Information processing system, information processing apparatus, information processing method, and recording medium

Abstract

The present disclosure relates to an information processing system, an information processing apparatus, an information processing method, and a recording medium. A software update system includes a vehicle data acquisition unit configured to acquire data on a state of a vehicle including data of a predetermined performance of the vehicle; an effect prediction unit configured to predict, based on the data acquired by the vehicle data acquisition unit, an effect on the predetermined performance when update data of software used in the vehicle for improving the predetermined performance is applied to the vehicle; and a transmission unit configured to transmit the update data to the vehicle when the effect predicted by the effect prediction unit satisfies a predetermined criterion, and to suppress transmission of the update data to the vehicle when the effect predicted by the effect prediction unit does not satisfy the predetermined criterion.

Description

Technical Field

[0001] This disclosure relates to information processing systems, etc. Background Technology

[0002] The technology of sending update data of software used in a vehicle (e.g., update data such as programs or parameters used in programs) from an external device to the vehicle and thus updating the vehicle's software is known (see Japanese Unexamined Patent Application Publication No. 2003-34200 (JP 2003-34200A)).

[0003] In JP 2003-34200A, an evaluation simulator is used to evaluate the operation of the vehicle before and after the software update, and the software is updated after it is determined that the vehicle's functions have been corrected in the desired direction through the software update. Summary of the Invention

[0004] However, the vehicles applying the updated data may differ in characteristics and operating conditions. Therefore, the actual effect of a software update may be relatively small depending on the vehicle's characteristics and operating conditions. Consequently, the software may be updated unnecessarily when the expected results are not achieved.

[0005] Therefore, this disclosure provides a technique for more appropriately updating software used in vehicles.

[0006] According to embodiments of this disclosure, an information processing system is provided, comprising: an acquisition unit configured to acquire vehicle data, including data on predetermined vehicle performance; a prediction unit configured to predict, based on the data acquired by the acquisition unit, the effect on the predetermined performance when updated data of software used in the vehicle for improving the predetermined performance is applied to the vehicle; and a delivery unit configured to deliver the updated data to the vehicle when the effect predicted by the prediction unit meets a predetermined benchmark, and to suppress the delivery of the updated data to the vehicle when the effect predicted by the prediction unit does not meet the predetermined benchmark.

[0007] According to another embodiment of this disclosure, an information processing apparatus is provided, comprising: an acquisition unit configured to acquire data of the vehicle, including data on the predetermined performance of the vehicle; a prediction unit configured to predict, based on the data acquired by the acquisition unit, the effect on the predetermined performance obtained when updated data of software used in the vehicle for improving the predetermined performance is applied to the vehicle; and a transmission unit configured to transmit the updated data to the vehicle when the effect predicted by the prediction unit meets the predetermined benchmark, and to suppress the transmission of the updated data to the vehicle when the effect predicted by the prediction unit does not meet the predetermined benchmark.

[0008] According to another embodiment of this disclosure, an information processing method executed by an information processing apparatus is provided, the information processing method comprising: an acquisition step: acquiring data of the vehicle, including data on the predetermined performance of the vehicle; a prediction step: based on the data acquired in the acquisition step, predicting the effect on the predetermined performance when updated data of software used in the vehicle for improving the predetermined performance is applied to the vehicle; and a transmission step: transmitting the updated data to the vehicle when the effect predicted in the prediction step meets the predetermined benchmark, and suppressing the transmission of the updated data to the vehicle when the effect predicted in the prediction step does not meet the predetermined benchmark.

[0009] According to another embodiment of this disclosure, a storage medium for a stored program is provided, the program causing an information processing device to perform: an acquisition step: acquiring data of the vehicle, including data on a predetermined performance of the vehicle; a prediction step: based on the data acquired in the acquisition step, predicting the effect on the predetermined performance when updated data of software used in the vehicle for improving the predetermined performance is applied to the vehicle; and a transmission step: transmitting the updated data to the vehicle when the effect predicted in the prediction step meets a predetermined benchmark, and suppressing the transmission of the updated data to the vehicle when the effect predicted in the prediction step does not meet the predetermined benchmark.

[0010] According to this embodiment, the software used in the vehicle can be updated more appropriately. Attached Figure Description

[0011] The features, advantages, and technical and industrial significance of exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, wherein like reference numerals denote like elements, and wherein:

[0012] Figure 1 This is a schematic diagram illustrating an example of a software update system;

[0013] Figure 2 This is a diagram illustrating an example of the vehicle's hardware configuration;

[0014] Figure 3 This is a diagram illustrating an example of the hardware configuration of a transmission server;

[0015] Figure 4 This is a functional block diagram illustrating an example of the functional configuration of a software update system;

[0016] Figure 5 This is an example diagram illustrating an updated shift characteristic diagram of a vehicle's transmission;

[0017] Figure 6 This is an example diagram illustrating an update of the switching characteristics diagram of the prime mover in a vehicle;

[0018] Figure 7 This is a diagram illustrating an example of the virtual simulation results of the aging variation of the vehicle state during gear shifts before and after the control logic of the transmission shift (upshift) is updated.

[0019] Figure 8 This is another example of a virtual simulation showing the changes in the vehicle's state over time during gear shifts before and after the transmission's shift (upshift) control logic is updated.

[0020] Figure 9 This is a flowchart illustrating an example of a routine performed by a delivery server for software updates in a vehicle.

[0021] Figure 10 This is a flowchart illustrating an example of a routine executed by an analysis server for software updates in a vehicle; and

[0022] Figure 11 This is a flowchart illustrating an example of a routine for software updates in a vehicle, executed by the central ECU. Detailed Implementation

[0023] In the following description, embodiments will be illustrated with reference to the accompanying drawings.

[0024] Overview of the software update system

[0025] The following will refer to Figure 1 An overview of the software update system 1 according to this embodiment is described.

[0026] Figure 1 This is a schematic diagram illustrating an example of software update system 1.

[0027] like Figure 1As shown, the software update system 1 (an example of an information processing system) includes a vehicle 10, a transmission server 20, an analysis server 30, and a user terminal 40.

[0028] The software update system 1 sends update data of the software used in vehicle 10 to vehicle 10 and updates the software of vehicle 10.

[0029] Examples of software for vehicle 10 include programs executed by a computer (on-board computer) installed in vehicle 10 (such as gateway electronic control unit (ECU) 12, ECU 13, or central ECU 19, which will be described later). Examples of software for vehicle 10 include various types of data, such as parameters used in the processing of programs executed by the on-board computer.

[0030] Vehicle 10 is the object whose software will be updated and travels using power transmitted from a predetermined prime mover, such as an engine or electric motor, to the drive wheels via a transmission system, which includes a gearbox, a differential, and a drive shaft.

[0031] Vehicle 10 is equipped with a communication device 11, which will be described later, and is communicatively connected to external devices such as transmission server 20 or analysis server 30 via a predetermined communication line. Therefore, vehicle 10 is able to send information signals to transmission server 20 or analysis server 30, or receive control signals or information signals (e.g., software update data) from transmission server 20 or analysis server 30.

[0032] For example, the planned communication lines include mobile communication networks such as base station terminals, satellite communication networks using communication satellites, and wide area networks (WANs) such as the Internet. For example, the planned communication lines may include local area networks (LANs) in which facilities housing transmission server 20 or analysis server 30 are installed. For example, the planned communication lines may include short-range communication lines based on radio communication standards such as WiFi and Bluetooth (registered trademark). In the following description, the same applies to communication lines used for communication between transmission server 20 and analysis server 30, and communication lines used for communication between transmission server 20 and user terminal 40, etc.

[0033] The number of vehicles 10 included in the software update system 1 can be one or more. In the latter case, the two or more vehicles 10 included in the software update system 1 can be of the same model, or can include two or more models of vehicles 10.

[0034] The transmission server 20 will transmit various types of data used in the vehicle 10 to the vehicle 10. Specifically, the transmission server 20 will transmit software update data to the vehicle 10.

[0035] For example, the transmission server 20 is a locally deployed server or cloud server located in a monitoring center or similar facility that comprehensively monitors the status of multiple vehicles 10. Alternatively, the transmission server 20 could be an edge server located in the area where the vehicles 10 primarily operate (e.g., the area where the vehicles 10 are legally registered). In this case, multiple transmission servers 20 could be provided for all vehicles 10 included in the software update system 1. The same applies to the analysis server 30 in the following description.

[0036] The transmission server 20 is communicatively connected to the vehicle 10 via the predetermined communication line described above. Therefore, the transmission server 20 is able to receive various information signals from the vehicle 10, or send various information signals (e.g., software update data), control signals (e.g., software update commands), etc. to the vehicle 10.

[0037] For example, analysis server 30 acquires various types of data (hereinafter referred to as "vehicle data") indicating the state of vehicle 10 from vehicle 10 or external devices associated with vehicle 10, and performs analyses associated with vehicle 10. Specifically, analysis server 30 analyzes the impact on predetermined performance resulting from updating the software of vehicle 10. The vehicle data to be acquired includes data on predetermined performance predicted to be improved by the software update. For example, external devices associated with vehicle 10 include server devices in a factory that store manufacturing data of vehicle 10. Examples of manufacturing data for vehicle 10 include data on manufacturing irregularities of vehicle 10, such as data on manufacturing irregularities of individual components of vehicle 10 or data on assembly irregularities of individual components of vehicle 10.

