Driving assistance method and driving assistance device

Abstract

It assists in controlling vehicle operation when disturbances occur due to road surface conditions. [Solution] The processor 10 acquires vehicle information including the position and speed of the vehicle, sets one or more target points i in front of the vehicle traveling along the target route RT, acquires a first road surface friction coefficient μi for the target point i, compares the acquired first road surface friction coefficient μi with a preset second road surface friction coefficient μs, and if the first road surface friction coefficient μi is lower than the second road surface friction coefficient μs, calculates the lateral acceleration Ayi acting in the vehicle width direction at the target point i, calculates the amount of deviation from the target route RT at the target point i based on the lateral acceleration Ayi, and if it is determined that the amount of deviation is greater than or equal to a predetermined value, starts deceleration control of the vehicle.

Description

Technical Field

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

Background Art

[0002] When it is determined that the vehicle is in a deviation state where it has deviated from the target trajectory, a suppression amount for reducing the target vehicle speed is calculated based on the deviation amount, the target vehicle speed is suppressed using a holding value that is the maximum value of the suppression amount, the vehicle is returned from the deviation state to the target trajectory, and when a preset release condition is satisfied, a technique is known in which the holding value of the suppression amount is decreased at a predetermined speed (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 the driving support of the vehicle when a disturbance caused by the road surface state in front of the vehicle occurs has not been studied.

[0005] The problem to be solved by the present invention is to support the driving of the vehicle when a disturbance caused by the road surface state in front of the vehicle occurs.

Means for Solving the Problems

[0006] The present invention solves the above problem by acquiring a first road surface friction coefficient with respect to a target point in front of the vehicle, comparing the acquired first road surface friction coefficient with a preset second road surface friction coefficient, calculating the lateral acceleration acting in the vehicle width direction at the target point if the first road surface friction coefficient is lower than the second road surface friction coefficient, calculating the amount of deviation from the target path at the target point based on the lateral acceleration, and initiating deceleration control of the vehicle if it is determined that the amount of deviation is greater than or equal to a predetermined value. [Effects of the Invention]

[0007] According to the present invention, it is possible to assist in the operation of a vehicle when disturbances occur due to the road surface conditions 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 is a functional block diagram related to driver assistance. [Figure 3] Figure 3 shows an example of vehicle deviation. [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 road surface information acquisition device 4, map information 5, and a navigation device 6. 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 30. 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 30. 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 30 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 road surface information acquisition device 4, 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 and the road surface information acquisition device 4.

[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 road surface information acquisition device 4 acquires a first road surface friction coefficient for each point (including the target point) along the target route traveled by the vehicle being driven. The first road surface friction coefficient for the target point may be the road surface friction coefficient of the target point itself, or the road surface friction coefficient of the area including the target point. The road surface information acquisition device 4 can acquire a first road surface friction coefficient using a sensor 2 mounted on the vehicle or on-board equipment. If the temperature detected by the thermometer (sensor 2) is within the road surface freezing temperature range, the road surface information acquisition device 4 may acquire a road surface friction coefficient defined as for freezing conditions as the first road surface friction coefficient. If the road surface information acquisition device 4 acquires rainfall information detected by the raindrop sensor (sensor 2) and operation information of the wipers that are operated during rainfall, it may acquire a road surface friction coefficient defined as for water film formation conditions as the first road surface friction coefficient. The road surface information acquisition device 4 may acquire weather information at the target location from an external device (sensor 2) and acquire road surface friction coefficients for each state defined according to the weather (freezing, water film formation, wet, dry) as the first road surface friction coefficient for the target location. The road surface information acquisition device 4 may calculate a first road surface friction coefficient for the target location based on detection information acquired from one or more of the G sensor, 6-axis inertia sensor, and road surface condition determination sensor. The first road surface friction coefficient includes the detected road surface friction coefficient and the road surface friction coefficient based on the detected conditions. The road surface information acquisition device 4 may acquire the first 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 4 sends request information including location identification information (coordinate values ​​such as latitude and longitude) to the server and acquires the first road surface friction coefficient for the target location output from the server. Preferably, the first road surface friction coefficient for the target location of other vehicles acquired via the server is limited to the first road surface friction coefficient stored (detected) within a predetermined time from the time the own vehicle passes the target location. Thus, the first road surface friction coefficient is a road surface friction coefficient that corresponds to the actual conditions of the target location. The first road surface friction coefficient is a road surface friction coefficient based on information detected at the target location.

