Information processing device, information processing method, and program

Abstract

To compare a vehicle having an internal combustion engine with a pure electric vehicle.SOLUTION: An information processing device acquires first travel related data corresponding to prescribed travel performed in the past by a first vehicle having an internal combination engine, acquires second travel related data predicted if a second vehicle being a pure electric automobile performs the prescribed travel, and outputs the first travel related data and the second travel related data in a comparable format, and the first and second travel related data include a prescribed time or travel cost.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] This disclosure relates to a technology for providing information regarding the driving of a vehicle.

Background Art

[0002] A system for comparing gasoline vehicles and electric vehicles is known. For example, Patent Document 1 discloses an in-vehicle device mounted on an electric vehicle, which calculates the driving cost in a gasoline vehicle and outputs it together with the driving cost of the host vehicle.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] An object of this disclosure is to compare a vehicle having an internal combustion engine with a pure electric vehicle.

Means for Solving the Problems

[0005] A first aspect of this disclosure is an information processing apparatus having a control unit that executes: acquiring trip information regarding one or more predetermined trips made by a first vehicle having an internal combustion engine in the past; and acquiring and outputting a result of a simulation when the predetermined trip is driven by a second vehicle that is a pure electric vehicle.

[0006] Moreover, a second aspect of this disclosure is a vehicle having an in-vehicle device that executes: acquiring trip information regarding one or more predetermined trips made by the host vehicle in the past; and acquiring and outputting a result of a simulation when the predetermined trip is driven by a second vehicle that is a pure electric vehicle.

[0007] Furthermore, a third aspect of this disclosure is an information processing method that includes a first step of acquiring trip information relating to one or more predetermined trips previously taken by a first vehicle having an internal combustion engine, and a second step of acquiring and outputting the results of a simulation in which the predetermined trips were driven by a second vehicle, which is a pure electric vehicle.

[0008] Another aspect of this disclosure is a program for causing a computer to execute the above-described information processing method, or a computer-readable storage medium that non-temporarily stores said program. [Effects of the Invention]

[0009] According to this disclosure, it is possible to compare vehicles with internal combustion engines with pure electric vehicles. [Brief explanation of the drawing]

[0010] [Figure 1] A diagram illustrating the vehicle system's overview. [Figure 2] A diagram illustrating the components of vehicle 10. [Figure 3] An example of vehicle data stored in the memory unit. [Figure 4] An example of a simulation model stored in the memory unit. [Figure 5] An example of map data stored in the memory unit. [Figure 6] A diagram illustrating the data transmitted and received between modules. [Figure 7A] The first figure shows the results of the simulation. [Figure 7B] The first figure shows the results of the simulation. [Figure 7C] The first figure shows the results of the simulation. [Figure 7D] The first figure shows the results of the simulation. [Figure 8] An example of an interface screen presented to the user. [Figure 9]Flowchart of the process performed by the control unit. [Figure 10] Flowchart of the process performed by the control unit.

Mode for Carrying Out the Invention

[0011] There is known a device that compares the cost when traveling by electricity and the cost when traveling by gasoline for users of electric vehicles and provides information. By providing such information to users of gasoline vehicles, it is possible to inspire them about electric vehicles. However, in such a device, since only the cost based on the distance is calculated, it is not possible to specifically convey what differences will occur when an electric vehicle travels the same route as a gasoline vehicle has traveled.

[0012] For example, a battery electric vehicle (hereinafter simply referred to as an "electric vehicle" or "BEV") takes time to charge. Instead of having a low running cost, it cannot perform rapid energy replenishment like a gasoline vehicle. That is, the total travel time can be different between a gasoline vehicle and an electric vehicle. When presenting the differences between a gasoline vehicle and an electric vehicle, it is preferable to comprehensively convey these elements in addition to the cost. The information processing device according to the present disclosure performs a comparison considering these elements.

[0013] An information processing device according to an aspect of the present disclosure includes a control unit that executes acquiring trip information regarding one or more predetermined trips made by a first vehicle having an internal combustion engine in the past, and acquiring and outputting the result of a simulation when the predetermined trip is traveled by a second vehicle that is a battery electric vehicle.

[0014] The information processing device may be a device mounted in a vehicle or a server device that provides information via a network. The trip information may be a past trip in the first vehicle, or may be a trip related to the current driving when the first vehicle is in motion. Also, the trip information may include a plurality of trips.

