Obstacle avoidance method and device for autonomous driving vehicle

Abstract

The present application discloses an obstacle avoidance method and device for an autonomous driving vehicle, and belongs to the field of autonomous driving technology. The method includes: determining the right of way result of the autonomous driving vehicle for the adjacent lane, calculating the safe distance between the autonomous driving vehicle and the obstacle based on the right of way result, the obstacle and the autonomous driving vehicle are traveling in the target direction, and the obstacle is located behind the autonomous driving vehicle in the target direction; determining the obstacle avoidance method of the autonomous driving vehicle based on the comparison result of the safe distance and the actual distance, the actual distance is the distance between the autonomous driving vehicle and the obstacle; controlling the autonomous driving vehicle to avoid the obstacle according to the obstacle avoidance method. Compared with determining the obstacle avoidance method of the autonomous driving vehicle only based on the current speed of the obstacle, calculating the safe distance between the autonomous driving vehicle and the obstacle based on the right of way result of the autonomous driving vehicle for the adjacent lane, and determining the obstacle avoidance method accordingly can reduce the probability of collision between the autonomous driving vehicle and the obstacle, and has higher safety.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of autonomous driving technology, and in particular to an obstacle avoidance method and device for an autonomous driving vehicle. Background Art

[0002] With the continuous development of autonomous driving technology, autonomous driving vehicles are gradually entering the public eye. One of the performance of autonomous driving vehicles is to avoid obstacles in time during driving, that is, obstacle avoidance, so as to avoid traffic accidents. Therefore, how to control autonomous driving vehicles to avoid obstacles is very important. Summary of the invention

[0003] The embodiment of the present application provides an obstacle avoidance method and device for an autonomous driving vehicle, which can be used to control an autonomous driving vehicle to avoid obstacles. The technical solution is as follows:

[0004] On the one hand, an embodiment of the present application provides an obstacle avoidance method for an autonomous driving vehicle, the method comprising:

[0005] Determine a right-of-way result of the autonomous driving vehicle for an adjacent lane, and calculate a safe distance between the autonomous driving vehicle and an obstacle according to the right-of-way result, the obstacle and the autonomous driving vehicle traveling in a target direction, and the obstacle is located behind the autonomous driving vehicle in the target direction;

[0006] Determining an obstacle avoidance method of the autonomous driving vehicle according to a comparison result between the safety distance and the actual distance, wherein the actual distance is the distance between the autonomous driving vehicle and the obstacle;

[0007] Control the automatic driving vehicle to perform obstacle avoidance driving according to the obstacle avoidance method.

[0008] In a possible implementation, determining the right of way result of the autonomous driving vehicle for an adjacent lane includes:

[0009] Determining a proportion of adjacent lanes occupied by the automated driving vehicle;

[0010] Based on the proportion of the adjacent lane occupied by the autonomous driving vehicle, the right of way result of the autonomous driving vehicle for the adjacent lane is determined.

[0011] In a possible implementation, calculating the safe distance between the autonomous driving vehicle and the obstacle according to the road right result includes:

[0012] Based on the right-of-way result indicating that the autonomous driving vehicle has the right of way of the adjacent lane, calculating a first distance between the autonomous driving vehicle and the obstacle according to a first parameter;

[0013] The determining of the obstacle avoidance method of the autonomous driving vehicle according to the comparison result between the safety distance and the actual distance includes:

[0014] The obstacle avoidance method of the autonomous driving vehicle is determined according to the comparison result between the first distance and the actual distance.

[0015] In a possible implementation, calculating the safe distance between the autonomous driving vehicle and the obstacle according to the road right result includes:

[0016] Based on the right-of-way result indicating that the autonomous driving vehicle does not have the right-of-way of the adjacent lane and the obstacle has the right-of-way of the adjacent lane, calculating a second distance between the autonomous driving vehicle and the obstacle according to a second parameter;

[0017] The determining of the obstacle avoidance method of the autonomous driving vehicle according to the comparison result between the safety distance and the actual distance includes:

[0018] The obstacle avoidance method of the automatic driving vehicle is determined according to the comparison result between the second distance and the actual distance.

[0019] In a possible implementation, calculating the safe distance between the autonomous driving vehicle and the obstacle according to the road right result includes:

[0020] Based on the right-of-way result indicating that the autonomous driving vehicle does not have the right-of-way of the adjacent lane, and the obstacle also does not have the right-of-way of the adjacent lane, calculating a first distance between the autonomous driving vehicle and the obstacle according to a first parameter;

[0021] The determining of the obstacle avoidance method of the autonomous driving vehicle according to the comparison result between the safety distance and the actual distance includes:

[0022] The obstacle avoidance method of the autonomous driving vehicle is determined according to the comparison result between the first distance and the actual distance.

