding vehicle reservation(s). 
     Transmission of the reservation result to the user is not performed for the vehicle reservation(s) where allocation of the electric vehicle  30  is not changed. 
     Note, that a notice indicating that the allocation of an electric vehicle  30  has changed, may be performed in manners different than the manner described above. 
     For example, a user may be presented with a notice when visiting the station  20 , and such notice regarding a change of vehicle allocation may be posted on a bulletin board or the like. 
     In S 05 , when the optimization process is not yet complete, the process proceeds to S 07 . 
     In S 07 , the system  100  determines whether another new, i.e., “newer”, reservation, which occurs after or subsequent to the new reservation described above, is input after the new reservation. 
     When the system  100  does not detect the input of any newer (i.e. subsequent) vehicle reservations, the optimization processing at S 05  is performed again. 
     When a newer vehicle reservation is input, the process proceeds to S 08 . 
     In S 08 , the optimization process started in S 04  is interrupted, and the processing method shown in  FIG. 9  is finished. Interruption of the optimization process performed at S 08  is similar to the interruption at time T 121  in  FIG. 7 , and the interruption at time T 125  in  FIG. 8 . 
     That is, when the reservation processor  130  is performing the optimization process for a first vehicle reservation request, in instances where a second, newer vehicle reservation request is input to the reservation request input  110 , the reservation processor  130  interrupts the optimization process being performed for the first vehicle reservation request. 
     Note that the “newer” reservation is accommodated by concurrently performing the processing method shown in  FIG. 9 . Such processing is similar to the processing that occurs at arrow AR 40  in  FIG. 7 , and processing that occurs at arrow AR 41  in  FIG. 8 . 
     In S 03 , when the system  100  determines that there is no additional time for performing the optimization process, the process proceeds to S 09 . 
     Having proceeded to S 09  means that a period of time from the completion of the simple process to the rental start time, for example, as indicated by the new reservation, is shorter than the threshold value, and the optimization process therefore cannot be performed. 
     Therefore, at S 09 , the allocation of the electric vehicle  30  to the new reservation is fixed to what has been allocated by the simple process in S 01 . That is, the vehicle allocated to the new reservation request during the simple process is fixed, and the new reservation is set as a fixed reservation. 
     After performing the simple process, when a period of time to from the end of the simple process to the rental start time for the new reservation is determined to be shorter than the threshold value, the reservation processor  130  fixes the allocation of the electric vehicle  30  to the new reservation request performed in the simple process, and does not change the corresponding vehicle allocation thereafter. 
     At S 10 , the system  100  determines whether any optimization processes were interrupted at S 08 . That is, the system  100  determines whether other vehicle reservations exist, where the respective optimization process was interrupted due to an input of a new reservation, i.e. newer than the existing vehicle reservation request. 
     When the system  100  determines that no optimization processes have been interrupted, the processing method shown in  FIG. 9  is finished. 
     If system  100  determines that optimization processes have been interrupted the processing method after S 04  is performed again. In such a manner, the allocation of an electric vehicle  30  to one or more vehicle reservations that have already been input into the system  100  (i.e., all the reservations prior to the new reservation) is analyzed, and the vehicle allocation for the unfixed reservation, where the allocation of the electric vehicle  30  is not yet fixed, is updated. 
     The optimization process started at S 04  and continuing to S 10  is similar to the processing that occurs at arrow AR 30  in  FIG. 7 . 
     However, there may be instances where an interrupted optimization process may be changed from an unfixed reservation to a fixed reservation after a lapse of time, for example, as represented by the process performed at S 13  in  FIG. 10 . In such case, the interrupted optimization process is not performed again. 
     As discussed above in regard to the example shown in  FIG. 8 , a result of the simple process performed prior to the optimization process may be finalized with regard to the allocation of the electric vehicle  30  to the vehicle reservation. 
     The examples described herein use electric vehicles  30  as the vehicles used in the vehicle sharing service, however, such vehicles  30  are not limited to electric vehicles. For example, the vehicle sharing service can also use “hybrid” vehicles having both a storage battery and an internal-combustion engine. 
     Further, the service vehicles  30  may also be wholly powered by internal-combustion engines. In such case, the operation cost E can still be calculable, for example, by omitting the second term and the third term from Equation 1, leaving only the vehicle transfer cost to be calculated. 
     Although the present disclosure has been practically described in connection with an embodiment thereof with reference to the accompanying drawings, it is to be noted that various changes and modifications become apparent to those skilled in the art. 
     For example, the above-described embodiment may have different configurations, in terms of different component arrangement, different material, different conditions, different shapes, different sizes and the like, other than the ones described above. 
     Further, different embodiments and the components used therein may be partially or as a whole combinable, unless otherwise described. 
     Such changes, modifications, and summarized schemes are to be understood as being within the scope of the present disclosure as defined by appended claims.