[0013] The driver assistance system 100 includes map information 5. Map information 5 is used in manual or autonomous driving control. When performing autonomous driving control, map information 5, which is high-precision map information including lane information 51 that identifies each lane, is used. Lane information 51 includes identification information that identifies each of the multiple lanes belonging to the road. Map information 5 is recorded in one or more of the following: ROM 12 or RAM 13, the storage device of the navigation device 6, and the storage device of an external server accessible by the processor 10 via the communication device 30.

[0014] The driver assistance system 100 includes a navigation device 6. The navigation device 6 refers to map information 5 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 6 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. One or more points among the points forming the target route are identified as target points.

[0015] The driving support system 100 has a vehicle controller 200. The vehicle controller 200 includes a steering control device 210, a drive control device 220, and a brake control device 230, and acquires command values for autonomous driving control according to a driving plan formulated by the processor 10 of the driving support device 1, and drives the host vehicle along a target path. The target path is composed of a plurality of continuous unit target trajectories. The target path 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 value is a control command value for the vehicle for the host vehicle to drive along the target path. The command value includes a set speed (including an upper limit speed and a target speed) when driving the vehicle, and the vehicle controller 200 drives the host vehicle according to the set speed. Based on the command value, the vehicle controller 200 inputs longitudinal and lateral forces for controlling the traveling position of the host vehicle during driving to the drive control device 220, the brake control device 230, and the steering control device 210. According to these input command values, the behavior of the vehicle body and the behavior of the wheels of the host vehicle are controlled so as to autonomously drive along the path to the destination at the target speed. At least one of the drive actuator of the vehicle body drive mechanism controlled by the drive control device 220 and the brake actuator of the vehicle body brake mechanism controlled by the brake control device 230, and the steering actuator of the steering control device 210 activated as necessary operate autonomously, and a driving control for autonomously driving the vehicle along the target path is executed. Further, the vehicle controller 200 can execute a manual driving according to a command value based on a manual operation of the driver input via the input / output device 20. Furthermore, the vehicle controller 200 can execute a driving that coordinates a command value based on a manual operation of the driver input via the input / output device 20 and a command value based on the driving plan.

[0016] The driving support device 1 included in the driving support system 100 supports autonomous driving control and manual driving control for driving the host vehicle along a target route. The driving support device 1 formulates a driving plan for driving the host vehicle along the target route. The driving plan includes command values for longitudinal and lateral forces for autonomously driving the host vehicle on the target route. The processor 10 included in the driving support device 1 stores a program in a ROM (Read Only Memory) 12 for controlling the driving (traveling) of the host vehicle so as to execute deceleration control of the host vehicle based on the evaluation result of the deviation amount from the target route, a CPU (Central Processing Unit) 11 that executes the program stored in this ROM 12, and a RAM (Random Access Memory) 13 that functions as an accessible storage device. The processor 10 implements this driving support method using each hardware of the driving support system 100. By the driving support of this embodiment, the host vehicle is caused to execute autonomous driving and / or manual (by hand) driving. The driving support device 1 includes an input / output device 20. The input / output device 20 has an input function for receiving an input from an occupant and an output function for outputting control contents to the occupant. The driving support device 1 includes a communication device 30. The communication device 30 executes communication with each device of the driving support system 100 using a CAN (Controller Area Network) communication system or the like. The communication device 30 has an inter-vehicle communication function with in-vehicle devices of other vehicles, a roadside-vehicle communication function with roadside devices, and a wireless communication function with external devices.

