Information processing device, vehicle, information processing system, information processing method, and information processing program

Abstract

To reduce a data amount of a feature amount to transmit it.SOLUTION: A brake ECU is an information processing device that calculates a feature amount related to drive of a driver and includes a CPU that calculates the feature amount, and an input / output interface that transmits information related to the calculated feature amount to the outside. The CPU identifies whether it is a predetermined status (for example, a collection scene) (Step S212, Step S221), and when it is identified that it is the predetermined status, information on the predetermined status is calculated as the feature amount (Step S222 to Step S225), and the feature amount is made statistics (Step S225, Step S232). The input / output interface transmits the feature amount that is statistically processed to the outside (Step S227, Step S233). The feature amount in which a plurality of feature amounts are statistically processed has smaller data amount than that of the plurality of feature amounts that are not statistically processed.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] This disclosure relates to an information processing device, a vehicle, an information processing system, an information processing method, and an information processing program, and in particular to an information processing device that calculates features related to a driver's driving, a vehicle including the information processing device, an information processing system that includes the vehicle and a server, an information processing method executed by the information processing device, and an information processing program executed by the information processing device. [Background technology]

[0002] Conventionally, there has been a safety driving support device that determines the speed of the host vehicle, determines the driving scene of the host vehicle, determines the driver's line of sight, determines a judgment range using the host vehicle's speed and driving scene, determines a judgment time using the host vehicle's speed and driving scene, determines whether the driver's line of sight remains outside the judgment range for a judgment time using the driver's line of sight, the vehicle speed and driving scene of the host vehicle, and the judgment range and judgment time that depend on the driver's line of sight, and determines whether the driver is looking away (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2017-215654 Summary of the Invention [Problem to be solved by the invention]

[0004] In such an apparatus, when data is transmitted from a processor in a vehicle, it is required to reduce the amount of data.

[0005] This disclosure has been made to solve such problems, and its purpose is to provide an information processing device, a vehicle, an information processing system, an information processing method, and an information processing program that are capable of transmitting a reduced amount of feature data. [Means for solving the problem]

[0006] The information processing device according to the present disclosure is an information processing device that calculates feature quantities related to a driver's driving, and includes a processor that calculates the feature quantities and a transmitter that transmits information related to the calculated feature quantities to an external device. The processor determines whether a predetermined situation exists, and if the predetermined situation exists, calculates information related to the predetermined situation as feature quantities and converts the feature quantities into statistics. The transmitter transmits the converted statistics to an external device.

[0007] According to this configuration, when a predetermined situation is identified, information about the predetermined situation is calculated as a feature, the feature is statistically quantified, and the statistical feature is transmitted to an external device. The feature obtained by quantifying a plurality of feature quantities has a smaller amount of data than the plurality of feature quantities that are not statistically quantified. As a result, it is possible to provide an information processing device that can transmit a reduced amount of feature data.

[0008] The transmitting unit may transmit the time when the feature amount is calculated together with information about the feature amount to an external device. With this configuration, the time when the feature amount is calculated can be identified externally.

[0009] The processor may calculate information relating to the frequency of the target event in a predetermined situation as the feature amount. With this configuration, the information relating to the frequency of the target event in a predetermined situation can be transmitted to the outside as the feature amount.

[0010] According to another aspect of the present disclosure, a vehicle includes an information processing device that calculates a feature quantity related to a driver's driving. The information processing device includes a processor that calculates the feature quantity and a transmitter that transmits information related to the calculated feature quantity to an external device. The processor identifies whether a predetermined situation exists, and if the predetermined situation is identified, calculates information related to the predetermined situation as a feature quantity and converts the feature quantity into a statistical quantity. The transmitter transmits the converted statistical quantity to an external device.

[0011] According to this configuration, it is possible to provide a vehicle that can transmit a reduced amount of data of the feature amount.

[0012] According to yet another aspect of the present disclosure, an information processing system includes a vehicle including an information processing device that calculates feature quantities related to a driver's driving, and a server. The information processing device includes a processor that calculates the feature quantities and a transmitter that transmits information related to the calculated feature quantities to an external device. The processor identifies whether a predetermined situation exists, and if the predetermined situation is identified, calculates information related to the predetermined situation as feature quantities and converts the feature quantities into statistics. The transmitter transmits the converted statistics to an external device.

[0013] According to this configuration, it is possible to provide an information processing system that can transmit a reduced amount of data of feature quantities.

[0014] According to yet another aspect of the present disclosure, an information processing method is executed by an information processing device that calculates a feature quantity related to a driver's driving. The information processing device includes a processor that calculates the feature quantity and a transmitter that transmits information related to the calculated feature quantity to an external device. The information processing method includes the steps of: identifying whether a predetermined situation exists; if the processor identifies the predetermined situation, calculating information related to the predetermined situation as a feature quantity; converting the feature quantity into a statistical quantity; and causing the transmitter to transmit the statistical feature quantity to an external device.

