Vehicle control device

Abstract

To provide a vehicle control device that can improve a driving capability of a driver.SOLUTION: A vehicle control device 100 comprises a controller 10 that can control a vehicle 1. The controller 10 is configured to estimate a traffic risk value, a travelling risk value and a driving capability value. The controller 10 executes first setting change processing for changing a threshold at which automatic vehicle posture stabilization control is started so that the automatic vehicle posture stabilization control is executed more quickly, when the travelling risk is not avoided by the driving capability; executes second setting change processing for changing a threshold at which automatic entering avoidance control is started so that the automatic entering avoidance control is executed more quickly, when the travelling risk is not avoided by the driving capability; and controls the vehicle 1 so that the vehicle travels on a target travelling route, when the traffic risk and the travelling risk are not avoided by the driving capability or when the driving capability is lower than a predetermined level.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present invention relates to a vehicle control device, and more particularly to a vehicle control device for driving assistance. [Background technology]

[0002] Currently, various automated driving technologies are being developed, with two development philosophies. The first development philosophies are the pursuit of convenience, and in technologies based on this development philosophies, the vehicle performs almost all vehicle operations on behalf of the driver. On the other hand, the second development philosophies are the pursuit of revitalizing the driver's mind and body, and in technologies based on this development philosophies, the driver performs vehicle operations by utilizing their own driving ability as much as possible, with the vehicle intervening in vehicle operations as an auxiliary.

[0003] To stimulate the driver's mind and body, it is preferable that the driving ability required of the driver according to the traffic environment and the like is balanced with the driver's current driving ability. If there is an imbalance between these, the driver may find driving boring or, conversely, experience psychological stress. In particular, elderly people with reduced driving ability and those with mild cognitive impairment (MCI) are prone to feeling stress.

[0004] Therefore, based on the second development concept, the present applicant has proposed a vehicle control device that provides driving assistance or driving load so as to balance required driving ability and current driving ability (see, for example, Patent Document 1). With this vehicle control device, the driver can drive the vehicle in a state where the required driving ability and current driving ability are balanced. This allows the driver to drive safely in a fun and focused state, regardless of the difficulty of the traffic environment or the level of the driver's current driving ability. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 6555649 Summary of the Invention [Problem to be solved by the invention]

[0006] However, in the technology described in Patent Document 1, the driver's current driving ability deficiency is compensated for by the driving assistance provided by the vehicle, so the driver does not need to maintain or improve his or her current driving ability, and there is a risk that the driver's current driving ability may actually deteriorate over time.

[0007] The present invention has been made to solve the above problems, and has an object to provide a vehicle control device that can improve the driving ability of a driver. [Means for solving the problem]

[0008] In order to achieve the above object, the present invention provides a vehicle control device that performs driving assistance control of a vehicle so that the vehicle travels in accordance with a traffic environment and a travel environment around the vehicle, the vehicle control device including a controller that calculates a target travel route based on the traffic environment and the travel environment and controls the vehicle so that the vehicle travels on the target travel route, the controller being configured to execute a traffic environment evaluation process that estimates a traffic risk value that represents the magnitude of a traffic risk that occurs when the vehicle enters a risk area in the traffic environment, the risk area including traffic participants and / or boundaries of a travel path; a travel environment evaluation process that estimates a travel risk value that represents the magnitude of a travel risk in the travel environment that destabilizes the attitude of the vehicle; and a driving ability evaluation process that estimates a driving ability value that represents the magnitude of the driving ability of a driver of the vehicle to avoid the traffic risk and the travel risk, the controller but Driving risk value Because it is smaller When it is determined that the driving risk cannot be avoided due to driving ability, a first setting change process is executed to change the threshold value at which the automatic vehicle attitude stabilization control for stabilizing the attitude of the vehicle is started so that the automatic vehicle attitude stabilization control for stabilizing the attitude of the vehicle is executed earlier, and the driving ability value but Traffic risk value Because it is smallerWhen it is determined that the traffic risk cannot be avoided by the driving ability, a second setting change process is performed to change the threshold at which the automatic entry avoidance control is started so that the automatic entry avoidance control for preventing the vehicle from entering the risk area is executed earlier, and the driving ability value but , traffic risks Value and driving risk value Because each of Traffic and driving risks Both If it is determined that the accident cannot be avoided due to driving ability, or if the driving ability score is is smaller than the predetermined threshold. If it is determined that the driving ability is lower than a predetermined level, the system controls the vehicle so that it travels along a target travel route.

[0009] According to the present invention configured as described above, risks when a vehicle travels are classified into traffic risks that depend on the traffic environment and driving risks that depend on the driving environment. Depending on the risk that is estimated to be unavoidable due to the driver's driving ability, driving assistance control such as automatic entry avoidance control or automatic vehicle stabilization control can be intervened earlier. Thus, the present invention makes it easier for appropriate driving assistance control corresponding to a lower level of driving ability among the driver's driving abilities corresponding to the two risks to intervene. Furthermore, since the present invention intervenes early when the vehicle's risk level is low, risk avoidance vehicle operation by the driving assistance control becomes a relatively gradual operation, and sudden risk avoidance vehicle operation is avoided. According to the present invention, the early and gradual intervention of driving assistance control allows the driver to learn situations (surrounding environment and vehicle operation by the driver) in which driving assistance control is likely to intervene. Furthermore, the driver can improve vehicle operation so that driving assistance control does not intervene for similar risks, thereby improving low-level driving ability over the long term.

[0010] In the present invention, preferably, the controller controls an automatic vehicle attitude stabilization control. Oga When executed, the automatic vehicle stabilization control Oga Notify the driver of the execution When the automatic entry avoidance control is executed, the driver of the vehicle is notified that the automatic entry avoidance control has been executed. In the present invention configured as described above, the driver can be notified that the driving assistance control has intervened.

[0011] Also, in the present invention, preferably, the controller Run When the risk of bankruptcy disappears, the first setting change procedure is performed. Reasonably Reset the thresholds changed in the When the traffic risk disappears, the threshold value changed in the second setting change process is returned to the initial setting threshold value of the vehicle. In the present invention configured in this manner, the setting of the threshold value for the driving assistance control can be changed each time a risk occurs based on the current driving ability value and the traffic risk value or the driving risk value. Therefore, as the driving ability improves, the threshold value will no longer be changed from the initial threshold value, and the higher the driver's driving ability, the greater the degree of freedom in vehicle operation.