[0017] First, the features of the driving support of this embodiment will be described. In the driving support of this embodiment, the processor 10 sets one or a plurality of target points i in front of the current position of the host vehicle traveling on the target route. The processor 10 acquires the speed of the host vehicle, the first road surface friction coefficient regarding the target point i, and a preset second road surface friction coefficient. The first road surface friction coefficient is a road surface friction coefficient based on information detected at the front target point i using a sensor 2 mounted on the host vehicle or another vehicle. Incidentally, if the target point i is within the detection range of sensor 2, the real-time first road surface friction coefficient can be obtained. The first road surface friction coefficient may be the road surface friction coefficient detected when the vehicle itself or another vehicle passes through the target point i. The first road surface friction coefficient detected in the past is stored in a memory device at least temporarily and provided to the processor 10. The processor 10 may limit the first road surface friction coefficient to be obtained to those detected or recorded within a predetermined time from the current time or the scheduled time of passing through the target point i. The predetermined time may be defined as a time interval such as 1 hour to 24 hours, 1 hour to 48 hours, or as a period during which the same weather or temperature conditions are maintained. By limiting the timing of obtaining the first road surface friction coefficient, it is possible to obtain a first road surface friction coefficient that indicates the road surface condition when the vehicle passes through the target point i. In other words, it is possible to exclude information from several weeks or months ago, when the road surface condition has already changed, and obtain a first road surface friction coefficient that indicates the current road surface condition at the target point i. On the other hand, the second road surface friction coefficient is a representative value of the provisionally defined road surface friction coefficient. In other words, it is a road surface friction coefficient that does not take into account the specific conditions of point i. For example, the second road surface friction coefficient may be a representative value such as the average, median, or mode of the road surface friction coefficient when the road surface is dry and the road surface has been maintained. The processor 10 compares the first road surface friction coefficient at target point i with the second road surface friction coefficient defined as a general value, and starts calculating the amount of deviation of the vehicle if the first road surface friction coefficient is lower than the second road surface friction coefficient. When the first road surface friction coefficient is lower than the second road surface friction coefficient, it is possible that the road surface at target point i on the target path that the vehicle is actually traveling on is more slippery than normal. The processor 10 determines that a disturbance has occurred due to the road surface condition at target point i in front of the vehicle, and that this disturbance may affect the driving control. Triggered by this determination, the processor 10 calculates the lateral acceleration acting in the vehicle width direction at target point i, and calculates the amount of deviation from the target path at target point i based on the lateral acceleration. If the processor 10 determines that the amount of deviation is greater than or equal to a predetermined value, it starts deceleration control of the vehicle.

[0018] Thus, if the actual first road surface friction coefficient at target point i is lower than a predetermined second road surface friction coefficient, the processor 10 predicts that the road surface condition at target point i ahead is more slippery than a typical road surface condition, and predicts that there is a high probability that a disturbance affecting driving control is occurring at target point i. When the processor 10 predicts the occurrence of this disturbance, it starts deceleration control of the vehicle upstream of target point i. By predicting the abnormal road surface condition at target point i before reaching it and starting deceleration control at an early timing, the vehicle can be decelerated to an appropriate speed before reaching target point i where the disturbance is occurring. As a result, deviation of the vehicle at target point i can be prevented.

[0019] Next, the driving support processing of this embodiment will be specifically described with reference to Figures 2 to 4. <Setting the target location> First, the processor 10 sets one or more target points i to be used for driving assistance processing. The processor 10 may set target points i at predetermined points on the target route. Target points i may be set at predetermined intervals. The processor 10 may set at least one target point i in a 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 on driving control tends to increase. 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 the vehicle where the turning curvature exceeds a predetermined value and sets target point i at points where disturbances to the driving control may occur. By monitoring the lateral acceleration and deviation amount at target point i, the processor 10 can preemptively execute appropriate driving control at the appropriate timing in response to disturbances caused by road surface conditions. 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 interval 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 interval 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 lateral acceleration and deviation amount are monitored at each target point i set at relatively short intervals, so that appropriate driving control can be executed in advance at the appropriate timing in response to disturbances caused by road surface conditions. In curved regions that are easily affected by road surface conditions, the deviation of the vehicle is monitored at a high frequency, while in straight regions that are less affected by road surface conditions, the monitoring load for deviation can be reduced. Based on the amount of deviation at the target point i set as described above, the processor 10 performs driving control.