[0023] In a possible implementation, determining the obstacle avoidance method of the autonomous driving vehicle according to a comparison result between the first distance and the actual distance includes:

[0024] Based on the first distance being smaller than the actual distance, determining that the obstacle avoidance method of the autonomous driving vehicle is to rush over the obstacle;

[0025] Based on the fact that the first distance is greater than the actual distance, it is determined that the obstacle avoidance method of the autonomous driving vehicle is to give way to the obstacle.

[0026] In a possible implementation, the first parameter includes , , , represents the distance traveled within the obstacle reaction time; represents the distance traveled after the obstacle reaction time; Indicates the distance traveled by the autonomous driving vehicle;

[0027] The calculating a first distance between the autonomous driving vehicle and the obstacle according to the first parameter includes:

[0028] Based on the , , Calculate a first distance between the autonomous driving vehicle and the obstacle according to the following formula;

[0029] d=

[0030] Wherein, the d represents the first distance.

[0031] In a possible implementation, the ;

[0032] Among them, the represents the speed of the obstacle; represents the minimum acceleration within the acceleration value range when the obstacle accelerates; and p represents the minimum reaction time within the obstacle reaction time value range after the autonomous driving vehicle brakes.

[0033] In a possible implementation, the ;

[0034] Among them, the Indicates the maximum acceleration within the acceleration value range when braking after the obstacle reaction time.

[0035] In a possible implementation, the ;

[0036] Among them, the represents the speed of the autonomous driving vehicle; Indicates the minimum acceleration within the acceleration value range when the autonomous driving vehicle brakes.

[0037] In another aspect, an obstacle avoidance device for an autonomous driving vehicle is provided, the device comprising:

[0038] a calculation module, configured to determine a right-of-way result of the autonomous driving vehicle for an adjacent lane, and calculate a safe distance between the autonomous driving vehicle and an obstacle according to the right-of-way result, wherein the obstacle and the autonomous driving vehicle are traveling in a target direction, and the obstacle is located behind the autonomous driving vehicle in the target direction;

[0039] A determination module, configured to determine an obstacle avoidance mode of the autonomous driving vehicle according to a comparison result between the safety distance and an actual distance, wherein the actual distance is the distance between the autonomous driving vehicle and the obstacle;

[0040] A control module is used to control the autonomous driving vehicle to perform obstacle avoidance driving according to the obstacle avoidance method.

[0041] In a possible implementation, the calculation module is used to determine the proportion of adjacent lanes occupied by the autonomous driving vehicle;

[0042] Based on the proportion of the adjacent lane occupied by the autonomous driving vehicle, the right of way result of the autonomous driving vehicle for the adjacent lane is determined.

[0043] In a possible implementation, the calculation module is configured to indicate that the autonomous driving vehicle has the right of way of an adjacent lane based on the right of way result, and calculate a first distance between the autonomous driving vehicle and the obstacle according to a first parameter;

[0044] The determination module is used to determine the obstacle avoidance method of the automatic driving vehicle based on the comparison result of the first distance and the actual distance.

[0045] In a possible implementation, the calculation module is configured to calculate a second distance between the autonomous driving vehicle and the obstacle according to a second parameter based on the right-of-way result indicating that the autonomous driving vehicle does not have the right-of-way of the adjacent lane and that the obstacle has the right-of-way of the adjacent lane;

[0046] The determination module is used to determine the obstacle avoidance method of the automatic driving vehicle based on the comparison result between the second distance and the actual distance.

[0047] In a possible implementation, the calculation module is configured to calculate a first distance between the autonomous driving vehicle and the obstacle according to a first parameter based on the right-of-way result indicating that the autonomous driving vehicle does not have the right-of-way of the adjacent lane and the obstacle also does not have the right-of-way of the adjacent lane;

[0048] The determination module is used to determine the obstacle avoidance method of the automatic driving vehicle based on the comparison result of the first distance and the actual distance.

[0049] In a possible implementation, the determining module is configured to determine, based on the first distance being smaller than the actual distance, that the obstacle avoidance method of the autonomous driving vehicle is to rush over the obstacle;

[0050] Based on the fact that the first distance is greater than the actual distance, it is determined that the obstacle avoidance method of the autonomous driving vehicle is to give way to the obstacle.