[0038] The analysis server 30 is communicatively connected to the vehicle 10 via the predetermined communication line described above. Therefore, the analysis server 30 is able to receive various information signals (e.g., vehicle data) from the vehicle 10, or send various information signals or control signals to the vehicle 10.

[0039] The analysis server 30 is communicatively connected to the transmission server 20 or the user terminal 40 via a predetermined communication line. Therefore, the analysis server 30 is able to send various information signals or control signals to the transmission server 20 or the user terminal 40, or receive various information signals or control signals from the transmission server 20 or the user terminal 40.

[0040] The functions of the transmission server 20 and the analysis server 30 can be implemented as a whole by a single server such as the transmission server 20 (an example of an information processing device), or by three or more servers separately.

[0041] User terminal 40 is a terminal device used (carried) by a user of vehicle 10. For example, the user of vehicle 10 is the owner of vehicle 10 or a family member of the owner of vehicle 10. User terminal 40 is a mobile (portable) terminal device, such as a smartphone, tablet, or laptop computer (PC). For example, user terminal 40 can be a fixed terminal device such as a desktop PC.

[0042] User terminal 40 is communicatively connected to transmission server 20 via the predetermined communication line described above. Therefore, user terminal 40 is able to receive control signals or information signals sent from transmission server 20, and allows the user of vehicle 10 to understand the information included in the signals using a display, speaker, etc. User terminal 40 is also able to send control signals or information signals corresponding to the input details to transmission server 20 in response to user input, and to send user requests corresponding to the user's input details to transmission server 20.

[0043] Hardware configuration of the software update system

[0044] Apart from Figure 1 In addition, the following will refer to Figure 2 and Figure 3 Describe the hardware configuration of software update system 1.

[0045] Vehicle hardware configuration

[0046] Figure 2 This is a diagram illustrating an example of the hardware configuration of vehicle 10.

[0047] like Figure 2 As shown, vehicle 10 includes a communication device 11, a gateway ECU 12, an ECU 13, a sensor 15, an input device 17, a display device 18, and a central ECU 19.

[0048] The communication device 11 communicates with the outside of the vehicle 10 via a predetermined communication line. The communication device 11 is, for example, a mobile communication module connected to a mobile communication network with a base station as its terminal and capable of communicating with the outside world; specifically, it may be a data communication module (DCM). The communication device 11 is communicatively connected to the gateway ECU 12, ECU 13, central ECU 19, etc., via the internal communication lines of the vehicle 10. The internal communication lines of the vehicle 10 are, for example, one-to-one communication lines or in-vehicle networks. In-vehicle networks are, for example, Controller Area Network (CAN), Local Interconnect Network (LIN), FlexRay, or in-vehicle Ethernet. For example, the communication device 11 can send predetermined signals to the outside in response to commands (requests) from the gateway ECU 12. Signals received by the communication device 11 from the outside are input to the gateway ECU 12.

[0049] The gateway ECU 12 serves as a gateway between the external communication lines of the vehicle 10 and the internal communication lines (e.g., in-vehicle network) of the vehicle 10.

[0050] The functions of the gateway ECU 12 can be implemented through any hardware, any combination of hardware and software, etc. For example, the gateway ECU 12 has the same hardware configuration as the central ECU 19, which will be described later, and can implement its various functions by loading a program installed in an auxiliary storage device into a memory device and having the central processing unit (CPU) execute the loaded program. In the following description, the ECU 13 can also be implemented in this way.

[0051] For example, the gateway ECU 12 uses known methods to verify whether the signals received by the communication device 11 from the outside are signals sent from an authorized transmission source and whether they are untampered signals. An authorized transmission source refers to a transmission source that has been pre-registered as a transmission source (e.g., transmission server 20 or analysis server 30) or a transmission source that has been pre-authenticated through bidirectional communication. The gateway ECU 12 only transmits data of signals that have been successfully authenticated from the signals received by the communication device 11 to a predetermined on-board unit (e.g., ECU 13 or central ECU 19) via the vehicle 10's internal communication lines.

[0052] For example, in response to requests from various devices in the vehicle 10, the gateway ECU 12 generates a signal including details such as predetermined information or commands (requests), and sends the generated signal to a predetermined destination (e.g., transmission server 20 or analysis server 30) via the communication device 11.

[0053] One or more ECUs 13 are installed in the vehicle 10. The ECUs 13 perform control of various functions of the vehicle 10. For example, the multiple ECUs 13 include an ECU 13 that controls the engine, which is the power source of the vehicle 10, an ECU 13 that controls the electric motor (electric generator: MG), which is the power source of the vehicle 10, and an ECU 13 that controls the gear position of the transmission of the vehicle 10.

[0054] One or more sensors 15 are installed in the vehicle 10. The sensors 15 output measurement data associated with the state of the vehicle 10. The outputs (measurement data) of the sensors 15 are input to the central ECU 19 via the internal communication lines of the vehicle 10. For example, the multiple sensors 15 include sensors 15 that measure the wheel speed of the wheels of the vehicle 10 (wheel speed sensors). For example, the multiple sensors 15 include sensors 15 that measure the longitudinal acceleration, lateral acceleration, or vertical acceleration of the vehicle 10 (accelerometer sensors). For example, the multiple sensors 15 include sensors 15 that measure the temperature of predetermined parts of the vehicle 10 (temperature sensors). Examples of temperature sensors include temperature sensors that measure the temperature of the drive battery or auxiliary-machine battery installed in the vehicle 10, coolant temperature sensors that measure the temperature of the coolant in various devices, and oil temperature sensors that measure the oil temperature of the lubricant in various devices. For example, the multiple sensors 15 include sensors 15 that measure the position of the vehicle 10 (Global Navigation Satellite System (GNSS) sensor).

[0055] Input device 17 is disposed within the passenger compartment of vehicle 10 and receives various inputs from occupants. For example, input device 17 includes an operational input device that receives operational input from occupants, such as buttons, toggle switches, levers, touch panels, or touchpads. For example, input device 17 includes a voice input device, such as a microphone, that receives voice input from occupants of vehicle 10. For example, input device 17 includes a gesture input device, such as a camera capable of capturing images of occupants in the passenger compartment of vehicle 10, that receives gesture input from occupants of vehicle 10. Input signals indicating details of the input received by input device 17 are input to central ECU 19 via internal communication lines of vehicle 10.

[0056] Display device 18 is positioned so that it can be seen from the driver's seat inside the vehicle 10, and displays various information screens. Display device 18 is, for example, a liquid crystal display or an organic electroluminescent (EL) display. Display device 18 is communicatively connected to central ECU 19 via internal communication lines of vehicle 10, and central ECU 19 can output control signals to display device 18 to display predetermined information screens.

[0057] For example, the central ECU 19 is the host control unit for various ECUs, including the gateway ECU 12 and the ECU 13 installed in the vehicle 10, and integrates the operation of various ECUs or serves as the registration destination for various types of data used in various ECUs.

[0058] The functions of the central ECU 19 are achieved through any hardware, or any combination of hardware and software. For example, ... Figure 2As shown, the central ECU 19 includes an auxiliary storage device 19A, a memory device 19B, a CPU 19C, and an interface device 19D connected via a bus B1.

[0059] Auxiliary storage device 19A is a non-volatile storage device that stores the program installed therein, as well as necessary files, data, etc. Auxiliary storage device 19A is, for example, flash memory.

[0060] Memory device 19B loads a program into auxiliary storage device 19A so that CPU 19C can read the program, for example, when a program start instruction is issued. For example, memory device 19B is static random access memory (SRAM).

[0061] For example, CPU 19C executes the program loaded into memory device 19B and implements various functions of central ECU 19 according to the program's commands.

[0062] For example, interface device 19D serves as an interface for connecting to the internal communication lines of vehicle 10. Interface device 19D may include multiple different types of interface devices to correspond to the type of communication lines to which they are connected.

[0063] For example, the programs used to implement the various functions of the central ECU 19 are provided by a portable recording medium 19E. In this case, the interface device 19D serves as an interface for reading data from or writing data to the recording medium 19E. For example, the recording medium 19E is a dedicated tool that connects to an external connector such as a data link coupler (DLC) via a detachable cable. For example, the recording medium 19E can be an SD memory card or a Universal Serial Bus (USB) memory. The program can be downloaded from another computer outside the vehicle 10 (e.g., a transfer server 20) via a predetermined communication line and installed in the auxiliary storage device 19A.

[0064] Hardware configuration of the transmission server

[0065] Figure 3 This is a diagram illustrating an example of the hardware configuration of the transmission server 20.

[0066] The functionality of the transmission server 20 can be implemented using any hardware, or any combination of hardware and software. For example, ... Figure 3 As shown, the transmission server 20 includes an external interface 21, an auxiliary storage device 22, a memory device 23, a CPU 24, a communication interface 26, an input device 27, and a display device 28 connected via a bus B2.

[0067] The analysis server 30 and user terminal 40 may have the same hardware configuration as the transmission server 20. In the following description, the hardware configuration of the analysis server 30 and user terminal 40 will not be illustrated or described.