[0015] The information processing device acquires and outputs a simulation result when a predetermined trip consisting of one or more trips is driven by a pure electric vehicle. The simulation may be performed by a virtual vehicle. For example, by simulating the transition of the remaining battery level, the driving cost of the pure electric vehicle can be calculated. Also, when the remaining battery level decreases during the route, by simulating charging, the total time required for the trip can be calculated. The charging simulation may be performed based on data related to charging spots (location, charging fee, output, etc.).

[0016] Also, the information processing device may output, in a comparable format (e.g., graphic), the first driving-related data generated based on the trip information and the second driving-related data generated based on the simulation result. The driving-related data may include, for example, driving cost, required time, CO2 emissions, etc. According to such a configuration, the differences between a vehicle having an internal combustion engine and a pure electric vehicle can be comprehensively conveyed to the vehicle user.

[0017] Hereinafter, specific embodiments of the present disclosure will be described based on the drawings. The hardware configuration, module configuration, functional configuration, etc. described in each embodiment are not intended to limit the disclosed technical scope only to those.

[0018] (First Embodiment) The outline of the vehicle system according to the first embodiment will be described with reference to FIG. 1. The vehicle system according to the present embodiment includes a vehicle 10 having an in-vehicle device 100 and a vehicle platform 200. In this embodiment, vehicle 10 is an automobile having an internal combustion engine. Vehicle 10 can be, for example, a gasoline automobile, a diesel automobile, a hybrid automobile, or a plug-in hybrid automobile. In the description of the embodiment, vehicle 10 will be assumed to be a gasoline automobile.

[0019] The in-vehicle device 100 is a device that provides information to the occupants of a vehicle (for example, a car navigation system). The in-vehicle device 100 is also called a car navigation system, infotainment system, or head unit. The in-vehicle device 100 can provide navigation and entertainment to the occupants of a vehicle. Furthermore, the in-vehicle device 100 has the function of accumulating data related to the driving of the vehicle 10 while the vehicle is in motion, and providing information based on the accumulated data. Specifically, the in-vehicle device 100 simulates and provides various data for when a pure electric vehicle (Battery Electric Vehicle, hereinafter referred to as "electric vehicle") performs the same driving as the vehicle 10. This allows the owner of the vehicle 10 to recognize, for example, the differences in cost and usability when switching from a gasoline car to an electric vehicle.

[0020] The vehicle platform 200 is a platform that includes a computer for controlling the vehicle 10. The vehicle platform 200 includes one or more computers for controlling the vehicle, such as an engine ECU, a body ECU, and an autonomous driving ECU. The vehicle platform 200 may also include one or more sensors for sensing the state of the vehicle.

[0021] Figure 2 is a diagram showing the components of the vehicle system according to this embodiment in more detail.

[0022] First, let me explain the in-vehicle device 100. The in-vehicle device 100 can be configured as a general-purpose computer. That is, the in-vehicle device 100 can be configured as a computer having a processor such as a CPU or GPU, main memory such as RAM or ROM, and auxiliary storage such as an EPROM, hard disk drive, or removable media. The auxiliary storage contains an operating system (OS), various programs, various tables, etc., and by executing the programs stored therein, various functions that meet predetermined purposes, as described later, can be realized. However, some or all of the functions may be realized by hardware circuits such as ASICs or FPGAs.

[0023] The in-vehicle device 100 comprises a control unit 101, a storage unit 102, a communication unit 203, an input / output unit 104, and a location information acquisition unit 105.

[0024] The control unit 101 is a computing device that manages the control performed by the in-vehicle device 100. The control unit 101 can be implemented by a computing device such as a CPU (Central Processing Unit). . The control unit 101 is comprised of three functional modules: a data acquisition unit 1011, a simulation unit 1012, and a notification unit 1013. Each functional module may be implemented by executing a stored program using a CPU.

[0025] The data acquisition unit 1011 periodically acquires vehicle data from the vehicle platform 200 (described later) while the vehicle 10 is in motion and stores it in the storage unit 102 (described later). Vehicle data refers to data related to the movement of the vehicle 10 and includes, for example, vehicle speed, position information, direction of travel, and other data related to the vehicle 10 (for example, sensor data acquired by on-board sensors).