[0051] In a possible implementation, the first parameter includes , , , represents the distance traveled within the obstacle reaction time; represents the distance traveled after the obstacle reaction time; Indicates the distance traveled by the autonomous driving vehicle;

[0052] The calculation module is used to , , Calculate a first distance between the autonomous driving vehicle and the obstacle according to the following formula;

[0053] d=

[0054] Wherein, the d represents the first distance.

[0055] In a possible implementation, the ;

[0056] Among them, the represents the speed of the obstacle; represents the minimum acceleration within the acceleration value range when the obstacle accelerates; and p represents the minimum reaction time within the obstacle reaction time value range after the autonomous driving vehicle brakes.

[0057] In a possible implementation, the ;

[0058] Among them, the Indicates the maximum acceleration within the acceleration value range when braking after the obstacle reaction time.

[0059] In a possible implementation, the ;

[0060] Among them, the represents the speed of the autonomous driving vehicle; Indicates the minimum acceleration within the acceleration value range when the autonomous driving vehicle brakes.

[0061] On the other hand, a computer device is provided, comprising a processor and a memory, wherein the memory stores at least one computer program, and the at least one computer program is loaded and executed by the processor so that the computer device implements any of the above-mentioned autonomous driving vehicle obstacle avoidance methods.

[0062] On the other hand, a computer-readable storage medium is also provided, in which at least one computer program is stored, and the at least one computer program is loaded and executed by a processor so that the computer implements any of the above-mentioned autonomous driving vehicle obstacle avoidance methods.

[0063] On the other hand, a computer program product or a computer program is also provided, wherein the computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes any of the above-mentioned autonomous driving vehicle obstacle avoidance methods.

[0064] The technical solution provided by the embodiments of the present application brings at least the following beneficial effects:

[0065] In the embodiment of the present application, the safe distance between the autonomous driving vehicle and the obstacle is calculated based on the right of way of the autonomous driving vehicle for the adjacent lane, and the obstacle avoidance method of the autonomous driving vehicle is determined based on the comparison result of the safe distance and the actual distance. Compared with the method of determining the obstacle avoidance method of the autonomous driving vehicle only based on the current speed of the obstacle, this method can reduce the probability of collision between the autonomous driving vehicle and the obstacle, and has higher safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0067] Figure 1 It is a schematic diagram of an implementation environment provided by an embodiment of the present application;

[0068] Figure 2 is a flow chart of an obstacle avoidance method for an autonomous driving vehicle provided in an embodiment of the present application;

[0069] Figure 3 is a schematic diagram of a road right situation of an autonomous driving vehicle provided in an embodiment of the present application;

[0070] Figure 4 is a schematic diagram of a road right situation of an autonomous driving vehicle provided in an embodiment of the present application;

[0071] Figure 5 is a schematic diagram of a road right situation of an autonomous driving vehicle provided in an embodiment of the present application;

[0072] Figure 6 It is a logic judgment diagram of an obstacle avoidance method for an autonomous driving vehicle provided in an embodiment of the present application;

[0073] Figure 7 is a schematic diagram of the structure of an obstacle avoidance device for an autonomous driving vehicle provided in an embodiment of the present application;

[0074] Figure 8 It is a structural diagram of a server provided in an embodiment of the present application;

[0075] Fig. 9 It is a structural diagram of a terminal provided in an embodiment of the present application. DETAILED DESCRIPTION

[0076] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0077] This application embodiment provides an obstacle avoidance method for an autonomous driving vehicle. Figure 1 , which shows a schematic diagram of an implementation environment of the method provided in an embodiment of the present application. The implementation environment may include: a terminal 11 and a server 12.

[0078] Among them, the terminal 11 is installed with an application or webpage that can control the autonomous driving vehicle to avoid obstacles. When the application or webpage needs to control the autonomous driving vehicle to avoid obstacles, the method provided in the embodiment of the present application can be applied to control it. The server 12 can store the speed information that needs to control the autonomous driving vehicle to avoid obstacles, and the terminal 11 can obtain the speed information that needs to control the autonomous driving vehicle to avoid obstacles from the server 12. Of course, the terminal 11 can also store the obtained speed information.

[0079] Optionally, the terminal 11 may be a smart device such as a mobile phone, a tablet computer, a personal computer, etc. The server 12 may be a single server, or a server cluster consisting of multiple servers, or a cloud computing service center. The terminal 11 establishes a communication connection with the server 12 via a wired or wireless network.