[0068] External interface 21 serves as an interface for reading data from or writing data to recording medium 21A. Recording medium 21A may be, for example, a floppy disk, optical disc (CD), digital versatile optical disc (DVD), Blu-ray disc (BD), SD memory card, or universal serial bus (USB) memory. Therefore, the transfer server 20 can read various types of data used in the processing and store the read data in auxiliary storage device 22, or use recording medium 21A to install programs for implementing various functions.

[0069] The transmission server 20 can obtain various types of data or programs from external devices via the communication interface 26.

[0070] Auxiliary storage device 22 stores various installed programs and various files, data, etc. required for processing. Auxiliary storage device 22 includes, for example, hard disk drives (HDDs), solid-state drives (SSDs), or flash memory.

[0071] When a command to start the program is issued, memory device 23 reads the program from auxiliary storage device 22 and stores the read program. Memory device 23 may include, for example, dynamic random access memory (DRAM) or static random access memory (SRAM).

[0072] The CPU 24 executes the program loaded from the auxiliary storage device 22 into the memory device 23, and implements various functions of the transfer server 20 according to the program.

[0073] The high-speed computing device 25 works in conjunction with the CPU 24 and performs computational processing at a relatively high speed. The high-speed computing device 25 includes, for example, a graphics processing unit (GPU), an application-specific integrated circuit (ASIC), or a field-programmable gate array (FPGA).

[0074] Depending on the required processing speed, the high-speed computing device 25 can be omitted.

[0075] Communication interface 26 serves as an interface for communicating with external devices. Therefore, the transmission server 20 can communicate with external devices such as vehicle 10, analysis server 30, or user terminal 40 via communication interface 26. Communication interface 26 may include various types of communication interfaces to correspond to the communication modes to which these devices are connected.

[0076] Input device 27 receives various inputs from the user.

[0077] Input device 27 includes, for example, an operation input device that receives mechanical operation input from a user. Operation input devices include, for example, buttons, toggle switches, joysticks, mice, and keyboards. Operation input devices also include, for example, a touch panel mounted in display device 28 or a touchpad mounted separately from display device 28.

[0078] Input device 27 includes, for example, a voice input device capable of receiving voice input from a user. The voice input device includes, for example, a microphone capable of collecting voice from a user.

[0079] Input device 27 includes, for example, a gesture input device capable of receiving gesture input from a user. The gesture input device includes, for example, a camera capable of capturing images of gestures from the user.

[0080] Input device 27 includes, for example, a biometric input device capable of receiving biometric input from a user. The biometric input device includes, for example, a camera capable of acquiring image data, including information about the user's fingerprint or iris.

[0081] Display device 28 displays information screens or operation screens to the user. Display device 28 includes, for example, a liquid crystal display or an organic EL display.

[0082] Software update system function configuration

[0083] Apart from Figures 1 to 3 In addition, the following will refer to Figure 4 Describe the functional configuration of software update system 1.

[0084] Figure 4 This is a functional block diagram illustrating an example of the functional configuration of software update system 1.

[0085] Vehicle Functional Configuration

[0086] like Figure 4 As shown, the gateway ECU 12 includes a communication unit 121 and a storage unit 122 as functional units. The function of the communication unit 121 can be implemented, for example, by loading a program installed in the auxiliary storage device of the gateway ECU 12 into a memory device and having the CPU execute the program. The function of the storage unit 122 can be implemented, for example, by using a storage area defined in the auxiliary storage device or the like of the gateway ECU 12.

[0087] The communication unit 121 controls the communication device 11 so that signals received from outside the vehicle 10 are input to the gateway ECU 12 or are sent to outside the vehicle 10.

[0088] Various types of data used in the gateway ECU 12 are stored in the storage unit 122. For example, data of various programs installed in the gateway ECU 12 (auxiliary storage device) are registered (stored) in the storage unit 122. For example, data of parameters referenced in the processing of various programs based on the gateway ECU 12 are registered (stored) in the storage unit 122.

[0089] The ECU 13 includes a storage unit 131 as a functional unit. For example, the function of the storage unit 131 is implemented through a storage area defined in the auxiliary storage device of the ECU 13.

[0090] Various types of data used in ECU 13 are stored in storage unit 131. For example, data of various programs installed in ECU 13 (auxiliary storage device) are registered (stored) in storage unit 131. For example, data of parameters referenced in the processing of various programs based on ECU 13 are registered (stored) in storage unit 131.

[0091] The central ECU 19 includes a vehicle data acquisition unit 191, a download processing unit 192, a storage unit 193, a software update unit 194, and a storage unit 195 as functional units. The functions of the vehicle data acquisition unit 191, the download processing unit 192, and the software update unit 194 can be implemented, for example, by loading a program installed in the auxiliary storage device 19A into the memory device 19B and having the CPU 19C execute the program. The functions of the storage units 193 and 195 can be implemented, for example, through a storage area defined in the auxiliary storage device 19A.

[0092] The vehicle data acquisition unit 191 acquires vehicle data indicating the status of vehicle 10 and sends the acquired vehicle data to the analysis server 30.

[0093] For example, the vehicle data acquisition unit 191 acquires vehicle data indicating the status of the vehicle 10 at predetermined intervals and sends (uploads) the acquired vehicle data to the analysis server 30 via the gateway ECU 12 (communication device 11). For example, the vehicle data acquisition unit 191 can upload the acquired vehicle data to the analysis server 30 in real time, or it can accumulate the acquired vehicle data in the memory device 19B or the auxiliary storage device 19A and send the accumulated vehicle data to the analysis server 30 together at a predetermined time.

[0094] For example, in response to a request received from the analysis server 30 via the gateway ECU 12 (communication device 11), the vehicle data acquisition unit 191 acquires the latest vehicle data and sends the acquired latest vehicle data to the analysis server 30 via the gateway ECU 12 (communication device 11).

[0095] The vehicle data to be transmitted includes, for example, measurement data output from sensor 15. The vehicle data to be transmitted also includes, for example, command values ​​output from various ECUs such as gateway ECU 12, ECU 13, and central ECU 19, or control data such as values ​​resulting from calculations during the control process.

[0096] The download processing unit 192 performs the processing of downloading software update data from the transfer server 20.

[0097] Storage unit 193 stores the software update data downloaded from the transfer server 20.

[0098] The software update unit 194 uses the software update data downloaded to the storage unit 193 to update the software used in the gateway ECU 12, ECU 13, central ECU 19, etc.

[0099] Various types of data used in the central ECU 19 are stored in the storage unit 195. For example, data from various programs installed in the central ECU 19 (auxiliary storage device) are registered (stored) in the storage unit 195. For example, data on parameters referenced in the processing of various programs in the central ECU 19 are registered (stored) in the storage unit 195.

[0100] Functional configuration of the transmission server

[0101] like Figure 4 As shown, the transmission server 20 includes a notification unit 201 and a transmission unit 202 as functional units. The functions of the notification unit 201 and the transmission unit 202 are implemented, for example, by loading a program installed in the auxiliary storage device 22 into the memory device 23 and causing the CPU 24 to execute the program.

[0102] When update data for the software used in vehicle 10 is available, notification unit 201 notifies the user of vehicle 10 that the update data exists. When the software update system 1 includes multiple vehicles 10, notification unit 201 only notifies the user of the vehicle 10 whose software needs to be updated based on the update data that the update data exists. This is because, for example, when the multiple vehicles 10 include two or more models of vehicle 10, whether the software needs to be updated and the details of the update differ depending on the vehicle model. For example, this is because, when the multiple vehicles 10 are the same model, whether the software needs to be updated and the details of the update differ depending on the service level. For example, this is also because the services that the user can accept differ depending on the contract details between the user and the service provider associated with the software update of vehicle 10, that is, the services provided to the user differ based on the cost (charge), and therefore the details of the software update also differ.

[0103] Specifically, the notification unit 201 sends a signal to the analysis server 30 requesting a prediction of the effect of a software update on the vehicle 10 to which update data is to be transmitted. When there are two or more vehicles 10 to which update data is to be transmitted, the notification unit 201 requests the analysis server 30 to predict the effect of the software update for each of the multiple vehicles 10. When the analysis server 30 receives the prediction result of the software update effect, the notification unit 201 determines whether the effect of the software update in the corresponding vehicle 10 meets a predetermined benchmark, which can be used to determine whether the user actually experiences the effect. When the effect of the software update in the corresponding vehicle 10 meets the predetermined benchmark, the notification unit 201 sends a signal to the vehicle 10 indicating the existence of software update data. Therefore, the central ECU 19 (download processing unit 192) of the vehicle 10 can notify the user of the existence of software update data via the display device 18. In this case, the notification unit 201 can send the signal indicating the existence of software update data to the user terminal 40 of the vehicle 10, instead of the vehicle 10, or to a location other than the vehicle 10. Therefore, the user terminal 40 (notification unit 401) can notify the user of vehicle 10 of the existence of software update data via the display device. In this case, when the user needs to pay for the software update, the notification unit 201 can send a signal to vehicle 10 or user terminal 40 indicating the existence of software update data and including the cost of the software update. Therefore, the central ECU 19 (download processing unit 192) of vehicle 10 can use the display device 18 to notify the user of vehicle 10 of the existence of software update data and the cost of the software update. The user terminal 40 (notification unit 401) can use the display device to notify the user of vehicle 10 of the existence of software update data and the cost of the software update. On the other hand, when the effect of the software update of the corresponding vehicle 10 does not meet the predetermined benchmark, the notification unit 201 does not send a signal indicating the existence of software update data to the user's corresponding vehicle 10 or user terminal 40. Therefore, since the transmission server 20 does not notify the user of the existence of software update data that is not very effective for the corresponding vehicle 10, the occurrence of software updates based on update data can be suppressed. Therefore, the transmission server 20 can update the software used in the vehicle 10 more appropriately.