[0026] Figure 3 shows an example of vehicle data acquired by the data acquisition unit 1011. In this embodiment, the vehicle data includes a trip identifier, location information, orientation information, and other sensor data. A trip is a unit of travel from when the vehicle's system power is turned on until the system power is turned off. The data acquisition unit 1011 assigns an identifier corresponding to a new trip each time the vehicle's system power is turned on. The location information is the location information of the vehicle 10 acquired by the location information acquisition unit 105, which will be described later. The direction information is the azimuth angle representing the direction of travel of the vehicle 10.

[0027] The sensor data can be any data relating to the vehicle's operation or the driving environment. For example, the sensor data may be data sensing the vehicle's movement, such as yaw rate, or data relating to driving operations. Furthermore, the sensor data may relate to the driving environment, such as outside temperature, presence or absence of rain, or presence or absence of snow. In addition, the sensor data may include data indicating the use of electrical components such as headlights, and whether the air conditioning is in use. This sensor data can be obtained from the ECU or sensor group of the vehicle platform 200. By referring to accumulated vehicle data, it is possible to obtain data on the vehicle's past driving routes or driving environment.

[0028] The simulation unit 1012 performs a simulation of what would happen if an electric vehicle performed a similar drive to that performed by vehicle 10, based on the accumulated vehicle data, the simulation model described later, and the map data. The specific method will be described later.

[0029] The notification unit 1013 generates and outputs information to present to the user based on the results of the simulation performed by the simulation unit 1012. The simulation results include data such as travel costs and travel time. The notification unit 1013 generates a user interface containing this data and outputs it via the input / output unit 104.

[0030] The memory unit 102 is a means for storing information and is composed of storage media such as RAM, magnetic disks, and flash memory. The storage unit 102 comprises a main memory and an auxiliary storage device. The main memory is the memory where programs executed by the control unit 101 and data used by said control programs are stored. The auxiliary storage device is the device where programs executed by the control unit 101 and data used by said control programs are stored. The auxiliary storage device may store programs executed by the control unit 101 packaged as applications. It may also store an operating system for running these applications. When a program stored in the auxiliary storage device is loaded into the main memory and executed by the control unit 101, the processes described below are performed.

[0031] The memory unit 102 stores the vehicle database 102A, the simulation model 102B, and the map data 102C.

[0032] The vehicle database 102A is a database in which the aforementioned vehicle data is stored. The vehicle database 102A is configured to store vehicle data corresponding to multiple trips.

[0033] Simulation model 102B is a model for simulating the operation of an electric vehicle. Figure 4 is a diagram illustrating the data included in simulation model 102B. As shown in the diagram, simulation model 102B includes a vehicle model and vehicle parameters. The vehicle model is a virtual model of an electric vehicle. The vehicle model represents the characteristics of the virtual vehicle (driving characteristics, weight, output, power consumption rate, etc.). The vehicle model may be defined for each type of virtual vehicle. The vehicle parameters are prerequisites for performing the simulation. Vehicle parameters include, for example, the number of occupants, the battery level at the start of driving (State of Charge, hereinafter "SoC"), and the threshold value for charging. Battery level (charging start conditions), etc., are defined.

[0034] Map data 102C is data about the roads on which the vehicle travels. Figure 5 is a diagram illustrating the data included in map data 102C. As shown in the diagram, map data 102C includes road data and charging spot data. Road data is data that defines the connection relationships between road links. Furthermore, road data may also store elements that affect the power consumption of electric vehicles, such as the elevation of each road segment. Charging spot data refers to data about public charging spots. This data includes information such as the name of the charging spot, location, operating hours, charger capacity, and charging fees.

[0035] The communication unit 103 is a communication interface that connects the in-vehicle device 100 to the bus of the in-vehicle network. The input / output unit 104 is a means for receiving input operations performed by the vehicle occupants and presenting information to the occupants. Specifically, it consists of a touch panel and its control means, and a liquid crystal display and its control means. In this embodiment, the touch panel and liquid crystal display consist of a single touch panel display. The input / output unit 104 may also include a unit for outputting audio (amplifier or speaker), a unit for inputting audio (microphone), etc.

