Driving assistance method and driving assistance device

Abstract

A processor 10: stores, as a stored route RT, a path of a host vehicle V1 estimated using peripheral information of the host vehicle V1 detected by an external environment sensor 2 during manual driving; causes the host vehicle to perform automated driving with the stored route RT as a target route when the host vehicle next travels along the stored route RT after the stored route RT has been stored; calculates, during automated driving, an amended route AT connected to an end point ED that is a predetermined distance D in a traveling direction from a start point ST located in the vicinity of the current location of the host vehicle V1, the start point ST being a point on the stored route RT; calculates a degree of deviation of the stored route RT from the amended route AT; and causes the host vehicle to perform automated driving on the amended route AT if the degree of deviation is at least equal to a predetermined value and it is determined that are no obstacles OB on the amended route AT.

Description

Driving support method and driving support device

[0001] The present invention relates to a vehicle driving support method and a driving support device.

[0002] There is known a vehicle control device that stores in advance a travel route driven by a driver, and then automatically drives the vehicle along the stored route. The technology improves route tracing accuracy during automatic driving by taking into account insufficient actuator operation amount during automatic driving, and storing the route by limiting the driver's operation amount during route storage traveling.

[0003] Japanese Patent No. 7261900

[0004] However, if there is an obstacle on the travel route when the route is stored, a route that detours around the obstacle is stored. Even if the obstacle does not exist during automatic driving, the host vehicle will travel along the stored avoidance route that detours around the obstacle.

[0005] The problem to be solved by the present invention is to prevent the host vehicle from traveling along the stored avoidance route when there is no obstacle during automatic driving, even if the route is stored when there is an obstacle on the travel route.

[0006] According to the present invention, after storing a storage route based on the trajectory of the host vehicle estimated using peripheral information of the host vehicle detected by sensors during manual driving, when the host vehicle travels along the storage route next time, the host vehicle is caused to perform automatic driving with the stored route as the target route. During automatic driving, a corrected route is generated connecting a start point located near the current position of the host vehicle, which is a point on the storage route, and an end point located a predetermined distance from the start point in the traveling direction. If the deviation degree of the storage route relative to the corrected route is equal to or greater than a predetermined value, and it is determined that there is no obstacle on the corrected route, the above problem is solved by causing the host vehicle to automatically drive along the corrected route.

[0007] According to the present invention, even if a route is stored when there is an obstacle on the travel route, the host vehicle can be prevented from traveling along the stored avoidance route when there is no obstacle during automatic driving.

[0008] Figure 1 is a system configuration diagram of the driver assistance system. Figure 2 is a diagram showing one aspect of the HMI. Figure 3 is a diagram showing an example of a memorized path based on the driving trajectory by the driver's manual driving. Figure 4 is a diagram illustrating automatic driving along the memorized path. Figure 5 is a diagram illustrating automatic driving using a memorized path generated considering the presence or absence of obstacles and missing parts. Figure 6(A) shows a memorized path when there are obstacles on the driving path, and Figure 6(B) shows a memorized path when there are no obstacles on the memorized path. Figures 7(A) and 7(B) are diagrams illustrating the process of generating a corrected path, and Figure 7(C) is a diagram illustrating the process of calculating the degree of deviation of the avoidance path from the corrected path. Figures 8(A), 8(B), and 8(C) are diagrams illustrating the process of generating a guidance path from the corrected path to the avoidance path. Figure 9(A) is a flowchart showing the control process of the memorized path creation mode, Figure 9(B) is a flowchart showing the control process of the automatic driving mode based on the memorized path, and Figure 9(C) is a flowchart showing the control process of the automatic driving mode based on the corrected path.

[0009] <First Embodiment> Figure 1 shows the hardware configuration of a driver assistance system 100 equipped with a driver assistance device 1 according to this embodiment. This driver assistance method is implemented by the processor 10 of the driver assistance device 1 using each piece of hardware of the driver assistance system 100. The driver assistance system 100 of this embodiment includes a driver assistance device 1, one or more external sensors 2 constituting a sensor, a position detection device 3, a storage device 4, a vehicle actuator 5, and an HMI (Human Machine Interface) 6. Each device exchanges information with each other via an on-board CAN (Controller Area Network).

[0010] Multiple external sensors 2 are installed on the vehicle and form a sensor group that works in cooperation with each other. The external sensors 2 detect the presence or absence of objects, including other vehicles, around the vehicle, the attributes of the objects (parked vehicles, pieces of wood, pallets, trash cans, pedestrians, puddles, other vehicles, etc.), the distance to the objects, the relative velocity of the objects, and the relative acceleration of the objects. The external sensors 2 provide the detection information to the processor 10. Based on the detection information from the external sensors 2, the processor 10 determines the behavior of the objects, including at least one of the following: position, direction of movement, amount of movement, velocity, and acceleration, and their changes, and uses the determination results to perform autonomous driving of the vehicle. The external sensors 2 include one or more cameras 21 placed on the vehicle. The cameras 21 include image sensors equipped with image sensors such as CCDs, ultrasonic cameras, and infrared cameras. The cameras 21 capture images of the vehicle's surroundings in all directions, and the detection results based on the captured images are used for autonomous driving control. The external sensors 2 include a radar device 22 that detects (measures distance) the presence of objects, the position of objects, and changes in their position around the vehicle. The radar system 22 measures the distance and direction from the vehicle to an object, as well as the distance between objects, by emitting radio waves and measuring the reflected waves from the object. The radar system 22 includes a laser radar, millimeter-wave radar (LRF), ultrasonic radar, and sonar. The external sensor 2 is equipped with a LiDAR (light detection and ranging) 23. The LiDAR 23 measures the distance and direction from the vehicle to an object, as well as the distance between objects, by irradiating laser light and measuring the reflected waves from the object.

