Control device for vehicle

Abstract

To inhibit unnecessary learning of a feature of a vehicle operation by a driver in a particular driving scene different from a usual one.SOLUTION: A control device 6 for a vehicle 100 sets a recommended value of a control parameter having an influence on a vehicle behavior so that the vehicle behavior becomes suitable for a driver, on the basis of a learning result obtained by learning a feature of vehicle operation by the driver. On the basis of a past driving history of the driver, the control device determines whether a driving scene during traveling is a particular driving scene different from usual driving scenes which account for a large proportion of driving scenes of the driver. If the driving scene during the traveling is the particular driving scene, the control device stops learning of the feature of the vehicle operation by the driver.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a vehicle control device. [Background technology]

[0002] Patent Document 1 discloses a conventional cruise control system that learns vehicle behavior that reflects the driver's preferences based on changes in the driver's biological information accompanying changes in the vehicle behavior. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2020-132124 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the conventional cruise control system described above, vehicle behavior is learned even in special driving situations that are different from normal driving situations, so there is a risk that vehicle behavior in special driving situations that are different from normal vehicle behavior may be unnecessarily learned.

[0005] The present invention has been made in view of such problems, and has an object to prevent unnecessary learning of the characteristics of a driver's vehicle operation in special driving situations. [Means for solving the problem]

[0006] In order to solve the above problems, a vehicle control device according to one embodiment of the present invention is configured to set recommended values ​​of control parameters that affect vehicle behavior so that the vehicle behavior is suitable for the driver based on the learning results of the characteristics of vehicle operation by the driver, determine based on the driver's past driving history whether the driving scene while traveling is a special driving scene that is different from normal driving scenes which account for a large proportion of the driver's driving scenes, and stop learning of the characteristics of vehicle operation by the driver if the driving scene while traveling is a special driving scene. Effect of the Invention

[0007] According to this aspect of the present invention, it is possible to prevent unnecessary learning of the characteristics of the driver's vehicle operation in special driving situations. [Brief description of the drawings]

[0008] [Figure 1] 1 is a schematic system configuration diagram of a vehicle according to an embodiment of the present invention; [Diagram 2] 10 is a flowchart illustrating an example of a process for setting a special driving scene for each driver. [Diagram 3] 4 is a flowchart illustrating an example of a vehicle operation learning process. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following description, like components are designated by like reference numerals.

[0010] FIG. 1 is a schematic system configuration diagram of a vehicle 100 according to an embodiment of the present invention.

[0011] The vehicle 100 includes an external environment sensor 1, an occupant sensor 2, a vehicle sensor 3, a human machine interface (HMI) 4, an actuator 5, and a control device 6. The external environment sensor 1, the occupant sensor 2, the vehicle sensor 3, the HMI 4, the actuator 5, and the control device 6 are communicatively connected to each other via an in-vehicle network 110 that complies with a standard such as a controller area network.

[0012] The external environment sensor 1 is a sensor for generating external environment data related to the environment around the vehicle 100. In this embodiment, the vehicle 100 includes, as the external environment sensor 1, one or more external cameras 11 for capturing images of the surroundings of the vehicle 100. Note that, in addition to the external camera 11, the external environment sensor 1 may include a distance measurement sensor (e.g., a LiDAR (Light Detection And Ranging) or a millimeter wave radar sensor) for measuring distances to targets such as other vehicles, pedestrians, and buildings around the vehicle 100.

[0013] The occupant sensor 2 is a sensor for generating occupant data related to a vehicle occupant. In this embodiment, the vehicle 100 includes, as the occupant sensor 2, a driver monitor camera 21 for capturing an image of the driver's appearance including the driver's face, and one or more internal cameras 22 for capturing images of occupants in the vehicle.

[0014] The vehicle sensor 3 is a sensor for generating vehicle data related to the state of the vehicle 100 such as the vehicle's traveling speed, acceleration, jerk (jerk), lateral acceleration, speed of change of steering angle, current position, etc. In this embodiment, the vehicle 100 includes, as the vehicle sensors 3, a speed sensor 31, an acceleration sensor 32, a yaw rate sensor 33, a steering angle sensor 34, a GNSS receiver 35, etc.

[0015] The HMI 4 is a user interface for exchanging information between the vehicle 100 and its occupants. The HMI 4 includes an output device 41, such as a center display, for notifying the vehicle occupant through the vehicle occupant's bodily senses (for example, vision, hearing, touch, etc.), and an input device 42, such as a touch panel or operation buttons, for the vehicle occupant to perform input operations and response operations.

[0016] The actuator 5 is various control components that are driven to make the vehicle 100 run, and includes, for example, a drive device (e.g., at least one of an internal combustion engine and a motor) required for accelerating the vehicle 100, a braking device (e.g., a brake actuator) required for braking the vehicle 100, and a steering device (e.g., a steering motor) required for steering the vehicle 100.

[0017] The control device 6 is an ECU (Electronic Control Unit) including an in-vehicle communication interface 61, a storage unit 62, and a processing unit 63.