[0036] The location information acquisition unit 105 includes a GPS antenna and a positioning module for determining location information. The GPS antenna is an antenna that receives positioning signals transmitted from positioning satellites (also called GNSS satellites). The positioning module is a module that calculates location information based on the signals received by the GPS antenna. The location information may include altitude.

[0037] The vehicle platform 200 is a platform that includes a computer for controlling the vehicle 10. The vehicle platform 200 includes one or more computers (ECUs 201) for controlling the vehicle, such as an engine ECU, a body ECU, and an autonomous driving ECU. The ECUs 201 can acquire and provide sensor data from on-board sensors (sensor group 202) for use by the data acquisition unit 1011.

[0038] The sensor group 202 includes sensors that acquire sensor data related to driving operations, such as a vehicle speed sensor that acquires vehicle speed, a steering sensor that acquires steering angle, and a throttle sensor that acquires throttle opening. Furthermore, the sensor group 202 may include sensors that sense the driving environment of the vehicle 10. Examples of such sensors include an outside temperature sensor, a rainfall sensor, and a snowfall sensor.

[0039] The network bus is a communication bus that constitutes the in-vehicle network. Although this example illustrates one bus, vehicle 10 may have two or more communication buses. Multiple communication buses may be connected to each other by a gateway that aggregates multiple communication buses.

[0040] Next, we will explain the details of the processing performed by the in-vehicle device 100. Figure 6 is a diagram illustrating the data flow between the components (modules) of the in-vehicle device 100. First, while the vehicle 10 is in motion, the data acquisition unit 1011 periodically acquires vehicle data from the vehicle platform 200. Vehicle data can be acquired, for example, from the ECU 201 or on-board sensors. The acquired vehicle data is stored in the vehicle database 102A in association with a trip identifier.

[0041] Next, after the vehicle 10 has finished its run, at a predetermined timing, the simulation unit 1012 determines the trip to be processed and executes a simulation of what would happen if the electric vehicle were to drive that trip. There may be one or more trips to be processed. The trips to be processed may be selected by the user of the vehicle 10 or they may be selected automatically. In the former case, the user may be presented with a list of trips to select from. The trip in question may be the most recent trip, or it may be multiple trips that occurred within a specified period (for example, the past month).

[0042] The simulation unit 1012 acquires vehicle data corresponding to the target trip (i.e., multiple records documenting the driving of vehicle 10) and performs a simulation of what would happen if the same driving were performed by an electric vehicle. The vehicle data includes data that meticulously represents the position information, direction of travel, speed, etc., of vehicle 10. By using the simulation model 102B to have a virtual vehicle (a virtual electric vehicle) perform the same driving, it is possible to simulate, for example, how the remaining charge of the drive battery changes. The simulation conditions (for example, the SoC at departure, the total weight of the vehicle, etc.) may be defined in the vehicle parameters included in the simulation model 102B.

[0043] Furthermore, if the vehicle data includes information about the driving environment, such as outside temperature, such information may be used in conjunction with the simulation. For example, if the outside temperature is low, the battery performance may be adjusted to be lower before performing the simulation. Alternatively, if the outside temperature is within a specified range, the remaining battery charge may be simulated assuming the use of the air conditioner or heater. Furthermore, the simulation may be performed in conjunction with map data 102C. For example, if map data 102C includes elevation data, the road gradient along the route may be calculated and used.

[0044] By performing such simulations, it is possible to calculate the interrelationships between elapsed time, distance traveled, and battery level for the target trip. Figure 7A shows the relationship between elapsed time and distance traveled, and the relationship between elapsed time and battery level. Figure 7B is a table showing the data obtained from the simulation (result data). The result data can represent, for example, the relationship between time and distance traveled, or the relationship between time and battery level. Based on the result data, the running cost of a virtual electric vehicle can be calculated.

[0045] Furthermore, the simulation unit 1012 can perform simulations related to charging as needed. For example, if the remaining charge of the drive battery falls below a predetermined value while the virtual vehicle is running, a charging simulation may be performed based on a predetermined rule (charging rule). For example, the simulation unit 1012 uses the charging spot data included in the map data 102C. Based on this, a charging station for the virtual vehicle is determined, and the simulation continues assuming that charging has taken place at that station.