[0015] According to this configuration, it is possible to provide an information processing method that can reduce the amount of data of the feature amount before transmitting it.

[0016] According to yet another aspect of the present disclosure, an information processing program is executed by an information processing device that calculates a feature quantity related to a driver's driving. The information processing device includes a processor that calculates the feature quantity and a transmitter that transmits information related to the calculated feature quantity to an external device. The information processing program causes the processor to execute the following steps: identifying whether a predetermined situation exists; if the predetermined situation is identified, calculating information related to the predetermined situation as a feature quantity; converting the feature quantity into statistics; and causing the transmitter to transmit the converted feature quantity to an external device.

[0017] According to this configuration, it is possible to provide an information processing method that can reduce the amount of data of the feature amount before transmitting it. [Effects of the Invention]

[0018] According to this disclosure, it is possible to provide an information processing device, a vehicle, an information processing system, an information processing method, and an information processing program that are capable of reducing the amount of data of feature quantities and transmitting them. [Brief explanation of the drawings]

[0019] [Figure 1] FIG. 1 is a diagram illustrating an example of a configuration of a vehicle information management system. [Figure 2] 1 is a diagram illustrating a configuration of an example of a vehicle information processing device according to an embodiment of the present invention; [Figure 3] FIG. 10 is a diagram for explaining an example of processing executed in a second processing unit. [Figure 4] 10 is a diagram for explaining an example of processing executed in a third processing unit. FIG. [Figure 5] 10 is a flowchart showing the flow of processing relating to feature quantities executed by a brake ECU and a central ECU. [Figure 6]FIG. 10 is a diagram for explaining data transmitted via the CAN. [Figure 7] FIG. 10 is a diagram for explaining data transmitted to a data center. DETAILED DESCRIPTION OF THE INVENTION

[0020] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are designated by the same reference numerals, and description thereof will not be repeated.

[0021] 1 is a diagram illustrating an example of the configuration of a vehicle information management system 1. As shown in FIG. 1, in this embodiment, the vehicle information management system 1 includes a plurality of vehicles 2 and 3, a communication network 6, a base station 7, and a data center 100.

[0022] The vehicles 2 and 3 may be any vehicles that are capable of communicating with the data center 100, and may be, for example, vehicles that use an engine as a drive source, electric vehicles that use an electric motor as a drive source, or hybrid vehicles that are equipped with an engine and an electric motor and use at least one of them as a drive source. Note that, for convenience of explanation, only two vehicles 2 and 3 are shown in Fig. 1, but the number of vehicles is not particularly limited to two, and may be three or more.

[0023] The vehicle information management system 1 is configured to acquire predetermined information from vehicles 2 and 3 that are configured to be able to communicate with the data center 100, and manage the acquired information.

[0024] The data center 100 includes a control device 110, a storage device 120, and a communication device 130. The control device 110, the storage device 120, and the communication device 130 are connected to each other by a communication bus 140 so that they can communicate with each other.

[0025] The control device 110 is configured to include a CPU (Central Processing Unit), memory (such as ROM (Read Only Memory) and RAM (Random Access Memory)), and input / output ports for inputting and outputting various signals, all of which are not shown. The various controls performed by the control device 110 are software processes, that is, programs stored in memory are read out by the CPU. The various controls performed by the control device 110 can also be realized by a general-purpose server (not shown) executing programs stored in a storage medium. However, the various controls performed by the control device 110 are not limited to software processes and may be processed by dedicated hardware (electronic circuits).

[0026] The storage device 120 stores predetermined information about a plurality of vehicles 2, 3 configured to be able to communicate with the data center 100. The predetermined information includes, for example, information about the characteristic quantities of each of the vehicles 2, 3 (described later) and information for identifying the vehicles 2, 3 (hereinafter referred to as vehicle ID). The vehicle ID is unique information set for each vehicle. The data center 100 can identify the vehicle that is the source of the transmission by the vehicle ID.

[0027] The communication device 130 realizes two-way communication between the control device 110 and the communication network 6. The data center 100 uses the communication device 130 to enable communication with a plurality of vehicles, including the vehicles 2 and 3, via a base station 7 provided on the communication network 6.

[0028] Next, a description will be given of the specific configuration of the vehicles 2 and 3. Since the vehicles 2 and 3 basically have the same configuration, the following description will be given of the configuration of the vehicle 2 as a representative.

[0029] The vehicle 2 includes drive wheels 50 and driven wheels 52. When the drive source operates to rotate the drive wheels 50, a drive force acts on the vehicle 2, causing the vehicle 2 to travel.