[0020] <Operation control processing> Next, the driving control processing will be explained. Figure 2 is a functional block diagram of the driving control processing of the processor 10. As shown in Figure 2, the processor 10 includes a followability determination function S101, a lateral acceleration calculation function S102, a lateral displacement calculation function S103, a deviation amount calculation function S104, a deviation determination function S105, a driving command generation function S106, a braking actuator operation function S107, and a steering actuator operation function S108. The following describes the processes performed by each function shown in Figure 2. In executing the driving control, the processor 10 obtains the first road surface friction coefficient of each target point i, the target route, and the speed profile of the driving plan for the target route. The speed profile includes the target speed at each point, including the target point i. The followability determination function S101 of the processor 10 determines whether the vehicle can follow the target route when driven at the target speed of the speed profile, based on the speed profile in the driving plan calculated from the state quantities of the vehicle and the shape of the target route, at any target point i in front of the vehicle. Specifically, the processor 10 obtains the target speed at target point i from the driving plan that drives the vehicle along the target route. The target speed in the driving plan is calculated considering the shape of the target route, including its curvature. The target speed in the driving plan is calculated considering the legal speed limit of the target route and / or the performance of the vehicle (including vehicle specifications). The processor 10 calculates a recommended speed based on the first road surface friction coefficient at target point i and the turning curvature of the target route at target point i. The recommended speed is calculated considering the detected first road surface friction coefficient, but the target speed is calculated without considering the road surface friction coefficient. The recommended speed is an appropriate speed that should be recommended, taking into account the specific road surface conditions, taking into account the first road surface friction coefficient at target point i. The tracking feasibility determination function S101 of the processor 10 compares the target speed with the recommended speed, and if it is determined that the target speed at point i is higher than the recommended speed, it is predicted that the driving based on the driving plan will be at an overspeed. The processor 10 determines that it will be difficult to follow the target path with the driving control based on the driving plan, and outputs a flag to that effect to the lateral acceleration calculation function S102. The lateral acceleration calculation function S102 uses the overspeed determination flag as a trigger to perform the process of calculating the amount of deviation from the target path. The processor 10 determines that the driving control will be affected by the change in the road surface friction coefficient at point i if the target speed at point i, based on the shape of the target path, is higher than the recommended speed based on the first road surface friction coefficient μi and the turning curvature at point i. In this embodiment, the processor determines whether driving according to the driving plan will result in overspeeding at point i by comparing the target speed with the recommended speed, which takes into account the specific road surface conditions, and determines the possibility that the vehicle will deviate from the target path at point i based on this determination. By extracting situations in which disturbances due to changes in the road surface friction coefficient occur and initiating deceleration control in advance in preparation for disturbances occurring at point i ahead of the vehicle, the influence of disturbances caused by road surface conditions on the driving control can be reduced.

[0021] As an example, the relationship between the target speed and the recommended speed at point i can be determined by the following formula. The right-hand side of the inequality sign is the recommended speed, and the left-hand side Vi* is the target speed. The processor 10 determines, using the following formula (1), that if the target speed at point i is higher than the recommended speed, the driving control based on the driving plan will result in an overspeed state at point i, and it will be difficult to follow the target route. In this case, the followability determination function S101 sends a flag indicating that followability is not possible to the lateral acceleration calculation function S102 of the processor 10.

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[0022] The lateral acceleration calculation function S102 of processor 10 calculates the lateral acceleration acting in the vehicle width direction at target point i. Specifically, the lateral acceleration calculation function S102 obtains the target speed Vi at target point i from a driving plan that drives the vehicle along a target path, calculates the first lateral acceleration from the target speed at target point i and the turning curvature ρ of the target path at target point i, and also calculates the second lateral acceleration based on the first road surface friction coefficient μi at target point i. The lateral acceleration calculation function S102 calculates the value obtained by subtracting the second lateral acceleration from the first lateral acceleration as the lateral acceleration of the vehicle at target point i. This makes it possible to calculate a highly accurate lateral acceleration that takes into account the first road surface friction coefficient μi at target point i. By using a highly accurate lateral acceleration, the possibility of deviation can also be judged with high accuracy.

[0023] As an example, the lateral acceleration ΔAyi can be calculated using the following equations (2-1) to (2-3). The processor 10 calculates the first lateral acceleration Ayi1 from the target velocity Vi at point i and the turning curvature ρi of the target path at point i using the following equation (2-1). The processor 10 calculates the second lateral acceleration Ayi2 based on the first road surface friction coefficient μi at point i using the following equation (2-2). The second lateral acceleration Ayi2 is the lateral acceleration acting between the tire and the road surface, taking into account the actual road surface friction coefficient μi. The processor 10 calculates the value obtained by subtracting the second lateral acceleration Ayi2 from the first lateral acceleration Ayi1 as the lateral acceleration ΔAyi of the vehicle at point i using the following equation (2-3). This allows us to determine the amount of lateral slip of the vehicle at point i based on the lateral acceleration ΔAyi, which is the first lateral acceleration Ayi1 that exceeds the second lateral acceleration Ayi2 based on the friction between the road surface and the tires at point i.

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[0024] The lateral displacement calculation function S103 of the processor 10 calculates the amount of deviation from the target path at target point i based on the lateral acceleration Ayi at target point i. The lateral displacement calculation function S103 sets a first target point i located relatively upstream on the target path, and a second target point i+1 adjacent to the first target point i downstream. The first target point i is closer to the current position of the vehicle than the second target point i+1. Then, the lateral displacement calculation function S103 uses the lateral acceleration Ayi at the first target point i to calculate the amount of lateral displacement in the width direction of the vehicle as it moves from the first target point i to the second target point i+1, and calculates the amount of deviation from the target path at target points i and i+1 based on that lateral displacement. This makes it possible to calculate the amount of deviation from the target path with high accuracy using the change in lateral acceleration considering the first road surface friction coefficient μi at target points i and i+1.