[0011] The position detection device 3 receives signals from the GNSS (Global Navigation Satellite System) 31 and detects the position of the vehicle. The position detection device 3 is equipped with an IMU (Inertial Measurement Unit) 32. The IMU 32 is an inertial measurement device that detects three-dimensional inertial motion and detects the relative position information and attitude of the vehicle by measuring the tilt and acceleration of three axes. The position detection device 3 further detects the position of the vehicle using the detection information from the gyro sensor and / or the detection information from the vehicle speed sensor. The position detection device 3 detects the position of the vehicle while it is moving (current position) over time and detects the trajectory of the vehicle based on the position at each point in time. The position detection device 3 provides the detection results to the processor 10.

[0012] The storage device 4 includes a map data storage unit 41. The map data storage unit 41 stores map data 41D in an absolute coordinate system, such as latitude / longitude. The map data 41D includes general map information that includes route information that the vehicle can travel. The map data storage unit 41 stores a stored route. The stored route is a route based on the trajectory of the vehicle estimated using surrounding information of the vehicle detected by the external sensor 2 during manual driving. In the stored route, each point on the stored route is associated with the characteristics of the surrounding information acquired when traveling to each point. The stored route functions as a map based on the characteristics. If the detected characteristics of the surrounding information are common, it can be determined that the vehicle is traveling to the same location. The stored route may be stored superimposed on the map information of the map data 41D based on its position. The storage device 4 allows the processor 10 to read and provides the requested information.

[0013] The vehicle actuator 5 includes a steering device 51, a drive device 52, and a braking device 53, and performs automatic driving so that the vehicle automatically travels along a target path in accordance with control commands generated by the processor 10. The vehicle actuator 5 also performs driving in accordance with control commands from the driver's manual operation.

[0014] The HMI6 is implemented, for example, in a touch panel display 61. The display 61 is equipped with a switch 62 that can be input by touch or press. In this embodiment, the HMI6 is provided with a GUI (Graphical User Interface) as shown in Figure 2, so that the driver can select between driving in memory path creation mode or driving in automatic driving mode. If the driver wants to create a memory path RT, they touch or press the switch 62a that selects "Memory Path Creation Mode" shown on screen Q of the display 61 in Figure 2. After creating and storing the memory path RT, if the driver wants to drive automatically, they touch or press the switch 62b that selects "Automatic Driving Mode". The mode selection command is output to the driving mode management unit 101 (see Figure 1), and the processor 10 executes driving support control according to each mode selected by the driver. The processor 10 outputs the memory path RT to be driven and the estimated position PV1 of the vehicle V1 (see Figure 2) from the peripheral information processing unit 102 to the HMI6 and displays them on screen Q of the display 61. Before starting autonomous driving in automatic driving mode, the driver manually moves the vehicle V1 onto the stored route RT while confirming the vehicle's current estimated position PV1. This enables autonomous driving of the vehicle V1 based on the stored route RT. Furthermore, when the vehicle V1 is traveling on the stored route RT in autonomous driving mode, the driver can know where it is currently traveling on the stored route RT. If there are multiple stored route RTs, they are displayed on the display 61, and the driver can select the stored route RT they wish to travel on using autonomous driving. In addition, the GUI of the display 61 can display the vehicle speed, the remaining distance to the target destination, and the current vehicle speed on screen Q.

[0015] The driver assistance device 1 performs automated driving, causing the vehicle to automatically travel along a target route. The target route in this embodiment includes one or more of the following: a stored route (including an avoidance route), a modified route, and a guided route, as described later. The processor 10 of the driver assistance device 1 includes a ROM (Read Only Memory) 12 that stores a program for creating a stored route during manual driving in accordance with the driver's input and for performing automated driving control when the vehicle next travels along the stored 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 may be composed of one or more integrated circuits. The driver assistance device 1 can recognize that manual driving in accordance with the driver's input is being performed.

[0016] As shown in Figure 1, the processor 10 includes a driving mode management unit 101, a peripheral information processing unit 102, a route generation unit 103, and a route following control unit 104. The processor 10 implements this driving support method by coordinating the software for realizing each function of each unit (101, 102, 103, and 104) with the hardware of the driving support system 100. The following describes each unit (101, 102, 103, and 104).