[0030] The vehicle 2 further includes an ADAS-ECU (Electronic Control Unit) 10, a brake ECU 20, a DCM (Data Communication Module) 30, and a central ECU 40.

[0031] The ADAS-ECU 10, the brake ECU 20, and the central ECU 40 are all computers that have a processor such as a CPU 11, 21, or 41 that executes a program, a memory 15, 25, or 45, and an input / output interface 13, 23, or 43, respectively.

[0032] The ADAS-ECU 10 includes a driving assistance system having functions related to driving assistance for the vehicle 2. The driving assistance system is configured to execute implemented applications to realize various functions for assisting driving of the vehicle 2, including at least one of steering control, drive control, and braking control of the vehicle 2. Applications implemented in the driving assistance system include, for example, an application that realizes the functions of an autonomous driving system (AD), an application that realizes the functions of an automatic parking system, and an application that realizes the functions of an advanced driver assist system (ADAS).

[0033] Examples of ADAS applications include at least one of the following: an application that realizes the function of adaptive cruise control (ACC (Adaptive Cruise Control) etc.), which maintains a constant distance between the vehicle and the vehicle ahead; an application that realizes the function of an auto speed limiter (ASL) that recognizes vehicle speed limits and maintains the vehicle's upper speed limit; an application that realizes the function of lane keeping assistance (LKA (Lane Keeping Assist) or LTA (Lane Tracing Assist) etc.), which maintains the vehicle in the lane in which it is traveling; an application that realizes the function of a collision mitigation braking system (AEB (Autonomous Emergency Braking) or PCS (Pre-Crash Safety) etc.), which automatically applies the brakes to reduce the damage of a collision; and an application that realizes the function of a lane departure warning (LDW (Lane Departure Warning) or LDA (Lane Departure Alert) etc.), which warns of vehicle 2's departure from its lane of travel.

[0034] Each application of this driving assistance system outputs a request for an action plan that ensures the marketability (function) of the application alone, based on information on the vehicle's surroundings and assistance requests from the driver acquired (input) from multiple sensors, to brake ECU 20. The multiple sensors include, for example, a vision sensor such as a forward-facing camera 71, millimeter-wave radar 72, a LiDAR (Light Detection And Ranging), or a position detection device.

[0035] The forward-facing camera 71 captures an image of the area ahead of the vehicle 2 and transmits the captured image data to the ADAS-ECU 10. The millimeter-wave radar 72 is a sensor that measures the distance, speed, and angle of surrounding objects, such as those ahead of the vehicle 2, using radio waves in the millimeter wave band (30 GHz band to 300 GHz band), and transmits the measurement result data to the ADAS-ECU 10. However, the multiple sensors connected to the ADAS-ECU 10 are not limited to being connected to the ADAS-ECU 10, and any one of the sensors may be connected to another ECU, and the detection result data of that sensor may be input to the ADAS-ECU 10 via a communication bus or the central ECU 40.

[0036] Each application acquires information on the vehicle's surroundings as recognition sensor information, which is an integration of detection results from one or more sensors, and also acquires assistance requests from the driver via a user interface (not shown), such as a switch. Each application can recognize other vehicles, obstacles, or people around the vehicle by, for example, processing images and videos of the vehicle's surroundings acquired by multiple sensors using artificial intelligence (AI) or an image processing processor. For example, using data from the forward-facing camera 71 and millimeter-wave radar 72, the inter-vehicle time is calculated from the inter-vehicle distance and relative speed between vehicle 2 and the preceding vehicle using the formula inter-vehicle distance / relative speed = inter-vehicle time.

[0037] The action plan also includes, for example, requirements regarding the longitudinal acceleration / deceleration to be generated in the vehicle 2, requirements regarding the steering angle of the vehicle 2, requirements regarding keeping the vehicle 2 stopped, and the like.

[0038] The brake ECU 20 uses detection results from the sensors to control a brake actuator that generates a braking force on the vehicle 2. Furthermore, the brake ECU 20 sets a motion request for the vehicle 2 to realize the request of the action plan from the ADAS-ECU 10. The motion request for the vehicle 2 set in the brake ECU 20 is realized by an actuator system (not shown) provided in the vehicle 2. The actuator system includes multiple types of actuator systems, such as a powertrain system, a brake system, and a steering system.

[0039] The brake ECU 20 is connected to, for example, a steering angle sensor 60, an accelerator pedal depression amount sensor 62, a brake pedal depression amount sensor 64, a first wheel speed sensor 54, and a second wheel speed sensor 56.

[0040] The steering angle sensor 60 detects the steering angle and transmits a signal indicating the detected steering angle to the brake ECU 20.

[0041] The accelerator pedal depression amount sensor 62 detects the depression amount of an accelerator pedal (not shown) and transmits to the brake ECU 20 a signal indicating the detected depression amount of the accelerator pedal.