[0012] In addition, preferably in the present invention, the driving ability value includes a basic driving ability value and a short-term driving ability value, the controller learns the vehicle operation of the driver of the vehicle to update the driver model, and estimates the basic driving ability value for avoiding traffic risks and driving risks based on the driver model, and the controller estimates the short-term driving ability value based on the alertness and / or driving motivation of the driver of the vehicle. In the present invention configured in this manner, by dividing driving ability into driving skills that fluctuate over the long term and short-term driving ability (noise factors) that fluctuate over the short term, it is possible to more accurately determine current driving ability and provide appropriate driving assistance control.

[0013] In addition, in the present invention, preferably, the controller executes a driving willingness determination process to determine the driver's willingness to drive, and in this driving willingness determination process, the controller is configured to determine the driver's willingness to drive based on at least the driver's facial expression, driving posture, or vehicle operation. [Effects of the Invention]

[0014] According to the vehicle control device of the present invention, the driving ability of the driver can be improved. [Brief explanation of the drawings]

[0015] [Figure 1] FIG. 2 is an explanatory diagram of vehicle control according to an embodiment of the present invention. [Figure 2]1 is a block diagram of a vehicle control device according to an embodiment of the present invention; [Figure 3] FIG. 2 is an explanatory diagram showing a processing flow of the vehicle control device according to the embodiment of the present invention. [Figure 4] 1 is a graph showing the relationship between a driver's driving ability and traffic risk and driving risk in an embodiment of the present invention. [Figure 5] 1 is a graph showing the relationship between willingness to drive and alertness in an embodiment of the present invention. [Figure 6] 1 is a table showing a driver's state according to the driver's willingness to drive and the level of alertness in an embodiment of the present invention. [Figure 7] 3 is a flowchart of a driving assistance control according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0016] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A vehicle control device according to an embodiment of the present invention will now be described with reference to the accompanying drawings. First, an overview of vehicle control provided by a vehicle control device according to an embodiment of the present invention will be described with reference to Fig. 1. Fig. 1 is an explanatory diagram of vehicle control.

[0017] The vehicle control device 100 of this embodiment (see FIG. 2) is configured on the premise that the driver will be the one to operate the vehicle 1. Therefore, the vehicle control device 100 assists the vehicle operation of the vehicle 1 at an appropriate level depending on the state of the driver. That is, in this embodiment, the driving assistance control of the vehicle 1 is provided in principle to fill the gap between the vehicle operation that the driver wants to perform and the vehicle operation that the driver can perform. For example, the driver's impaired driving function is mainly assisted. Furthermore, the vehicle control device 100 is configured to automatically switch the vehicle 1 to automatic driving control at a predetermined time.

[0018] Specifically, when the driver has normal driving ability, the vehicle control device 100 intervenes in vehicle operation only at specific times to perform driving assistance control (automatic acceleration, automatic braking, automatic steering, etc.). Specific times include, for example, when the driver's driving ability is temporarily reduced (e.g., due to fatigue or drowsiness) or when the driving environment is relatively difficult (e.g., complex surrounding traffic conditions, complex road shape, dark surroundings). Furthermore, when the driving ability of a driver (e.g., elderly or MCI) is partially reduced (e.g., due to insufficient muscle strength to operate the steering wheel), the vehicle control device 100 compensates for the reduced driving ability. Furthermore, the vehicle control device 100 performs driving assistance control to maintain or recover reduced driving ability or further improve driving ability.

[0019] On the other hand, when an abnormality sign is detected in which the driver's consciousness level or driving ability is decreasing suddenly or over a predetermined time (several minutes to several tens of minutes) (for example, when an acute illness occurs or when the drowsiness level is high), the vehicle control device 100 performs driving assistance control to maintain safe driving. Also, in the event of an abnormality in which the driver's consciousness or driving ability is lost, the vehicle control device 100 executes automatic driving control and performs processing to notify the outside of an emergency in order to avoid an accident.

[0020] Next, the configuration of a vehicle control device according to an embodiment of the present invention will be described with reference to Fig. 2. Fig. 2 is a block diagram of the vehicle control device. As shown in Fig. 2, the vehicle control device 100 mainly includes a controller 10 such as an ECU (Electronic Control Unit), an in-vehicle device 20, a vehicle control system 40, and an information notification device 50.

[0021] The in-vehicle device 20 includes an in-vehicle camera 21, an outside-vehicle camera 22, a radar 23, a plurality of vehicle behavior sensors (vehicle speed sensor 24, acceleration sensor 25, yaw rate sensor 26) that detect the behavior of the vehicle 1, a plurality of operation detection sensors (steering angle sensor 27, steering torque sensor 28, accelerator opening sensor 29, brake depression amount sensor 30) that detect the driver's operation, a positioning device 31, a navigation device 32, and an information and communication device 33.

[0022] The vehicle control system 40 includes an engine control system 41, a brake control system 42, and a steering control system 43, which respectively correspond to the vehicle's running, stopping, and turning functions. The information notification device 50 includes a display device 51, an audio output device 52, an information transmission device 53, and a plurality of actuators 54.

[0023] The controller 10 is configured by a computer device including a processor 11, a memory 12 that stores various programs and data executed by the processor 11, an input / output device, etc. The controller 10 is configured to output control signals for performing vehicle control (driving assistance control and automatic driving control) to the vehicle control system 40 and the information notification device 50 based on signals received from the in-vehicle device 20.

[0024] The in-vehicle camera 21 captures an image of the driver of the vehicle 1 and outputs image information. The controller 10 determines, based on this image information, in particular, the facial expression and upper body posture of the driver. The exterior camera 22 captures images of the surroundings of the vehicle 1 (typically, the area in front of the vehicle 1) and outputs image information. Based on this image information, the controller 10 identifies objects outside the vehicle and their positions. The objects include at least traffic participants and boundaries of the roadway. Specifically, the objects include surrounding moving bodies (vehicles, pedestrians, etc.) and stationary structures (obstacles, parked vehicles, roadways, lane markings, stop lines, traffic signals, traffic signs, intersections, etc.).

[0025] The radar 23 measures the position and speed of an object present around the vehicle 1 (typically in front of the vehicle 1). For example, the radar 23 may be a millimeter wave radar, a laser radar (LIDAR), an ultrasonic sensor, or the like.

[0026] The vehicle speed sensor 24 detects the speed (vehicle speed) of the vehicle 1. The acceleration sensor 25 detects the acceleration of the vehicle 1. The yaw rate sensor 26 detects the yaw rate generated in the vehicle 1. The steering angle sensor 27 detects the rotation angle (steering angle) of the steering wheel 43b of the vehicle 1. The steering torque sensor 28 detects the rotation torque associated with the rotation of the steering wheel 43b. The accelerator opening sensor 29 detects the depression amount of the accelerator pedal 41b. The brake depression amount sensor 30 detects the depression amount of the brake pedal 42b.