[0080] Optionally, the terminal 11 can be any electronic product that can interact with the user through one or more methods such as a keyboard, a touchpad, a touch screen, a remote control, voice interaction or a handwriting device, such as a PC (Personal Computer), a mobile phone, a smart phone, a PDA (Personal Digital Assistant), a wearable device, a PPC (Pocket PC), a tablet computer, a smart car machine, a smart TV, a smart speaker, etc. The server 12 can be a server, a server cluster consisting of multiple servers, or a cloud computing service center. The terminal 11 establishes a communication connection with the server 12 through a wired or wireless network.

[0081] Those skilled in the art should understand that the above-mentioned terminal 11 and server 12 are only examples, and other existing or future terminals or servers that are applicable to the present application should also be included in the protection scope of the present application and are included here by reference.

[0082] The present application provides an obstacle avoidance method for an autonomous driving vehicle. The method can be applied to the above Figure 1 The implementation environment shown. Figure 2 As shown, taking the method applied to a terminal as an example, the method includes steps 201 to 203.

[0083] In step 201, the right of way result of the autonomous driving vehicle for the adjacent lane is determined, and the safe distance between the autonomous driving vehicle and the obstacle is calculated based on the right of way result. The obstacle and the autonomous driving vehicle travel in the target direction, and the obstacle is located behind the autonomous driving vehicle in the target direction.

[0084] In an exemplary embodiment, before determining the right-of-way result of the autonomous driving vehicle for the adjacent lane, it is necessary to first determine whether the scene in which the autonomous driving vehicle is currently located is an obstacle avoidance scene. Exemplarily, if the autonomous driving vehicle is traveling in a target direction (for example, if the autonomous driving vehicle is traveling from east to west, then the target direction is the west), and there is an obstacle in the area in front of the autonomous driving vehicle in the target direction, then the current scene can be determined to be an obstacle avoidance scene. Among them, the embodiment of the present application does not limit the category of obstacles. For example, the obstacle can be a moving vehicle or a pedestrian. The range size of the area in front of the autonomous driving vehicle can be set based on experience or determined based on input information. For example, the range size of the area in front of the autonomous driving vehicle is the area within 30 meters directly in front of the autonomous driving vehicle, or it can be a semicircular area in front of the autonomous driving vehicle with the autonomous driving vehicle as the center and a radius of 30 meters.

[0085] The embodiments of the present application do not limit the method for determining obstacles in the area in front of the autonomous driving vehicle. For example, the radar can be used to emit lasers to scan the area in front of the autonomous driving vehicle to determine whether there are obstacles in the area. For example, the radar can be installed on the top of the autonomous driving vehicle, or in front of or behind the autonomous driving vehicle. The embodiments of the present application do not limit the installation location of the radar. After the radar scans the area in front of the autonomous driving vehicle, it uploads the scanning results to the terminal, and the terminal can determine whether the current scene is an obstacle avoidance scene based on the scanning results.

[0086] Based on the current scene of the autonomous driving vehicle being an obstacle avoidance scene, it is necessary to further determine the right of way result of the autonomous driving vehicle for the adjacent lane. In one possible implementation, determining the right of way result of the autonomous driving vehicle for the adjacent lane includes: determining the proportion of the adjacent lane occupied by the autonomous driving vehicle; and determining the right of way result of the autonomous driving vehicle for the adjacent lane based on the proportion of the adjacent lane occupied by the autonomous driving vehicle.

[0087] Exemplarily, if the proportion of adjacent lanes occupied by the autonomous driving vehicle is greater than a threshold, it is determined that the autonomous driving vehicle has the right of way of the adjacent lane; similarly, if the proportion of adjacent lanes occupied by the autonomous driving vehicle is less than a threshold, it is determined that the autonomous driving vehicle does not have the right of way of the adjacent lane. Among them, the value range of the threshold can be set based on experience or based on a scenario. For example, the value range of the threshold can be 0-1, and the embodiment of the present application does not limit the size of the threshold, as long as it is within the value range. Exemplarily, the threshold can be 1 / 2 or 1 / 3. Taking the threshold size of 1 / 2 as an example, when the proportion of adjacent lanes occupied by the autonomous driving vehicle is greater than 1 / 2, it can be determined that the autonomous driving vehicle has the right of way of the adjacent road.