[0017] [Driving Mode Management Unit] The driving mode management unit 101 manages the state of the vehicle in three modes: memorized route creation mode, automatic driving mode, and manual driving mode. When the driving mode management unit 101 receives a memorized route creation instruction from the driver via the switch 62a of the HMI 6, it starts the memorized route creation mode. In memorized route creation mode, the driving mode management unit 101 outputs an instruction to the surrounding information processing unit 102 to store the trajectory, which is an accumulation of feature quantities extracted from the surrounding information detected by the external sensor 2 during manual driving and the vehicle's position estimated by the surrounding information matching process. Here, the feature quantities are stored in the map data storage unit 41 so that they can be used for estimating the vehicle's position during automatic driving, and the trajectory of the vehicle V1 is stored in the map data storage unit 41 so that it can be used as a target route during automatic driving. Since the memorized route creation mode is executed while the driver is driving manually, it is not operated after the route generation unit 103 is started. The driving mode management unit 101 receives an instruction from the driver via switch 62b on the HMI 6 to execute automatic driving after the stored route RT has been stored. The driving mode management unit 101 activates the automatic driving mode when it receives an instruction from the driver via the HMI 6 to select the stored route RT that the driver wants to drive automatically on. Automatic driving of the vehicle is achieved by automatic driving control. The driving mode management unit 101 outputs an instruction to the surrounding information processing unit 102 to estimate the position of the vehicle by matching the feature quantities stored in the map data storage unit 41 of the storage device 4 with the surrounding information currently detected by the external sensor 2. At the same time, the driving mode management unit 101 outputs an instruction to the storage device 4 to output the stored route RT to the route generation unit 103. The manual driving mode is a mode in which the vehicle is driven by manual driving based on the driver's operation of the steering wheel and / or accelerator pedal or brake pedal, without intervention from automatic driving control.

[0018] [Surrounding Information Processing Unit] The surrounding information processing unit 102 stores the estimated trajectory of the vehicle, which is determined using the surrounding information of the vehicle detected by the external sensor 2 during manual driving, as a stored path RT. In stored path creation mode, the trajectory traveled by the driver during manual driving is stored in the map data storage unit 41 as a stored path RT. The surrounding information processing unit 102 extracts static feature quantities of features from the surrounding information detected by the external sensor 2 (for example, LiDAR point cloud), associates them with each point, and stores them in the map data storage unit 41 of the storage device 4 as map data 41D. The surrounding information processing unit 102 estimates the position of the vehicle while storing the feature quantities extracted from the surrounding information acquired at each point during driving. The feature quantities stored in the map data storage unit 41 are used in a matching process with surrounding information acquired during automatic driving in order to estimate the position of the vehicle during automatic driving. The estimated position of the vehicle is accumulated as the vehicle trajectory for creating a stored path, and is stored in the map data storage unit 41 of the storage device 4 as a stored path RT after the stored path creation mode ends.

[0019] The surrounding information processing unit 102 acquires surrounding information based on the image captured by the camera 21 and surrounding information based on the point cloud of scan data from the radar device 22 and / or LiDAR 23. The surrounding information processing unit 102 applies a feature extraction algorithm according to the nature of the detected data and acquires features. Incidentally, the surrounding information processing unit 102 can also store the point cloud acquired using LiDAR 23 directly as surrounding information. However, when using LiDAR 23, tens of thousands of points are acquired in a single sample, which increases the amount of data. For this reason, in this embodiment, features are extracted from the surrounding information and saved. Saving the features extracted from the point cloud reduces the amount of data to be saved and also reduces the processing load of self-position estimation by matching processing. If the environment is such that the GNSS 31 signal can be received, the self-position estimation can be performed using the data from GNSS 31 and / or IMU 32. Furthermore, the accuracy of position estimation may be improved by estimating the self-position by combining judgment based on feature matching processing and judgment based on the received signals from GNSS 31 and / or IMU 32. On the other hand, in automatic driving mode, the surrounding information processing unit 102 performs a position estimation of the vehicle by matching the feature quantities stored in the map data storage unit 41 with the surrounding information currently detected by the external sensor 2, and outputs that position and the stored path RT stored in the map data storage unit 41 to the path generation unit 103. As shown in Figure 1, the surrounding information processing unit 102 outputs the trajectory of the vehicle and the stored path to the path generation unit 103.

[0020] [Route Generation Unit] In automatic driving mode, the route generation unit 103 uses the position of the vehicle V1 output from the surrounding information processing unit 102 as a starting point, extracts a route around the vehicle from the stored route RT also output from the surrounding information processing unit 102, and sets it as the target route for route following control. Here, for example, a smoothing process may be performed on the stored route RT to make the route smoother and set as the target route. If an obstacle is detected in front of the vehicle, an avoidance route to avoid the obstacle may be generated and set as the target route. This target route is output to the route following control unit 104 as the target value for the vehicle's route following control. In addition, the route generation unit 103 may calculate the curvature of the route from the target route, and the route following control unit 104 may add a curve deceleration function according to the curvature of the route. The target route includes the modified route. As shown in Figure 1, the route generation unit 103 outputs the target route to the route following control unit 104. Note that the route generation process may be performed using a known navigation device.

[0021] [Route Following Control Unit] The route following control unit 104 automatically drives the vehicle along a target route, including a stored route. After the trajectory is stored in the map data 41D of the map data storage unit 41, the route following control unit 104 will automatically drive the vehicle along the stored route RT when it is time to travel along the stored route RT. The route following control unit 104 outputs steering commands to the steering device 51 to control the lateral position of the vehicle so that the vehicle can follow the target route output from the route generation unit 103. The route following control unit 104 also calculates acceleration and deceleration commands to control the vehicle speed to a predetermined speed by limiting the vehicle speed, setting the speed, or decelerating on curves, and outputs them to the drive unit 52 and / or braking unit 53, respectively.