[0027] The positioning device 31 includes a GPS receiver and / or a gyro sensor, and detects the position (current vehicle position information) of the vehicle 1. The navigation device 32 stores map information internally and can provide the map information to the controller 10. The controller 10 can calculate the entire driving route (including driving lanes, intersections, traffic signals, etc.) to the destination based on the map information and the current vehicle position information.

[0028] The information communication device 33 communicates with external communication devices. For example, the information communication device 33 performs vehicle-to-vehicle communication with other vehicles and road-to-vehicle communication with communication devices outside the vehicle, receives various driving information and traffic information (traffic congestion information, speed limit information, etc.), and provides the information to the controller 10.

[0029] The engine control system 41 controls the driving force of an engine device (internal combustion engine, electric motor, etc.) of the vehicle 1. The controller 10 drives the engine device and can accelerate or decelerate the vehicle 1 by transmitting a control signal to the engine control device 41a based on an input from the accelerator pedal 41b.

[0030] The brake control system 42 controls the driving force of the brake device of the vehicle 1. The brake control system 42 includes brake actuators such as a hydraulic pump and a valve unit. The controller 10 drives the brake device and decelerates the vehicle 1 by sending a control signal to the brake control device 42a based on an input from a brake pedal 42b.

[0031] The steering control system 43 controls the driving force of the steering device of the vehicle 1. The steering control system 43 includes, for example, an electric motor of an electric power steering system. The controller 10 can drive the steering device and change the traveling direction of the vehicle 1 by sending a control signal to the steering control device 43a based on an input from the steering wheel 43b.

[0032] The display device 51 can visually display support information (visual information) for assisting the driver in vehicle operation in a display area. Specifically, the display device 51 is a HUD. The display area corresponds to the size of the entire windshield of the vehicle 1 or a part of it, and the support information is displayed within the field of view of the driver. Also, a liquid crystal display may be used instead of the HUD. The audio output device 52 is, for example, a speaker, and can provide the driver with assistance information (auditory information) to assist the driver in operating the vehicle. The information transmitting device 53 can transmit information relating to driving assistance to an external information communication device (for example, a mobile information terminal of the driver).

[0033] The actuator 54 is configured with an electric motor, a gear mechanism, etc. The multiple actuators 54 are configured to move multiple operating parts (e.g., accelerator pedal 41b, brake pedal 42b, steering wheel 43b) that the driver operates when driving the vehicle 1 in the operating direction without input from the driver. The controller 10 outputs a control signal to each actuator 54, causing the corresponding operating part to perform a desired behavior.

[0034] The vehicle control system (for example, engine control system, brake control system, steering control system) of this embodiment operates by a drive-by-wire system, and is configured such that an operation input from an operation unit is transmitted as a control signal via the controller 10, and a drive device corresponding to the operation unit receives the control signal and drives based on the control signal. Therefore, the controller 10 can output a control signal to the drive device independently of the movement of the operation unit by the actuator 54.

[0035] Next, the processing flow of the vehicle control device according to the embodiment of the present invention will be described with reference to Fig. 3. Fig. 3 is an explanatory diagram showing the processing flow of the vehicle control device. Specifically, Fig. 3 shows that the controller 10 processes input information from the in-vehicle device 20, thereby providing various vehicle controls (driving assistance control, automatic driving control) using the vehicle control system 40 and the information notification device 50.

[0036] Vehicle control includes ADAS (Advanced Driver Assistance System), automatic acceleration, automatic braking, automatic steering, automatic vehicle stabilization control, and automated driving (level 3 or higher). ADAS includes at least support functions (automatic entry avoidance control) for following the vehicle ahead, preventing collisions with the vehicle ahead, and preventing lane departure. Automatic vehicle stabilization control is a control to stabilize the vehicle 1's attitude, i.e., vehicle dynamics (pitch, roll, yaw), and prevent skidding, rollover, etc.

[0037] The in-vehicle device 20 continuously transmits the acquired information to the controller 10. The controller 10 performs the following calculations or evaluations based on the acquired information. The controller 10 evaluates the traffic environment around the vehicle 1 (traffic environment evaluation) based on input information from the outside camera 22, radar 23, positioning device 31, navigation device 32 (map information), etc. Specifically, the controller 10 calculates the positions, speeds, etc. of objects around the vehicle 1 (vehicles, pedestrians, boundary lines, guardrails, stop lines, traffic signs, etc.).

[0038] The controller 10 also evaluates the driver's physical function (physical function evaluation) based on information from the steering angle sensor 27, steering torque sensor 28, brake depression amount sensor 30, in-vehicle camera 21, etc. Specifically, the controller 10 estimates the level of the driver's physical function, such as operating the operating unit with an appropriate amount of operation and operation speed, and visually perceiving visual stimuli outside the vehicle. Whether the driver is operating with an appropriate amount of operation and operation speed is evaluated based on the difference between the operation amount and operation speed (steering angle, steering angle speed, depression amount of brake pedal 42b, depression speed, brake hydraulic pressure, etc.) actually input by the driver via the operating unit and the target operation amount and operation speed when traveling along the target traveling route. The target traveling route is calculated based on driving requirements (destination, etc.) using the results of a traffic environment evaluation, a traveling environment evaluation, a physical function evaluation, etc., so that the vehicle 1 travels safely and efficiently.

[0039] Furthermore, the controller 10 evaluates the driving environment around the vehicle 1 (driving environment evaluation) based on information from the outside camera 22, the vehicle speed sensor 24, the acceleration sensor 25, the positioning device 31, etc. Specifically, the controller 10 estimates physical quantities that affect the vehicle dynamics (for example, the radius of the curve on the road and the road surface friction coefficient). The controller 10 also calculates the current vehicle dynamics of the vehicle 1 (vehicle dynamics calculation) based on information from the vehicle speed sensor 24, acceleration sensor 25, yaw rate sensor 26, etc. The vehicle dynamics includes speed, acceleration, yaw rate, three-axis rotation moment (pitch, yaw, roll), etc.

[0040] The controller 10 also determines the level of alertness of the driver based on image information from the in-vehicle camera 21 (alertness determination). For example, the level of alertness is evaluated based on the degree to which the driver's eyes and / or mouth are open, and the position or posture of the driver's upper body. The level of alertness can be evaluated, for example, on a four-level scale (zero, low, medium, high alertness).

[0041] Furthermore, the controller 10 determines whether there is a predicted risk in the traffic environment evaluation and the driving environment evaluation. The predicted risk includes a traffic risk caused by the traffic environment (e.g., collision of the vehicle 1 with another vehicle) and a driving risk caused by the driving environment that affects the vehicle dynamics (e.g., spinning out on a curved road). The controller 10 then evaluates the risk avoidance behavior taken by the driver in response to the predicted risk based on information from the on-board device 20, the in-vehicle camera 21, etc. (risk avoidance behavior evaluation).

