Driving assistance method and driving assistance device

Abstract

The system assists driving control by using a target speed profile that takes into account the road surface friction coefficient in front of the vehicle. [Solution] The processor 10 calculates a first speed VS1 at a target point i set in front of the vehicle based on the road friction coefficient μ and curvature ρ, calculates a second speed VS2 at a target point i where acceleration is performed based on the maximum acceleration determined using the road friction coefficient μ, calculates a third speed VS3 at a target point i where deceleration is performed based on the maximum deceleration determined using the road friction coefficient μ, selects a second speed VS2 lower than the first speed VS1 at a target point i where acceleration is performed, selects a third speed VS3 lower than the first speed VS1 at a target point i where deceleration is performed, selects a first speed VS1 at a target point i where driving other than acceleration and deceleration is performed, and calculates a target speed profile TP that associates the selected target speed TVS with the target point i to support the driving of the vehicle V1.

Description

Technical Field

[0001] It relates to a method and device for assisting vehicle driving.

Background Art

[0002] There is known a technique of obtaining a sudden deceleration point decelerated due to the same sudden deceleration cause and an initial vehicle speed at the sudden deceleration point, obtaining a vehicle speed transition for stopping the vehicle before a point where the vehicle stops when the vehicle is decelerated at each sudden deceleration point, and prompting a vehicle approaching the sudden deceleration cause at a vehicle speed exceeding the vehicle speed transition to pay attention to driving (Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, there is a problem that vehicle speed control according to a change in the road surface friction coefficient in front of the vehicle has not been studied.

[0005] The problem to be solved by the present invention is to control the vehicle speed according to a change in the road surface friction coefficient in front of the vehicle.

Means for Solving the Problems

[0006] The present invention solves the above problem by calculating a first speed at a target point based on the road friction coefficient and curvature of the target point in front of the vehicle, calculating a second speed at a target point where acceleration is performed based on the maximum acceleration during acceleration determined using the road friction coefficient, calculating a third speed at a target point where deceleration is performed based on the maximum deceleration during deceleration determined using the road friction coefficient, selecting a second speed lower than the first speed as the target speed at a target point where acceleration is performed, selecting a third speed lower than the first speed as the target speed at a target point where deceleration is performed, selecting the first speed as the target speed at a target point where driving other than acceleration or deceleration is performed, and supporting the driving of the vehicle according to a target speed profile associated with the target point based on the selected target speed. [Effects of the Invention]

[0007] According to the present invention, the vehicle speed can be controlled in accordance with the change in the coefficient of friction of the road surface in front of the vehicle. [Brief explanation of the drawing]

[0008] [Figure 1] Figure 1 is a block diagram showing the configuration of the driver assistance system. [Figure 2] Figure 2(a) shows an example of a target path, (b1) in (b) shows the turning curvature μi of the target path, (b2) shows the change in the road surface friction coefficient, and (b3) shows the first velocity profile based on the road surface friction coefficient. [Figure 3] Figure 3(a) shows the first velocity profile, Figure 3(b) shows the second velocity profile, Figure 3(c) shows the third velocity profile, and Figure 3(d) shows the target velocity profile. [Figure 4] Figure 4 is a flowchart showing an example of a driver assistance procedure. [Modes for carrying out the invention]

[0009] Embodiments of the present invention will be described below with reference to the drawings. Figure 1 shows the hardware configuration of a driver assistance system 100 equipped with a driver assistance device 1 of a vehicle according to this embodiment. The driver assistance device 1 assists in the driving control of the vehicle to follow a target route. The driving control includes autonomous driving control and manual driving control by the occupant. The processor 10 of the driver assistance device 1 implements this driver assistance method using the hardware of the driver assistance system 100.

[0010] The driver assistance system 100 includes one or more sensors 2, a vehicle information acquisition device 3, a driving environment information acquisition device 4, a road surface friction coefficient calculation device 5, map information 6, and a navigation device 7. Sensor 2 detects the vehicle itself and the surrounding environment. Sensor 2 detects the vehicle's current position (including its relative position to objects), the boundary of the road the vehicle is traveling on, the area of ​​the road the vehicle is traveling on, the road surface of the road the vehicle is traveling on, the presence or absence of objects including other vehicles, the distance to objects, the relative velocity of objects, and the relative acceleration of objects. Multiple Sensor 2s are installed on the vehicle, forming a sensor system that works in cooperation with each other. Sensor 2 detects objects, including other vehicles, traveling in front of, behind, and to the left and right sides of the vehicle. Sensor 2 provides various detection information to the processor 10. Based on the detection information, the processor 10 determines the position, attitude, motion state (velocity, acceleration, behavior, direction of travel, etc.) of objects and their changes, and uses the results of that determination to perform driving assistance, including autonomous driving control. Sensor 2 includes one or more cameras 21 positioned on the vehicle. The cameras 21 capture images of the vehicle in all directions. Cameras 21 include image sensors equipped with image sensors such as CCDs, ultrasonic cameras, and infrared cameras. Cameras 21 include at least a front camera that captures images in front of the vehicle, a rear camera that captures images of the rear or rear-side of the vehicle, and left and right side cameras that capture images of the left and right sides, the front and rear of the left and right sides of the vehicle. The configuration of the cameras 21 is not limited as long as they can capture images in all directions of the vehicle. The cameras 21 of Sensor 2 acquire imaging information of the road on which the vehicle V1 is traveling, and based on the imaging information, detect one or more of the following: the left and right boundaries of the road, the road formed between the boundaries, the center of the road, the position of the vehicle relative to the road, and the road surface condition of the road. Sensor 2 includes a radar device 22 that detects (measures distances) the presence, position, and positional changes of objects around the vehicle. The radar device 22 is a device that measures the distance and direction from the vehicle to the object, the positional relationship and distance between objects, by emitting electromagnetic waves toward an object and measuring the reflected waves. The radar device 22 includes a laser radar, a millimeter-wave radar (LRF), a LiDAR unit (light detection and ranging unit), an ultrasonic radar, and sonar. The radar device 22 of Sensor 2 acquires measurement information regarding the structure of the road on which the vehicle V1 is traveling, and based on the measurement information, detects the left and right boundaries of the road, the road formed between the boundaries, the center of the road, and the position of the vehicle relative to the road. Sensor 2 includes a receiver for GPS (Global Positioning System) and GNSS (Global Navigation Satellite System) signals, a gyro sensor or IMU (Inertial Measurement Unit), and a vehicle speed sensor, which are used to detect the current position of the vehicle. Sensor 2 includes a road surface condition determination sensor. The road surface condition determination sensor may be contact-type or non-contact-type. The form of the road surface condition determination sensor is not particularly limited, but it has electrodes and determines the wetness of the road surface (thickness of the water film) based on changes in impedance. If the road surface condition determination sensor is installed on the roadside, the detection result may be obtained via the communication device 40. Sensor 2 can also use a camera 21 as a road surface condition determination sensor to detect the wetness, snowfall, and freezing conditions of the road surface from the characteristics of the captured image. Sensor 2 may also include a thermometer and a raindrop sensor and detect the road surface condition using information on freezing temperature and rainfall. Sensor 2 may include a G-sensor or a 6-axis inertial sensor. Sensor 2 detects road surface conditions, including the road surface friction coefficient, based on detection information from the G-sensor or the 6-axis inertial sensor. Sensor 2 can also acquire detection information from each in-vehicle device or external device via the communication device 40. Sensor 2 can acquire weather, temperature, and road surface information for each point (including target points) along the target route from each in-vehicle device or external device of other vehicles. The communication means of the communication device 40 is not particularly limited and can include short-range wireless communication such as vehicle-to-vehicle communication, or wireless communication between an external device and a vehicle. Each sensor 2 sends the acquired detection information to the vehicle information acquisition device 3, the driving environment information acquisition device 4, the road surface friction coefficient calculation device 5, or the processor 10, in response to a request or command. The processor 10 may acquire detection information directly from the camera 21 and radar device 22, or it may acquire detection information via the vehicle information acquisition device 3, the driving environment information acquisition device 4, or the road surface friction coefficient calculation device 5.