[0088] After determining the right of way result of the autonomous driving vehicle for the adjacent lane, a safe distance between the autonomous driving vehicle and the obstacle is calculated according to the right of way result. In one possible implementation, calculating the safe distance between the autonomous driving vehicle and the obstacle according to the right of way result includes: based on the right of way result indicating that the autonomous driving vehicle has the right of way of the adjacent lane, calculating a first distance between the autonomous driving vehicle and the obstacle according to a first parameter.

[0089] For example, the right of way result indicates that the autonomous driving vehicle has the right of way of the adjacent lane as follows: Figure 3 . Figure 3 A schematic diagram of the road right situation of an autonomous driving vehicle. Figure 3 In the figure, 301 is obstacle 1 located in front of the autonomous driving vehicle in the target direction; 302 is the autonomous driving vehicle; and 303 is obstacle 2 located behind the autonomous driving vehicle in the target direction. Figure 3It can be seen that the autonomous driving vehicle and obstacle 2 are traveling in the same direction, and the autonomous driving vehicle has the right of way in the adjacent lane, while obstacle 2 does not have the right of way in the adjacent lane. In addition, Figure 3 Only one possible situation in which the autonomous driving vehicle has the right of way of the adjacent road is shown, and it does not constitute a complete limitation on the right of way of the autonomous driving vehicle having the right of way of the adjacent lane. That is to say, as long as the autonomous driving vehicle has the right of way of the adjacent lane, regardless of whether the obstacle behind the autonomous driving vehicle has the right of way of the adjacent lane, the autonomous driving vehicle can be indicated to have the right of way of the adjacent lane based on the right of way result, and the first distance between the autonomous driving vehicle and the obstacle is calculated according to the first parameter. Optionally, the first distance is a safety distance. The safety distance satisfies the distance that the autonomous driving vehicle brakes suddenly, the obstacle behind the autonomous driving vehicle accelerates within the reaction time, and decelerates after the reaction time without collision.

[0090] In a possible implementation, the first parameter includes , , , Indicates the distance traveled within the obstacle reaction time; Indicates the distance traveled after the obstacle reaction time; represents the distance traveled by the autonomous driving vehicle; calculating the first distance between the autonomous driving vehicle and the obstacle according to the first parameter, including: based on , , Calculate the first distance between the autonomous driving vehicle and the obstacle according to the following formula;

[0091]

[0092] in, Indicates the first distance.

[0093] In one possible implementation, ;in, Indicates the speed of the obstacle; It represents the minimum acceleration in the acceleration value range when the obstacle accelerates; p represents the minimum reaction time in the obstacle reaction time value range after the autonomous driving vehicle brakes.

[0094] In one possible implementation, ;in, Indicates the maximum acceleration within the acceleration value range when braking after the obstacle reaction time.

[0095] In one possible implementation, ;in, represents the speed of the autonomous vehicle; Indicates the minimum acceleration within the acceleration value range when the autonomous driving vehicle brakes.

[0096] In the embodiment of the present application, the first distance is the distance at which the autonomous driving vehicle does not collide with the obstacle after the autonomous driving vehicle brakes suddenly with the minimum acceleration and the obstacle accelerates with the minimum acceleration within the shortest reaction time, and after the autonomous driving vehicle brakes with the maximum acceleration after the reaction time.

[0097] The embodiment of the present application does not limit the acceleration value interval when the obstacle accelerates, the obstacle reaction time value interval, the acceleration value interval when braking after the obstacle reaction time, and the acceleration value interval when the autonomous driving vehicle brakes. The above value intervals can be set based on experience and can also be flexibly adjusted according to the application scenario. For example, the acceleration value interval when the obstacle accelerates can be 1-1.5m / s 2 .

[0098] In one possible implementation, a safe distance between the autonomous driving vehicle and an obstacle is calculated based on a right of way result, including: based on the right of way result indicating that the autonomous driving vehicle does not have the right of way of an adjacent lane, and the obstacle has the right of way of an adjacent lane, calculating a second distance between the autonomous driving vehicle and the obstacle according to a second parameter.

[0099] For example, the right of way result indicates that the autonomous driving vehicle does not have the right of way in the adjacent lane, and the obstacle has the right of way in the adjacent lane as shown below: Figure 4 , Figure 4 A schematic diagram of the road right situation of an autonomous driving vehicle. Figure 4 401 is obstacle 1 located in front of the autonomous driving vehicle in the target direction; 402 is the autonomous driving vehicle; 403 is obstacle 2 located behind the autonomous driving vehicle in the target direction. Figure 4 It can be seen that the autonomous driving vehicle and obstacle 2 are traveling in the same direction, and the autonomous driving vehicle does not have the right of way of the adjacent lane, while obstacle 2 has the right of way of the adjacent lane. At this time, the second distance between the autonomous driving vehicle and the obstacle can be calculated according to the second parameter.