[0042] Risks include vehicle accidents such as a collision of vehicle 1 and states in which vehicle 1 loses or loses its stability (spins, rollovers, etc.). Risk objects that can cause risk include traffic participants (other vehicles, pedestrians, etc.), guardrails, boundaries, traffic signals (red lights), stop lines, etc. Risk objects also include risk-generating parts of the roadway (such as clipping points on curved roads). These objects are considered risk objects if they are likely to cause a risk in the near future (within a predetermined time, such as 10 seconds) if the current vehicle behavior (vehicle dynamics) continues. Risk avoidance behavior is an action taken by the driver in response to a predicted risk, and is particularly a vehicle operation (acceleration, braking, and / or steering) performed to reduce the probability of the predicted risk occurring. For example, when the predicted paths of vehicle 1 and another vehicle intersect and a collision between the two vehicles is predicted, this is a vehicle operation that reduces the probability of a collision, or a vehicle operation that makes the closest distance between vehicle 1 and another vehicle equal to or greater than a predetermined distance. Furthermore, risk targets may include objects that may not pose a risk at present but should be perceived while driving, and objects that may pose a risk in the future beyond a predetermined time.

[0043] The risk avoidance behavior also includes the driver's behavior of perceiving a risk object (for example, another vehicle with a possibility of collision, or the vicinity of a clipping point on a curved road) before operating the operating unit. For example, the driver's gaze directed toward a risk object based on image information from the in-vehicle camera 21, or the driver's posture in response to the risk (i.e., the driver's perception of a risk object) are also included in the risk avoidance behavior.

[0044] The controller 10 also evaluates the driver's current cognitive load based on the results of the traffic environment evaluation (cognitive load evaluation). For example, the controller 10 evaluates that the greater the number of objects within a predetermined distance from the vehicle 1, the greater the driver's cognitive load, depending on the vehicle speed. The cognitive load can be evaluated, for example, in three stages (low, medium, and high). The controller 10 may also analyze, learn, and update the driver's cognitive ability level based on information about the driver's vehicle operation and line of sight. In this case, the cognitive load evaluation can be calculated as the ratio of the current cognitive load to the driver's cognitive ability level.

[0045] The controller 10 also evaluates the driver's current willingness to drive (driving willingness evaluation). The willingness to drive is affected by the driver's physical and mental state and external factors. For example, the willingness to drive tends to decrease due to factors such as the driver's fatigue, the simplicity or complexity of the traffic environment and the driving environment (e.g., a straight road with little traffic). The controller 10 evaluates the driver's willingness to drive based on an image of the driver (facial expression, driving posture, etc.) obtained from the in-vehicle camera 21. For example, the controller 10 determines that the driver's willingness to drive is low when it detects a narrow field of view, frequent yawning, frequent looking away from the road, or the driver not directing their gaze toward an eye-catching object or the rearview mirror. The controller 10 also evaluates the driver's willingness to drive based on the vehicle operation performed on the operating unit based on the detection information from the in-vehicle device 20. For example, the controller 10 determines that the driver's willingness to drive is low when it detects a delay in the driver's actual vehicle operation compared with the vehicle operation estimated by a driver model. The willingness to drive can be evaluated, for example, on three levels (low, medium, high).

[0046] The controller 10 also stores in a storage unit a vehicle model that defines the physical motion of the vehicle 1. The vehicle model uses equations of motion to represent the relationship between the specifications of the vehicle 1 (mass, wheelbase, etc.) and physical variables (speed, acceleration, steering angle, etc.). The vehicle model can also apply the results of a driving environment evaluation (for example, road surface friction coefficient).

[0047] The controller 10 also stores a driver model of the driver who drives the vehicle 1 in a storage unit. The controller 10 analyzes and learns the driver's operating characteristics based on input information from the in-vehicle device 20 and constantly updates the driver model. The driver model represents the driver's operating characteristics, including the amount of operation for a specific operation under certain conditions, a reaction delay time (time constant), and the like. The results of a cognitive load assessment (level of cognitive load) and a physical function assessment can also be applied to the driver model. For example, in a situation where the cognitive load is high, the driver model is corrected so that the driver's operating ability decreases. Furthermore, if the results of the physical function assessment determine that the pedal force or arm strength is low, this is reflected in the time constants related to the amount of operation and the operating speed of the operating parts. The controller 10 can predict the driver's operation by using the driver model. The controller 10 also stores an ideal driver model, which represents the operating characteristics of an ideal driver with high driving ability, in a storage unit, and can therefore predict ideal operations.

[0048] The controller 10 can calculate vehicle dynamics predicted to occur between now and the near future (vehicle dynamics prediction calculation) by applying input information from the in-vehicle device 20 to the vehicle model and the driver model. That is, by inputting current conditions (traffic environment, driving environment, cognitive load, physical function) into the driver model and the vehicle model, the controller 10 can predict vehicle operations (type of operation, amount of operation, operation timing, etc.) performed by the driver between now and a predetermined time period (for example, 10 seconds from now), and calculate predicted vehicle dynamics caused by the predicted vehicle operation.

[0049] Furthermore, the controller 10 performs a driving ability evaluation. Driving ability represents the level of the driver's ability to avoid various risks. The controller 10 evaluates or calculates the driving ability relative to risk based on the results of the risk aversion behavior evaluation (risk aversion behavior performed by the driver), the difference between predicted vehicle dynamics and actual vehicle dynamics, the results of the cognitive load evaluation (degree of cognitive load), the results of the driving motivation evaluation, and the results of the alertness determination. The driving ability relative to risk may be, for example, the required risk aversion time required for the driver to avoid the predicted risk. The required risk aversion time may be the time from the start of the risk aversion behavior to the disappearance of the predicted risk, or the time required from the driver's perception of the risk to the completion of the risk aversion behavior. In this case, if the driving ability is evaluated low, the required risk aversion time is output as a larger value. Note that if the driving motivation or alertness is low, the driving ability is evaluated low.

[0050] The controller 10 uses a driver model to calculate, for example, a predicted driving route of the vehicle 1 at a future time point, assuming that the current vehicle behavior continues for a predetermined time. When the predetermined time reaches a certain time, the risk cannot be avoided using the predicted driving route at that time. Then, the time until the risk occurs on the predicted driving route calculated at this time (risk margin time) may be set as the risk avoidance required time.