[0011] The vehicle information acquisition device 3 calculates the vehicle's position, attitude, speed, acceleration, angular velocity, behavior, and direction of travel based on detection information acquired from the sensor 2 and provides this information to the processor 10. The vehicle's position includes a predicted position to be passed at a predetermined future timing, calculated based on the current position and the vehicle's speed. The vehicle information acquisition device 3 calculates the timing of passing a target point ahead based on the current position and the vehicle's speed and provides this information to the processor 10. The vehicle information acquisition device 3 also calculates the vehicle's lateral position relative to the road and provides this information to the processor 10.

[0012] The driving environment information acquisition device 4 acquires driving environment information related to road surface conditions. The driving environment information acquisition device 4 comprises a road surface information acquisition device 41, a weather information acquisition device 42, a temperature information acquisition device 43, and a storage device 44. The road surface information acquisition device 41 acquires the road surface friction coefficient for each point (including the target point) along the target route traveled by the vehicle being driven. The road surface friction coefficient for the target point may be the road surface friction coefficient for the target point itself, or it may be the road surface friction coefficient for the area including the target point. The road surface information acquisition device 41 may also acquire the road surface friction coefficient for the target point based on detection information acquired from one or more of the G sensor, the 6-axis inertial sensor, and the road surface condition determination sensor. Hereinafter, the information for the "target point" includes information for the area including the target point. The road surface information acquisition device 41 may acquire the road surface friction coefficient acquired by sensors or on-board equipment of other vehicles via a server. The server stores the road surface friction coefficient acquired by sensors or on-board equipment of other vehicles in association with location identification information (coordinate values ​​such as latitude and longitude). The road surface information acquisition device 41 sends request information including location identification information (coordinate values ​​such as latitude and longitude) to the server and acquires the road surface friction coefficient for the target location output from the server. When the road surface information acquisition device 41 acquires the road surface friction coefficient recorded by other vehicles via a server, it is preferable to acquire the road surface friction coefficient stored (detected) within a predetermined time from the time the vehicle passes the target location. The acquired road surface friction coefficient may be the road surface friction coefficient actually detected, or it may be a surface friction coefficient predicted based on the detected conditions. The road surface information acquisition device 41 can acquire the road surface friction coefficient using the sensor 2 or on-board equipment mounted on the vehicle. If the temperature detected by the thermometer, which is the sensor 2, is in the road surface freezing temperature range, the road surface information acquisition device 41 may acquire the road surface friction coefficient defined and stored as the road surface friction coefficient for freezing conditions. If the road surface information acquisition device 41 acquires rainfall information detected by the raindrop sensor, which is the sensor 2, or operation information of the wipers that are operated during rainfall, the road surface friction coefficient with water film formation defined and stored as the road surface friction coefficient with water film formation conditions. The weather information acquisition device 42 acquires weather information at the target location from an external device acting as a sensor 2. The external device includes a server, and the weather information acquisition device 42 acquires weather information stored by other vehicles. The weather information includes one or more of the following: clear skies, rainfall, rainfall amount, snowfall, and snowfall amount. When the weather information is common, the road surface conditions tend to be common as well. The weather information acquisition device 42 provides the acquired weather information to the road surface information acquisition device 41. As described above, the road surface information acquisition device 41 acquires the road surface friction coefficient for each state defined according to the weather: freezing, water film formation, wet, and dry, as the road surface friction coefficient for the target location. The temperature information acquisition device 43 acquires temperature information at the target location from a thermometer, which acts as sensor 2. The weather information acquisition device 42 can also acquire weather information stored on a server by other vehicles. When temperature information is common, road surface conditions tend to be common. The temperature information acquisition device 43 provides the acquired temperature information to the road surface information acquisition device 41. As described above, the road surface information acquisition device 41 acquires the road surface friction coefficients for each state—freezing, water film formation, wet, and dry—which are defined and stored according to the temperature, as the road surface friction coefficients for the target location. Of course, the road surface friction coefficients for each state, which are defined and stored according to the weather and temperature, may also be acquired as the road surface friction coefficients for the target location.

[0013] The road surface information acquisition device 41 stores the road surface friction coefficient for each acquired target point in the storage device 44. The storage device 44 may be mounted in the vehicle itself or another vehicle, or it may be located on an external server. The storage device 44 stores road surface friction coefficient information 441, including the road surface friction coefficient, in a state that can be read by the processor 10. The road surface information acquisition device 41 stores the road surface friction coefficient information 441, which associates the acquired road surface friction coefficient for a target point with the location information of the target point, in the storage device 44 in a state that can be read by the processor 10. The road surface friction coefficient information 441 may also be included in the map information 6 based on the location information. This allows the road surface friction coefficient to be retrieved from the storage device 44 in the past when passing over a common target point and used in subsequent driving assistance control. The target point associated with the road surface friction coefficient may be defined as a specific point, or as an area encompassing that point. The road surface information acquisition device 41 stores the area encompassing the target point as location information, associating it with the acquired road surface friction coefficient, as road surface friction coefficient information 441 in the storage device 44. If the target point is defined as a pinpoint location, the probability of the vehicle passing through a location matching that target point again decreases, reducing the opportunities to utilize past road surface friction coefficients. By associating an extended area of ​​the target point with the road surface friction coefficient in the road surface friction coefficient information 441, the previously acquired road surface friction coefficient can be read and used when the vehicle passes through a location that partially or completely overlaps with the area. The road surface information acquisition device 41 stores the road surface friction coefficient information 441 by associating the location information of the target point with the road surface friction coefficient of the area where the road surface environment is common. The road surface friction coefficients of areas where the road surface environment is common tend to be common or similar. For this reason, roads belonging to the same expressway or designated section are judged to have a common road surface environment, and a common road surface coefficient is assigned and stored as road surface friction coefficient information 441. In addition, the road surface friction coefficients of areas where the road attributes of the target route are common tend to be common or similar. For example, the road surface environment of vehicle-only roads such as expressways tends to be common. For this reason, roads with common road attributes are judged to have a common road surface environment, and a common road surface coefficient is assigned and stored as road surface friction coefficient information 441. As a result, based on the current road surface environment, road surface friction coefficients acquired in the past in areas where the road surface environment is common, such as expressways, can be read and used.