[0042] The brake pedal depression amount sensor 64 detects the depression amount of a brake pedal (not shown) and transmits a signal indicating the detected depression amount of the brake pedal to the brake ECU 20.

[0043] The first wheel speed sensor 54 detects the rotation speed (wheel speed) of the drive wheels 50. The first wheel speed sensor 54 transmits a signal indicating the detected rotation speed of the drive wheels 50 to the brake ECU 20.

[0044] The second wheel speed sensor 56 detects the rotation speed of the driven wheels 52. The second wheel speed sensor 56 transmits a signal indicating the detected rotation speed of the driven wheels 52 to the brake ECU 20.

[0045] 1 has been described as an example in which the steering angle sensor 60, accelerator pedal depression amount sensor 62, brake pedal depression amount sensor 64, first wheel speed sensor 54, and second wheel speed sensor 56 are connected to the brake ECU 20 and transmit their detection results directly to the brake ECU 20. However, any of the sensors may be connected to another ECU and input to the brake ECU 20 via a communication bus or the central ECU 40.

[0046] Furthermore, the brake ECU 20 receives, for example, information regarding the action plan from the ADAS-ECU 10, as well as information regarding the operating status of various applications, information regarding other driving operations such as shift range, and information regarding the behavior of the vehicle 2.

[0047] The DCM 30 is a communication module configured to enable two-way communication with the data center 100 .

[0048] The central ECU 40 is configured to be able to communicate with, for example, the brake ECU 20, and is also configured to be able to communicate with the data center 100 using the DCM 30. The central ECU 40 transmits information received from the brake ECU 20 to the data center 100 via the DCM 30, for example.

[0049] In this embodiment, the central ECU 40 has been described as transmitting information received from the brake ECU 20 to the data center 100 via the DCM 30, but it may also have a function (gateway function) such as relaying communications between various ECUs, or it may include a memory (not shown) whose stored contents can be updated using update information from the data center 100, and predetermined information including update information stored in the memory from various ECUs is read out when the system of the vehicle 2 is started.

[0050] In vehicle 2 having the above-described configuration, it is conceivable that the vehicle speed of the vehicle is determined, the driving scene of the vehicle is determined, the driver's line of sight state is determined, the vehicle speed of the vehicle and the driving scene of the vehicle are used to determine a judgment range, the vehicle speed of the vehicle and the driving scene of the vehicle are used to determine a judgment time, and using the driver's line of sight state and the judgment range and judgment time that depend on the vehicle speed and the driving scene of the vehicle, it is determined whether the driver's line of sight direction has remained outside the judgment range for the judgment time, and whether the driver is looking away.

[0051] In this case, when data is transmitted from an ECU that performs the above-described processing, it is required to reduce the amount of data.

[0052] Therefore, the brake ECU 20 determines whether a predetermined situation exists, and if so, calculates information about the predetermined situation as a feature, converts the feature into a statistical quantity, and transmits the statistical quantity of the feature to the outside.

[0053] A feature obtained by statisticizing a plurality of feature quantities has a smaller data volume than a plurality of feature quantities that are not statisticized, and as a result, the data volume of the feature quantities can be reduced and transmitted.

[0054] 2 is a diagram illustrating an example of the configuration of a vehicle information processing device according to this embodiment. The vehicle information processing device according to this embodiment is realized by a brake ECU 20.

[0055] The brake ECU 20 includes a first processing unit 22, a second processing unit 24, and a third processing unit 26. The first processing unit 22, the second processing unit 24, and the third processing unit are virtually configured inside the brake ECU 20 by the CPU 21, the memory 25, and the input / output interface 23 of the brake ECU 20 operating in cooperation with each other.

[0056] The first processing unit 22 receives information indicating the depression amount of the accelerator pedal and information indicating the depression amount of the brake pedal as information related to the driving operation of the vehicle 2. Furthermore, the first processing unit 22 receives a request for an action plan from the ADAS-ECU 10 and information indicating the operation state of the driving assistance system as information related to the operation state of the driving assistance of the vehicle 2. Furthermore, the first processing unit 22 receives information indicating detection results from various sensors as information related to the behavior of the vehicle 2. The first processing unit 22 outputs to the second processing unit 24 the input information received during a period in which a predetermined condition is satisfied during the period in which the input information is received.

[0057] The second processing unit 24 calculates a feature quantity related to the operation of the vehicle 2 using the input information received during a period in which a predetermined condition is met during the period in which the input information is received.

[0058] Fig. 3 is a diagram illustrating an example of processing executed by second processing unit 24. As shown in Fig. 3, input information received during a period in which a predetermined condition is met within a period in which input information is received is input to second processing unit 24. Second processing unit 24 uses the input information to determine whether the predetermined condition is met.