[0051] The controller 10 can update the driving ability data using the calculated driving ability evaluation. A driver's driving ability changes over time. For example, beginner drivers tend to improve their driving ability, while elderly people tend to decline. For the driving ability data, multiple driving ability data sets may be set corresponding to multiple evaluation periods. For example, short-term (1 to 6 months from the present), medium-term (3 to 9 months from the present), and long-term (1 to 2 years from the present) motor ability data sets can be created.

[0052] The controller 10 determines the content of driving assistance based on the current vehicle dynamics, the results of the driving ability assessment (current driving ability), the results of the cognitive load assessment, and the results of the physical function assessment. The controller 10 executes driving assistance control or automated driving control based on this calculation. During normal driving, a driver (e.g., a beginner or elderly driver) demonstrates driving performance using their own driving functions (perceptual function, judgment function, physical function). However, if the driver is unable to avoid a predicted risk (i.e., if the driver's driving performance does not meet the driving ability required to avoid the predicted risk), the controller 10 executes driving assistance control to compensate for the insufficient driving ability. Furthermore, in the event of an abnormality (e.g., loss of consciousness), for example, automated driving control is executed.

[0053] Furthermore, the controller 10 compares the result of the driving ability assessment (current driving ability relative to predicted risk) with the driving ability data, and if the current driving ability is lower than the past driving ability, the controller 10 performs assistance (including automatic driving) to compensate for the lowered driving ability. Furthermore, when the driver's level of alertness is medium (for example, mild drowsiness), the controller 10 performs a process to wake the driver (for example, blow cool air to the driver), and when the driver's level of alertness is low (for example, severe drowsiness or loss of consciousness), the controller 10 performs automatic driving.

[0054] Next, the relationship between a driver's driving ability and risk in an embodiment of the present invention will be described. Figure 4 is a graph showing the relationship between a driver's driving ability and traffic risk and driving risk. In Figure 4, the further away from the origin, the higher the driving ability and the greater the risk. In this embodiment, risks are classified into two different types: traffic risk due to the traffic environment (Y axis) and driving risk due to the driving environment (X axis).

[0055] Traffic risk is a risk related to the complexity of surrounding traffic, specifically the risk of vehicle 1 entering a risk area. Entering a risk area means contact or collision with surrounding traffic participants (vehicles, pedestrians, etc.) of vehicle 1, or contact or crossing a boundary of the travel path (boundary line, guardrail, stop line, etc.). Driving risk is a risk related to vehicle dynamics, specifically a decrease in the postural stability of vehicle 1, resulting in a spin or rollover. In this embodiment, these traffic risks and driving risks can be expressed as estimated times (risk margin times) until these risks occur. In this case, the smaller the risk margin times (traffic risk values, driving risk values), the greater the risk.

[0056] Furthermore, driving ability (Z-axis) includes the driver's driving skills (basic driving ability) and short-term driving ability. Basic driving ability is a driving ability calculated taking into account physical and cognitive functions and may fluctuate over the long term, while short-term driving ability is a correction factor (or noise factor) calculated based on alertness and driving motivation, and may fluctuate over the short term. Therefore, the driver's current driving ability value is calculated using a value representing the magnitude of basic driving ability and a value representing the magnitude of short-term driving ability. When specific traffic risks and / or driving risks are predicted, the basic driving ability value can be the required risk avoidance time calculated for these predicted risks. In this case, the shorter the required risk avoidance time (driving ability value (seconds)), the higher the driving ability.

[0057] On the other hand, the short-term motor ability can be a coefficient k multiplied by the basic driving ability value or a time t added to the basic driving ability value. For example, the coefficient k can include the product of a coefficient k1 based on the level of alertness and a coefficient k2 based on the willingness to drive. The coefficient k1 is set (e.g., infinity, 1.5, 1.2, 1.0, in that order) according to the result of the alertness determination (zero, low, medium, high), and the coefficient k2 is set (e.g., 1.5, 1.2, 1.0, in that order) according to the result of the willingness to drive evaluation (low, medium, high). The added time t can include the sum of the time t1 based on the level of alertness and the time t2 based on the willingness to drive. The time t1 is set (e.g., infinity, 2 seconds, 1 second, 0 seconds, in that order) according to the result of the alertness determination (zero, low, medium, high), and the time t2 is set (e.g., 2 seconds, 1 second, 0 seconds, in that order) according to the result of the willingness to drive evaluation (low, medium, high).

[0058] When the driving risk is high (see point A0), the driver's motivation to drive decreases and the current driving ability becomes lower (the time required to avoid the risk becomes longer). If vehicle control intervenes at this time, the driving risk is substantially reduced (see point A1), the driver's motivation to drive is restored, and the current driving ability becomes higher. Furthermore, by repeating similar situations, the driver's experience level increases and the driving ability itself improves, so the driver becomes able to avoid similar driving risks without vehicle control (see point A2). In this embodiment, the driver's driving ability can be improved in this way. Furthermore, when the traffic risk is high (see point B0), the driving ability can also be improved. On the other hand, when the risk is high and the current driving ability is extremely low (see point C0, for example, loss of consciousness), or when the risk is not high but the current driving ability is extremely low (see point D0, for example, the driving route is monotonous and the driving ability is low), in this embodiment, the vehicle 1 is automatically controlled.

[0059] In this embodiment, risks are classified into two different types of risks, namely, traffic risks and driving risks, and vehicle control for avoiding each risk is also a different type of vehicle control. That is, vehicle control related to traffic risks is automatic entry avoidance control that avoids vehicle 1 entering a risk area (boundary of traffic participants or driving route), such as preceding vehicle following control, preceding vehicle collision prevention control, lane departure prevention control, etc. On the other hand, vehicle control related to driving risks is automatic vehicle attitude stabilization control of vehicle 1, such as skid prevention control, rollover prevention control, etc. By classifying risks in this way, the driver can recognize the type of driving skill deficiency based on the type of vehicle control intervened when encountering a risk, and can easily improve their driving skills.

[0060] Next, the relationship between driving motivation and alertness in this embodiment will be described. FIG. 5 is a graph showing the relationship between driving motivation and alertness, and FIG. 6 is a table showing the driver's state according to driving motivation and alertness. According to FIG. 5, the higher the driving motivation, the higher the level of alertness tends to be. Furthermore, the higher the driving motivation, the smaller the variation in alertness. In other words, when the driving motivation is high, the level of alertness is also high, but when the driving motivation is low, the variation in alertness is large. FIG. 6 shows exemplary driver states and vehicle operations corresponding to each state of driving motivation and alertness. The controller 10 can estimate the driving motivation and alertness from the driver's facial expression, driving posture, or vehicle operation by referring to FIG. 6.