[0014] The road surface information acquisition device 41 stores road surface friction coefficient information 441 in the storage device 44 in a format readable by the processor 10. This information associates the acquired road surface friction coefficient for a target location with a road surface environment that includes at least one of the following: weather, temperature, and road surface condition. The processor 10 may acquire road surface friction coefficient information 441 where the weather of the target location is common, or where the weather and temperature are common, or where the weather, temperature, and road surface condition are common. The more search conditions there are, the more road surface friction coefficient information 441 can be acquired under conditions that match the current state of the vehicle, and an appropriate target speed profile TP can be calculated. This allows the system to acquire previously detected or estimated road surface friction coefficients from the storage device 44 when passing a target location under common road surface conditions, and use them in subsequent driving assistance control. The road surface information acquisition device 41 stores, in a state readable by the processor 10, road surface friction coefficient information 441 in which the acquired road surface friction coefficient regarding the target location is associated with the timing (time) at which it was detected or acquired, in the storage device 44. If the road surface friction coefficients are common or have a predetermined time difference, there is a high possibility that the road surface conditions are common. Thereby, when passing through the target location at a common or predetermined range of timings, the road surface friction coefficient detected or estimated in the past can be acquired from the storage device 44 and used in subsequent driving support control.

[0015] The road surface friction coefficient calculation device 5 calculates one road surface friction coefficient based on a plurality of road surface friction coefficients stored in the storage device 44. The road surface friction coefficient calculation device 5 stores the calculated one road surface friction coefficient in the storage device 44 as road surface friction coefficient information 441, at least in association with the position information of the target location. The road surface friction coefficient calculation device 5 further stores the calculated one road surface friction coefficient in the storage device 44 as road surface friction coefficient information 441, in association with the road surface environment and / or timing (time). An example of a method for estimating the road surface friction coefficient based on the timing when the road surface friction coefficient was acquired will be described. The storage device 44 stores the road surface friction coefficient information 441 by associating the time when it was acquired with the road surface friction coefficient for common target locations. The road surface friction coefficient calculation device 5 extracts one or more road surface friction coefficients acquired within a predetermined time from the current timing from the road surface friction coefficient information 441 in the storage device 44 for common target locations. When a plurality of road surface friction coefficients are acquired, the road surface friction coefficient calculation device 5 multiplies them by different weighting coefficients according to the length of time from the current time (the temporal distance of the acquired timing). The road surface friction coefficient calculation device 5 sets the first weighting coefficient for the (older) road surface friction coefficient acquired at a timing far from the current time to be lower than the second weighting coefficient for the (newer) road surface friction coefficient acquired at a timing closer to the current time. The road surface friction coefficient calculation device 5 calculates the elapsed time from the timing when the extracted road surface friction coefficient was acquired to the current time, and when the elapsed time is less than the predetermined time, multiplies the first weighting coefficient by the road surface friction coefficient, and when the elapsed time is greater than or equal to the predetermined time, multiplies the second weighting coefficient by the road surface friction coefficient. The road surface friction coefficient calculation device 5 calculates an estimated value of the road surface friction coefficient based on the sum of the road surface friction coefficient multiplied by the first weighting coefficient and the road surface friction coefficient multiplied by the second weighting coefficient, and stores it in the storage device 44 as road surface friction coefficient information 441 in association with the position information of the target location. The road surface friction coefficient calculation device 5 can estimate a road surface friction coefficient that reflects the actual situation at the time of estimation by relatively increasing the weighting of the road surface friction coefficient acquired at a time close to the timing when the host vehicle passes through the target location and relatively decreasing the weighting of the road surface friction coefficient acquired at a time far from the timing when the host vehicle passes through the target location. An example of a method for calculating an estimated value of the road surface friction coefficient is shown below. In the following formula, the first weighting coefficient a is set to be lower than the second weighting coefficient b.

Equation

[0016] Another example of a method for estimating the road surface friction coefficient based on the confidence level of the acquired road surface friction coefficient is described. The memory device 44 stores road surface friction coefficient information 441, associating the confidence level and road surface friction coefficient at the time the target location was acquired with the common target location. The confidence level of the road surface friction coefficient is an index value that indicates the accuracy of the value. For example, a confidence level is assigned according to the accuracy of the detection method for the road surface friction coefficient and the data used, with a higher level indicating higher confidence. For example, the confidence level of the road surface friction coefficient based on the road surface condition determined by a road surface condition determination sensor, which is installed on the roadside and obtains detection information obtained by contacting the road surface with a detection terminal, is judged to be higher than the confidence level of the road surface friction coefficient based on the road surface condition determined by an image processing function based on detection information (image information) obtained without contacting the road surface, such as images captured by camera 21. For example, the confidence level of the road surface friction coefficient based on the road surface condition determined from weather and temperature is judged to be higher than the confidence level of the road surface friction coefficient based on the road surface condition determined from weather only or temperature only. This is because a higher accuracy can be expected for the confidence level of the road surface friction coefficient when more factors are considered. As an example, the confidence level of a measured road surface friction coefficient that differs little from the road surface friction coefficient predicted from the climate and / or temperature is judged to be higher than the confidence level of a measured road surface friction coefficient that differs greatly from the road surface friction coefficient predicted from the climate and / or temperature. If a high road surface friction coefficient is detected when the temperature is below freezing, the confidence level of that road surface friction coefficient is judged to be low, even if it is a measured value. If a low road surface friction coefficient is detected when the temperature is below freezing, the confidence level of that road surface friction coefficient is judged to be high because the measured value matches the road surface environment. As an example, the confidence level of a road surface friction coefficient detected when the braking actuator is at maximum output is judged to be higher than the confidence level of a road surface friction coefficient detected when the braking actuator is not at maximum output. This is because the calculation error of the road surface friction coefficient calculated when the braking force is at maximum output tends to be small. The road surface friction coefficient calculation device 5 extracts one or more road surface friction coefficients common to the target points from the road surface friction coefficient information 441 in the storage device 44. If multiple road surface friction coefficients are obtained, the road surface friction coefficient calculation device 5 multiplies them by different weighting coefficients according to the confidence level (accuracy of the value) of the road surface friction coefficient values. The road surface friction coefficient calculation device 5 sets the first weighting coefficient for road surface friction coefficients with relatively low confidence levels lower than the second weighting coefficient for road surface friction coefficients with relatively high confidence levels. If the confidence level of the extracted road surface friction coefficients is less than a predetermined value, the road surface friction coefficient calculation device 5 multiplies the road surface friction coefficient by the first weighting coefficient, and if the confidence level of the extracted road surface friction coefficients is equal to or greater than the predetermined value, it multiplies the road surface friction coefficient by the second weighting coefficient. The road surface friction coefficient calculation device 5 calculates an estimated value of the road surface friction coefficient based on the sum of the road surface friction coefficient multiplied by the first weighting coefficient and the road surface friction coefficient multiplied by the second weighting coefficient, and stores it in the storage device 44 as road surface friction coefficient information 441 associated with the location information of the target point. In this example as well, it can be calculated using the above formula (1). In formula (1), the first weighting coefficient a is set to a lower value than the second weighting coefficient b. By relatively increasing the weighting of road surface friction coefficients with high confidence in the road surface friction coefficient, that is, road surface friction coefficients with high detection accuracy, and relatively decreasing the weighting of road surface friction coefficients with low detection accuracy, it is possible to estimate a road surface friction coefficient that reflects the conditions at the time of detection.