[0046] Examples of charging rules include: "If the SoC's charge level falls below 20%, fast charge it at the nearest charging station until it reaches over 80%," or "If the SoC's charge level falls below 20%, fast charge it for 30 minutes at the nearest charging station." Alternatively, the charging rule could be: "If there is charging equipment at the destination, charge as much as possible before the next departure time."

[0047] The driving simulation continues even while charging. For example, if charging is performed for 30 minutes along the route, the arrival time at the destination will be delayed by 30 minutes. The simulation unit 1012 may also simulate the charging state. For example, if the charging speed changes depending on the battery state (SoC or internal temperature), this may also be simulated. For this reason, the state of the drive battery itself (for example, the internal temperature of the battery cells) may also be simulated. This allows us to obtain simulation results that take into account charging along the route, as shown in Figure 7C. The illustrated example shows the changes in SoC and driving distance when charging is performed along the route.

[0048] Figure 7D shows an example of result data when charging is performed along the route. As illustrated, the result data may include fields that store data related to charging. In the illustrated example, the status field is a field that identifies whether the virtual vehicle is in a driving state or a charging state.

[0049] The simulation results are transmitted to the notification unit 1013. The simulation results may be a set of records as shown in Figure 7B or Figure 7D. The simulation results may also include data on driving costs. Driving costs can be calculated based on the amount of electricity consumed, the amount of gasoline consumed, the amount of electricity charged, etc. The costs associated with refueling and charging may be determined based on pre-stored data or obtained via a network. For example, data could be obtained from a device that provides real-time gasoline and charging prices and used to calculate the running cost.

[0050] The notification unit 1013 visualizes and outputs the differences between driving the same trip using a gasoline vehicle and an electric vehicle, respectively, based on the simulation results obtained from the simulation unit 1012. Figure 8 shows an example of information output by the notification unit 1013. In this example, the notification unit 1013 generates and outputs an image that shows the trip duration and driving cost in a format that allows for comparison between gasoline vehicles and electric vehicles. The notification unit 1013 may also output information other than the required time and driving cost. For example, it may calculate and output CO2 emissions. It may also output the time and number of times the virtual vehicle was charged. The notification unit 1013 may output the generated image via the input / output unit 104. Furthermore, if the in-vehicle device 100 has a wireless communication module, the generated image may be transmitted to an external device via wireless communication.

[0051] Next, the processing flow executed by each module of the control unit 101 will be explained using a flowchart. The flowchart shown in Figure 9 is executed periodically by the on-board device 100 while the vehicle 10 is in motion.

[0052] In step S11, the data acquisition unit 1011 acquires sensor data via the vehicle platform 200. In step S12, the data acquisition unit 1011 generates vehicle data based on the acquired sensor data. The generated vehicle data is stored in the vehicle database 102A. Next, in step S13, the simulation unit 1012 determines whether the vehicle 10's running (trip) has finished. For example, if an operation is performed to shut down the vehicle 10's running system, this step results in a positive determination. If the trip has not finished, the process returns to step S11 and the same process is repeated.

[0053] In step S14, the simulation unit 1012 decides whether or not to perform a simulation using an electric vehicle. For example, a rule may be set that the simulation will be performed if certain conditions are met, and if these conditions are met, the determination in this step is affirmative. Examples of predetermined conditions include "the trip ends" or "a predetermined period of time (one day, one week, one month, etc.) has elapsed." Alternatively, the in-vehicle device 100 may propose to the user that the simulation be performed. If the user agrees to this, the determination in this step is affirmative. If the conditions are met in this step, the process proceeds to step S15. If the conditions are not met, the process ends.

[0054] Next, in step S15, the simulation unit 1012 determines the trip to be simulated. The trip to be simulated may be selected by the user of the vehicle 10, or, if a predetermined rule is set, the system may determine it according to that rule. For example, if the simulation targets multiple trips that occurred in a predetermined period in the past (e.g., one month), the trips that occurred during that period will be selected. If the user is allowed to select the trip, a list of trips may be generated based on vehicle data.

[0055] In step S16, the simulation unit 1012 performs a simulation of what would happen if the determined trip was driven by an electric vehicle. The simulation is performed using a virtual vehicle defined in the simulation model 102B (vehicle model). In this step, vehicle data corresponding to the target trip is extracted from the vehicle database 102A, and based on the extracted vehicle data, the virtual vehicle is made to perform the same driving as the vehicle 10. That is, the virtual vehicle is driven at the same speed and acceleration as the vehicle 10. This makes it possible to simulate the change in the remaining charge of the drive battery of the virtual vehicle. The simulation results in a set of virtual vehicle statuses, as shown in Figure 7B or Figure 7D.