[0018] The in-vehicle communication interface 61 includes an interface circuit for connecting the control device 6 to the in-vehicle network 110 .

[0019] The storage unit 62 has a storage medium such as a hard disk drive (HDD), a solid disk drive (SSD), or a semiconductor memory, and stores various computer programs and data used for processing in the processing unit 63.

[0020] The processing unit 63 has one or more central processing units (CPUs) and their peripheral circuits. The processing unit 63 executes various computer programs stored in the storage unit 62 and performs overall control of the vehicle 100, and is, for example, a processor.

[0021] As an example of the processing performed by the processing unit 63, for example, the processing unit 63 identifies the driver of the vehicle 100, and acquires driving history data of each driver every time the driver drives the vehicle 100, and stores the data in the storage unit 62. The driving history data includes, for example, various vehicle information such as the driving time of each driver, the time when each driver used the vehicle 100, and the driving speed when each driver drove the vehicle 100, as well as the number of passengers, weather, location information, remaining fuel information, and the like.

[0022] In addition, for example, the processing unit 63 learns the vehicle operation characteristics of each driver of the vehicle 100, and performs personalized control by proposing recommended setting values ​​or recommended control modes to each driver via the HMI 4 for various control parameters that affect the vehicle behavior (e.g., upper and lower limits of acceleration, upper and lower limits of jerk, upper limit of lateral acceleration, upper limit of the rate of change of steering angle, setting value of inter-vehicle distance, etc.) so that the vehicle behavior suits the preferences of each driver during automatic driving or when various driving assistance such as following driving is performed.

[0023] Here, the driver's vehicle operation may vary between a normal driving scene, which occupies a large proportion of the driver's driving scenes, and a special driving scene that is different from the normal driving scene. Examples of special driving scenes include when the number of passengers in the vehicle is different from the normal number of passengers, when the weather is different from the normal weather, when the vehicle is used for a different period of time than the normal use, when the remaining energy of the vehicle (remaining fuel or battery) is extremely low, and when the vehicle is used in a different area from the normal use area due to travel or the like.

[0024] Therefore, for example, for a driver who spends a lot of time driving alone, a normal driving scene occurs when there is one passenger in the vehicle, and a special driving scene occurs when there are two or more passengers in the vehicle. Also, for example, if a driver spends more time driving on fine or cloudy days than on other bad weather such as rain, snow, or thick fog, then fine or cloudy days will be normal driving scenes, and bad weather will be special driving scenes. Note that, since the driver usually spends more time driving on fine or cloudy days than on bad weather, bad weather can be unequivocally considered to be a special driving scene.

[0025] For example, if a driver frequently uses a vehicle during commuting hours, or if the driver uses the vehicle for a longer period of time during commuting hours than other periods of time, the commuting hours will be the normal driving scene, and the other periods of time will be the special driving scene. For example, if a driver frequently uses a vehicle during the day, or if the driver uses the vehicle for a longer period of time during the day than at night, the daytime will be the normal driving scene, and the nighttime will be the special driving scene. Note that, since the driving time during the day is usually longer than at night, the nighttime can be unequivocally considered to be the special driving scene.

[0026] In a special driving scene, the vehicle operation may be more cautious or, conversely, more agile than in a normal driving scene. When the driver's vehicle operation changes, the vehicle behavior naturally changes. Therefore, if the characteristics of the driver's vehicle operation in a special driving scene, which occupies a small proportion of the driver's driving scenes, are learned, the vehicle behavior during automatic driving or driving assistance may deviate from the driver's preferred vehicle behavior, and the driver may feel uncomfortable with the vehicle behavior. Therefore, in this embodiment, it is determined whether the current driving scene is a special driving scene, and if it is a special driving scene, the characteristics of the driver's vehicle operation are not learned.

[0027] 2 is a flowchart illustrating an example of a process for setting a special driving scene for each driver, which is performed by the processing unit 63 and, in turn, the control device 6. The control device 6 performs this routine, for example, when the vehicle 100 is started.

[0028] In step S1, the control device 6 identifies the driver based on an external image of the driver captured by the driver monitor camera 21.

[0029] In step S2, the control device 6 refers to the driving history data of the specified driver and determines whether the time the driver has driven alone is the longest among the total driving time in a certain period in the past. If the time the driver has driven alone is the longest, the control device 6 proceeds to the process of step S3, and if not, proceeds to the process of step S4.

[0030] In step S3, the control device 6 sets the case where the number of passengers is two or more as a special driving scene for the specified driver.

[0031] In step S4, the control device 6 refers to the driving history data of the identified driver and determines whether the time the passenger sits in the passenger seat is longer than the time the passenger sits in the back seat. If the time the passenger sits in the passenger seat is longer than the time the passenger sits in the back seat, the control device 6 proceeds to processing in step S5, and if the time is shorter, the control device 6 proceeds to processing in step S6.

[0032] In step S5, the control device 6 sets a time when there is no passenger and when the passenger is not in the passenger seat as a special driving scene for the identified driver.

[0033] In step S6, the control device 6 sets a time when there is no passenger and when there is no passenger in the back seat as a special driving scene for the identified driver.