[0022] The driving assistance method of this embodiment operates in the following two steps: [Step 1: Memory Route Creation Mode (Manual Driving)] The processor 10 of the driving assistance device 1 extracts static feature quantities of features from surrounding information (e.g., LiDAR point cloud) obtained from the external sensor 2 while the driver manually drives along an arbitrary route. At the same time, the processor 10 estimates the vehicle's position from the surrounding information that changes as the vehicle moves. Positioning information from GNSS 31 can be used for the vehicle position estimation process. As shown in Figure 3, when the processor 10 determines that the vehicle has reached the target point GL, it stores the trajectory TJ, which is an accumulation of the vehicle's position estimated at a predetermined period from the starting point DP, as a memory route RT. [Step 2: Automatic Driving Mode] As shown in Figure 4, when the driving assistance device 1 is driving automatically, the processor 10 estimates the vehicle's position by feature matching, which compares the surrounding information detected by the external sensor 2 with the feature quantities stored in the map data 41D. Based on map data 41D stored in the map data storage unit 41, which is obtained from past manual driving data, the vehicle's position is estimated using current surrounding information detected by the external sensor 2. GNSS 31 positioning information can be used for the vehicle position estimation process. This allows the processor 10 to determine the estimated position PV1 of the vehicle V1 while driving and execute route-following control to perform automatic driving along the stored route RT. While not particularly limited, this embodiment of driving assistance is used in last-mile automatic driving, connecting the nearest station or bus stop to a destination such as home, in areas not included in high-precision maps, such as private roads outside of public roads like main roads.

[0023] The estimated position PV1 of the vehicle V1 and the stored path RT are identified in an absolute coordinate system common to the map data 41D. The processor 10 outputs steering commands to control the lateral position of the vehicle and acceleration / deceleration commands to control the vehicle speed to a predetermined speed to the vehicle actuator 5 as needed. The path generation process performed by the path generation unit 103 in this embodiment includes a path correction process. As shown in Figure 5, the path generation unit 103 determines whether or not an obstacle OB exists on the corrected path AT (described later) and whether or not a missing section HL exists in the road, and sets a target path according to the determination. In this embodiment, the obstacle OB is a real object on the road surface of the path and does not include missing sections HL that are formed below the road surface (underground) and do not actually exist on the road surface.

[0024] As shown in Figure 6(A), when in memory route creation mode, if an obstacle OB exists on the driving route, the driver performing manual driving will drive to avoid the obstacle OB. Therefore, the memory route RT becomes an avoidance route that bypasses the obstacle OB. The memory route RT, including the avoidance route, is defined in an absolute coordinate system based on latitude (+ / -X direction in the figure) and longitude (+ / -Y in the figure). Similar to the memory route RT (including the avoidance route), the target route, including the corrected route AT and guidance route MT described later, can also be defined in an absolute coordinate system. Note that a planar coordinate system in meters may also be used. When using a planar coordinate system, the processing of this embodiment can be applied even in places where GPS signals cannot be received and latitude and longitude cannot be handled, such as underground parking lots. As shown in Figure 6(B), when driving to the same point again in automatic driving mode, even if the obstacle OB is gone (the gone obstacle OB' is shown by a dashed line), the vehicle V1 will still drive along the memory route RT (avoidance route) that bypasses the location where the obstacle OB was located (a location where nothing is currently present). Furthermore, the definition of an obstacle (OB) is not limited to any object that the driver would decide to avoid during manual driving, including wood chips, pallets, trash cans, vehicles parked on the roadside, pedestrians, and puddles (objects to avoid splashing water).

[0025] The method for correcting the route in automatic driving of the driver assistance device 1 will be explained with reference to Figures 7 and 8. The processor 10 creates a stored route RT in advance based on the trajectory TJ created by the driver's manual driving in the stored route creation mode. Then, as shown in Figure 7(A), the processor 10 sets a starting point ST located near the current position CP of the vehicle V1 on the stored route RT during automatic driving in the automatic driving mode. The processor 10 sets the starting point ST as a point located less than a first predetermined distance W from the current position CP of the vehicle V1 on the stored route RT. The processor 10 may also set the starting point ST as a point on the stored route RT that is the shortest distance from the current position CP of the vehicle V1. The processor 10 sets the ending point ED as a point located on the stored route RT and separated from the starting point ST by a second predetermined distance D along the direction of travel of the stored route RT. The second predetermined distance D can be defined according to the vehicle speed of the vehicle V1. For example, the higher the vehicle speed, the longer the second predetermined distance can be set. While not particularly limited, when the vehicle speed is approximately 20 km / h to 40 km / h, the second predetermined distance D can be set to 20 m to 80 m. Alternatively, the predetermined distance D [m] = vehicle speed V [m / s] × predetermined time t [s], and the predetermined time t can be fixed, allowing the length of D to be variable depending on the vehicle speed. For example, by fixing the predetermined time to 1 s or 2 s ahead, the predetermined distance D can be determined according to the actual vehicle speed at that time. Incidentally, during autonomous driving, the memorized route RT is used as the target route, but errors may occur in the estimated position due to changes in the surrounding environment, and the vehicle V1 cannot always travel along the target route RT. To account for the case where the current position of the vehicle V1 deviates from the memorized route RT, in the process of setting the start point ST and end point DE, the start point ST located near the current position is set on the memorized route RT, and the end point ED, a predetermined distance ahead, is set on the memorized route RT. This makes it possible to generate a corrected route AT that is appropriate as a basis for calculating the degree of deviation, which will be described later. Next, as shown in Figure 7(B), the processor 10 generates a modified path AT connecting the starting point ST and the ending point ED.The method for generating the corrected route AT is not particularly limited. For example, the position coordinates, attitude, and curvature of the starting point ST and ending point ED of the corrected route AT are set, and the corrected route AT is generated considering the vehicle motion between them. The method for generating the corrected route AT is not limited as long as it is a method for calculating a route that the vehicle V1 can travel between the starting point ST and ending point ED by automatic driving. The setting process of the starting point ST and ending point ED of the corrected route AT, and the generation process of the corrected route AT are performed at predetermined intervals. Although Figure 7(B) shows a straight corrected route AT as an example, the corrected route AT is set on a road that includes the curvature that the vehicle actually travels on. As shown in Figure 7(C), the processor 10 calculates the degree of deviation of the stored route RT with respect to the corrected route AT. The processor 10 calculates the distance dn (n = 1, 2, 3, …, n) at multiple points between the stored route RT and the corrected route AT as the degree of deviation. The calculation process of the degree of deviation is performed at predetermined intervals following the generation process of the corrected route AT. In the example shown in Figure 7(C), perpendicular lines are extended from each point set at interval L along the corrected path AT toward the memory path RT, and the distance to where the perpendicular line intersects with the memory path RT is defined as the deviation distance dn. The deviation distance dn may also be the distance in the path width direction. The processor 10 determines that the degree of deviation is greater than or equal to a predetermined value if the deviation distance dn is greater than or equal to a predetermined distance. Here, the condition that the deviation distance dn is greater than or equal to a predetermined distance can be set as follows, for example: (1) The largest deviation distance dn among multiple deviation distances dn is greater than or equal to a predetermined distance. (2) The average of multiple deviation distances dn is greater than or equal to a predetermined distance. (3) Several points are selected in descending order of deviation distance dn, and all of them are greater than or equal to a predetermined distance. The thresholds (predetermined distances) in (1) to (3) may be the same value or different values. If the representative values ​​of these deviation distances dn are greater than or equal to a predetermined distance, the processor 10 determines that the degree of deviation is greater than or equal to a predetermined value.