[0056] Furthermore, when performing simulations, information about the driving environment may be used. For example, if the elevation of each point is defined in map data 102C, the gradient of each road segment may be calculated. This makes it possible to accurately calculate the amount of electricity required for driving and the amount of regenerative power. Furthermore, when conducting simulations, power consumption unrelated to driving may also be considered. For example, based on the time of day and outside temperature, it may be determined whether headlights, car air conditioning, heaters, etc., are used, and the remaining battery level may be simulated taking into account the power consumption of these devices.

[0057] Figure 10 is a detailed flowchart of the process performed by the simulation unit 1012 in step S16. The illustrated process is executed periodically during the simulation. First, in step S161, a driving simulation is performed for a predetermined unit section, and Update the status of the vehicle. The predetermined unit section may be each road segment. In step S162, it is determined whether or not a charging trigger has occurred. For example, if a rule is set that "charge when the SoC falls below 20%", and the SoC falls below 20%, then this step results in a positive determination. If this step results in a positive determination, the process proceeds to step S163, where a charging simulation is performed. Specifically, based on the charging spot data, the nearest available charging spot is searched for, and the battery level of the virtual vehicle is updated as if charging had been performed at that charging spot. Once charging is complete, the process returns to step S161, and the driving simulation continues. If no charging trigger has occurred, the process proceeds to step S164.

[0058] In step S164, it is determined whether the virtual vehicle has arrived at its destination. If the virtual vehicle has not arrived at its destination, the process returns to step S161. If the virtual vehicle has arrived at its destination, the process proceeds to step S165. If charging facilities are available at the destination (for example, your home), you may have the virtual vehicle charge during this step.

[0059] In step S165, it is determined whether there are any trips remaining to be processed. If there are any trips remaining to be processed, the next trip is selected, and the process returns to step S161. If there are no trips remaining to be processed, the process proceeds to step S166.

[0060] In step S166, the running cost is calculated based on the simulation results. The running cost may be calculated based on the amount of gasoline (or electricity) consumed, or, if charging occurred during the simulation, based on the amount of electricity charged. If the fees differ for each charging spot, the fee for charging may be calculated using the unit price defined in the charging spot data. Furthermore, when charging at home, the fee for charging may be determined based on the electricity contract.

[0061] Returning to Figure 9, we continue the explanation. In step S17, the notification unit 1013 generates and outputs information (user interface screen) to present to the user based on the data obtained from the simulation. This generates and outputs a screen like the one shown in Figure 8. This screen includes at least an image that shows the difference in travel costs and the difference in travel time in a comparable format.

[0062] As described above, the in-vehicle device 100 according to the first embodiment performs a simulation of what would happen if an electric vehicle performed the same driving based on the driving history of the vehicle 10, and outputs the results. This allows the user of the vehicle 10 to know how much difference there is in driving costs and required time between a gasoline vehicle and an electric vehicle. Furthermore, since such comparisons can be made for any given trip, the user of vehicle 10 can see how the differences in monetary and time costs manifest themselves for each trip.

[0063] (Modification of the first embodiment) In the first embodiment, no special consideration is given to refueling gasoline vehicles. However, if the location and time of refueling can be recorded, stops at gas stations can be omitted in the simulation of electric vehicles.

[0064] Furthermore, in the first embodiment, the simulation was performed using a specific trip that was designated or selected, but the system automatically performs comparisons with multiple past trips and then adjusts the results accordingly. You may also rank the vehicles. This will allow users to recognize, for example, in what situations the differences between gasoline cars and electric cars become more pronounced. You may also output past comparison results in a time series. This will allow users to recognize how the difference in running costs changes depending on the season.

[0065] Furthermore, in the first embodiment, the simulation was performed after the vehicle 10 had finished its run, but the simulation may be performed in real time. For example, the simulation may be designed to calculate and display in real time the differences between a gasoline vehicle and an electric vehicle when they depart from the same location at the same time.