[0059] The predetermined conditions include a condition that the driving situation of the vehicle 2 is a predetermined driving situation corresponding to the feature amount. The predetermined conditions are set in advance based on the calculated feature amount.

[0060] If it is determined that the predetermined condition is met, the second processing unit 24 turns on a met flag and outputs a signal indicating the state of the met flag as a scene identification signal.

[0061] Furthermore, when it is determined that the predetermined condition is met, the second processing unit 24 calculates a feature amount related to the operation of the vehicle 2 using input information received during the period in which the predetermined condition is met. For example, when the predetermined condition is met, the second processing unit 24 calculates the feature amount and stores (saves) the calculated feature amount in the memory 25 in association with a time. The second processing unit 24 outputs the calculated feature amount together with a scene identification signal and the calculation time.

[0062] The third processing unit 26 uses the information output from the second processing unit 24 to perform pre-processing (e.g., processing to generate information about changes in the vehicle 2) before transmitting information to the central ECU via a CAN (Controller Area Network). As pre-processing, the third processing unit 26 performs concealment of the feature amount (e.g., statistical processing) and detects changes in the feature amount (e.g., changes from past trips or the presence or absence of sudden changes). For example, when the state of the establishment flag included in the scene identification signal is in a predetermined state (e.g., the on state), the third processing unit 26 generates information about changes in the vehicle 2 using the information output from the second processing unit 24.

[0063] Fig. 4 is a diagram illustrating an example of processing executed in the third processing unit 26. As shown in Fig. 4, the scene classification signal, the feature amount, and information indicating the calculation time are input to the third processing unit 26 from the second processing unit 24.

[0064] The third processing unit 26 outputs information required for determining whether the history of changes in the feature amount corresponds to a predetermined state at the data center 100. The third processing unit 26 outputs the generated information to the central ECU 40.

[0065] The central ECU 40 transmits the information input from the third processing unit 26 to the data center 100 via the DCM 30.

[0066] The information transmitted from the DCM 30 to the data center 100 includes, for example, a processing time, a scene identification number, and feature amounts (there are multiple sets of scene identification numbers and feature amounts). Therefore, the data center 100 stores the information input from the DCM 30 as a single data block in the storage device 120. This enables the data center 100 to acquire statistics regarding changes in the feature amounts of each of the vehicles 2 and 3 that can communicate with the data center 100, as well as statistics regarding changes in the driving behavior characteristics of the drivers.

[0067] 5 is a flowchart showing the flow of processing related to feature quantities executed by the brake ECU 20 and the central ECU 40. Referring to FIG. 5, the feature quantity transmission processing executed by the brake ECU 20 is called and executed by a higher-level processing at every predetermined control period. The feature quantity reception processing executed by the central ECU 40 is called and executed by a higher-level processing at every predetermined control period.

[0068] First, the CPU 21 of the brake ECU 20 determines whether or not the data acquisition period for calculating the feature amount is the same (for example, a relatively short period such as every 1000 ms) (step S211). If it is determined that the data acquisition period is not the same (NO in step S211), the CPU 21 proceeds to step S231.

[0069] On the other hand, if it is determined that it is the acquisition period (YES in step S211), the CPU 21 acquires data for calculating feature quantities from the ADAS-ECU 10 or the like (step S212). Next, the CPU 21 identifies a collection scene from the acquired data (step S213). The collection scene is, for example, (1) a scene in which the distance to the preceding vehicle has undergone a predetermined change that allows estimation of driver behavior that reduces the risk with the preceding vehicle, (2) a scene in which a tire-related value (for example, the absolute value of the steering wheel angular velocity, the absolute value of the vector sum of the vehicle acceleration) has changed, (3) a scene in which the steering angle and acceleration of the vehicle 2 have changed, (4) a scene in which the driver has operated the accelerator pedal and the brake pedal, and (5) a scene in which the wheel speed of the vehicle 2 has changed.

[0070] Then, CPU 21 determines whether the current situation is a predetermined collection scene (step S221). If CPU 21 determines that the current situation is not a predetermined collection scene (NO in step S221), CPU 21 proceeds to the process of step S225.

[0071] On the other hand, if it is determined that the scene is a predetermined collection scene (YES in step S221), the CPU 21 increments the total number of scenes Ns, that is, adds 1 to the original Ns to set the new value as Ns (step S222).