[0100] In a possible implementation, the second parameter includes , , ; Indicates the distance traveled within the obstacle reaction time; Indicates the distance traveled after the obstacle reaction time; represents the distance traveled by the autonomous driving vehicle; and calculating the second distance between the autonomous driving vehicle and the obstacle according to the second parameter, including: based on , , Calculate the second distance between the autonomous driving vehicle and the obstacle according to the following formula;

[0101]

[0102] in, Indicates the second distance.

[0103] In one possible implementation, ;in, Indicates the maximum acceleration within the acceleration value range when the obstacle accelerates; It indicates the maximum reaction time within the obstacle reaction time range after the autonomous driving vehicle brakes.

[0104] In one possible implementation, ;in, Indicates the minimum acceleration within the acceleration value range when braking after the obstacle reaction time.

[0105] In one possible implementation, ;in, Indicates the maximum acceleration within the acceleration value range when the autonomous driving vehicle brakes.

[0106] In the embodiment of the present application, the second distance is the distance at which the autonomous driving vehicle does not collide with the obstacle after the autonomous driving vehicle brakes suddenly with the maximum acceleration, the obstacle accelerates at the maximum acceleration within the longest reaction time, and brakes with the minimum acceleration after the reaction time.

[0107] In one possible implementation, a safe distance between the autonomous driving vehicle and an obstacle is calculated based on a right of way result, including: based on the right of way result indicating that the autonomous driving vehicle does not have the right of way of an adjacent lane, and the obstacle also does not have the right of way of an adjacent lane, calculating a first distance between the autonomous driving vehicle and the obstacle according to a first parameter.

[0108] For example, the right of way result indicates that the autonomous driving vehicle does not have the right of way in the adjacent lane, and the obstacle does not have the right of way in the adjacent lane as shown below: Figure 5 . Figure 5 A schematic diagram of the road right situation of an autonomous driving vehicle. Figure 5 In the figure, 501 is obstacle 1 located in front of the autonomous driving vehicle in the target direction; 502 is the autonomous driving vehicle; and 503 is obstacle 2 located behind the autonomous driving vehicle in the target direction. Figure 5It can be seen that the autonomous driving vehicle and obstacle 2 are traveling in the same direction, and the autonomous driving vehicle does not have the right of way in the adjacent lane, and obstacle 2 does not have the right of way in the adjacent lane. At this time, the first distance between the autonomous driving vehicle and the obstacle can be calculated according to the first parameter. Among them, the calculation method of the first distance has been described in detail in the previous article and will not be repeated here.

[0109] In step 202, the obstacle avoidance method of the autonomous driving vehicle is determined based on the comparison result between the safety distance and the actual distance, where the actual distance is the distance between the autonomous driving vehicle and the obstacle.

[0110] After calculating the safe distance between the autonomous driving vehicle and the obstacle based on the right-of-way result of the autonomous driving vehicle for the adjacent lane, the safe distance and the actual distance can be compared, and the obstacle avoidance method of the autonomous driving vehicle can be determined based on the comparison result. If the safe distance is smaller than the actual distance, it can be determined that the obstacle avoidance method of the autonomous driving vehicle is to rush over the obstacle; if the safe distance is larger than the actual distance, it can be determined that the obstacle avoidance method of the autonomous driving vehicle is to give way to the obstacle. The embodiment of the present application does not limit the method for measuring the actual distance between the autonomous driving vehicle and the obstacle. For example, the current actual distance between the autonomous driving vehicle and the obstacle can be obtained by scanning with a radar located behind the autonomous driving vehicle.

[0111] Exemplarily, according to the content in step 201, when the right of way result indicates that the autonomous driving vehicle has the right of way of the adjacent lane, the first distance between the autonomous driving vehicle and the obstacle needs to be calculated according to the first parameter. At this time, in a possible implementation, determining the obstacle avoidance method of the autonomous driving vehicle according to the comparison result of the safety distance and the actual distance includes: determining the obstacle avoidance method of the autonomous driving vehicle according to the comparison result of the first distance and the actual distance.

[0112] The obstacle avoidance method of the autonomous driving vehicle is determined based on the comparison result between the first distance and the actual distance, including: based on the first distance being smaller than the actual distance, determining that the obstacle avoidance method of the autonomous driving vehicle is to rush over the obstacle; based on the first distance being larger than the actual distance, determining that the obstacle avoidance method of the autonomous driving vehicle is to give way to the obstacle.