[0026] If the processor 10 determines that the degree of deviation is greater than or equal to a predetermined value and that there are no obstacles OB on the corrected path AT, it will automatically drive the vehicle V1 along the generated corrected path AT instead of the stored path RT. According to this embodiment, a corrected path AT is generated that connects the starting point ST, located near the current position of the vehicle on the stored path RT, to the ending point ED, which is a predetermined distance ahead in the direction of travel. If the degree of deviation between the corrected path AT and the stored path RT is greater than or equal to a predetermined value and there are no obstacles OB (including other vehicles, pedestrians, etc., in addition to ground objects) on the corrected path AT, the corrected path AT is driven automatically, eliminating the need to travel along a previously stored avoidance path (stored path RT) that detours around obstacles that do not currently exist. Furthermore, automatic driving that detours around areas where there are no obstacles OB (areas where it should be possible to drive) can cause discomfort to the driver. In this embodiment, since the corrected path AT is driven when there are no obstacles OB, the driver does not feel any discomfort with the route of the automatic driving. Furthermore, since it avoids taking detours through areas without obstacles or out-of-bounds (OB) zones, it prevents a decrease in energy efficiency.

[0027] The processor 10 determines that if the degree of deviation is greater than or equal to a predetermined value, the stored path RT is an avoidance path in which driving was performed to avoid the obstacle OB. In other words, it considers the stored path RT that the driver drove to avoid the obstacle OB as an avoidance path. In determining the degree of deviation between the corrected path AT and the stored path RT, the processor 10 determines that if the degree of deviation between the corrected path AT and the stored path RT is greater than or equal to a predetermined value, the stored path RT in that section is an avoidance path in which the driver is presumed to have avoided the obstacle OB while driving in stored path creation mode. Therefore, it is possible to determine whether or not it was a path to avoid the obstacle OB by performing calculations based on limited information, consisting only of path information.

[0028] The processor 10 generates a corrected path AT at predetermined intervals and performs a process to calculate the degree of deviation. Although not particularly limited, the processor 10 can perform the calculation of the degree of deviation when the referenced memory path RT has a predetermined shape. The processor 10 determines whether the memory path RT near the current position of the vehicle V1 includes a path of a predetermined shape. The predetermined shape has the characteristics of an avoidance path in which driving to avoid an obstacle OB is performed. Specifically, as shown in Figure 6(A), the predetermined shape is a shape in which the curvature of the memory path RT before avoiding the obstacle OB (upstream side) is greater than or equal to a first predetermined curvature in the direction of travel (in the +Y direction in the figure), the curvature of the memory path RT becomes zero, and the curvature of the memory path RT is less than a second predetermined curvature. Specifically, the predetermined shape has the following characteristics in order to avoid an obstacle OB that was present on the memory path RT: (i) it turns to the right (+X direction in Figure 6) or to the left (-X direction in Figure 6) relative to the direction of travel of the memory path RT before the start of avoidance (the curvature of the memory path RT becomes equal to or greater than the first predetermined curvature), (ii) it reverses direction of turning at the point where it passes to the side of the obstacle OB and turns to the left (-X direction in Figure 6) or to the right (+X direction in Figure 6) (the curvature of the memory path RT becomes zero), and (iii) it returns to the avoidance path RT (the curvature of the memory path RT becomes less than the second predetermined curvature). The first predetermined curvature and the second predetermined curvature may be the same value or may be different values. When a section of the memory path RT with the predetermined shape is detected, the degree of deviation of the memory path RT with respect to the corrected path AT is calculated. This reduces the number of times the degree of deviation calculation process is performed because the degree of deviation is calculated when traveling along the memory path RT which has the shape characteristics of the avoidance path that the obstacle OB avoids.