[0017] The driver assistance system 100 includes map information 6. Map information 6 is used in manual or autonomous driving control. When performing autonomous driving control, map information 6, which is high-precision map information including lane information 61 that identifies each lane, is used. Lane information 61 includes identification information that identifies each of the multiple lanes belonging to the road. Map information 6 is recorded in one or more of the following: ROM 12 or RAM 13, the storage device of the navigation device 7, and the storage device of an external server accessible to the processor 10 via the communication device 40.

[0018] The driver assistance system 100 includes a navigation device 7. The navigation device 7 refers to map information 6 and calculates a target route from the current location to a set destination. The trajectory information of the target route calculated by the navigation device 7 is provided to the vehicle controller 200 and used for autonomous driving control. The trajectory information of the target route includes location information, trajectory information, and turning curvature (hereinafter also referred to as curvature). One or more points among the points that make up the target route are identified as target points.

[0019] The driver assistance system 100 has a vehicle controller 200. The vehicle controller 200 includes a steering control device 210, a drive control device 220, and a braking control device 230, and acquires command values ​​for autonomous driving control according to a driving plan formulated by the processor 10 of the driver assistance device 1, and causes the vehicle to drive along a target route. The target route consists of a plurality of consecutive unit target trajectories. The target route includes command values ​​for driving control associated with each point, including the target point. The command values ​​for driving control are generated by the vehicle controller 200 or the processor 10. The command values ​​are vehicle control command values ​​for the vehicle to drive along the target route. The command values ​​include the set speed (including upper speed limit and target speed) when driving the vehicle, and the vehicle controller 200 drives the vehicle according to the set speed. Based on the command values, the vehicle controller 200 inputs longitudinal and lateral forces to the drive control device 220, the braking control device 230, and the steering control device 210 to control the driving position of the vehicle during driving. In accordance with these input command values, the behavior of the vehicle body and wheels is controlled to autonomously drive along the route to the destination at the target speed. At least one of the drive actuators of the vehicle body's drive mechanism controlled by the drive control device 220 and the brake actuators of the vehicle body's braking mechanism controlled by the brake control device 230, along with the steering actuator of the steering control device 210 which is activated as needed, operate autonomously to perform driving control that allows the vehicle to autonomously drive along the target route. In addition, the vehicle controller 200 can perform manual driving according to command values ​​based on the driver's manual operations input via the input device 20. Furthermore, the vehicle controller 200 can perform driving that coordinates command values ​​based on the driver's manual operations input via the input device 20 with command values ​​based on the driving plan.

[0020] The driver assistance device 1 of the driver assistance system 100 supports autonomous driving control and manual driving control to drive the vehicle along a target route. The driver assistance device 1 formulates a driving plan to drive the vehicle along a target route. The driving plan includes command values ​​for longitudinal and lateral forces to drive the vehicle autonomously along the target route. The processor 10 of the driver assistance device 1 includes a ROM (Read Only Memory) 12 that stores a program for controlling the driving (driving) of the vehicle to execute deceleration control of the vehicle based on the evaluation result of the amount of deviation from the target route, a CPU (Central Processing Unit) 11 that executes the program stored in the ROM 12, and a RAM (Random Access Memory) 13 that functions as an accessible storage device. The processor 10 implements this driver assistance method using each hardware of the driver assistance system 100. With the driver assistance of this embodiment, the vehicle is made to perform autonomous driving and / or manual (manual) driving. The driver assistance device 1 is equipped with an input device 20. The input device 20 receives input of driving operations from the occupant and input of in-vehicle equipment operations. The input device 20 includes a steering wheel, accelerator pedal, brake pedal, touch panel type display with input function, and microphone for voice input. The driver assistance device 1 includes an output device 30. The output device 30 includes a display, speaker, and lamp. The output device 30 outputs the control contents of the driver assistance device 1. The driver assistance device 1 includes a communication device 40. The communication device 40 performs communication with each device of the driver assistance system 100 using a CAN (Controller Area Network) communication system or the like. The communication device 40 has vehicle-to-vehicle communication functions with on-board devices of other vehicles, vehicle-to-infrastructure communication functions with roadside devices, and wireless communication functions with external devices.

[0021] The features of the driver assistance system in this embodiment will be described. Figure 2(a) shows an example of a scene in which the driver assistance control of this embodiment is executed. The vehicle V1 drives along the target path RT. In this example, the target path RT has a predetermined curvature ρ and is a steady circle. The vehicle V1 travels along the target path RT in a steady-state circular turn. The processor 10 acquires the position and speed of the vehicle using the sensor 2. The processor 10 acquires the road surface friction coefficient μ for the target point i. The processor 10 may also acquire the road surface friction coefficient μ using the road surface information acquisition device 41. The processor 10 acquires the turning curvature ρ for the target point i of the target path RT. The processor 10 may acquire the turning curvature ρ of the target path RT from map information 6 or calculate it from the forward image information of the camera 21. Figure 2(b)(b1) shows the turning curvature ρi as a function of the distance from the current position (origin 0) of the vehicle V1. The distance is along the direction of travel of the vehicle V1, and one or more target points i are set on the target path RT along this direction of travel. In the driving assistance of this embodiment, the processor 10 sets one or more target points i in front of the current position of the vehicle traveling along the target route. The processor 10 obtains the speed of the vehicle and the road surface friction coefficient related to the target point i. The road surface friction coefficient μn is a road surface friction coefficient based on information detected at the target point i in front using sensors 2 mounted on the vehicle or other vehicles. Past detected road surface friction coefficients are stored at least temporarily in the storage device 44 as road surface friction coefficient information 441 and provided to the processor 10. The aforementioned road surface friction coefficient calculation device 5 may calculate an estimated value of a single road surface friction coefficient by referring to the road surface friction coefficient information 441 in the storage device 44. The road surface friction coefficient calculation device 5 stores the calculated estimated value of the road surface friction coefficient in the storage device 44 as road surface friction coefficient information 441, associated with the target position i.