[0104] The transmission unit 202 transmits software update data to the vehicle 10. For example, when the effect of a software update in the corresponding vehicle 10 meets a predetermined benchmark and an update permission signal is received from the vehicle 10 or the user terminal 40, the notification unit 201 sends a transmission command for update data to the transmission unit 202, and the transmission unit 202 sends the update data to the corresponding vehicle 10 in response to the transmission command. On the other hand, when the effect of a software update in the corresponding vehicle 10 does not meet the predetermined benchmark, the transmission unit 202 suppresses the transmission of update data. Therefore, the transmission server 20 can suppress software updates that are less effective in the corresponding vehicle 10, thereby updating the software used in the vehicle 10 more appropriately.

[0105] Analysis server configuration

[0106] like Figure 4 As shown, the analysis server 30 includes a vehicle data acquisition unit 301, a vehicle data storage unit 302, a virtual vehicle model generation unit 303, a virtual vehicle model storage unit 304, a simulator unit 305, and an effect prediction unit 306 as functional units. The functions of the virtual vehicle model generation unit 303, the simulator unit 305, and the effect prediction unit 306 are implemented, for example, by loading a program installed in the auxiliary storage device of the analysis server 30 into a memory device and having the CPU execute the program. The function of the virtual vehicle model storage unit 304 is implemented, for example, by using a storage area defined in the auxiliary storage device of the analysis server 30.

[0107] The vehicle data acquisition unit 301 acquires vehicle data received from the vehicle 10 or an external device associated with the vehicle 10.

[0108] The vehicle data storage unit 302 stores the vehicle data acquired by the vehicle data acquisition unit 301.

[0109] The virtual vehicle model generation unit 303 (an example of a generation unit) generates a virtual model (hereinafter referred to as the "virtual vehicle model") corresponding to the vehicle 10. The virtual vehicle model is a model that reproduces various characteristics of the vehicle 10 in virtual space. For example, the virtual vehicle model can be a complete vehicle model that reproduces all characteristics of the vehicle 10, or it can be a partial vehicle model that only reproduces some characteristics (performance) of the vehicle 10, which will be the object of effect prediction described later. The virtual vehicle model can be a three-dimensional model that reproduces a part or the entire shape of the vehicle 10.

[0110] For example, the virtual vehicle model generation unit 303 generates a virtual vehicle model by reflecting vehicle data indicating the latest state of vehicle 10 stored in the vehicle data storage unit 302 in a general virtual model, which is shared by vehicles 10 of the same model or the same class. The general virtual model may be, for example, a complete vehicle model or a partial vehicle model with the final specifications of the model or class corresponding to vehicle 10 and prepared during the development stage of the model corresponding to vehicle 10.

[0111] For example, the virtual vehicle model generation unit 303 generates and updates a virtual model based on vehicle data repeatedly acquired by the vehicle data acquisition unit 301 in chronological order. Specifically, the virtual vehicle model generation unit 303 can generate and update a virtual vehicle model based on a vehicle model shared by vehicle 10 and on vehicle data repeatedly uploaded from vehicle 10. Therefore, the virtual vehicle model generation unit 303 can generate (update) a virtual vehicle model based on at least one of the following: changes in vehicle 10 over time, operating conditions of vehicle 10, and changes in vehicle 10 components. Thus, changes in vehicle 10 over time, operating conditions of vehicle 10, or changes in vehicle 10 components can be reflected in the virtual vehicle model. For example, the operating conditions of vehicle 10 may include the environmental conditions of using vehicle 10, the driving conditions when using vehicle 10, and the frequency of use of vehicle 10. For example, changes in vehicle 10 components may include changes in hardware such as components of vehicle 10, changes in vehicle 10 software, and changes in the type of coolant or lubricant used in vehicle 10. The virtual vehicle model generation unit 303 can generate a virtual vehicle model based on manufacturing irregularities of the vehicle 10 stored in the vehicle data storage unit 302. Therefore, the virtual vehicle model generation unit 303 can reflect the manufacturing irregularities of the vehicle 10 in the virtual vehicle model. The virtual vehicle model generation unit 303 can generate a digital twin of the virtual vehicle model by updating the virtual vehicle model in real time based on vehicle data uploaded sequentially from the vehicle 10.

[0112] The virtual vehicle model generated by the virtual vehicle model generation unit 303 is stored in the virtual vehicle model storage unit 304. When the number of vehicles 10 included in the software update system 1 is two or more, virtual vehicle models for each of the two or more vehicles 10 are stored.

[0113] The simulator unit 305 uses the virtual vehicle model of vehicle 10 registered (stored) in the virtual vehicle model storage unit 304 to perform virtual simulation of vehicle 10. The virtual simulation of vehicle 10 includes driving simulation of vehicle 10 under predetermined driving conditions.

[0114] Effect prediction unit 306 (an example of a prediction unit) responds to a request from the transmission server 20 and predicts the effect obtained by updating the software used in vehicle 10.

[0115] For example, the effect prediction unit 306 predicts the effect of the software update based on the details of the software update and the vehicle data of the vehicle 10 whose software is to be updated (see, for example, the effect described later). Figure 5 as well as Figure 6 Specifically, the effect prediction unit 306 predicts the effect of the software update by determining the extent to which the driving conditions or conditions relating to the operating environment of the vehicle 10 changed by the software update correspond to the operating state of the vehicle 10 identified based on vehicle data of the vehicle 10. This is because the frequency with which the driving conditions or conditions relating to the operating environment affected by the software update are met varies depending on the operating state of the vehicle 10.

[0116] For example, effect prediction unit 306 can predict the effect of software update by having simulator unit 305 perform virtual simulation of vehicle 10 using a virtual vehicle model of vehicle 10 (see, for example, described later). Figure 7 as well as Figure 8Specifically, the virtual vehicle model generation unit 303 generates a virtual vehicle model corresponding to the software update based on the latest virtual vehicle model of vehicle 10, according to instructions from the effect prediction unit 306. The simulator unit 305, according to instructions from the effect prediction unit 306, uses the virtual vehicle model corresponding to vehicle 10 after the software update to virtually simulate the driving of vehicle 10 under predetermined driving conditions. Since the virtual simulation of vehicle 10 is performed, the predetermined driving conditions vary depending on the details of the software update. Then, the effect prediction unit 306 predicts the effect of the software update based on the results of the virtual simulation using the virtual vehicle model corresponding to vehicle 10 after the software update. For example, the effect prediction unit 306 can predict the effect of the software update by comparing the latest vehicle data stored in the vehicle data storage unit 302 with the data from the virtual simulation results corresponding to the vehicle data of vehicle 10 after the software update. Therefore, based on the assumption that the existing (latest) vehicle data of vehicle 10 stored in the vehicle data storage unit 302 represents the state of vehicle 10 before the software update, the effect prediction unit 306 can use a relatively simple method to predict the effect of the software update. For example, the effect prediction unit 306 can predict the effect of the software update by comparing the results of virtual simulations using virtual vehicle models corresponding to the vehicle 10 before and after the software update. In this case, the effect prediction unit 306 instructs the simulator unit 305 to perform virtual simulations under the same conditions, using the virtual vehicle model corresponding to the vehicle 10 before the software update and the virtual vehicle model corresponding to the vehicle 10 after the software update. Therefore, the effect prediction unit 306 can ensure that the driving conditions, etc., which are the premises for the data to be compared, are approximately the same. Consequently, the effect prediction unit 306 can predict the effect more accurately.

[0117] For example, the effect prediction unit 306 can predict the effect by determining whether the indicator value improved by the software update meets a predetermined benchmark. The effect prediction unit 306 can predict the effect based on the indicator value improved by the software update.

[0118] For example, the effect prediction unit 306 can select a method for predicting the effect based on the details of the software update. Specifically, when predicting the effect of the software update based on the details of the software update, the effect prediction unit 306 can determine whether to perform a virtual simulation based on a virtual vehicle model corresponding to vehicle 10. For example, whether to perform a virtual simulation can be specified for each piece of update data and can be automatically determined based on the specified details. For example, the determination of whether to perform a virtual simulation can be based on the details of the update data and information such as the table used for the effect items of the software update.

[0119] For example, the effect prediction unit 306 can consider the period of time the user will use vehicle 10 in the future to predict whether the software update is effective or to what extent. The effect prediction unit 306 can also refer to data stored in the vehicle data storage unit 302, such as the time vehicle 10 was registered as a new vehicle and the last inspection time of vehicle 10, to predict the period of time the user will use vehicle 10 in the future. This is because the user benefits from the software update for a short period, and the effect may be greatly reduced if the user needs to replace vehicle 10 in a short time. Specifically, the effect prediction unit 306 can set a predetermined benchmark for determining its effectiveness or a benchmark for defining the degree of effectiveness to increase relatively as the period of time the user will use vehicle 10 in the future becomes shorter. When the user's future period of use of vehicle 10 does not meet the predetermined benchmark, the effect prediction unit 306 can predict that the software update will be ineffective.