[0113] Exemplarily, when the right of way result indicates that the autonomous driving vehicle does not have the right of way of the adjacent lane, and the obstacle has the right of way of the adjacent lane, the second distance between the autonomous driving vehicle and the obstacle is calculated according to the second parameter. At this time, in a possible implementation, determining the obstacle avoidance method of the autonomous driving vehicle according to the comparison result of the safety distance and the actual distance includes: determining the obstacle avoidance method of the autonomous driving vehicle according to the comparison result of the second distance and the actual distance.

[0114] The obstacle avoidance method of the autonomous driving vehicle is determined based on the comparison result between the second distance and the actual distance, including: based on the second distance being smaller than the actual distance, determining that the obstacle avoidance method of the autonomous driving vehicle is to rush over the obstacle; based on the second distance being larger than the actual distance, determining that the obstacle avoidance method of the autonomous driving vehicle is to give way to the obstacle.

[0115] For example, when the right of way result indicates that the autonomous driving vehicle does not have the right of way of the adjacent lane, and the obstacle does not have the right of way of the adjacent lane, the first distance between the autonomous driving vehicle and the obstacle is calculated according to the first parameter. At this time, the possible implementation method of determining the obstacle avoidance method of the autonomous driving vehicle based on the comparison result of the safe distance and the actual distance has been described in detail above and will not be repeated here.

[0116] In step 203, the automatic driving vehicle is controlled to drive in an obstacle avoidance manner.

[0117] According to the content in step 202, after determining the obstacle avoidance method of the autonomous driving vehicle based on the comparison result of the safety distance and the actual distance, the autonomous driving vehicle can be controlled to avoid obstacles according to the determined obstacle avoidance method.

[0118] Figure 6 This is the logic judgment diagram of the obstacle avoidance method of the autonomous driving vehicle. Figure 6 In the process, step 601 is scene recognition. According to step 602, it is determined whether the scene currently in which the autonomous driving vehicle is located is an obstacle avoidance scene. If the current scene is an obstacle avoidance scene, step 604 is executed to calculate the feasibility of overtaking. If the current scene is not an obstacle avoidance scene, step 603 is executed to exit the scene recognition process. After calculating the feasibility of overtaking, step 605 is executed to determine whether the autonomous driving vehicle can pass first. If so, step 606 is executed to make an overtaking decision, and step 608 is executed to pass the result to the longitudinal decision to control the obstacle avoidance method of the autonomous driving vehicle. If not, step 607 is executed, and the autonomous driving vehicle needs to give way to the obstacle. At the same time, step 608 needs to be executed to pass the result to the longitudinal decision to control the autonomous driving vehicle.

[0119] Before calculating the feasibility of overtaking of the autonomous driving vehicle, it is necessary to determine the right of way, that is, to execute step 6041 to determine whether the autonomous driving vehicle has the right of way of the adjacent lane. If the autonomous driving vehicle has the right of way of the adjacent lane, step 6042 can be executed to aggressively calculate the feasibility of overtaking; if the autonomous driving vehicle does not have the right of way of the adjacent lane, step 6043 is executed to determine whether the obstacle has the right of way of the adjacent lane. If the autonomous driving vehicle does not have the right of way of the adjacent lane, and the obstacle does not have the right of way of the adjacent lane, step 6042 is still executed to aggressively calculate the feasibility of overtaking; if the autonomous driving vehicle does not have the right of way of the adjacent lane, and the obstacle has the right of way of the adjacent lane, step 6044 is executed to conservatively calculate the feasibility of overtaking. Among them, calculating the feasibility of overtaking is to calculate the safe distance between the autonomous driving vehicle and the obstacle. Therefore, the aggressive calculation of overtaking feasibility mentioned above corresponds to the first distance. Similarly, the conservative calculation of overtaking feasibility corresponds to the second distance.

[0120] Therefore, execute step 6045, and when calculating the safe distance, execute step 6046, that is, different parameters are used for radical and conservative methods. The specific implementation method of this step has been explained in detail in the previous article and will not be repeated here. After calculating the safe distance between the autonomous driving vehicle and the obstacle according to the radical method or the conservative method, step 6047 needs to be executed to compare whether the safe distance is greater than the actual distance. If so, execute step 6048, it is unsafe to overtake and you need to give way; if not, execute step 6049, you can safely overtake and rush.