[0072] Next, the CPU 21 determines whether a target event has occurred (step S223). (1) If the collected scene is a scene in which the distance between the vehicle and the preceding vehicle has undergone a predetermined change that allows estimation of driver behavior that reduces the risk to the preceding vehicle, the target event is an event in which the driver has performed risk-reducing behavior in such a scene. (2) If the collected scene is a scene in which a tire-related value (e.g., the absolute value of the steering wheel angular velocity or the absolute value of the vector sum of the vehicle acceleration) has changed, the target event is an event that satisfies a predetermined criterion for determining that the tire condition has changed. (3) If the collected scene is a scene in which the steering angle and acceleration of the vehicle 2 have changed, the target event is an event that satisfies a predetermined criterion for determining that the slip ratio of the drive wheels has changed. (4) If the collected scene is a scene in which the driver operates the accelerator pedal and brake pedal, the target event is an event that satisfies a predetermined criterion for determining the driver's proficiency. (5) If the collected scene is a scene in which the wheel speed of the vehicle 2 has changed, the target event is an event that satisfies a predetermined criterion for determining that the vehicle is traveling on a highway. If it is determined that the target event has not occurred (NO in step S223), CPU 21 proceeds to the process of step S225.

[0073] On the other hand, if it is determined that the target event has occurred (YES in step S223), the CPU 21 counts the number of times Nb that the target event has occurred, that is, adds 1 to the original Nb to set the new Nb (step S224).

[0074] Next, the CPU 21 calculates the feature quantity = Nb / Ns (step S225). The CPU 21 performs feature concealment (for example, statistical processing) as pre-processing of the current value of the feature quantity for transmission to the CAN (step S226). Note that calculating the frequency such as Nb / Ns is also statistical processing and is included in concealment. The CPU 21 transmits the concealed feature quantity to the central ECU 40 via the CAN (step S227).

[0075] 6 is a diagram illustrating data transmitted via the CAN. Referring to FIG. 6, transmission data frames 111A to 111N transmitted to the central ECU 40 include data classification numbers 101A to 101N, processing times 102A to 102N, collected scenes 103A to 103N, and statistically quantified feature amounts 104A to 104N, respectively.

[0076] The data of the data classification numbers 101A to 101N include data indicating numbers for classifying the types of data included in these transmission data frames 111A to 111N, for example, data indicating numbers for classifying the types of data such as vehicle control data or notification data in a user interface, etc. In Fig. 6, the data of the data classification numbers 101A to 101N are set to data of numbers indicating that the data is a data type including statistically quantified feature amounts in each collection scene.

[0077] The processing times 102A to 102N include data indicating the time when the feature amounts included in these transmission data frames 111A to 111N were calculated. The collected scenes 103A to 103N include data indicating numbers that identify the collection scenes of the feature amounts included in these transmission data frames 111A to 111N. The statistically quantified feature amounts 104A to 104N include data indicating the statistically quantified feature amounts.

[0078] 5, the CPU 41 of the central ECU 40 determines whether or not the transmission data frames 111A to 111N of the feature quantities of the current values ​​have been received from the brake ECU 20 (step S411). If it is determined that the current values ​​have been received (YES in step S411), the CPU 41 stores the data of the received transmission data frames 111A to 111N of the current values ​​in the memory 45 (step S412).

[0079] The CPU 21 of the brake ECU 20 determines whether or not it is the start of operation of the vehicle 2 (start of a trip) (step S231). If it is determined that it is not the start of a trip (NO in step S231), the CPU 21 returns the process to be executed to the upper process that called this feature amount transmission process.

[0080] On the other hand, if it is determined that the trip has started (YES in step S231), the final feature value Nb / Ns of the previous trip is added to the integrated value ΣNb / ΣNs of the past feature values ​​(step S232), and the integrated integrated value ΣNb / ΣNs of the past feature values ​​is transmitted to the central ECU 40 via the CAN (step S233). The transmission data frame at this time is as described in FIG. 6.

[0081] The CPU 41 of the central ECU 40 determines whether or not it has received the past integrated value ΣNb / ΣNs of the feature amount from the brake ECU 20 (step S431). If it determines that it has not received the past value (NO in step S431), the CPU 41 returns the process to be executed to the upper process that called this feature amount receiving process.

[0082] On the other hand, if it is determined that past values ​​have been received (YES in step S431), the CPU 41 stores the received past value data in the memory 45 (step S432) and transmits it to the data center 100 (step S433). After that, the CPU 41 returns the processing to be executed to the upper process that called this feature amount receiving processing.

[0083] Fig. 7 is a diagram for explaining data transmitted to the data center 100. Referring to Fig. 7, the data transmitted to the data center 100 is transmitted using a RoB (Record of Behavior) mechanism. The RoB is a system for storing abnormalities in the system of the vehicle 2 and transmitting the information to an external device (for example, the data center 100).

[0084] The RoB data 121A to 121C transmitted and stored by the RoB each include a RoB code 105A to 105C defined in the design and indicating the type of data, the data length + data 106A to 106C of the target included in the RoB data 121A to 121C, the trip 107A to 107C in which the data occurred (the cumulative mileage of vehicle 2 since its manufacture), and the time 108A to 108C in which the data occurred.