[0022] Here, the method for setting target points i will be explained. The processor 10 sets one or more target points i used for driving assistance processing on the target route RT in front of the current position of the vehicle V1. The processor 10 may also set target points i at predetermined points on the target route. Target points i may also be set at predetermined intervals. The processor 10 may set at least one target point i in the region where the turning curvature of the target path is greater than or equal to a predetermined value. In the region where the turning curvature of the target path is greater than or equal to a predetermined value (nonlinear portion), the influence of changes in the road surface friction coefficient (non-uniformity) on driving control tends to be greater. In other words, changes in the road surface friction coefficient are more likely to act as a disturbance on driving control. The processor 10 extracts points in front of its own vehicle where the turning curvature is greater than or equal to a predetermined value and sets target point i at points where disturbances on driving control may occur. Furthermore, the processor 10 can set multiple target points in regions where the turning curvature of the target path is greater than or equal to a predetermined value. Specifically, the processor 10 sets multiple target points i such that the spacing between target points set adjacent to each other in regions where the turning curvature of the target path is greater than or equal to a predetermined value is narrower than the spacing between target points set adjacent to each other in regions where the turning curvature of the target path is less than a predetermined value. In other words, multiple target points i are set at relatively narrow intervals in regions where the turning curvature of the target path is greater than or equal to a predetermined value (nonlinear portion), and multiple target points i are set at relatively wide intervals in regions where the curvature of the target path is less than a predetermined value (linear, straight portion). As a result, in situations where the turning curvature in front of the vehicle is greater than or equal to a predetermined value and there is a high possibility that changes in the road surface friction coefficient will affect driving control, the maximum acceleration / maximum deceleration at each target point i set at relatively short intervals is monitored, so that an appropriate target speed profile can be calculated in response to disturbances caused by road surface conditions, and driving control can be appropriately supported. In curved areas, which are highly susceptible to road surface conditions, the system monitors the maximum acceleration / deceleration acting on the vehicle at a high frequency, while in straight areas, which are less affected by road surface conditions, the monitoring load for the appropriate speed profile can be reduced.

[0023] Figure 2(b)(b2) shows the road surface friction coefficient μi on the target route RT. Road surface friction coefficients μ1, μ2, μ3, and μ4 are obtained for each predetermined area of ​​the target route RT. Different road surface friction coefficients are sometimes grouped together and shown as "μ". The start and end points of each area are defined by the coordinates of the target point. The road surface friction coefficient μ1 of area a, which is closest to the current position of the vehicle V1, is higher than the road surface friction coefficient μ2 of the adjacent area b. The road surface friction coefficient μ3 of area c, which is traveled after area b, is higher than the road surface friction coefficient μ2 that was passed before it. The road surface friction coefficient μ4 of area d, which is traveled after area c, is lower than the road surface friction coefficient μ3 that was passed before it. Although not particularly limited, road surface friction coefficients μ1 and μ3 are approximately equal, and road surface friction coefficients μ2 and μ4, which are relatively lower than these, are approximately equal. The road surface friction coefficient of the target route RT is non-uniform (mottled) and varies depending on the driving position / driving area. When the road surface friction coefficient μi changes, the first velocity VS1i, which is derived from the turning curvature ρi and the road surface friction coefficient μi, also changes. Figure 2(b3) shows the first velocity profile P1, which is the first velocity VS1(Vgeoi) at each point (including the target point), when the curvature is constant as shown in Figure 2(b1) and when the road surface friction coefficient μ changes as shown in Figure 2(b2). Here, an example with constant curvature is shown to demonstrate the effect of the road surface friction coefficient μ, but this driving assistance method can also be applied when the curvature is not constant.

[0024] The processor 10 calculates the first velocity VS1(Vgeoi) at target point i based on the road surface friction coefficient μ and curvature ρ. The first velocity VS1(Vgeoi) is the maximum speed at which the vehicle V1 can travel along the target route RT, and is geometrically calculated based on the road surface friction coefficient μi and turning curvature ρi at each target point i on the target route RT. The first velocity VS1(Vgeoi) does not take into account the acceleration and deceleration components acting on the vehicle V1. Specifically, the first velocity VS1(Vgeoi) is calculated by the following equation (2).

number

[0025] Based on Figure 3, the method for calculating the target speed profile TP, in which the target speed TVS is defined at each target point i, will be explained. Figure 3(a) shows the first speed profile P1, Figure 3(b) shows the second speed profile P2 for the second speed VS2 (VLimAcci) during acceleration, and Figure 3(c) shows the third speed profile P3 for the third speed VS3 (VLimDeci) during deceleration.

[0026] Figure 3(a) shows the first speed profile P1, in which the first speed VS1 corresponding to the change in the road surface friction coefficient μ is associated with the target point i. This corresponds to the first speed profile P1 shown in Figure 2(b3). The first speed VS1 is calculated based on equation (2) above. Figure 3(b) shows the second speed profile P2, in which the second speed VS2 is associated with the target point i. The processor 10 calculates the second speed VS2 at the target point i where acceleration is performed, using the maximum acceleration AxAcc obtained using the road surface friction coefficient μ. The second speed VS2 is the speed that can be achieved when the vehicle V1 travels along the target path RT, calculated based on acceleration considering the road surface friction coefficient μi, acceleration considering the acceleration performance of the drive actuator of the drive control device 220, or a predefined acceleration. The second speed VS2(VLimAcci) is calculated using the following equation (3). The component AxAcc of the maximum acceleration is calculated using μg (where g is the acceleration due to gravity).

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[0027] Figure 3(c) shows the third speed profile P3, in which the third speed VS3(VLimDeci) is associated with the target point i. The processor 10 calculates the third speed VS3(VLimDeci) at the target point i where deceleration is performed, using the component AxDec of the maximum deceleration acting during deceleration, which is determined using the road surface friction coefficient μ. The third speed VS3 is the speed that the vehicle V1 can achieve when traveling along the target path RT, calculated based on deceleration considering the road surface friction coefficient μi, deceleration considering the braking performance of the braking actuator, or a predefined deceleration. The third speed VS3 is calculated using the following equation (5). The maximum deceleration AxDec is calculated using μg (where g is the acceleration due to gravity).

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[0028] The processor 10 selects the first speed VS1 as the target speed TVS for locations other than the target location i where acceleration is not occurring (i.e., location i where deceleration is not occurring), and calculates a target speed profile TP by associating the selected target speed TVS with location i. Figure 3(d) shows the target speed profile TP obtained by connecting the first speed VS1, second speed VS2, and third speed VS3 selected by the above method along location i arranged in order of increasing distance from the current position.

[0029] Comparing the target speed profile TP and the first speed profile P1 in Figure 3(d), the speed change is more gradual. If the road surface friction coefficient is not uniform along the target route RT and changes abruptly, applying the brakes from a point of abrupt deceleration may result in a large G-jerk in the vehicle V1 in order to decelerate it to a speed at which it can turn. In contrast, according to the driving support method of this embodiment, the target speed profile TP is calculated at the point where the road surface friction coefficient changes, taking into account the maximum acceleration and deceleration using the road surface friction coefficient. Therefore, even when driving along a target route with an uneven (mottled) road surface friction coefficient, the generation or amount of G-jerk can be suppressed. In particular, if the target route RT is not a straight route but involves curvature, it is susceptible to the effects of fluctuations in the road surface friction coefficient. In this embodiment, the first speed VS1 based on the road surface friction coefficient and turning curvature is set as the upper limit, and the constraint is that the first speed VS1 should not be exceeded. Therefore, at the point where the road surface friction coefficient changes, it is possible to avoid formulating a driving plan at a speed exceeding the first speed VS1. In this way, a target speed profile TP can be prepared in advance that is appropriate for the speed of acceleration and deceleration acting on the vehicle V1 during acceleration and deceleration, while ensuring that the first speed VS1 is not exceeded (avoiding overspeeding). Incidentally, from the perspective of controlling the speed of the vehicle, if the first speed VS1 when driving in an area with a low road surface friction coefficient is set as the target speed, the vehicle's speed may be too slow to keep up with the traffic flow (disrupting the traffic flow), and this cannot be said to be an appropriate speed plan. In this embodiment, a relatively high speed is set as the target speed TVS in areas other than areas with a low road surface friction coefficient, and a relatively low speed is set as the target speed TVS in areas with a low road surface friction coefficient. When switching between these speeds, a target speed TVS is set in advance to prepare for deceleration or acceleration, so that the driving of the vehicle can be supported at an appropriate speed to follow the traffic flow. Thus, in this embodiment, since the maximum acceleration during acceleration and the maximum deceleration during deceleration are used, a target speed is set that mitigates the speed change when accelerating in response to an increase in the road surface friction coefficient μ, and the amount of speed change when decelerating in response to a decrease in the road surface friction coefficient μ is reduced, thereby mitigating the speed change when traveling along the target path.