[0066] Furthermore, in the first embodiment, the in-vehicle device 100 provided information, but the in-vehicle device 100 may transmit vehicle data to a server device, and the server device may perform simulations and provide information. In this case, the server device may transmit the simulation results to a terminal held by the user of the vehicle 10.

[0067] (modified version) The embodiments described above are merely examples, and this disclosure may be modified as appropriate without departing from its essence. For example, the processes and means described in this disclosure can be freely combined and implemented, as long as no technical inconsistencies arise.

[0068] Furthermore, a process described as being performed by a single device may be divided and executed by multiple devices. Conversely, a process described as being performed by different devices may be executed by a single device. In a computer system, the hardware configuration (server configuration) by which each function is implemented can be flexibly changed.

[0069] The present disclosure can also be realized by supplying a computer program implementing the functions described in the embodiments above to a computer, and having one or more processors in the computer read and execute the program. Such a computer program may be provided to the computer by a non-temporary computer-readable storage medium that can be connected to the computer's system bus, or it may be provided to the computer via a network. Non-temporary computer-readable storage mediums include, for example, any type of disk such as magnetic disks (floppy disks, hard disk drives (HDDs), etc.), optical disks (CD-ROMs, DVDs, Blu-ray discs, etc.), read-only memory (ROM), random access memory (RAM), EPROM, EEPROM, magnetic cards, flash memory, optical cards, and any type of medium suitable for storing electronic instructions. [Explanation of Symbols]

[0070] 100...In-vehicle equipment 101... Control Unit 102...Storage section 103... Communications Department 104...Input / output section 200... Vehicle platform 201···ECU 202... Sensor group

Claims

1. To acquire first driving-related data corresponding to a predetermined mileage previously performed by a first vehicle having an internal combustion engine, To obtain second driving-related data that is predicted when the aforementioned predetermined driving is performed by a second vehicle, which is a pure electric vehicle, Outputting the first driving-related data and the second driving-related data in a comparable format, It has a control unit that performs the following: The aforementioned first and second driving-related data include the time required. Information processing device.

2. The control unit generates the second driving-related data by performing a simulation of the second vehicle performing the predetermined driving course. The information processing apparatus according to claim 1.

3. The control unit simulates the driving of the second vehicle using a virtual vehicle having predetermined parameters. The information processing apparatus according to claim 2.

4. The predetermined parameters include at least one of the following: the type of virtual vehicle, the initial battery level, and the charging start conditions. The information processing apparatus according to claim 3.

5. The control unit, when the remaining battery level of the virtual vehicle falls below a predetermined threshold during the simulation, further performs a simulation related to charging. The information processing apparatus according to claim 3.

6. The control unit further acquires charging spot information, which is information about public charging spots, and performs a simulation related to charging based on the charging spot information. The information processing apparatus according to claim 5.

7. The aforementioned charging spot information includes information on the geographical location, charging fee, and charging speed for each charging spot. The information processing apparatus according to claim 6.

8. The aforementioned predetermined mileage is a mileage included in the past mileage history of the first vehicle. The information processing apparatus according to any one of claims 1 to 7.

9. The information processing device is A first step is to acquire first driving-related data corresponding to a predetermined mileage previously performed by a first vehicle having an internal combustion engine, A second step is to obtain second driving-related data that is predicted when the predetermined driving is performed by a second vehicle, which is a pure electric vehicle. A third step involves outputting the first driving-related data and the second driving-related data in a comparable format, Execute, The aforementioned first and second driving-related data include the time required. Information processing methods.

10. In the second step, the second driving-related data is generated by performing a simulation of the second vehicle performing the predetermined driving maneuver. The information processing method according to claim 9.

11. In the second step, the driving of the second vehicle is simulated using a virtual vehicle having predetermined parameters. The information processing method according to claim 10.

12. The predetermined parameters include at least one of the following: the type of virtual vehicle, the initial battery level, and the charging start conditions. The information processing method according to claim 11.

13. In the second step, if the battery level of the virtual vehicle falls below a predetermined threshold during the simulation, a further simulation related to charging is performed. The information processing method according to claim 11.

14. In the second step, charging spot information, which is information about public charging spots, is further acquired, and a simulation of charging is performed based on the charging spot information. The information processing method according to claim 13.

15. A program for causing a computer to execute the information processing method described in any one of claims 9 to 14.

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