[0120] User terminal function configuration

[0121] like Figure 4 As shown, the user terminal 40 includes a notification unit 401 as a functional unit. The function of the notification unit 401 is implemented, for example, by loading a program installed in the auxiliary storage device of the user terminal 40 into the memory device and causing the CPU to execute the program.

[0122] Based on a signal received from the transmission server 20, the notification unit 401 notifies the user via a display device of the existence of software update data for the vehicle 10. Therefore, the user of the vehicle 10 can determine whether software update data for the vehicle 10 exists at times other than when the vehicle 10 is in use. Thus, for example, the user can enter a software update permission into the user terminal 40 and complete the software update when the vehicle 10 is not in use.

[0123] Examples of methods for predicting the effects of vehicle software updates

[0124] The following will refer to Figures 5 to 8 An example describing a method for predicting the effects of software updates on vehicle 10, performed by effect prediction unit 306.

[0125] First Example

[0126] Figure 5 This is an example of an updated diagram showing the shift characteristics of the transmission of vehicle 10. Specifically, Figure 5 The coordinate system illustrates the switching conditions between the first and second gears, between the second and third gears, and between the third and fourth gears in the transmission of vehicle 10. The coordinate system has the vehicle speed of vehicle 10 as the horizontal axis and the required driving force of vehicle 10 as the vertical axis.

[0127] For example, the required driving force of vehicle 10 is determined based on the amount of accelerator operation by the driver of vehicle 10. Figure 5 In the diagram, solid lines represent shift conditions for upshifting (shift lines), and dashed lines represent shift conditions for downshifting (shift lines).

[0128] like Figure 5 As shown, in this example, the switching condition between the third and fourth gears is changed from shift line 501 to shift line 502 by a software update of ECU 13, which controls the shift position of the transmission.

[0129] For example, consider a scenario where a user of vehicle 10 uses operation point 503 relatively frequently. Based on the shift line 501, at operation point 503, no upshift from third to fourth gear occurs in the transmission; third gear is held, thus maintaining a higher speed for the prime mover, such as an engine or electric motor. Consequently, the energy consumption of vehicle 10 increases relatively. On the other hand, when a software update is performed and the switching conditions are updated to shift line 502, an upshift from third to fourth gear occurs at operation point 503, fourth gear is held, and thus maintaining a lower speed for the prime mover, such as an engine or electric motor. Consequently, the energy consumption of vehicle 10 decreases relatively, and fuel efficiency or electrical efficiency improves. Therefore, the effect prediction unit 306 can predict that there is an improvement in energy consumption due to the software update, or that the degree of improvement is high.

[0130] For example, consider a scenario where the user of vehicle 10 uses operation point 504 relatively frequently. Operation point 504 is within the same vehicle speed range as operation point 503 but requires less driving force compared to operation point 503. In this case, whether it's shift line 501 or 502, the upshift from third to fourth gear in the transmission is completed at operation point 504, and fourth gear is maintained. Therefore, the effect prediction unit 306 can predict effects without software updates or with relatively low effect levels. The same applies, for example, when the user of vehicle 10 does not use the vehicle speed range 505 affected by the change in switching conditions, or when its frequency is very low.

[0131] In this way, in this example, the effect prediction unit 306 is able to predict the effect of the software (shift characteristic map) update based on vehicle data of the required driving force and vehicle speed that are sequentially uploaded from vehicle 10 (accumulated in vehicle data storage unit 302).

[0132] For software updates associated with upshift / downshift conditions in the transmission, the effect prediction unit 306 can predict the effects of the software update based on the results of a virtual simulation based on a virtual vehicle model of the vehicle 10. For example, for software updates associated with upshift / downshift conditions in the transmission, the effect prediction unit 306 can predict the effects of the update on the power performance of the vehicle 10 under predetermined driving conditions through a virtual simulation based on a virtual vehicle model of the vehicle 10.

[0133] Second example

[0134] Figure 6 This is an example diagram illustrating an updated switching characteristic diagram of the prime mover in vehicle 10. In this example, vehicle 10 is a so-called hybrid electric vehicle capable of operating by switching between two prime movers, including an engine and an electric motor. Specifically, Figure 6 The diagram illustrates the switching conditions between a state where the vehicle 10 can travel using only the electric motor (MG) when the engine is stopped and a state where the vehicle 10 can travel using the engine when the engine is started. The coordinate system has the vehicle speed of the vehicle 10 on the horizontal axis and the required driving force of the vehicle 10 on the vertical axis.

[0135] The states in which vehicle 10 is allowed to run using the engine can include states in which vehicle 10 is allowed to run using only the engine and states in which vehicle 10 is allowed to run using both the engine and the electric motor.

[0136] like Figure 6 As shown, in this example, by updating the software in ECU13, which comprehensively controls the operating states of the two prime movers, the switching condition for switching between the state that allows the vehicle 10 to run using only the electric motor and the state that allows the vehicle 10 to run using the engine is updated from switching line 601 (thin solid line) to switching line 602 (thick solid line).

[0137] For example, consider a scenario where the user of vehicle 10 uses operation point 603 frequently. Based on the premise of switching line 601, at operation point 603, the engine starts and vehicle 10 uses the engine's power to travel. On the other hand, when a software update is performed and the switching condition is updated to switching line 602, vehicle 10 can be allowed to travel at operation point 603 using only the electric motor's power, thereby improving the fuel efficiency of vehicle 10. Therefore, the effect prediction unit 306 can predict that the software update has an effect on improving the fuel efficiency of vehicle 10, or that the effect is relatively high.

[0138] For example, consider a scenario where the user of vehicle 10 uses operating point 604 at a relatively high frequency, where operating point 604 is within the same vehicle speed range as operating point 603 but requires less driving force than operating point 603. In this case, regardless of whether switching lines 601 or 602 are used, at operating point 604, vehicle 10 is allowed to travel solely using the power of the electric motor. Therefore, the effect prediction unit 306 can predict that the improvement in fuel efficiency of vehicle 10 through software updates will have no effect or a relatively low effect. The same applies, for example, when the user of vehicle 10 does not use operating area 605 affected by changes in switching conditions or uses it very infrequently.

[0139] In this way, in this example, the effect prediction unit 306 is able to predict the effect of the software (prime mover switching characteristic map) update based on vehicle data of the required driving force and vehicle speed sequentially uploaded from vehicle 10.

[0140] Third Example

[0141] Figure 7 This is a diagram (timing diagram 700) illustrating an example of the results of a virtual simulation of the time-varying changes in the vehicle state during gear shifting (upshifting) in vehicle 10 before and after the update of the control logic for gear shifting (upshifting) in the transmission of vehicle 10. Specifically, Figure 7 The figure illustrates the results of a virtual simulation based on a virtual vehicle model of vehicle 10 included in software update system 1. Timing diagram 700 includes timing diagrams 701 to 704 indicating the time-varying disengagement pressure command value, engagement pressure command value, prime mover (engine) speed, and longitudinal acceleration of vehicle 10 during gear shifts. Figure 8 This is another example (timing diagram 800) illustrating the results of a virtual simulation of the time-varying changes in the vehicle state during gear shifting (upshifting) in vehicle 10 before and after the update of the control logic for gear shifting (upshifting) in vehicle 10. Specifically, Figure 8 The figure shows the results of a virtual simulation of a virtual vehicle model of another vehicle 10, which is included in the software update system 1 and is equipped with a transmission of the same specifications as the aforementioned vehicle 10. The timing diagram 800 includes timing diagrams 801 to 804 indicating the time-varying disengagement pressure command value, engagement pressure command value, output shaft speed of the transmission, and longitudinal acceleration of the vehicle 10 during transmission shifts.

[0142] The disengagement pressure command value indicates the hydraulic command value used to operate transmission components (e.g., brakes or clutches) that shift gears from engaged to disengaged. The engagement pressure command value indicates the hydraulic command value used to operate transmission components that shift gears from disengaged to engaged. Figure 7 and Figure 8In the process, the control logic for gear shifting of the transmission is the same before and after the software update. Therefore, the timing diagrams 701 and 702, as well as timing diagrams 801 and 802, corresponding to the control logic are identical.

[0143] like Figure 7 and Figure 8 As shown, in this example, the transmission's shift control logic is updated so that the time from the start of shifting (upshifting) (start of decreasing disengagement pressure command value) to the end (end of increasing engagement pressure command value) (shift time) is shortened.

[0144] In timing diagram 703, the rate of change (rate of change over time) of the prime mover (engine) speed due to gear shifting also increases relatively with the update of the control logic. In timing diagram 704, the fluctuation of the longitudinal acceleration of vehicle 10 due to gear shifting increases relatively. Therefore, the user can clearly feel the increase in shifting speed. Figure 7 In the case of the vehicle 10 shown, the effect prediction unit 306 can predict that the improvement in shift speed caused by the software update has an effect, or a high degree of effect.

[0145] On the other hand, in timing diagram 803, before and after the control logic update, the rate of change (rate of change over time) of the prime mover (engine) speed caused by the gear shift remains essentially unchanged. In timing diagram 804, before and after the control logic update, the fluctuation in the longitudinal acceleration of vehicle 10 caused by the gear shift remains essentially unchanged in magnitude. Therefore, it is unlikely that the user will actually perceive an increase in the shift speed. Thus, in Figure 8 In the case of the vehicle 10 shown, the effect prediction unit 306 can predict that the improvement in shift speed caused by the software update has no effect or a relatively low effect.