[0030] In this embodiment, the maximum acceleration corresponds to AxAcc on the right-hand side of equation (3). The maximum acceleration is calculated using one or more of the following: a first acceleration calculated based on the road surface friction coefficient μ, a second acceleration calculated based on the acceleration performance of the drive actuator of the drive control device 220, and a preset third acceleration. Although not particularly limited, the maximum acceleration can be calculated based on the first acceleration and the second acceleration. The maximum acceleration can be calculated based on the first acceleration and the third acceleration. The maximum acceleration can be calculated based on the first acceleration, the second acceleration, and the third acceleration. The maximum acceleration can be calculated based on the first acceleration, the second acceleration, or the third acceleration.

[0031] The processor 10 can calculate the maximum acceleration using the road surface friction coefficient μ at the target point i. Specifically, it can calculate AxAcc in equation (3) using AxAcc = μg. The first acceleration is the acceleration during acceleration, which is determined using the road surface friction coefficient μ. The processor 10 may further calculate the maximum acceleration based on the acceleration performance of the drive actuator of the vehicle's drive control device 220. The processor 10 calculates a second acceleration based on the acceleration performance of the drive actuator and uses the second acceleration to calculate the maximum acceleration. The acceleration performance includes the maximum acceleration amount or acceleration gradient of each vehicle. Since the acceleration performance differs depending on the vehicle (vehicle type, vehicle specifications) and driving environment, it is preferable to determine it experimentally in advance and store it. By calculating the maximum acceleration using the acceleration performance of the vehicle's drive actuator, it is possible to calculate a target speed TVS that reflects the actual driving conditions better than when using the maximum acceleration based only on the road surface friction coefficient μ. The processor 10 may further calculate the maximum acceleration using a preset third acceleration. The third acceleration is the upper limit of the allowable acceleration in driving control. The third acceleration is a threshold based on the acceleration at which occupants experience negative impressions such as discomfort, surprise, or anxiety due to acceleration. The third deceleration may be 0.2G to 0.4G, although this is not particularly limited. The third deceleration may be 0.3G, although this is not particularly limited.

[0032] In this embodiment, the maximum deceleration corresponds to AxDec on the right-hand side of equation (5). The maximum deceleration is calculated using one or more of the following: a first deceleration calculated based on the road surface friction coefficient μ, a second deceleration calculated based on the braking performance of the braking actuator of the braking control device 230, and a preset third deceleration degree. Although not particularly limited, the maximum deceleration can be calculated based on the first and second decelerations. The maximum deceleration can be calculated based on the first and third decelerations. The maximum deceleration can be calculated based on the first, second, and third decelerations. The maximum deceleration can be calculated based on the first, second, or third deceleration. The processor 10 can calculate the maximum deceleration using the road surface friction coefficient μ at the target point i. Specifically, it can be calculated using AxDec = μg for AxDec in equation (5). The first deceleration is the deceleration during deceleration, which is determined using the road surface friction coefficient μ. The processor 10 further calculates a second deceleration based on the braking performance of the braking actuator of the vehicle's braking control device 230, and uses the second deceleration to calculate the maximum deceleration. Braking performance includes the maximum deceleration amount or deceleration gradient of each vehicle. Since braking performance differs depending on the vehicle (vehicle type, vehicle specifications) and driving environment, it is preferable to determine it experimentally in advance and store it. By calculating the maximum deceleration using the braking performance of the vehicle's braking actuator, it is possible to calculate a target speed TVS that reflects the actual driving conditions better than when using the maximum deceleration based solely on the road surface friction coefficient μ. The processor 10 may further calculate the maximum deceleration using a preset third deceleration. The third deceleration is the permissible upper limit of the degree of deceleration allowed in driving control. The third deceleration is a threshold based on the deceleration at which occupants experience negative impressions such as discomfort, surprise, or anxiety due to the deceleration. The third deceleration may be 0.2G to 0.4G, although it is not particularly limited. The third deceleration may be 0.3G, although it is not particularly limited.

[0033] The processor 10 selects the lowest value among the first acceleration calculated based on the road surface friction coefficient μ, the second acceleration calculated based on the acceleration performance of the drive actuator, or a preset third acceleration, and uses the selected value to calculate the maximum acceleration. If the first acceleration is greater than the second or third acceleration, the processor 10 selects the second or third acceleration instead of the first acceleration and uses the second or third acceleration to calculate the maximum acceleration. The processor 10 also selects the lowest value among the first deceleration calculated based on the road surface friction coefficient μ, the second deceleration calculated based on the braking performance of the drive actuator, or a preset third deceleration, and uses the selected value to determine the maximum deceleration. If the first deceleration is greater than the second or third deceleration, the processor 10 selects the second or third deceleration instead of the first deceleration and uses the second or third deceleration to calculate the maximum deceleration. This makes it possible to generate a target speed profile TP with small, gradual speed changes, even if the road surface friction coefficient of the target path RT is not uniform.

[0034] Here, the third deceleration is lower than the first and second decelerations (third deceleration < first deceleration, third deceleration < second deceleration). The relative magnitudes of the first and second decelerations are not particularly limited. When the third deceleration is selected, the processor 10 determines whether the vehicle can follow the target route RT when decelerating at the maximum deceleration calculated using the third deceleration. Although not particularly limited, the processor 10 calculates the target speed TVS at target point i based on the maximum deceleration calculated using the third deceleration at target point i. If the calculated target speed TVS is higher than the first speed VS1 at target point i, the processor 10 predicts that the vehicle will be overspeeding at target point i and determines that it cannot follow the target route RT. If the calculated target speed TVS is less than or equal to the first speed VS1 at target point i, the processor 10 predicts that the vehicle will not be overspeeding at target point i and determines that it can follow the target route RT. If the processor 10 determines that its own vehicle cannot follow the target route RT, it changes the maximum deceleration to the maximum deceleration calculated using the first or second deceleration. This allows the system to calculate a target speed TVS with a gradual change in speed, assuming that the vehicle can follow the target route RT.