[0061] Next, a processing flow of the driving assistance control of the vehicle control device according to the embodiment of the present invention will be described. Fig. 7 is a flowchart of the driving assistance control. After receiving a driving request (destination, etc.) from the driver or an external device via an input device (e.g., a navigation device 32, an information communication device 33), the controller 10 repeatedly performs the driving assistance control over time (e.g., every 0.1 seconds).

[0062] 7, the controller 10 acquires information from the in-vehicle device 20 at predetermined time intervals (e.g., every 0.1 seconds) (S1). Based on the acquired information, the controller 10 executes processes of traffic environment evaluation (S2), driving environment evaluation (S3), physical function evaluation, and cognitive function evaluation (S4). Based on the acquired information, the controller 10 also executes risk aversion behavior evaluation and vehicle dynamics calculation.

[0063] The controller 10 also estimates the magnitude of traffic risk in the traffic environment evaluation (S2) and the magnitude of driving risk in the driving environment evaluation (S3). Specifically, the controller 10 determines whether or not there is a possibility of a risk occurring within a predetermined time due to the current vehicle behavior (vehicle dynamics) based on the traffic environment evaluation and the driving environment evaluation. The controller 10 calculates the time from the present until the predicted risk (traffic risk and driving risk) occurs (i.e., the risk margin time TTR (time to risk)). In this embodiment, the risk margin time TTR corresponds to the traffic risk value or the driving risk value. If the risk margin time TTR is equal to or shorter than a predetermined time (e.g., 10 seconds), it is determined that there is a predicted risk. The risk margin time TTR is the predicted time until the vehicle 1 enters a risk area if the vehicle 1 maintains its current vehicle behavior (vehicle dynamics such as speed and acceleration). Entering a risk area refers, for example, to a position in a curve where a collision between the vehicle 1 and another vehicle or a spinout of the vehicle 1 is predicted. Note that if a predicted risk is not detected, the processing may be terminated.

[0064] The controller 10 also performs calculations of a target driving route based on the acquired information and driving requirements. The target driving route includes a target driving trajectory (position information of multiple positions) from the present until a predetermined time (e.g., 10 seconds from now) and the speed at each position on the trajectory. The controller 10 calculates the target driving route so as to achieve predetermined safety and driving efficiency using the driving requirements and the results of traffic environment evaluation, driving environment evaluation, physical function evaluation, etc. The controller 10 can calculate multiple target driving routes that satisfy predetermined constraints (e.g., lateral acceleration being equal to or less than a predetermined value). For example, if an obstacle is present ahead of the vehicle 1, the controller 10 can set multiple target driving routes to avoid the obstacle. Note that even if the vehicle 1 deviates from the target driving route, it can still travel on another driving route. However, since the other driving routes are below predetermined standards, driving efficiency and ride comfort will be poor.

[0065] The controller 10 also calculates target vehicle dynamics for traveling along the target traveling route. The target vehicle dynamics include the speed, acceleration, yaw rate, and three-axis rotation moment (pitch, yaw, roll) at each position on the target traveling route. The target vehicle dynamics are control target values ​​used when the vehicle 1 executes driving assistance control and automatic driving control. A plurality of target vehicle dynamics (or control target values) can be set corresponding to a plurality of target traveling routes.

[0066] Furthermore, the controller 10 calculates target vehicle operation amounts (accelerator opening, brake depression amount, steering angle, etc.) which are driving performance requirements for the driver and the vehicle 1 in order to achieve the physical quantities of the target vehicle dynamics at each position on the target driving route, or control signals for the control system 40. Driving performance requirements having a predetermined range are set by a plurality of target driving routes.

[0067] The controller 10 also estimates the driver's driving skill using the results of the traffic environment evaluation, the driving environment evaluation, the physical function evaluation, etc. (S5). In this embodiment, the driving skill is the ability to avoid predicted risks, and more specifically, the time required to avoid predicted risks (required risk avoidance time TER). For this reason, the controller 10 calculates a predicted driving route based on a driver model. Then, based on this predicted driving route, the controller 10 calculates the required risk avoidance time TER. For example, when an obstacle is present ahead of the vehicle 1, the controller 10 predicts a vehicle operation that the driver will perform to avoid the obstacle based on the driver model. Then, the controller 10 sets the time required for this evasive vehicle operation as the required risk avoidance time TER.

[0068] The controller 10 also executes a wakefulness determination process (S6) to determine whether the wakefulness is lower than a predetermined threshold (S7). In addition, in step S6, it may be determined whether the current driving ability value taking the wakefulness into consideration is higher than a predetermined threshold (or whether the driving ability is lower than a predetermined level). In this case, it is determined whether the value of the driving skill calculated in step S5 corrected by a coefficient k1 or t1 based on the wakefulness is higher than the predetermined threshold.

[0069] If the level of alertness is lower than the predetermined threshold (S7: No; the evaluation result of the level of alertness is "zero"), the driver is unconscious or extremely sleepy, so the controller 10 executes automatic driving (S8). On the other hand, if the level of alertness is equal to or higher than the predetermined threshold (the evaluation result of the level of alertness is "low," "medium," or "high") (S7: Yes), the controller 10 executes a process to evaluate the driver's motivation to drive (S9), and further executes a process to evaluate the driver's driving ability (S10). In the driving ability evaluation process, the value of the driving skill (S5) is corrected based on the driver's level of alertness (S6) and motivation to drive (S9).

[0070] Then, the controller 10 determines whether the traffic risk and driving risk can be avoided based on the driver's current driving ability. First, if both the traffic risk and driving risk cannot be avoided based on the driver's current driving ability (S11: Yes), the controller 10 executes automatic driving (S12). In this case, the driving ability value is greater than the traffic risk value and the driving risk value.

[0071] Traffic risk and driving risk are different types of risk, but they can coexist in the same situation. For example, when avoiding an obstacle on a snow-covered road, or when a vehicle ahead brakes on a highway. In these cases, the traffic risk of colliding with an obstacle or a vehicle ahead and the driving risk of losing stability due to slipping coexist. In such cases, the driving ability value is calculated for both of these risks, and each is compared with the corresponding risk value. If both the traffic risk and the driving risk cannot be avoided (S11: Yes), vehicle 1 switches to autonomous driving for safety reasons.

[0072] Furthermore, if the traffic risk can be avoided by the current driving ability but the driving risk cannot be avoided by the current driving ability (S13: Yes), the controller 10 executes a first setting change process (S14) so ​​that automatic vehicle attitude stabilization control ("Control 1") that stabilizes the attitude of the vehicle 1 is executed early. In this case, the driving ability value is smaller than the traffic risk value but larger than the driving risk value.