[0146] One reason for the differences in the effects of control logic updates between vehicles 10 equipped with transmissions of the same specifications is, for example, the effect of the viscosity of the lubricant used in the transmission. For instance, when a commercially available lubricant with a higher viscosity than the factory-filled lubricant is used in the transmission, the user is unlikely to actually perceive an increase in shift speed. Another reason for the differences in the effects of control logic updates between vehicles 10 equipped with transmissions of the same specifications is, for example, the effect of manufacturing irregularities in the clutch assembly clearance of the transmission. For instance, when the clutch assembly clearance of the transmission is close to the lower limit of the manufacturing allowable range, the user is unlikely to actually perceive an increase in shift speed compared to when the clearance is close to the upper limit. Finally, another reason for the differences in the effects of control logic updates between vehicles 10 equipped with transmissions of the same specifications is, for instance, the effect of the cumulative shift frequency of the transmission. For instance, when the cumulative shift frequency is relatively low after vehicle 10 leaves the factory or after a new transmission is installed, the clutch assembly clearance of the transmission may be smaller compared to when the cumulative shift frequency is relatively high, and the user is unlikely to actually perceive an increase in shift speed. One reason for the differences in the effects of control logic updates between vehicles 10 equipped with transmissions of the same specifications is the influence of air leakage in the solenoid valves that engage and disengage the transmission's clutches or brakes. For example, when the air leakage in the transmission's solenoid valves is smaller, the shift speed is higher compared to when the leakage is larger. Therefore, even if the control logic is updated, the user is unlikely to actually perceive an increase in shift speed. Another reason for the differences in the effects of control logic updates between vehicles 10 equipped with transmissions of the same specifications is the influence of the temperature environment in which the vehicle 10 is used. For example, when the vehicle 10 is used in a so-called cold region with very low temperatures, the viscosity of the lubricant is higher compared to when the vehicle is used at higher temperatures. Therefore, even if the control logic is updated, the user is unlikely to actually perceive an increase in shift speed.

[0147] In this way, in this example, the effect prediction unit 306 is able to predict the update effect of the software (the program associated with the shift control logic of the transmission) based on the results of a virtual simulation of transmission shifting based on a virtual vehicle model.

[0148] Software update processing

[0149] The following will refer to Figures 9 to 11 Describe the software update process in vehicle 10.

[0150] Figure 9 This is a flowchart illustrating an example of software update processing performed in vehicle 10 by the transfer server 20. Figure 10This is a flowchart illustrating an example of software update processing in vehicle 10 performed by analysis server 30. Figure 11 This is a flowchart illustrating an example of software update processing in vehicle 10 performed by the central ECU 19.

[0151] For example, Figure 9 The routine in the flowchart shown is executed repeatedly at predetermined time intervals. When a request to predict the effect of a software update is received from the transmission server 20, the following is executed: Figure 10 The flowchart shown is an example. When a notification indicating the existence of software update data is received from the transmission server 20, the following procedure is executed: Figure 11 The flowchart shown is an example.

[0152] Figure 9 The processing steps S110 to S118 are performed for each vehicle 10 whose update data is to be transmitted.

[0153] like Figure 9 As shown, in step S102, the notification unit 201 determines whether there is software update data for vehicle 10, specifically, whether new update data has been registered. When software update data for vehicle 10 exists, the notification unit 201 executes the processing in step S104, and when there is no software update data for vehicle 10, the flowchart routine ends.

[0154] In step S104, the notification unit 201 determines the vehicle 10 to which update data is to be transmitted. For example, data indicating that the vehicle 10 to which update data is to be transmitted is registered in the transmission server 20 along with the update data.

[0155] When step S104 is completed, the transmission server 20 executes step S106.

[0156] In step S106, the notification unit 201 sends a request to the analysis server 30 to predict the effect of the software update on vehicle 10. The prediction request sent includes data indicating the vehicle 10 to which the effect is to be predicted (i.e., the vehicle 10 to which the update data will be transmitted), details of the update data, characteristics (performance) of the vehicle to which the effect is to be predicted, etc.

[0157] When step S106 is completed, the transmission server 20 executes step S108.

[0158] When the analysis server 30 receives a signal including the prediction request sent in step S106, it begins... Figure 10 The flowchart shown is an example.

[0159] In step S202, the effect prediction unit 306 determines the vehicle 10 whose effect is to be predicted based on the data included in the signal receiving from the transmission server 20, which includes a request for prediction.

[0160] When step S202 is completed, the analysis server 30 executes step S204.

[0161] In step S204, the vehicle data acquisition unit 301 sends a signal to the vehicle 10 whose effect is to be predicted, requesting the transmission of the latest vehicle data. At this time, the vehicle data acquisition unit 301 can request all available vehicle data. The vehicle data acquisition unit 301 can request only some data including the vehicle data required for the effect prediction, that is, vehicle data of the predetermined performance of the vehicle 10 improved through software updates based on corresponding updated data.

[0162] When step S204 is completed, the analysis server 30 executes step S206.

[0163] In step S206, the vehicle data acquisition unit 301 acquires vehicle data received from the vehicle 10 whose effect is to be predicted, and stores the acquired vehicle data in the vehicle data storage unit 302.

[0164] When step S206 is completed, the analysis server 30 executes step S208.

[0165] If, due to reasons such as communication failure, no vehicle data is received from vehicle 10 whose effect is to be predicted even after a certain period of time, the analysis server 30 can return to step S204 and repeat the routine. If vehicle data is automatically uploaded from vehicle 10 (vehicle data acquisition unit 191) at a higher frequency and the latest vehicle data has been stored in vehicle data storage unit 302, the processing in steps S204 and S206 can be skipped.

[0166] In step S208, the effect prediction unit 306 determines whether a virtual simulation needs to be performed to predict the effect of the software update. When a virtual simulation needs to be performed to predict the effect of the software update, the effect prediction unit 306 performs the processing of step S210, and when a virtual simulation does not need to be performed, it performs the processing of step S214.

[0167] In step S210, the virtual vehicle model generation unit 303 generates virtual vehicle models reflecting the latest vehicle data for each vehicle 10 whose effects are to be predicted. For example, the virtual vehicle model generation unit 303 generates a virtual vehicle model corresponding to the vehicle 10 before the software update by reflecting the latest vehicle data in a general virtual model corresponding to the vehicle 10 as described above. For example, the virtual vehicle model generation unit 303 generates a virtual vehicle model corresponding to the vehicle 10 before the software update by reflecting the latest vehicle data in a newly generated virtual vehicle model (e.g., a digital twin) registered in the virtual vehicle model storage unit 304. The virtual vehicle model generation unit 303 generates a virtual vehicle model corresponding to the vehicle 10 after the software update by reflecting the details of the updated data based on the corresponding virtual vehicle model before the software update.

[0168] When step S210 is completed, the analysis server 30 executes step S212.

[0169] In step S212, the effect prediction unit 306 causes the simulator unit 305 to perform virtual simulations for software updates on each vehicle 10 for which the effect to be predicted. Specifically, the simulator unit 305 uses the corresponding virtual vehicle model generated by the virtual vehicle model generation unit 303 after the software update to perform virtual simulations on the corresponding vehicle 10 after the software update. The simulator unit 305 can also use the corresponding virtual vehicle model generated by the virtual vehicle model generation unit 303 as described above before the software update to perform virtual simulations on the corresponding vehicle 10 before the software update.

[0170] When step S212 is completed, the analysis server 30 executes step S214.

[0171] In step S214, the effect prediction unit 306 predicts the effect of the software update for each vehicle 10 whose effect is to be predicted. For example, when the routine proceeds from step S208 to step S214, the effect prediction unit 306 predicts the update effect of the software based on the details of the software update and the history of the vehicle data of the vehicle 10 to be updated as described above (see, for example, see...). Figure 5 and Figure 6 For example, when the routine proceeds from step S212 to step S214, the effect prediction unit 306 predicts the effect of the software update by comparing the data from the virtual simulation corresponding to the latest vehicle data with the vehicle data of vehicle 10 after the software update as described above. The effect prediction unit 306 can predict the effect of the software update by comparing the results of the virtual simulation corresponding to vehicle 10 before and after the software update as described above.

[0172] When step S214 is completed, the analysis server 30 executes step S216.

[0173] In step S216, the effect prediction unit 306 sends the prediction result of the software update effect of the vehicle 10 to be sent the update data to the transmission server 20.

[0174] When step S216 is completed, the analysis server 30 terminates this routine of the flowchart.

[0175] Return to reference Figure 9 In step S108, the notification unit 201 obtains the prediction results of the effect of the software update of the vehicle 10 received from the analysis server 30.

[0176] When step S108 is completed, the analysis server 30 executes step S110.

[0177] If, due to some reason such as a communication failure, no prediction result of the effect of the software update of vehicle 10 is received from the analysis server 30 after a certain period of time, the transmission server 20 may return to step S106 and repeat the routine.