[0029] Even if the processor determines that there are no obstacles OB on the corrected route AT, it reduces the vehicle speed of the vehicle V1 and drives along the corrected route AT. In automated driving along the corrected route AT, the vehicle is driven at a low set speed VS (<ThV) with the speed limit ThV reduced, as shown in Figure 8(A). Here, the low set speed VS is set to a speed equivalent to slow driving of 10 km / h or less, where the vehicle V1 can stop at any time or avoid obstacles OB or missing sections HL. By reducing the vehicle speed when driving along the corrected route AT, it is possible to make it easier for the vehicle V1 to take driving actions to avoid obstacles OB or missing sections of the road if they exist on the corrected route AT. In addition, by reducing the vehicle speed when driving along the corrected route AT, the driver can return to the memorized route (avoidance route) at any time.

[0030] When the vehicle V1 is traveling along the corrected route AT, if the processor detects a missing section HL in the corrected route AT, it calculates a guided route MT to move the vehicle V1 from the corrected route AT to the memory route RT. The guided route MT is a route that assumes the vehicle V1 will pass through the missing section HL (passing through areas other than the missing section HL), starting from a point on the corrected route AT, passing between the corrected route AT and the memory route RT (avoidance route), and ending from a point on the memory route RT. The guided route MT is connected to the memory route RT. After the processor 10 has the vehicle V1 automatically drive the guided route MT, it has the vehicle V1 automatically drive the memory route RT connected to the guided route MT. The detection of a missing section HL occurs when the confidence level of the detection result of the missing section HL in the route (road) is above a predetermined threshold. The missing section HL includes sinkholes, holes, steps, etc., formed underground from the road surface due to the partial loss of road constituent materials or pavement materials. The confidence level of the detection result for missing section HL is determined based on the number of times a detection result indicating the presence of missing section HL is output, and the frequency of output of a detection result indicating the presence of missing section HL per unit time or unit distance traveled. The processor 10 determines that the higher the number of times or frequency of output of a detection result indicating the presence of missing section HL, the higher the confidence level of the detection result for missing section HL. The processor 10 determines that the confidence level of the detection result for missing section HL is above a predetermined threshold if the number of times or frequency of output of a detection result indicating the presence of missing section HL is above a predetermined number. Furthermore, the confidence level of the detection result for missing section HL can be defined according to the size and / or depth of the missing section HL of the road surface in which its presence was detected, such as a sinkhole, hole, or step. This is because if the size and / or depth of the missing section HL, such as a sinkhole, hole, or step, of the road surface is small, it does not affect the driving of the vehicle and does not need to be avoided. The processor 10 determines that the confidence level is above a predetermined threshold if the size and / or depth of the detected missing section HL, such as a sinkhole, hole, or step, of the road surface is above a predetermined length. Specifically, the processor 10 causes the vehicle V1 to automatically drive along the guided route MT.During automatic driving along the corrected route AT, if a missing section HL is detected on the driving path as shown in Figure 8(B), and it is determined that there is a high probability that the missing section HL exists (confidence level is above a predetermined threshold) (i.e., it is not a false detection of the missing section HL), then, as shown in Figure 8(C), a guidance route MT is generated to return from the corrected route AT to the stored route RT (avoidance route), thereby avoiding the missing section HL. Once the vehicle V1 returns to the stored route RT (avoidance route), the set speed is increased again within the speed limit range, and the vehicle returns to normal automatic driving along the stored route RT. Here, the speed limit may be the speed limit set within the private property if the guidance route MT is on private property. The set speed VS may be the speed during manual driving by the driver when the stored route RT is generated. The set speed VS may be reduced (decelerated) according to the curvature of the sequence of points in the stored route RT. Furthermore, even if the speed limit set within the private property is 30 km / h, the speed limit may be set to 10 km / h and the set speed reduced while driving on the corrected route RT or guidance route MT.

[0031] According to this embodiment, if a missing section HL is detected on the corrected path AT during automatic driving mode, it may be impossible to drive on the corrected path AT, especially if the confidence level for detecting the missing section HL is above a predetermined value (i.e., not a false detection). In this case, the vehicle can be guided back to the stored path RT (avoidance path) by calculating a guidance path MT that returns the vehicle from the corrected path AT to the stored path RT (avoidance path). Furthermore, according to this embodiment, by reducing the set vehicle speed VS and driving on the corrected path AT, if a missing section HL exists on the corrected path AT, the driver can always avoid the missing section HL and return to the stored path RT (avoidance path). Even if there are no obstacles OB on the road surface of the corrected path AT, there is a possibility that a missing section HL exists below the road surface. Unlike three-dimensional obstacles that exist on the road surface (positive direction of the detection coordinates), missing sections HL are located below the road surface (negative direction of the detection coordinates), making it difficult to obtain a detection signal depending on the gradient of the path and the attitude of the vehicle. In addition, the shape of the missing section HL is indeterminate, and its shape characteristics cannot be defined, making it difficult to determine whether or not it is a missing section HL. By reducing the set vehicle speed VS and driving along the corrected route AT, the number of judgment processing cycles per unit distance can be increased, allowing for the detection of missing parts HL in the corrected route AT with high accuracy. Thus, in the memory route creation mode, if the driver generates a avoidance route RT that avoids the missing part HL rather than the obstacle OB, the vehicle can be driven along the guided route MT without driving along the corrected route RT where the missing part HL is located, and the memory route RT (avoidance route) can be driven.