[0035] When the processor 10 calculates the maximum deceleration and changes the third deceleration to the first or second deceleration, it uses the output device 30 of the vehicle V1 to output information to the occupants indicating that driving will be supported at a deceleration higher than the third deceleration. The display of the output device 30 may show text such as "Caution: Deceleration" or a graphic indicating an increase in the amount of deceleration. The speaker of the output device 30 may output text such as "Decelerating" or a beep sound to warn the occupants. The lamp of the output device 30 may be turned on or flashed to warn the occupants. This allows the occupants to be notified in advance that a deceleration change exceeding the third deceleration is occurring, which may cause anxiety among the occupants.

[0036] The control procedure for the support processing of the operation control in this embodiment will be described below based on the flowchart in Figure 4. The processor 10 acquires vehicle information, including the vehicle's position (including its current position) and speed, using the sensor 2 and / or the vehicle information acquisition device 3 (S1). The vehicle information includes the vehicle's specifications, status, and control information. The processor 10 calculates the target route RT from the current position to the destination by referring to the map information 6 (S2). The route calculation process may be performed by the navigation device 7. The processor 10 calculates a driving plan to have the vehicle drive the target route RT (S3). The driving plan includes the target speed at each point (including the target point i). The target route and driving plan in this embodiment are formulated without considering the road surface friction coefficient.

[0037] The processor 10 sets one or more target points i in front of the vehicle V1 on the target route RT (S4). As described above, the processor 10 may set the target points i to include points where the curvature ρ is greater than or equal to a predetermined value, or it may set the target points i by relatively narrowing the intervals between them in a region that includes points where the curvature ρ is greater than or equal to a predetermined value. Since disturbances due to changes in the road surface friction coefficient are likely to occur in places where the target route RT is not straight, it is preferable to execute the driving assistance of this embodiment in such situations. The processor 10 may also set target points i in front of the vehicle V1 when a change in the road surface friction coefficient μ is predicted. The processor 10 may set target points i to include points where a change in the road surface friction coefficient μ is predicted. Since the appropriate target speed also changes in situations where the road surface friction coefficient of the target route RT is not uniform (it is patchy) and the road surface friction coefficient changes, it is preferable to execute the driving assistance of this embodiment in such situations.

[0038] The processor 10 acquires the road surface friction coefficient μi for the set target point i using one or more of the sensor 2, the driving environment information acquisition device 4, and the road surface friction coefficient calculation device 5 (S5). As described above, the method for acquiring the road surface friction coefficient μi is to acquire it from the sensor 2 mounted on the vehicle itself, to acquire it from the sensor 2 mounted on another vehicle via vehicle-to-vehicle communication, or to acquire it via an external server. The road surface friction coefficient information 441 is stored in advance in a readable recording medium such as the storage device 44, ROM 12, or RAM 13. The processor 10 may acquire the road surface friction coefficient calculated by the road surface friction coefficient calculation device 5 based on a plurality of road surface friction coefficients μ stored in the storage device 44 by the vehicle itself or another vehicle. The processor 10 acquires the curvature ρi for the target point i (S6).

[0039] The processor 10 calculates the first velocity VGioi(VS1) at the target point i based on the road surface friction coefficient μi and curvature ρi (S7). Although not particularly limited, the processor 10 calculates the first velocity VGioi(VS1) using the above equation (2). The processor 10 stores the road surface friction coefficient μi, which was obtained in S5 and used to calculate the first velocity VGioi(VS1), in the storage device 44 (S8). The processor 10 stores the road surface friction coefficient μi in a readable format in association with the location information (coordinate information, area identification information) of the target point i. The processor 10 stores the road surface friction coefficient μi in the storage device 44 as road surface friction coefficient information 441 in a readable format in association with the road surface environment, which includes one or more of the weather, temperature, and road surface conditions of the target point i.

[0040] The processor 10 calculates the second speed VLimAcci(VS2) at the target point i where acceleration is performed using the road surface friction coefficient μi (S9). Although not particularly limited, the processor 10 calculates the second speed VLimAcci(VS2) using the above equation (3). The maximum acceleration AxAcc used in calculating the second speed VLimAcci(VS2) is calculated based on the lowest value among the first acceleration calculated based on the road surface friction coefficient μi, the second acceleration calculated based on the acceleration performance of the drive actuator, or a preset third acceleration. The processor 10 calculates the third speed VLimDeci(VS3) at the target point i where deceleration is performed using the road surface friction coefficient μi (S10). Although not particularly limited, the processor 10 calculates the third speed VLimDeci(VS3) using the above formula (5). The maximum deceleration AxDec used in calculating the third speed VLimDeci(VS3) is calculated based on the first deceleration calculated based on the road surface friction coefficient μi, the second deceleration calculated based on the braking performance of the braking actuator, or a preset third deceleration degree.

[0041] The processor 10 identifies target points i where acceleration will be performed and target points i where deceleration will be performed based on the first speed VGioi(VS1) (S11). The processor 10 may also identify target points i where acceleration will be performed and target points i where deceleration will be performed based on the road surface friction coefficient μi of the target point i in front of the vehicle. In the first speed profile TP, the processor 10 identifies target points (i+1)(i-1) as target points where acceleration will be performed if the difference in the increase of the first speed VGioi(VS1) between adjacent target points (i,i-1)(i,i-1) is greater than or equal to a predetermined value. The processor 10 identifies target point i-1 as a target point where deceleration will be performed if the difference in the decrease of the first speed VGioi(VS1) between adjacent target points (i,i-1)(i,i+1) is greater than or equal to a predetermined value. As shown in Figures 2(b2) and 2(b3), the first speed VGioi(VS1) increases where the road surface friction coefficient μi increases, and decreases where the road surface friction coefficient μi decreases. Based on this trend, the target point i where the first speed VGioi(VS1) changes (accelerates / decels) based on the change in the road surface friction coefficient μi can be identified. The processor 10 identifies target points (i+1) and (i-1) as target points where acceleration will be performed if the difference in the increase of the road surface friction coefficient μi between adjacent target points (i,i+1) and (i,i-1) is greater than or equal to a predetermined value. The processor 10 identifies target points (i-1) and (i+1) as target points where deceleration will be performed if the difference in the decrease of the road surface friction coefficient μi between adjacent target points (i,i-1) and (i,i+1) is greater than or equal to a predetermined value. The processor 10 may identify multiple target points located in the vicinity (both adjacent, within a predetermined distance range) of a single target point where a speed change has been calculated as target points where acceleration or deceleration will be performed.

[0042] The processor 10 selects a second speed VLimAcci(VS2) as the target speed TVS at target point i where acceleration is performed, which is lower than the first speed VGioi(VS1) (S12). As shown in Figure 3(b), the processor 10 selects the second speed VLimAcci(VS2) instead of the first speed VGioi(VS1) at target point ai+1 where acceleration is performed. The target point i where acceleration is performed may be a point where the increase in the speed of the vehicle V1 or the acceleration is greater than or equal to a first predetermined value. The processor 10 selects a third speed VLimDeci(VS3), which is lower than the first speed VGioi(VS1), as the target speed TVS at target point i where deceleration is performed (S13). As shown in Figure 3(c), the processor 10 selects the third speed VLimDeci(VS3) instead of the first speed VGioi(VS1) at target point di-1 where acceleration is performed. The target point i where deceleration is performed may be a point where the amount of reduction or deceleration of the vehicle's speed V1 is greater than or equal to a second predetermined value. The first predetermined value and the second predetermined value may be the same or different.