[0178] In step S110, the notification unit 201 determines whether the effect of the software update for the corresponding vehicle 10 meets a predetermined benchmark based on the prediction result obtained from the analysis server 30. For example, when the effect prediction unit 306 predicts whether the software update for the vehicle 10 has an effect, and the prediction result indicates that an effect exists, the effect is determined to meet the predetermined benchmark. For example, as described above, when the effect prediction unit 306 predicts the degree of effect of the software update for the vehicle 10, and the degree of effect is equal to or greater than the predetermined benchmark, the effect is determined to meet the predetermined benchmark. When the effect of the software update for the corresponding vehicle 10 meets the predetermined benchmark, the notification unit 201 executes the processing of step S112, and when the effect of the software update does not meet the predetermined benchmark, the processing of step S118 is executed.

[0179] In step S112, the notification unit 201 sends a notification to the vehicle 10 indicating that there is software update data.

[0180] When step S112 is completed, the transmission server 20 executes step S114.

[0181] In step S112, instead of the vehicle 10 as described above or other than the vehicle 10, the notification unit 201 may send a notification signal to the user terminal 40 of the user of the vehicle 10.

[0182] When the signal sent in step S112 is received, the central ECU 19 of vehicle 10 begins... Figure 11 The flowchart shown is an example.

[0183] In step S302, the download processing unit 192 causes the display device 18 to display a notification screen indicating the existence of software update data. Therefore, the user of vehicle 10 can confirm the existence of software update data and determine whether to perform a software update.

[0184] When step S302 is completed and an input indicating whether to perform a software update is received via input device 17, the central ECU 19 executes step S304.

[0185] In step S304, the download processing unit 192 determines whether it has received input for licensing software updates. If input for licensing software updates has been received, the download processing unit 192 executes the processing in step S306, and if no input for licensing software updates has been received, that is, if input for rejecting software updates has been received, the download processing unit 192 executes the processing in step S312.

[0186] In step S306, the download processing unit 192 sends a signal indicating a license software update (hereinafter referred to as the "update license signal") to the transmission server 20 via the gateway ECU 12 (communication device 11).

[0187] When step S306 is completed, the central ECU 19 executes step S308.

[0188] like Figure 9 As shown, in step S114, the notification unit 201 determines whether an input for a licensed software update has been received in the vehicle 10. Specifically, the notification unit 201 determines whether an update license signal has been received from the vehicle 10 to which update data is to be transmitted. When an update license signal has been received from the vehicle 10, the notification unit 201 executes the processing of step S116.

[0189] In step S116, the transmission unit 202 transmits the update data to the vehicle 10 and causes the vehicle 10 (central ECU 19) to perform a software update.

[0190] When step S116 is completed, the transmission server 20 executes step S120.

[0191] like Figure 11 As shown, in step S308, the download processing unit 192 downloads the updated data transmitted from the transmission server 20 via the gateway ECU 12 (communication device 11).

[0192] When step S308 is completed, the central ECU 19 executes step S310.

[0193] In step S310, the software update unit 194 performs a software update using the update data downloaded to the storage unit 193, based on the software update command received from the transmission server 20.

[0194] Once the update data has been fully downloaded from the transmission server 20, the software update unit 194 can perform a software update based on its own decision.

[0195] When step S310 is completed, the central ECU 19 ends this routine of the flowchart.

[0196] On the other hand, in step S312, the download processing unit 192 sends a signal indicating that the software update has been rejected (hereinafter referred to as the "update rejection signal") to the transmission server 20 via the gateway ECU 12 (communication device 11).

[0197] When step S312 is completed, the central ECU 19 ends this routine of the flowchart.

[0198] As described above, when a signal for notifying the existence of updated data is sent from the transmission server 20 to the user terminal 40, in addition to the processing in steps S308 and S310, the user terminal 40 (notification unit 401) performs the same actions as above. Figure 10 The same routine is shown in the flowchart. When an update permission signal is sent from user terminal 40 to transmission server 20, central ECU 19 executes only the command from transmission server 20. Figure 11 The flowchart shown illustrates the processing of steps S308 and S310.

[0199] like Figure 9 As shown, in step S114, when no update permission signal is received from vehicle 10, that is, when an update rejection signal is received from vehicle 10, the notification unit 201 performs the processing of step S120.

[0200] On the other hand, in step S118, the transmission unit 202 determines that the transmission of software update data is suppressed. Therefore, as described above, the transmission server 20 can suppress software updates with relatively low effectiveness, thereby enabling more appropriate updates to the software used in the vehicle 10. At this time, the transmission unit 202 can record data, such as information indicating that the transmission of update data corresponding to a specific vehicle 10 (e.g., a sign), has been suppressed in a predetermined storage area of ​​the auxiliary storage device 22 of the transmission server 20. Therefore, the transmission server 20 can later determine that update data corresponding to a specific vehicle 10 has been suppressed, thereby preventing the occurrence of the corresponding update data being mistakenly sent to the specific vehicle 10.

[0201] When the processing of step S118 is completed, the transmission server 20 executes the processing of step S120.

[0202] In step S120, the transmission server 20 determines whether steps S110 to S118 have been completed for all vehicles 10 to which update data is to be transmitted. If these steps have not been completed for all vehicles 10 to which update data is to be transmitted, the transmission server 20 returns to step S110 and performs steps S110 to S118 on the vehicles 10 to which update data is to be transmitted that have not yet completed their processing. On the other hand, when the processing has been completed for all vehicles 10 to which update data is to be transmitted, the transmission server 20 terminates this routine of the flowchart.

[0203] Before the user is asked to determine whether to grant permission for a software update, the update data can be transmitted to vehicle 10. In this case, the transmission server 20 performs the process of transmitting the software update data to the corresponding vehicle 10, instead of performing the process in step S112, and sends a signal to the corresponding vehicle 10 in step S116 to execute a command to perform a software update. In this case, when the software update data has been completely downloaded, the central ECU 19 begins... Figure 11 The flowchart shown is an example, and the processing of receiving the signal for the command to perform a software update from the transmission server 20 is executed, instead of the processing in step S308. In this case, when the central ECU 19 determines whether to perform the software update itself, Figure 11 The processing of steps S306 and S308 in the process is skipped.

[0204] In this way, in this example, when the effect of a software update does not meet a predetermined benchmark, the software update system 1 can more appropriately update the software used in the vehicle 10 by suppressing the sending of update data to the corresponding vehicle 10.

[0205] operate

[0206] The operation of the software update system 1 according to this embodiment will now be described.

[0207] In this embodiment, the software update system 1 includes a vehicle data acquisition unit 301, an effect prediction unit 306, and a transmission unit 202. Specifically, the vehicle data acquisition unit 301 is configured to acquire data of the vehicle 10, including data on the predetermined performance of the vehicle 10. The effect prediction unit 306 is configured to predict, based on the data acquired by the vehicle data acquisition unit 301, the effect on the predetermined performance when updated data of the software used in the vehicle 10 for improving the predetermined performance is applied to the vehicle 10. The transmission unit 202 is configured to transmit the updated data to the vehicle 10 when the effect predicted by the effect prediction unit 306 meets a predetermined benchmark, and to suppress the transmission of the updated data to the vehicle 10 when the effect predicted by the effect prediction unit 306 does not meet the predetermined benchmark.

[0208] With this configuration, the software update system 1 can prevent the occurrence of ineffective software updates being performed uselessly in the corresponding vehicle 10. Therefore, the software update system 1 can update the software used in the vehicle 10 more appropriately.

[0209] In this embodiment, the software update system 1 may further include a virtual vehicle model generation unit 303. Specifically, the virtual vehicle model generation unit 303 may be configured to generate a virtual vehicle model corresponding to the vehicle 10 based on the data acquired by the vehicle data acquisition unit 301. The effect prediction unit 306 may be configured to predict the effect obtained when the updated data is applied to the vehicle 10 by performing a virtual simulation using the virtual vehicle model generated by the virtual vehicle model generation unit 303.

[0210] Using this configuration, software update system 1 can specifically predict the effects obtained through software updates.

[0211] In this embodiment, the effect prediction unit 306 can be configured to predict the effect by comparing the latest data on the predetermined performance of the vehicle 10 obtained by the vehicle data acquisition unit 301 with data obtained through virtual simulation, which is based on a virtual vehicle model corresponding to the vehicle 10 after a software update based on the updated data.

[0212] With this configuration, the software update system 1 can more easily predict the effects of the software update using existing (latest) vehicle data acquired by the vehicle data acquisition unit 301.

[0213] In this embodiment, the effect prediction unit 306 can be configured to predict the effect by comparing data obtained through a virtual simulation based on a virtual vehicle model corresponding to vehicle 10 before and after a software update based on updated data.

[0214] Using this configuration, the software update system 1 can more accurately predict the effects of software updates on the vehicle 10.

[0215] In this embodiment, the effect prediction unit 306 can be configured to determine whether to perform a virtual simulation when predicting the effect based on the details of the software update based on the updated data.

[0216] With this configuration, for example, software update system 1 can achieve a balance between simplifying the process for predicting the effects of software updates and improving the accuracy of predicting the effects of software updates, thereby improving the efficiency of the process.

[0217] In this embodiment, the effect prediction unit 306 can be configured to change the driving conditions of the vehicle 10 during virtual simulation based on the details of software updates based on updated data.