[0025] As an example, the lateral displacement calculation function S103 uses the lateral acceleration Ayi at the first target point i to calculate the lateral displacement Δyi+1 in the vehicle width direction of the vehicle as it moves from the first target point i to the second target point i+1 using the following equation (3).

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[0026] Here, Figure 3 shows the lateral displacement Δyi (i=0, 2, 3, 4) in the vehicle width direction W relative to the target path RT in the driving lane LN. The driving plan specifies that the vehicle V1 moves along the target path RT at target points i (i=P0~P4) at target speeds v*0~V*3 of the speed profile. In the example shown in Figure 3, the vehicle V1 is located on the target path RT at target point i=P0. However, in the region of target points i=P1~P3, the road surface friction coefficient decreases and disturbances occur in the road surface condition, so the vehicle V1 is subjected to a lateral force, resulting in a lateral displacement and a change in its lateral position toward the road boundary TB. The change in lateral position accumulates (gradually increases), and the vehicle V1 is unable to follow the target path RT and gradually deviates from the target path RT.

[0027] The deviation amount calculation function S104 of the processor 10 calculates the deviation amount of the vehicle V1 from the target path RT at target point i+1 based on the lateral displacement amount Δyi+1 of the vehicle V1 between each target point. The deviation amount is the distance along the vehicle width direction W between the target path RT and the reference position of the vehicle V1. The reference position of the vehicle V1 may be the center of gravity of the vehicle or the midpoint of the vehicle width. The deviation amount may be the lateral displacement amount yi at each target point i, or the lateral displacement amount Δyi+1 between adjacent target points (between target point i and i+1). The deviation amount may also be calculated based on the distance ΔRn (ΔR0~ΔR3) between the road boundary TB shown in Figure 3 and the reference position of the vehicle V1. The processor 10 may acquire the road width LW on which the vehicle is traveling and calculate the distance ΔRn between the road boundary TB and the reference position of the vehicle V1 by subtracting the lateral displacement yi,Δyi+1 from half of the road width LW. The road width LW may be calculated based on the detection result of the sensor 2 or acquired from the lane information 51 of the map information 5. When the distance ΔRn from the road boundary TB is less than a predetermined value, the processor 10 may determine that the vehicle has deviated from the target path RT. The predetermined value for distance ΔRn is the residual allowable distance to the road boundary and is a threshold for maintaining the state in which the vehicle does not deviate from the road. The predetermined value for distance ΔRn can be set according to the vehicle width, road width, steering performance, braking performance, driving performance, etc. It is not particularly limited, but may be 1m, 0.5m, 0.3m, etc.

[0028] The deviation detection function S105 of the processor 10 determines that the vehicle V1 has deviated at the target point if it determines that the amount of deviation is greater than or equal to a predetermined value. The predetermined value may be defined as the amount of deviation based on the lateral displacement Δyi from the target path RT, or as the amount of deviation based on the approach distance ΔRn to the road boundary TB. As an example, regarding the first predetermined value for the deviation amount based on the lateral displacement Δyi from the target route RT, the first predetermined value when the vehicle speed of the vehicle V1 is high may be lower than the value when the vehicle speed is low. The intention is that even a small deviation (lateral displacement) will be judged as a deviation at high speeds. Similarly, the first predetermined value when the vehicle weight of the vehicle V1 is heavy may be lower than the value when the vehicle weight is light. The first predetermined value when the road width LW of the target route RT is narrow may be lower than the value when the road width LW is wide. The first predetermined value when the traffic volume of the target route RT is high may be lower than the value when the traffic volume is low. The first predetermined value when the speed limit of the target route RT is high may be lower than the value when the speed limit is low. Regarding the second predetermined value for the amount of deviation based on the approach distance ΔRn to the road boundary TB, the second predetermined value when the vehicle speed of the vehicle V1 is high may be higher than the value when the vehicle speed is low. The intention is that at high speeds, a deviation may be judged even if there is a distance to the road boundary. Similarly, the second predetermined value when the vehicle weight of the vehicle V1 is heavy may be higher than the value when the vehicle weight is light. The second predetermined value when the road width LW of the target route RT is narrow may be higher than the value when the road width LW is wide. The second predetermined value when the traffic volume of the target route RT is high may be higher than the value when the traffic volume is low. The second predetermined value when the speed limit of the target route RT is high may be higher than the value when the speed limit is low. The first and second predetermined values ​​may be defined based on the braking performance of the vehicle V1. This allows for appropriate judgment of deviation depending on the situation.