[0085] In this embodiment, the RoB codes 105A to 105C include data indicating a number that classifies the type of data contained in the RoB data 121A to 121C, and in this embodiment, a code is set that indicates that the RoB data 121A to 121C is a data type that includes statistically quantified features in each collection scene.

[0086] In this embodiment, data length + data 106A-106C includes the collection scene data, feature data, and the combined data length of these data. Trips 107A-107C where this data occurred include the trips where this RoB data 121A-121C was created. Times 108A-108C where this data occurred include data indicating the time when the feature was calculated.

[0087] [Variations] (1) In the above-described embodiment, statistical processing (concealment) is performed by calculating the frequency Nb / Ns. However, this is not limiting, and concealment may be performed by other statistical processing, such as calculating the average value, the minimum value, the maximum value, or the standard deviation. Furthermore, concealment may be performed by calculating abruptly changing feature amounts or gradually changing feature amounts.

[0088] (2) In the above-described embodiment, the past feature amount is transmitted at the start of the trip as shown in step S231 of Fig. 5. However, this is not limited to this, and the past feature amount may be transmitted at other timings, such as at the end of the trip or a predetermined time (for example, several minutes, such as five minutes) after the start of the trip.

[0089] (3) In the above-described embodiment, as shown in FIG. 1, the vehicle 2 includes the central ECU 40. However, the present invention is not limited to this, and the vehicle 2 may not include the central ECU 40. In this case, the brake ECU 20 creates the RoB data 121A to 121C shown in FIG. 7 and transmits them to the data center 100.

[0090] (4) In the above-described embodiment, the process of Fig. 5 is executed by the brake ECU 20. However, this is not limiting, and the process of Fig. 5 may be executed by another information processing device, for example, another ECU of the vehicle 2 or an external information processing device (for example, the data center 100).

[0091] (5) The above-described embodiments can be understood as disclosure of an information processing device such as the brake ECU 20, as disclosure of a vehicle 2, 3 including the information processing device, as disclosure of an information processing system such as a vehicle information management system 1 including the vehicle 2, 3 and a server such as a data center 100, as disclosure of an information processing method executed by the information processing device, or as disclosure of an information processing program executed by the information processing device.

[0092] [summary] (1) As shown in FIG. 1, the brake ECU 20 is an information processing device that calculates features related to the driver's driving, and includes a CPU 21 that calculates the features and an input / output interface 23 that transmits information related to the calculated features to an external device. As shown in FIGS. 2 to 7, the CPU 21 identifies whether a predetermined situation (e.g., a captured scene) exists (e.g., steps S212 and S221). If the predetermined situation is identified, the CPU 21 calculates information related to the predetermined situation as features (e.g., steps S222 to S225) and converts the features into statistics (e.g., steps S225 and S232). The input / output interface 23 transmits the converted statistics to an external device (e.g., steps S227 and S233).

[0093] As a result, when a predetermined situation is identified, information about the predetermined situation is calculated as a feature, the feature is statistically quantified, and the statistical feature is transmitted to the outside. A feature obtained by quantifying a plurality of feature quantities has a smaller amount of data than a plurality of feature quantities that are not statistically quantified. As a result, the amount of data of the feature quantities can be reduced before transmission.

[0094] 5 and 6, the input / output interface 23 transmits the time when the feature amount is calculated together with information about the feature amount to the outside (for example, step S227, step S233). This makes it possible to externally identify the time when the feature amount is calculated.

[0095] (3) As shown in Fig. 5, the CPU 21 calculates information about the frequency of the target event in a predetermined situation as a feature (for example, step S225). This makes it possible to transmit the information about the frequency of the target event in a predetermined situation as a feature to the outside.

[0096] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present disclosure is defined by the claims, not by the description of the above embodiments, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0097] 1 Vehicle information management system, 2, 3 Vehicle, 6 Communication network, 7 Base station, 10 ADAS-ECU, 11, 21, 41 CPU, 13, 23, 43 Input / output interface, 15, 25, 45 Memory, 20 Brake ECU, 22 First processing unit, 24 Second processing unit, 26 Third processing unit, 30 DCM, 40 Central ECU, 50 Drive wheel, 52 Driven wheel, 54 First wheel speed sensor, 56 Second wheel speed sensor, 60 Steering angle sensor, 62 Accelerator pedal depression amount sensor, 64 Brake pedal depression amount sensor, 71 Forward-facing camera, 72 Millimeter-wave radar, 100 Data center, 101A to 101N Data classification number, 102A to 102N Processing time, 103A to 103N Collection scene, 104A to 104N Feature, 105A to 105C RoB code, 106A to 106C data length + data, 107A to 107C trip, 108A to 108C time, 110 control device, 111A to 111N data frame for transmission, 120 storage device, 121A to 121C RoB data, 130 communication device, 140 communication bus.