[0073] The automatic vehicle attitude stabilization control starts operating when a predetermined condition is satisfied. The predetermined condition is, for example, that a control parameter(s) reaches a threshold value for starting operation. The threshold value is usually set to an initial setting threshold value. The control parameters are, for example, a slip ratio, a vehicle speed, a yaw rate, and a lateral acceleration. At the time of processing in step S14, the control parameter has not reached the initial setting threshold value, so the automatic stabilization control has not started.

[0074] If the driver continues the current vehicle operation after the process in step S14, a driving risk (for example, a spin) will occur. However, since the predetermined conditions are met before the driving risk occurs, the automatic stabilization control starts to operate.

[0075] In this embodiment, a first setting change process is executed (S14) to change the threshold value from the initial setting threshold value to the early start threshold value so that the automatic stabilization control is started early. That is, the automatic stabilization control normally starts when the control parameter reaches the initial setting threshold value, but after the first setting change process (S14), the automatic stabilization control starts when the control parameter reaches the early start threshold value. Note that the threshold value is returned to the initial setting threshold value after the driving risk is eliminated.

[0076] Whether or not automatic stabilization control is executed after the processing of step S14 depends on the actual vehicle operation of the driver. If the control parameter does not reach the early start threshold, automatic stabilization control is not executed. On the other hand, if the control parameter reaches the early start threshold, automatic stabilization control is executed earlier than usual, and the attitude of the vehicle 1 is stabilized. In other words, when the early start threshold is set, automatic stabilization control operates when the attitude of the vehicle 1 is more stable than usual.

[0077] Furthermore, when the automatic stabilization control begins to operate, the controller 10 uses the information notification device 50 to notify the driver of the intervention of the automatic stabilization control. By learning that the automatic stabilization control has intervened, the driver can learn that the amount and timing of vehicle operation performed by the driver in a situation that destabilizes the vehicle dynamism (for example, driving on a curved, icy road) were inappropriate. The driver can then improve their driving skills so that the automatic stabilization control will not intervene in similar situations. Furthermore, the improvement in driving skills is reflected in the driver model, thereby improving the driving ability value.

[0078] Furthermore, if the driving risk can be avoided based on the current driving ability but the traffic risk cannot be avoided based on the current driving ability (S15: Yes), the controller 10 executes a second setting change process (S16) so that automatic entry avoidance control ("control 2") that prevents the vehicle 1 from entering the risk area is executed early. In this case, the driving ability value is smaller than the driving risk value but larger than the traffic risk value.

[0079] The automatic entry avoidance control starts operating when a predetermined condition is satisfied. The predetermined condition is, for example, that a control parameter (one or more) reaches a threshold value for starting operation. The threshold value is usually set to an initial setting threshold value. For example, in the case of automatic brake control (automatic entry avoidance control), the control parameter is the inter-vehicle distance between the vehicle 1 and the vehicle ahead, and in the case of lane departure prevention control (automatic entry avoidance control), the control parameter is the lateral distance between the vehicle 1 and the boundary line. At the time of processing in step S16, the control parameter has not reached the initial setting threshold value, so the automatic entry avoidance control has not started.

[0080] If the driver continues the current vehicle operation after the process in step S16, a traffic risk (for example, a collision with a vehicle ahead or deviation from a boundary line) will occur. However, because a predetermined condition is met before the traffic risk occurs, automatic entry avoidance control will start operating.

[0081] In this embodiment, a second setting change process is executed (S16) to change the threshold value from the initial setting threshold value to the early start threshold value so that the automatic entry avoidance control is started early. That is, the automatic entry avoidance control normally starts operating when the control parameter reaches the initial setting threshold value, but after the second setting change process (S16), it starts operating when the control parameter reaches the early start threshold value. Note that the threshold value is returned to the initial setting threshold value after the traffic risk has disappeared.

[0082] For example, in automatic brake control (automatic entry avoidance control), the control parameter (the distance between the preceding vehicle and vehicle 1) has an initial setting threshold of 2 m and an early start threshold of 3 m. Also, in lane departure prevention control (automatic entry avoidance control), the control parameter (the lateral distance between vehicle 1 and the boundary line) has an initial setting threshold of 0.5 m and an early start threshold of 0.7 m.

[0083] Whether or not the automatic entry avoidance control is executed after the processing of step S16 depends on the actual vehicle operation of the driver. If the control parameter does not reach the early start threshold, the automatic entry avoidance control is not executed. On the other hand, if the control parameter reaches the early start threshold, the automatic entry avoidance control is executed earlier than usual, and entry of the vehicle 1 into the risk zone is avoided. In other words, when the early start threshold is set, sudden braking and abrupt steering during the automatic entry avoidance control are suppressed compared to normal times.

[0084] Furthermore, when the automatic entry avoidance control starts to operate, the controller 10 uses the information notification device 50 to notify the driver of the intervention of the automatic entry avoidance control. By learning of the intervention of the automatic entry avoidance control, the driver can learn that the amount and timing of the vehicle operation performed by the driver in a situation where the vehicle was entering a risk area were inappropriate. The driver can then improve their driving skills so that the automatic entry avoidance control does not intervene in similar situations. Furthermore, the improvement in driving skills is reflected in the driver model, thereby improving the driving ability value.

[0085] In addition, if the traffic risk and driving risk can be avoided by the current driving ability (S15: No), the controller 10 ends the process without executing the setting change process. In this case, the driving ability value is smaller than the traffic risk value and the driving risk value.

[0086] The operation of the vehicle control device 100 according to the embodiment of the present invention will be described below. The vehicle control device 100 of this embodiment performs driving assistance control of the vehicle 1 so that the vehicle 1 travels in accordance with the traffic environment and traveling environment around the vehicle 1. The vehicle control device 100 includes a controller 10 that calculates a target traveling route based on the traffic environment and traveling environment and controls the vehicle 1 so that the vehicle 1 travels on the target traveling route, and the controller 10 is configured to execute a traffic environment evaluation process (S2) that estimates a traffic risk value that indicates the magnitude of a traffic risk that occurs when the vehicle 1 enters a risk area in the traffic environment, the risk area including traffic participants and / or boundaries of a traveling path; a traveling environment evaluation process (S3) that estimates a traveling risk value that indicates the magnitude of a traveling risk in the traveling environment that destabilizes the attitude of the vehicle 1; and a driving ability evaluation process (S9) that estimates a driving ability value that indicates the magnitude of the driving ability of the driver of the vehicle 1 to avoid the traffic risk and the traveling risk, and the controller 10 determines whether the traveling risk can be avoided by driving ability based on the driving ability value and the traveling risk value. If it is determined that the traffic risk will not be avoided due to driving ability (S13: Yes), a first setting change process is executed to change the threshold at which automatic vehicle attitude stabilization control is started so that automatic vehicle attitude stabilization control that stabilizes the attitude of vehicle 1 is executed sooner (S14). If it is determined that the traffic risk will not be avoided due to driving ability based on the driving ability value and the traffic risk value (S15: Yes), a second setting change process is executed to change the threshold at which automatic entry avoidance control is started so that automatic entry avoidance control to avoid vehicle 1 entering the risk area is executed sooner (S16). If it is determined that the traffic risk and driving risk will not be avoided due to driving ability based on the driving ability value, traffic risk value, and driving risk value (S11: Yes), or if it is determined that the driving ability is lower than a predetermined level based on the driving ability value (S7: No), vehicle 1 is controlled to travel on the target driving route.