[0032] The control procedure for the driver assistance control of this embodiment will be explained based on Figures 9(A), 9(B), and 9(C). Figure 9(A) is a flowchart showing the control procedure in memory path creation mode. When the driver inputs a command to start memory path creation mode via switch 62a of the HMI6, the processor 10 starts memory path creation mode (M1). After the memory path creation mode is started, manual driving is performed by the driver (M2). The processor 10 acquires surrounding information detected by the external sensor 2 while the vehicle V1 is traveling along an arbitrary route. The processor 10 accumulates the changes in the position of the vehicle V1 estimated based on the acquired surrounding information, generates a trajectory TJ, and creates a memory path RT including the trajectory TJ (M3). To end the memory path creation mode, for example, the "Memory Path Creation Mode" switch 62a on the GUI of the HMI6 can be pressed again to end the memory path creation mode. When the vehicle V1 reaches the target point GL set by the driver and stops the vehicle, the driver touches or presses switch 62a on the HMI6 again to input an instruction to end the memory path creation mode. Upon receiving the instruction, the processor 10 terminates the memory path creation process. Processes M2 and M3 continue in a loop until an instruction to end the memory path creation mode is input (NO in M4). Once the instruction to end the memory path creation mode is input and the memory path creation process is completed (YES in M4), the created memory path RT is stored as map data 41D in the map data storage unit 41 of the memory device 4 (M5). Here, the map data 41D includes the memory path RT which stores the estimated trajectory TJ of the vehicle, and feature quantities extracted from surrounding information detected by the external sensor 2. The feature quantities are stored in the map data storage unit 41 in association with the position of the memory path RT. The memory path RT is used as the target path for the path-following control of the vehicle V1. The stored feature quantities are used for position estimation during autonomous driving. The surrounding information detected by the external sensor 2 is matched with stored feature quantities, and the position of the vehicle V1 is estimated based on the results.

[0033] Figure 9(B) is a flowchart showing the control procedure for the automatic driving mode. If multiple memorized routes RT are stored, the driver selects one memorized route RT to drive automatically (A1). The processor 10 displays the multiple memorized routes RT on the display 61 and identifies the memorized route RT selected by the driver using the HMI 6. The processor 10 may also automatically select the memorized route RT closest to the position of the vehicle V1. In this case, for example, if on the ground, the processor may have a function to find the latitude and longitude of the starting point of the memorized route RT from the GPS position information (latitude and longitude) and automatically select the map of the memorized route RT. If the driver inputs via switch 62b on the HMI 6 that they want to start the automatic driving mode (YES in A2), the driver assistance device 1 becomes ready for automatic driving. The processor 10 waits for input until it receives input that it wants to start the automatic driving mode (NO in A2). The processor 10 confirms that the vehicle V1 is located on the memorized route RT and starts route following control. If the vehicle is not on the stored route RT, the processor 10 guides the driver to move to the starting position for automated driving on the stored route RT by manual driving (A3). The starting position for automated driving on the stored route RT is displayed on the display 61, although this is not particularly limited, to prompt the driver to move the vehicle by manual driving. The display of the starting position may be performed while driving towards the starting point of the stored route RT, or when the vehicle V1 stops before reaching the starting point. The processor 10 recognizes the starting position (map coordinate value) on the map data 41D (A4). If the processor 10 determines that the vehicle V1 is on the stored route RT (YES in A5), it corrects the stored route RT, sets the corrected route as the target route, and starts automated driving to have the vehicle V1 travel along the target route (A6). Processes A3 and A4 are repeated until the vehicle V1 moves to the starting point on the stored route RT. When the vehicle V1 moves to a point on the memory path RT, the processor 10 continues autonomous driving along the target path until the vehicle reaches the target point GL. Once the vehicle reaches the target point GL (YES in A7), the autonomous driving mode is terminated.

[0034] Figure 9(C) is a flowchart showing the control procedure for correcting the route when an obstacle that was present in the memory route creation mode is no longer present in the automatic driving mode. Figure 9(C) shows the details of the process A6 in Figure 9(B). In process A6, the processor 10 performs follow-the-memory driving control to the memory route RT (A6-1) and, at predetermined intervals, sets a starting point ST on the memory route RT near the vehicle V1 and an ending point ED at a predetermined distance D forward from the starting point ST (A6-2). The starting point ST and ending point ED are endpoints of the memory route RT, and the distance along the road from the starting point ST to the ending point ED is a predetermined distance D. Next, the processor 10 generates a corrected route AT connecting the starting point ST and the ending point ED (A6-3). The method for generating the corrected route AT is not particularly limited and there are various methods, but for example, a method can be used in which the position coordinates, attitude, and curvature of the starting point ST and ending point ED of the corrected route AT are set, and the route is generated considering the vehicle motion between them. The route generation algorithm is not limited as long as it is a method that allows the vehicle V1 to automatically travel between the starting point ST and the ending point ED, which are the endpoints of the route.