[0029] The driving command generation function S106 of the processor 10 generates a driving control command for the vehicle if the deviation detection function S105 determines that the vehicle V1 will deviate from the target route RT at target point i. The processor 10 outputs a deceleration command to the braking actuator of the braking control device 230. The braking actuator operation function S107 of the braking control device 230 decelerates the vehicle based on the deceleration command. In controlling the deceleration of the vehicle, the driving command generation function S106 sets the amount of deceleration lower when the distance from the vehicle's current position to target point i is relatively long than when the distance from the vehicle's current position to target point i is relatively short. In other words, if there is a possibility of deviating from the target route RT at target point i which is close to the vehicle's current position, the vehicle is decelerated with a high amount of deceleration. The change in the amount of deceleration (deceleration rate) may be constant or may change. This allows for deceleration control with a lower deceleration amount when the distance to target point i is long compared to when it is short. When the distance to target point i is long, deviation at target point i can be avoided without outputting the maximum deceleration amount of the vehicle. When the distance to target point i is long, deviation at target point i can be avoided while reducing the deceleration amount and making the speed change gradual. The vehicle can decelerate with a deceleration amount appropriate to the situation and pass through target point i at an appropriate speed.

[0030] Furthermore, in controlling the deceleration of the vehicle, the processor 10 sets the deceleration amount lower when the deviation from the target path RT at point i is relatively small than the deceleration amount when the deviation from the target path RT at point i is relatively large. In other words, if there is a possibility that the vehicle V1 will deviate significantly from the target path RT at point i, the processor 10 decelerates the vehicle with a high deceleration amount. A relatively small deviation means that the distance between the target path RT and the vehicle's reference position is relatively short. A relatively large deviation means that the distance between the target path RT and the vehicle's reference position is relatively long. The change in the deceleration amount (deceleration) may be constant or may change. As a result, when the deviation from the target path RT at target point i is small, deceleration control can be performed with a lower deceleration amount than when the deviation is large. When the deviation at target point i is small, the deviation at target point i can be avoided without outputting the maximum deceleration amount of the vehicle. When the deviation at target point i is small, the deviation at target point i can be avoided while reducing the deceleration amount and making the speed change gradual. On the other hand, when the deviation at target point i is large, the deviation at target point i can be avoided by outputting a relatively large deceleration amount. The speed of the vehicle can be reduced with a deceleration amount corresponding to the deviation at target point i, thereby avoiding the deviation at target point i. Note that the braking control device 230 and the drive control device 220 work together.

[0031] Furthermore, the driving command generation function S106 of the processor 10 outputs a steering command to the steering actuator of the steering control device 210. The steering actuator operation function S108 of the steering control device 210 controls the amount of steering of the vehicle based on the steering command. When the driving command generation function S106 performs deceleration control of the vehicle, it controls the steering angle so that the slip angle of the vehicle is less than a predetermined value. Specifically, if it is determined that the vehicle is deviating from the target path RT, in this deceleration control, the direction of travel of the vehicle's tires is approximated to the direction of the vehicle's velocity vector. The steering control device 210 may set the target value of steering control to 0 [deg]. The predetermined value is a value close to 0. In other words, the steering control device 210 makes the slip angle of the vehicle as small as possible. This allows the braking force of the tires to be applied to the maximum extent along the direction of the vehicle's velocity vector, enabling an efficient reduction in the vehicle's speed. Sufficient deceleration can be achieved before reaching the target point i ahead.

[0032] The control procedure for operation control in this embodiment will be described below based on the flowchart in Figure 4. The processor 10 acquires vehicle information, including the current position and speed of the vehicle, using the sensor 2 and / or the vehicle information acquisition device 3 (S1). The vehicle information includes vehicle specifications, vehicle status, and vehicle control information. The processor 10 calculates a target route RT from the current position to the destination by referring to the map information 5 (S2). The route calculation process may be performed by the navigation device 6. The processor 10 calculates a driving plan to have the vehicle drive the target route RT (S3). The driving plan includes a 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.