[0043] The processor 10 selects the first speed VGioi(VS1) as the target speed TVS at target point i where driving other than acceleration and deceleration is performed (S14). As shown in Figures 3(b) and 3(c), the processor 10 selects the first speed VGioi(VS1) at target point i where neither acceleration nor deceleration is performed. Target point i where driving other than acceleration is performed is a point where the increase in the speed of the vehicle V1 or the acceleration is less than a first predetermined value. Target point i where driving other than deceleration is performed is a point where the decrease in the speed of the vehicle V1 or the deceleration is less than a second predetermined value. The processor 10 generates a target speed profile TP that associates the selected target speed TVS with the target point i (S15). The processor 10 generates acceleration control commands and deceleration control commands for each target point i according to the defined target speed profile TP and outputs them to the vehicle controller 200 (S16). The vehicle controller 200 performs support for the driving control of its own vehicle V1 (S17). The drive actuator of the drive control device 220 of the vehicle controller 200 performs drive control according to the acceleration control command. The brake actuator of the brake control device 230 of the vehicle controller 200 performs brake control according to the brake control command. [Explanation of Symbols]

[0044] 100…Driving assistance system, 1…Driving assistance device, 10…Processor, 11…CPU, 12…ROM, 13…RAM, 20…Input device, 30…Output device, 40…Communication device, 2…Sensor, 21…Camera, 22…Radar device, 3…Vehicle information acquisition device, 4…Driving environment information acquisition device, 5…Road surface friction coefficient calculation device, 6…Map information, 61…Lane information, 7…Navigation device, 200…Vehicle controller, 210…Steering control device, 220…Drive control device, 230…Braking control device

Claims

1. A driver assistance method used in a processor to assist in driving the vehicle traveling along a target route, The aforementioned processor, The vehicle information, including the position and speed of the vehicle, is acquired. Setting one or more target points in front of the vehicle's current position, The road surface friction coefficient and curvature related to the aforementioned target point are obtained. Based on the aforementioned road surface friction coefficient and curvature, the first speed at the target point is calculated. Using the maximum acceleration during acceleration determined using the aforementioned road surface friction coefficient, the second speed at the target point where acceleration is performed is calculated. Using the maximum deceleration during deceleration determined using the aforementioned road surface friction coefficient, the third speed at the target point where deceleration is performed is calculated. At the target location where acceleration is performed, a second speed lower than the first speed is selected as the target speed; at the target location where deceleration is performed, a third speed lower than the first speed is selected as the target speed; at the target location where driving other than acceleration and other than deceleration is performed, the first speed is selected as the target speed; and a target speed profile is generated that associates the selected target speed with the target location. A driving assistance method that assists in driving the vehicle in accordance with the target speed profile.

2. The driving assistance method according to claim 1, wherein the processor calculates the maximum acceleration using the acceleration performance of the vehicle's drive actuator and calculates the maximum deceleration using the braking performance of the vehicle's brake actuator.

3. The driving assistance method according to claim 1, wherein the processor selects the lowest value among a first acceleration calculated based on the road surface friction coefficient, a second acceleration calculated based on the acceleration performance of the vehicle's drive actuator, or a preset third acceleration, and calculates the maximum acceleration using the selected value, and selects the lowest value among a first deceleration calculated based on the road surface friction coefficient, a second deceleration calculated based on the braking performance of the vehicle's brake actuator, or a preset third deceleration, and calculates the maximum deceleration using the selected value.

4. The third deceleration is lower than the first and second decelerations. The driving assistance method according to claim 3, in which the processor determines that, when the third deceleration is selected, the vehicle cannot follow the target path when decelerated at the maximum deceleration calculated using the third deceleration, it changes the third deceleration to the first deceleration or the second deceleration, and calculates the maximum deceleration using the changed first deceleration or second deceleration.

5. The driving assistance method according to claim 4, wherein when the processor changes the third deceleration to the first deceleration or the second deceleration to calculate the maximum deceleration, it outputs using the vehicle's output device that driving is supported at a deceleration higher than the third deceleration.

6. The driving assistance method according to claim 1, wherein the processor stores the acquired road surface friction coefficient for the target point in a storage device in a state that can be read by the processor, in association with the location information of the target point.

7. The driving assistance method according to claim 6, wherein the processor stores the region including the target point as position information and associates it with the road surface friction coefficient.

8. The driving assistance method according to claim 7, wherein the processor stores the region where the road surface environment is common as the position information of the target point, corresponding to the road surface friction coefficient.

9. The driving assistance method according to claim 6, wherein the processor associates the acquired road surface friction coefficient for the target location with a road surface environment including one or more of the weather, temperature, and road surface conditions of the target location, and stores it in a storage device in a state that can be read by the processor.

10. The driving assistance method according to claim 6, wherein the processor stores the road surface friction coefficient in association with the timing at which the road surface friction coefficient was acquired, sets a first weighting coefficient for the road surface friction coefficient acquired at a timing relatively far from the current time to be lower than a second weighting coefficient for the road surface friction coefficient acquired at a timing close to the current time, calculates an estimated value of the road surface friction coefficient based on the sum of the road surface friction coefficient multiplied by the first weighting coefficient and the road surface friction coefficient multiplied by the second weighting coefficient, and stores it in association with the position information of the target point.

11. The driving assistance method according to claim 6, wherein the processor stores the road surface friction coefficient in association with the confidence level of the road surface friction coefficient, sets a first weighting coefficient for the road surface friction coefficient with a relatively low confidence level lower than a second weighting coefficient for the road surface friction coefficient with a relatively high confidence level, calculates an estimated value of the road surface friction coefficient based on the sum of the road surface friction coefficient multiplied by the first weighting coefficient and the road surface friction coefficient multiplied by the second weighting coefficient, and stores it in association with the location information of the target point.

12. A driver assistance system equipped with a processor that assists in driving the vehicle along a target route, The aforementioned processor, The vehicle information, including the position and speed of the vehicle, is acquired. Setting one or more target points in front of the vehicle's current position, The road surface friction coefficient and curvature related to the aforementioned target point are obtained. Based on the aforementioned road surface friction coefficient and curvature, the first speed at the target point is calculated. Using the maximum acceleration during acceleration determined using the aforementioned road surface friction coefficient, the second speed at the target point where acceleration is performed is calculated. Using the maximum deceleration during deceleration determined using the aforementioned road surface friction coefficient, the third speed at the target point where deceleration is performed is calculated. At the target location where acceleration is performed, a second speed lower than the first speed is selected as the target speed; at the target location where deceleration is performed, a third speed lower than the first speed is selected as the target speed; at the target location where driving other than acceleration and other than deceleration is performed, the first speed is selected as the target speed; and a target speed profile is generated that associates the selected target speed with the target location. A driver assistance device that assists in driving the vehicle according to the aforementioned target speed profile.

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