[0218] Using this configuration, the software update system 1 can perform a virtual simulation of the vehicle 10 based on the driving conditions affected by the software update of the vehicle 10. Therefore, the software update system 1 can more accurately predict the effects of the software update of the vehicle 10.

[0219] In this embodiment, the vehicle data acquisition unit 301 can be configured to acquire the latest vehicle data. The virtual vehicle model generation unit 303 can be configured to generate a virtual vehicle model by reflecting the vehicle data acquired by the vehicle data acquisition unit 301 in a general model corresponding to the vehicle 10.

[0220] Using this configuration, the software update system 1 can, for example, use a virtual model (universal model) shared by multiple vehicles 10 of the same model to predict the effects of software updates. Therefore, for example, the software update system 1 can reduce the labor or time required to prepare virtual vehicle models for evaluating the effects of software updates, and more effectively predict the effects of software updates.

[0221] In this embodiment, the vehicle data acquisition unit 301 can be configured to repeatedly acquire data about the state of the vehicle 10 over time. The virtual vehicle model generation unit 303 can be configured to use the data about the state of the vehicle 10 acquired by the vehicle data acquisition unit 301 to perform the generation and updating of a virtual vehicle model.

[0222] Using this configuration, the software update system 1 can generate virtual vehicle models suitable for the specific conditions of each vehicle 10 (such as the usage status of the vehicle 10). Therefore, the software update system 1 can more accurately predict the effects of software updates on the vehicle 10.

[0223] In this embodiment, the virtual vehicle model generation unit 303 can be configured to generate a virtual vehicle model reflecting the manufacturing irregularities of the vehicle 10 based on the vehicle data acquired by the vehicle data acquisition unit 301.

[0224] Using this configuration, the software update system 1 is able to reflect the manufacturing irregularities of vehicle 10, which are unique to vehicle 10, in the virtual vehicle model.

[0225] In this embodiment, the virtual vehicle model generation unit 303 can be configured to generate a virtual vehicle model based on the data acquired by the vehicle data acquisition unit 301, which reflects at least one of the time-related changes of the vehicle 10, the operating conditions of the vehicle 10, and the changes of the vehicle's components.

[0226] Using this configuration, the software update system 1 can reflect, in the virtual vehicle model, the time-related changes of the vehicle 10, the operating conditions of the vehicle 10, and the changes in the components of the vehicle 10, which are unique to the vehicle 10.

[0227] In this embodiment, the virtual vehicle model can be a digital twin corresponding to vehicle 10.

[0228] Using this configuration, the software update system 1 can predict the effects of software updates using a virtual vehicle model (digital twin) that accurately reflects the latest state of the vehicle 10. Therefore, the software update system 1 can more accurately predict the effects of software updates on the vehicle 10.

[0229] In this embodiment, the effect prediction unit 306 can be configured to predict the effect taking into account the time period during which the user will use the vehicle 10 in the future.

[0230] Using this configuration, the software update system 1 can predict the effect of the software update on the vehicle 10, taking into account the user's specific circumstances.

[0231] Although the embodiments have been described in detail above, this disclosure is not limited to such specific embodiments, but can be modified or improved in various forms without departing from the spirit of the appended claims.

Claims

1. An information processing system, comprising: An acquisition unit is configured to acquire data of the vehicle, including data on the vehicle's predetermined performance. A prediction unit is configured to predict, based on the data acquired by the acquisition unit, the effect on the predetermined performance when updated data of the software used in the vehicle for improving the predetermined performance is applied to the vehicle. as well as A transmission unit is configured to transmit the updated data to the vehicle when the effect predicted by the prediction unit meets a predetermined benchmark, and to suppress the transmission of the updated data to the vehicle when the effect predicted by the prediction unit does not meet the predetermined benchmark. The information processing system further includes a generation unit configured to generate a virtual model corresponding to the vehicle based on the data acquired by the acquisition unit, wherein the virtual model reflects at least one of the vehicle’s time-related changes and changes in the vehicle’s components. The prediction unit is configured to predict the effect by performing a virtual simulation using the virtual model, taking into account the time period during which the user will use the vehicle in the future. The acquisition unit is configured to repeatedly acquire data about the state of the vehicle over time, and the generation unit is configured to use the data about the state of the vehicle acquired by the acquisition unit to perform the generation and updating of the virtual model. The generation unit is configured to generate a virtual model reflecting the manufacturing irregularities of the vehicle based on the data acquired by the acquisition unit.

2. The information processing system according to claim 1, wherein, The prediction unit is configured to predict the effect by comparing the latest data on the vehicle's predetermined performance obtained by the acquisition unit with data obtained via virtual simulation, the virtual simulation being based on a virtual model corresponding to the vehicle after the software is updated based on the updated data.

3. The information processing system according to claim 1, wherein, The prediction unit is configured to predict the effect by comparing data obtained via a virtual simulation based on the virtual model corresponding to the vehicle before and after the software is updated with the updated data.

4. The information processing system according to any one of claims 1 to 3, wherein, The prediction unit is configured to determine, based on the details of the software update based on the updated data, whether to perform the virtual simulation when predicting the effect.

5. The information processing system according to any one of claims 1 to 3, wherein, The prediction unit is configured to change the vehicle's driving conditions during the execution of the virtual simulation based on details of software updates based on the updated data.

6. The information processing system according to any one of claims 1 to 3, wherein, The acquisition unit is configured to acquire the latest data of the vehicle, and The generation unit is configured to generate the virtual model by reflecting the data acquired by the acquisition unit in a general model corresponding to the vehicle.

7. The information processing system according to claim 1, wherein, The virtual model is a digital twin corresponding to the vehicle.

8. The information processing system according to claim 1, wherein, The virtual model also reflects the operating conditions of the vehicle.

9. An information processing apparatus, comprising: An acquisition unit is configured to acquire data of the vehicle, including data on the vehicle's predetermined performance. A prediction unit is configured to predict, based on the data acquired by the acquisition unit, the effect on the predetermined performance when updated data of the software used in the vehicle for improving the predetermined performance is applied to the vehicle. as well as A transmission unit is configured to transmit the updated data to the vehicle when the effect predicted by the prediction unit meets a predetermined benchmark, and to suppress the transmission of the updated data to the vehicle when the effect predicted by the prediction unit does not meet the predetermined benchmark. The information processing device further includes a generation unit configured to generate a virtual model corresponding to the vehicle based on the data acquired by the acquisition unit, wherein the virtual model reflects at least one of the vehicle’s time-related changes and changes in the vehicle’s components. The prediction unit is configured to predict the effect by performing a virtual simulation using the virtual model, taking into account the time period during which the user will use the vehicle in the future. The acquisition unit is configured to repeatedly acquire data about the state of the vehicle over time, and the generation unit is configured to use the data about the state of the vehicle acquired by the acquisition unit to perform the generation and updating of the virtual model. The generation unit is configured to generate a virtual model reflecting the manufacturing irregularities of the vehicle based on the data acquired by the acquisition unit.

10. An information processing method, executed by an information processing device, the information processing method comprising: Acquisition Steps: Acquire vehicle data, including data on the vehicle's predetermined performance. Prediction step: Based on the data acquired in the acquisition step, predict the effect on the predetermined performance when updated data of the software used in the vehicle for improving the predetermined performance is applied to the vehicle; as well as Transmission step: When the effect predicted in the prediction step meets the predetermined benchmark, the updated data is transmitted to the vehicle; and when the effect predicted in the prediction step does not meet the predetermined benchmark, the transmission of the updated data to the vehicle is suppressed. The information processing method further includes: Generation step: Generate a virtual model corresponding to the vehicle based on the data obtained in the acquisition step, wherein the virtual model reflects at least one of the time-related changes of the vehicle and the changes of the vehicle's components; In the prediction step, the effect is predicted by performing a virtual simulation using the virtual model, taking into account the time period during which the user will use the vehicle in the future. In the acquisition step, data about the state of the vehicle is repeatedly acquired over time, and in the generation step, the virtual model is generated and updated using the data about the state of the vehicle acquired in the acquisition step. In the generation step, a virtual model reflecting the manufacturing irregularities of the vehicle is generated based on the data acquired in the acquisition step.

11. A storage medium for a stored program, the program causing an information processing device to execute: Acquisition Steps: Acquire vehicle data, including data on the vehicle's predetermined performance. Prediction step: Based on the data acquired in the acquisition step, predict the effect on the predetermined performance when updated data of the software used in the vehicle for improving the predetermined performance is applied to the vehicle; as well as Transmission step: When the effect predicted in the prediction step meets the predetermined benchmark, the updated data is transmitted to the vehicle; and when the effect predicted in the prediction step does not meet the predetermined benchmark, the transmission of the updated data to the vehicle is suppressed. The procedure further causes the information processing device to execute: Generation step: Generate a virtual model corresponding to the vehicle based on the data obtained in the acquisition step, wherein the virtual model reflects at least one of the time-related changes of the vehicle and the changes of the vehicle's components; In the prediction step, the effect is predicted by performing a virtual simulation using the virtual model, taking into account the time period during which the user will use the vehicle in the future. In the acquisition step, data about the state of the vehicle is repeatedly acquired over time, and in the generation step, the virtual model is generated and updated using the data about the state of the vehicle acquired in the acquisition step. In the generation step, a virtual model reflecting the manufacturing irregularities of the vehicle is generated based on the data acquired in the acquisition step.

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