[0035] Next, the deviation distance dn (n = 1, 2, 3, …, n) between the corrected route AT and the memorized route RT (avoidance route) is calculated at multiple points. If the deviation distance dn is greater than or equal to a predetermined distance, the memorized route RT is considered the avoidance route that the driver would have taken to avoid the obstacle OB (A6-4, A6-5). If there is no obstacle OB on the corrected route AT (NO in A6-6), the vehicle speed is reduced and the vehicle drives automatically at a low speed (A6-7). By reducing the vehicle speed and driving the vehicle V1 at a low speed, it is made easier to take driving actions to avoid missing sections HL, etc., on the corrected route AT. Here, low speed means a speed at which stopping or steering avoidance is possible at any time, for example, a vehicle speed of 10 km / h or less or a slow speed. During automatic driving along the corrected route AT, missing sections HL are detected on the road surface of the driving route (YES in A6-8), and the confidence level of the presence of missing sections HL is calculated (A6-10). If the confidence level is above a predetermined threshold and it is determined that there is a high probability that a missing section HL exists, a guided route MT is generated to return from the corrected route AT to the stored route RT (avoidance route) (A6-11). By having the vehicle V1 travel along the guided route MT, it becomes possible to travel while avoiding the missing section HL. If no missing section HL is detected in the corrected route AT, that is, if it is determined that there is no missing section HL in the corrected route AT (NO in A6-8), the processes in A6-7 and A6-8 are repeated until the travel through the section of the corrected route AT that is subject to route correction is completed (NO in A6-9). Once the travel through the section of the corrected route AT is completed (YES in A6-9), the process is terminated. Once the vehicle V1 has moved onto the avoidance route, which is the stored route RT, the set speed VS is increased again within the speed limit range to the predetermined speed, and the vehicle returns to normal automatic driving along the stored route RT. Here, the speed limit may be set to the speed limit established within the private property, the speed driven by the driver when the memory route creation mode is executed if there is no established speed limit, or the speed at which the vehicle decelerates around curves according to the curvature of the sequence of points in the memory route RT. After the vehicle V1 returns to the avoidance route, i.e., the memory route RT, the process in A6 continues until the vehicle V1 reaches the target point GL (NO in A7). Once the vehicle V1 reaches the target point GL by automatic driving, the automatic driving mode is terminated (YES in A7).

[0036] 100...Driving support system, 1...Driving support device, 10...Processor, 11...CPU, 12...ROM, 13...RAM, 101...Driving mode management unit, 102...Peripheral information processing unit, 103...Route generation unit, 104...Route following control unit, 2...External sensor, 21...Camera, 22...Radar device, 23...LiDAR, 3...Position detection device, 31...GNNS, 32...IMU, 4...Storage device, 41...Map data storage unit, 41D...Map data, 5...Vehicle actuator, 51...Steering device, 52...Drive device, 53...Braking device, 6...HMI, 61...Display, 62...Switch

Claims

1. A driving assistance method used in a processor to control the automatic driving of a vehicle, wherein the processor stores the trajectory of the vehicle estimated using surrounding information of the vehicle detected by sensors during manual driving of the vehicle as a stored path, and after storing, when the vehicle next travels along the stored path, it is instructed to automatically drive the vehicle using the stored path as the target path, and during the automatic driving, it generates a corrected path connecting a starting point located near the current position of the vehicle, which is a point on the stored path, and an ending point located at a predetermined distance in the direction of travel from the starting point, it calculates the degree of deviation of the stored path from the corrected path, and if the degree of deviation is greater than or equal to a predetermined value and it is determined that there are no obstacles on the corrected path, it is instructed to automatically drive the vehicle along the corrected path.

2. The driving assistance method according to claim 1, wherein the processor determines that the memory path is an avoidance path in which driving to avoid the obstacle has been performed if the degree of deviation is greater than or equal to a predetermined value, and if it determines that there is no obstacle on the corrected path, it causes the vehicle to automatically drive the corrected path.

3. The driving assistance method according to claim 1 or 2, wherein the processor reduces the vehicle speed of the vehicle and causes the vehicle to automatically drive along the corrected path, even if it determines that there are no obstacles in the corrected path.

4. The driving assistance method according to any one of claims 1 to 3, wherein when the vehicle is traveling along the corrected path, the processor detects a missing portion in the corrected path, and if the confidence level of the detection result of the missing portion is above a predetermined threshold, the processor calculates a guidance path to move the vehicle from the corrected path to the storage path, and causes the vehicle to automatically drive along the guidance path.

5. The driving support method according to any one of claims 1 to 4, wherein the processor detects a section of the storage path in which the curvature of the storage path is greater than or equal to a predetermined curvature, the curvature of the storage path is zero, and the curvature of the storage path is less than a predetermined curvature, and calculates the degree of deviation of the storage path from the corrected path.

6. A driver assistance device comprising a processor for controlling the automatic driving of a vehicle, wherein the processor stores the trajectory of the vehicle estimated using surrounding information of the vehicle detected by sensors during manual driving of the vehicle as a stored path, and after storage, when the vehicle next travels along the stored path, it is instructed to automatically drive the vehicle using the stored path as the target path, and during the automatic driving, it generates a corrected path connecting a starting point located near the current position of the vehicle, which is a point on the stored path, and an ending point located at a predetermined distance in the direction of travel from the starting point, it calculates the degree of deviation of the stored path from the corrected path, and if the degree of deviation is greater than or equal to a predetermined value and it is determined that there are no obstacles on the corrected path, it is instructed to automatically drive the vehicle along the corrected path.

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