[0087] In this embodiment configured as described above, risks when the vehicle 1 travels are classified into traffic risks that depend on the traffic environment and driving risks that depend on the driving environment. Depending on the risk that is estimated to be unavoidable based on the driver's driving ability, driving assistance control using automatic entry avoidance control or automatic vehicle stabilization control can be intervened earlier. In this embodiment, appropriate driving assistance control corresponding to a lower level of driving ability among the driver's driving abilities corresponding to the two risks is more likely to intervene. Furthermore, in this embodiment, driving assistance control intervenes early when the vehicle 1 is at a low risk level, so risk avoidance vehicle operation by driving assistance control is relatively gradual, and sudden risk avoidance vehicle operation is avoided. In this embodiment, the early and gradual intervention of driving assistance control allows the driver to learn situations (surrounding environment and vehicle operation by the driver) in which driving assistance control is likely to intervene. Furthermore, the driver can improve vehicle operation so that driving assistance control does not intervene for similar risks, thereby improving low-level driving ability over the long term.

[0088] In addition, in this embodiment, preferably, when the automatic vehicle attitude stabilization control and the automatic entry avoidance control are executed, the controller 10 notifies the driver of the vehicle 1 that the automatic vehicle attitude stabilization control and the automatic entry avoidance control have been executed. In this embodiment configured in this manner, the driver can recognize that the driving assistance control has intervened by the notification.

[0089] In addition, in this embodiment, preferably, when the traffic risk and driving risk are eliminated, the controller 10 returns the thresholds changed in the first setting change process and the second setting change process to the initial setting thresholds of the vehicle. In this embodiment configured as above, the setting of the thresholds for the driving assistance control can be changed each time a risk occurs based on the current driving ability value and the traffic risk value or the driving risk value. Therefore, as the driving ability improves, the thresholds will no longer be changed from the initial thresholds, and the higher the driver's driving ability, the greater the degree of freedom in vehicle operation.

[0090] In this embodiment, preferably, the driving ability value includes a basic driving ability value and a short-term driving ability value, and the controller 10 learns the vehicle operation of the driver of the vehicle 1 to update the driver model and estimates the basic driving ability value for avoiding traffic risks and driving risks based on the driver model (S5), and the controller 10 estimates the short-term driving ability value based on the alertness and / or driving motivation of the driver of the vehicle (S9). In this embodiment configured as above, by dividing driving ability into driving skills that fluctuate over the long term and short-term driving ability (noise factors) that fluctuate over the short term, it is possible to more accurately determine current driving ability and provide appropriate driving assistance control.

[0091] In addition, in this embodiment, preferably, the controller 10 executes a driving willingness determination process (S9) to determine the driver's willingness to drive, and in this driving willingness determination process, is configured to determine the driver's willingness to drive based on at least the driver's facial expression, driving posture, or vehicle operation. [Explanation of symbols]

[0092] 1 vehicle 10 Controller 20 Onboard equipment 40 Vehicle Control System 50 Information notification device

Claims

1. A vehicle control device that performs driving assistance control of a vehicle so that the vehicle travels in accordance with a traffic environment and a traveling environment around the vehicle, a controller that calculates a target driving route based on the traffic environment and the driving environment and controls the vehicle so that the vehicle drives along the target driving route; The controller a traffic environment assessment process for estimating a traffic risk value representing a magnitude of a traffic risk caused by the vehicle entering a risk area in the traffic environment, the risk area including a boundary of a traffic participant and / or a travel route; a driving environment evaluation process for estimating a driving risk value representing the magnitude of a driving risk in the driving environment that destabilizes the attitude of the vehicle; a driving ability evaluation process for estimating a driving ability value representing the magnitude of the driving ability of the driver of the vehicle to avoid the traffic risk and the driving risk, The controller When it is determined that the driving risk cannot be avoided by the driving ability because the driving ability value is smaller than the driving risk value, a first setting change process is executed to change a threshold value at which the automatic vehicle attitude stabilization control for stabilizing the attitude of the vehicle is started so that the automatic vehicle attitude stabilization control for stabilizing the attitude of the vehicle is executed earlier; When it is determined that the traffic risk cannot be avoided by the driving ability because the driving ability value is smaller than the traffic risk value, a second setting change process is executed to change a threshold value at which the automatic entry avoidance control for avoiding the vehicle from entering the risk area is started so that the automatic entry avoidance control for avoiding the vehicle from entering the risk area is executed earlier; A vehicle control device that controls the vehicle to travel on the target driving route when it determines that both the traffic risk and the driving risk cannot be avoided by the driving ability because the driving ability value is smaller than each of the traffic risk value and the driving risk value, or when it determines that the driving ability is lower than a predetermined level because the driving ability value is smaller than a predetermined threshold.

2. 2. The vehicle control device according to claim 1, wherein, when the automatic vehicle attitude stabilization control is executed, the controller notifies a driver of the vehicle that the automatic vehicle attitude stabilization control has been executed, and when the automatic entry avoidance control is executed, the controller notifies a driver of the vehicle that the automatic entry avoidance control has been executed.

3. 3. The vehicle control device according to claim 1, wherein the controller returns the threshold value changed in the first setting change process to the initial setting threshold value of the vehicle when the driving risk is eliminated, and returns the threshold value changed in the second setting change process to the initial setting threshold value of the vehicle when the traffic risk is eliminated.

4. The driving ability value includes a basic driving ability value and a short-term driving ability value, the controller learns vehicle operations of the driver of the vehicle to update a driver model, and estimates the basic driving ability value for avoiding the traffic risk and the driving risk based on the driver model; 4. The vehicle control device according to claim 1, wherein the controller estimates the short-term driving ability value based on a level of alertness and / or a driving motivation of the driver of the vehicle.

5. The vehicle control device described in any one of claims 1 to 4, wherein the controller executes a driving willingness determination process to determine the driver's willingness to drive, and in this driving willingness determination process, is configured to determine the driver's willingness to drive based on at least the driver's facial expression, driving posture, or vehicle operation.

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