Claims

1. An information processing device that calculates a feature amount related to a driver's driving, a processor for calculating the feature amount; a receiving unit that receives, as input information, at least one of information regarding a driving operation of a vehicle, information regarding an operating state of a driving assistance system of the vehicle, and information regarding a behavior of the vehicle; a transmitting unit that transmits information about the calculated feature amount to an external device, The processor: determining whether a predetermined condition is satisfied when the driving operation, the operating state, or the behavior becomes a predetermined state based on the input information received by the receiving unit; If the predetermined condition is met, the situation is determined to be a predetermined situation; When the predetermined situation is identified, information relating to the predetermined situation is calculated as a feature amount using the input information accepted by the accepting unit during a period in which the predetermined condition is satisfied during a period in which the input information is accepted; converting the feature amount into a statistical quantity; The transmission unit transmits the statistically quantified feature to an outside.

2. The information processing apparatus according to claim 1 , wherein the transmission unit transmits the time at which the feature amount was calculated together with information related to the feature amount to an external device.

3. The processor: The information processing apparatus according to claim 1 , wherein information relating to a frequency of a target event in the predetermined situation is calculated as the feature amount.

4. A vehicle including an information processing device that calculates a feature amount related to a driver's driving, The information processing device includes: a processor for calculating the feature amount; a receiving unit that receives, as input information, at least one of information regarding a driving operation of the vehicle, information regarding an operating state of a driving assistance system of the vehicle, and information regarding a behavior of the vehicle; a transmitting unit that transmits information about the calculated feature amount to an external device, The processor: determining whether a predetermined condition is satisfied when the driving operation, the operating state, or the behavior becomes a predetermined state based on the input information received by the receiving unit; If the predetermined condition is met, the situation is determined to be a predetermined situation; When the predetermined situation is identified, information relating to the predetermined situation is calculated as a feature amount using the input information accepted by the accepting unit during a period in which the predetermined condition is satisfied during a period in which the input information is accepted; converting the feature amount into a statistical quantity; The transmission unit transmits the statistically quantified feature to an outside of the vehicle.

5. An information processing system including a vehicle including an information processing device that calculates a feature amount related to a driver's driving, and a server, The information processing device includes: a processor for calculating the feature amount; a receiving unit that receives, as input information, at least one of information regarding a driving operation of the vehicle, information regarding an operating state of a driving assistance system of the vehicle, and information regarding a behavior of the vehicle; a transmitting unit that transmits information about the calculated feature amount to an external device, The processor: determining whether a predetermined condition is satisfied when the driving operation, the operating state, or the behavior becomes a predetermined state based on the input information received by the receiving unit; If the predetermined condition is met, the situation is determined to be a predetermined situation; When the predetermined situation is identified, information relating to the predetermined situation is calculated as a feature amount using the input information accepted by the accepting unit during a period in which the predetermined condition is satisfied during a period in which the input information is accepted; converting the feature amount into a statistical quantity; The transmission unit transmits the statistically quantified feature to an outside.

6. An information processing method executed by an information processing device that calculates a feature amount related to a driver's driving, The information processing device includes: a processor for calculating the feature amount; a receiving unit that receives, as input information, at least one of information regarding a driving operation of a vehicle, information regarding an operating state of a driving assistance system of the vehicle, and information regarding a behavior of the vehicle; a transmitting unit that transmits information about the calculated feature amount to an external device, The information processing method includes the steps of: determining whether a predetermined condition is satisfied when the driving operation, the operating state, or the behavior becomes a predetermined state based on the input information received by the receiving unit; a step of identifying a predetermined situation when the predetermined condition is met; when the predetermined situation is identified, calculating information about the predetermined situation as a feature amount using the input information accepted by the accepting unit during a period in which the predetermined condition is satisfied during a period in which the input information is accepted; converting the feature amount into a statistical quantity; and transmitting the statistically quantified feature quantity to an external device by the transmitting unit.

7. An information processing program executed by an information processing device that calculates a feature amount related to a driver's driving, The information processing device includes: a processor for calculating the feature amount; a receiving unit that receives, as input information, at least one of information regarding a driving operation of a vehicle, information regarding an operating state of a driving assistance system of the vehicle, and information regarding a behavior of the vehicle; a transmitting unit that transmits information about the calculated feature amount to an external device, The information processing program determining whether a predetermined condition is satisfied when the driving operation, the operating state, or the behavior becomes a predetermined state based on the input information received by the receiving unit; a step of identifying a predetermined situation when the predetermined condition is met; when the predetermined situation is identified, calculating information about the predetermined situation as a feature amount using the input information accepted by the accepting unit during a period in which the predetermined condition is satisfied during a period in which the input information is accepted; converting the feature amount into a statistical quantity; and causing the transmitting unit to transmit the statistically quantified feature to an external device.

Images