[0034] In step S7, the control device 6 refers to the driving history data of the identified driver and determines whether the driver's vehicle operation has changed due to the influence of the weather, specifically, whether the characteristics of the driver's vehicle operation have differed between fine weather or cloudy weather and bad weather such as rain, snow, or thick fog. If the driver's vehicle operation has changed due to the influence of the weather, the control device 6 proceeds to the process of step S8. On the other hand, if the driver's vehicle operation has not changed due to the influence of the weather, the control device 6 proceeds to the process of step S9 without setting a special driving scene for the weather, since there is no problem in learning the characteristics of the driver's vehicle operation regardless of the weather.

[0035] In step S8, the control device 6 sets bad weather as a special driving scene for the identified driver.

[0036] In step S9, the control device 6 refers to the driving history data of the identified driver and determines whether the daytime use time in the past certain period is longer than the nighttime use time. If the daytime use time in the past certain period is longer than the nighttime use time, the control device 6 proceeds to the process of step S10. On the other hand, if the daytime use time in the past certain period is shorter than the nighttime use time, the control device 6 ends the current process without setting a special driving scene for the use time of the vehicle 100.

[0037] In step S10, the control device 6 sets a nighttime driving scene as a special driving scene for a specified driver.

[0038] 3 is a flowchart illustrating an example of a vehicle operation learning process performed by the processing unit 63 and, ultimately, the control device 6. The control device 6 repeatedly executes this routine, for example, at a predetermined calculation interval.

[0039] In step S11, the control device 6 detects the current riding situation (number of passengers and their riding location), the current weather, and the current time, and determines whether the current driving scene corresponds to the special driving scene described above with reference to Fig. 2. If the current driving scene corresponds to the special driving scene described above with reference to Fig. 2, the control device 6 proceeds to processing in step S12. On the other hand, if the current driving scene corresponds to the special driving scene described above with reference to Fig. 2, the control device 6 proceeds to processing in step S13.

[0040] In step S12, the control device 6 stops various processes for learning the characteristics of the driver's vehicle operation (for example, processes for generating teacher data from the results of the driver's vehicle operation and control parameters that affect the vehicle behavior, etc.).

[0041] In step S13, the control device 6 determines whether the remaining energy of the vehicle 100 is less than a predetermined amount, since if the remaining energy of the vehicle 100 is extremely low, the vehicle operation may be changed from normal, such as by performing acceleration operations more slowly than normal. If the remaining energy of the vehicle 100 is less than the predetermined amount, the control device 6 determines that the current driving scene is a special driving scene and proceeds to processing of step S12. On the other hand, if the remaining energy of the vehicle 100 is equal to or greater than the predetermined amount, the control device 6 proceeds to processing of step S14.

[0042] In step S14, the control device 6 determines whether the area in which the vehicle 100 is used is different from the area in which it is usually used, since if the area in which the vehicle 100 is used is different from the area in which it is usually used, the vehicle operation may be different from the usual one. If the area in which the vehicle 100 is used is different from the area in which it is usually used, the control device 6 determines that the current driving scene is a special driving scene and proceeds to the process of step S12. On the other hand, if the area in which the vehicle 100 is used is not different from the area in which it is usually used, the control device 6 proceeds to the process of step S15.

[0043] In step S15, the control device 6 carries out various processes for learning the characteristics of the driver's vehicle operation.

[0044] The control device 6 of the vehicle 100 according to the present embodiment described above is configured to set recommended values ​​of control parameters that affect the vehicle behavior so that the vehicle behavior is suitable for the driver based on the learning result of learning the characteristics of the vehicle operation by the driver, to determine whether the driving scene during driving is a normal driving scene that occupies a large proportion of the driver's driving scenes, or a special driving scene different from the normal driving scene, based on the driver's past driving history, and to stop learning the characteristics of the vehicle operation by the driver if the driving scene during driving is a special driving scene. This makes it possible to suppress unnecessary learning of the characteristics of the vehicle operation of the driver in a special driving scene.

[0045] Although the embodiments of the present invention have been described above, the above-mentioned embodiments merely show some of the application examples of the present invention, and it is not intended that the technical scope of the present invention be limited to the specific configurations of the above-mentioned embodiments.

[0046] For example, in the above embodiment, the computer program executed in the control device 6 may be provided in a form recorded on a computer-readable portable recording medium, such as a semiconductor memory, a magnetic recording medium, or an optical recording medium. [Explanation of symbols]

[0047] 6. Control device 100 vehicles

Claims

[Claim 1] A control device for a vehicle, Based on a learning result of the characteristics of the vehicle operation by the driver, a recommended value of a control parameter that affects the vehicle behavior is set so that the vehicle behavior is suitable for the driver; Based on the past driving history of the driver, it is determined whether a driving scene during travel is a special driving scene different from a normal driving scene which occupies a large proportion of the driving scenes of the driver; If the driving scene during driving is the special driving scene, learning of the characteristics of the vehicle operation by the driver is stopped. Vehicle control device.

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