[0033] The processor 10 sets one or more target points i on the target route RT (S4). The processor 10 uses the sensor 2 or the road surface information acquisition device 4 to acquire a first road surface friction coefficient μi for the set target points i (S5). As mentioned above, the method for acquiring the first 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 processor 10 acquires a pre-set second road surface friction coefficient μs (S6). As mentioned above, the second road surface friction coefficient is a representative value of the road surface friction coefficient of a typical road. The second road surface friction coefficient is pre-stored in a readable recording medium such as ROM 12 or RAM 13. The first road surface friction coefficient μi and the second road surface friction coefficient μs are compared (S7). If the first road surface friction coefficient μi is lower than the second road surface friction coefficient μs (first road surface friction coefficient μi < second road surface friction coefficient μs: the first road surface friction coefficient μi is less than the second road surface friction coefficient μs) (Yes in S8), the process proceeds to S10 and the lateral acceleration Ayi1 is calculated using the above formula (2-1). On the other hand, if the first road surface friction coefficient μi is greater than or equal to the second road surface friction coefficient μs (No in S8), the processor 10 determines that the road surface condition at target point i in front of the vehicle will not cause the vehicle V1 to deviate. In other words, it is determined that there is no possibility of disturbances occurring based on the road surface condition. In this case, the vehicle is driven according to the planned driving plan (S9).

[0034] In S10, the processor 10 calculates the lateral acceleration Ayi acting in the vehicle width direction at the target point i (S10). Although not particularly limited, S30-S31 may be executed in the calculation process of the lateral acceleration Ayi. For example, the processor 10 calculates the first lateral acceleration Ayi1 = ρi * Vi * from the target velocity at the target point i and the turning curvature of the target path at the target point i. 2 The processor calculates (S10). The processor 10 calculates the second lateral acceleration Ayi2 = μig based on the first road surface friction coefficient μi at the target point i (S30). The processor 10 calculates the first lateral acceleration Ayi1 = ρi * Vi * 2 The lateral acceleration Ayi of the vehicle at point i is calculated as ΔAyi, obtained by subtracting the second lateral acceleration Ayi2 = μig from (S31). The lateral acceleration Ayi corresponds to the lateral acceleration ΔAyi in equation (2-3) above. The processing in S30-S31 corresponds to the processing of the lateral acceleration calculation function S102 described above.

[0035] Once the lateral acceleration Ayi is calculated (S10), the processor 10 uses the lateral acceleration Ayi at target point i to calculate the amount of lateral movement between the two target points (S11). While not particularly limited, as an example of specific processing, as in S40, the processor 10 uses the lateral acceleration Ayi at the first target point i to calculate the lateral displacement Δyi+1 of the vehicle in the vehicle width direction accompanying the movement from the first target point i to the second target point i+1 (S40). Based on the lateral displacement Δyi+1, the processor 10 calculates the amount of deviation from the target path RT at target point i+1 (S12). If the processor 10 determines that the amount of deviation is greater than or equal to a predetermined value (S13), it determines that there is a possibility of deviation (S14), generates a deceleration command, and outputs it to the braking control device 230 (S15). If the processor 10 determines that the amount of deviation is greater than or equal to a predetermined value (YES in S13), it determines that there is a possibility of deviation (S14), generates a steering command, and outputs it to the steering control device 210 (S16). The vehicle controller 200 executes the deceleration command and / or steering command (S17). On the other hand, if it is determined that the deviation is less than a predetermined value (NO in S13), the process proceeds to S9, and the operation is carried out according to the already planned operation plan. The process in S40 corresponds to the process of the deviation amount calculation function S104 described above. In this way, by using the first road surface friction coefficient μi at the target point i in front of the vehicle, the amount of deviation from the target path RT at the target point i can be calculated in advance, making it possible to predict future deviation risks considering road surface conditions. If a deviation risk at the target point i ahead is detected, even if the vehicle is not currently deviating from the target path RT, deceleration control can be initiated to prevent or suppress the deviation at the target point i ahead.

[0036] In addition, the subroutines S20-S23 can be executed in parallel with or before / after the processing of S1-S8. The subroutines S20-S23 are executed before the lateral acceleration calculation process in S10. The processor 10 obtains the target speed Vi* at target point i from the driving plan which causes the vehicle to drive along the target path RT (S20). The processor 10 obtains the turning curvature ρi* of the target path RT at target point i (S21). The processor 10 calculates the recommended speed based on the first road surface friction coefficient μi at target point i and the turning curvature ρi* at target point i. If it is determined that the target speed Vi* is higher than the recommended speed as shown in equation (1) above (YES in S23), the process proceeds to S10 and executes the lateral acceleration calculation process used to calculate the deviation amount. If it is determined that the target speed Vi* is below the recommended speed (NO in S23), then there will be no overspeeding at target point i, and the possibility of deviation is low, so driving control is executed according to the driving plan (S9). The processing in S20-S23 corresponds to the processing of the followability determination function S101 described above. The processing in S20-S23 is an additional process and can be skipped. [Explanation of Symbols]

[0037] 100…Driving assistance system, 1…Driving assistance device, 10…Processor, 11…CPU, 12…ROM, 13…RAM, 20…Input / output device, 30…Communication device, 2…Sensor, 21…Camera, 22…Radar device, 3…Vehicle information acquisition device, 4…Road surface information acquisition device, 5…Map information, 51…Lane information, 6…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 to follow a target path, The aforementioned processor, The vehicle information, including the position and speed of the vehicle, is acquired. One or more target points are set in front of the vehicle traveling along the aforementioned target route. The first road surface friction coefficient for the aforementioned target point is obtained, The acquired first road surface friction coefficient is compared with a preset second road surface friction coefficient. If the first road surface friction coefficient is lower than the second road surface friction coefficient, the lateral acceleration acting in the vehicle width direction at the target point is calculated, and the amount of deviation from the target path at the target point is calculated based on the lateral acceleration. A driving assistance method that initiates deceleration control of the vehicle if it is determined that the amount of deviation is greater than or equal to a predetermined value.

2. The aforementioned processor, The target speed at the target point is obtained from the driving plan which drives the vehicle along the target route. The recommended speed is calculated based on the first road surface friction coefficient at the target point and the turning curvature of the target path at the target point. The driving assistance method according to claim 1, wherein if the target speed is determined to be higher than the recommended speed, the amount of deviation from the target path is calculated based on the lateral acceleration.

3. The aforementioned processor, The target speed at the target point is obtained from the driving plan which drives the vehicle along the target route. The driving assistance method according to claim 1, comprising: calculating a first lateral acceleration from the target speed at the target point and the turning curvature of the target path at the target point; calculating a second lateral acceleration based on the first road surface friction coefficient at the target point; and calculating the value obtained by subtracting the second lateral acceleration from the first lateral acceleration as the lateral acceleration of the vehicle at the target point.

4. A first target point located relatively upstream in the aforementioned target path and a second target point adjacent to the first target point located downstream are defined. Using the lateral acceleration at the first target point, the amount of lateral displacement in the vehicle width direction of the vehicle accompanying movement from the first target point to the second target point is calculated. The driving support method according to claim 1, which calculates the amount of deviation from the target path at the second target point based on the amount of lateral displacement.

5. The aforementioned processor, The driving assistance method according to claim 1, wherein at least one target point is set in a region where the turning curvature of the target path is greater than or equal to a predetermined value.

6. The aforementioned processor, Multiple target points are set in a region where the turning curvature of the target path is greater than or equal to a predetermined value. The driving assistance method according to claim 1, wherein the interval between target points set adjacent to an area where the turning curvature of the target path is greater than or equal to a predetermined value is narrower than the interval between target points set adjacent to an area where the turning curvature of the target path is less than a predetermined value.

7. The aforementioned processor, The driving assistance method according to claim 1, wherein when performing deceleration control of the vehicle, the steering angle is controlled so that the slip angle of the vehicle is less than a predetermined value.

8. The aforementioned processor, The driving assistance method according to claim 1, wherein, in the deceleration control of the vehicle, the amount of deceleration when the distance from the current position of the vehicle to the target point is relatively long is set lower than the amount of deceleration when the distance from the current position of the vehicle to the target point is relatively short.

9. The aforementioned processor, The driving assistance method according to claim 1, wherein in the deceleration control of the vehicle, the amount of deceleration when the amount of deviation from the target path at the target point is relatively small is set lower than the amount of deceleration when the amount of deviation from the target path at the target point is relatively large.

10. A driver assistance system equipped with a processor that assists in driving the vehicle to follow a target route, The aforementioned processor, The vehicle information, including the position and speed of the vehicle, is acquired. One or more target points are set in front of the vehicle traveling along the aforementioned target route. The first road surface friction coefficient for the aforementioned target point is obtained, The acquired first road surface friction coefficient is compared with a preset second road surface friction coefficient. If the first road surface friction coefficient is lower than the second road surface friction coefficient, the lateral acceleration acting in the vehicle width direction at the target point is calculated, and the amount of deviation from the target path at the target point is calculated based on the lateral acceleration. A driving assistance device that initiates deceleration control of the vehicle if it is determined that the deviation amount is greater than or equal to a predetermined value.

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