[0121] In the embodiment of the present application, the safe distance between the autonomous driving vehicle and the obstacle is calculated based on the right of way of the autonomous driving vehicle for the adjacent lane, and the obstacle avoidance method of the autonomous driving vehicle is determined based on the comparison result of the safe distance and the actual distance. Compared with the method of determining the obstacle avoidance method of the autonomous driving vehicle only based on the current speed of the obstacle, this method can reduce the probability of collision between the autonomous driving vehicle and the obstacle, and has higher safety.

[0122] See also Figure 7 , an embodiment of the present application provides an obstacle avoidance device for an autonomous driving vehicle, the device comprising:

[0123] A calculation module 701 is used to determine the right of way result of the autonomous driving vehicle for the adjacent lane, and calculate the safe distance between the autonomous driving vehicle and the obstacle according to the right of way result, the obstacle and the autonomous driving vehicle are traveling in a target direction, and the obstacle is located behind the autonomous driving vehicle in the target direction;

[0124] A determination module 702 is used to determine an obstacle avoidance method of the autonomous driving vehicle according to a comparison result between a safety distance and an actual distance, where the actual distance is the distance between the autonomous driving vehicle and the obstacle;

[0125] The control module 703 is used to control the autonomous driving vehicle to perform obstacle avoidance driving in an obstacle avoidance manner.

[0126] In one possible implementation, the calculation module 701 is used to determine the proportion of adjacent lanes occupied by the autonomous driving vehicle;

[0127] Based on the proportion of adjacent lanes occupied by the autonomous driving vehicle, the right of way results of the autonomous driving vehicle for the adjacent lanes are determined.

[0128] In a possible implementation, the calculation module 701 is configured to indicate that the autonomous driving vehicle has the right of way of an adjacent lane based on the right of way result, and calculate a first distance between the autonomous driving vehicle and the obstacle according to a first parameter;

[0129] The determination module 702 is used to determine the obstacle avoidance method of the automatic driving vehicle according to the comparison result between the first distance and the actual distance.

[0130] In one possible implementation, the calculation module 701 is configured to calculate a second distance between the autonomous driving vehicle and the obstacle according to a second parameter based on the right-of-way result indicating that the autonomous driving vehicle does not have the right-of-way of an adjacent lane and the obstacle has the right-of-way of the adjacent lane;

[0131] The determination module 702 is used to determine the obstacle avoidance method of the automatic driving vehicle according to the comparison result between the second distance and the actual distance.

[0132] In one possible implementation, the calculation module 701 is configured to calculate a first distance between the autonomous driving vehicle and the obstacle according to a first parameter based on the right of way result indicating that the autonomous driving vehicle does not have the right of way of an adjacent lane and the obstacle does not have the right of way of the adjacent lane;

[0133] The determination module 702 is used to determine the obstacle avoidance method of the automatic driving vehicle according to the comparison result between the first distance and the actual distance.

[0134] In a possible implementation, the determination module 702 is configured to determine that the obstacle avoidance mode of the autonomous driving vehicle is to rush over the obstacle based on the first distance being less than the actual distance;

[0135] Based on the first distance being greater than the actual distance, it is determined that the obstacle avoidance method of the autonomous driving vehicle is to give way to the obstacle.

[0136] In a possible implementation, the first parameter includes , , , Indicates the distance traveled within the obstacle reaction time; Indicates the distance traveled after the obstacle reaction time; Indicates the distance traveled by the autonomous vehicle;

[0137] The calculation module 701 is used to calculate , , Calculate the first distance between the autonomous driving vehicle and the obstacle according to the following formula;

[0138]

[0139] in, Indicates the first distance.

[0140] In one possible implementation, ;

[0141] in, Indicates the speed of the obstacle; It represents the minimum acceleration in the acceleration value range when the obstacle accelerates; p represents the minimum reaction time in the obstacle reaction time value range after the autonomous driving vehicle brakes.

[0142] In one possible implementation, ;

[0143] in, Indicates the maximum acceleration within the acceleration value range when braking after the obstacle reaction time.

[0144] In one possible implementation, ;

[0145] in, represents the speed of the autonomous vehicle; Indicates the minimum acceleration within the acceleration value range when the autonomous driving vehicle brakes.

[0146] In the embodiment of the present application, the safe distance between the autonomous driving vehicle and the obstacle is calculated based on the right of way result of the autonomous driving vehicle for the adjacent lane, and the obstacle avoidance method of the autonomous driving vehicle is determined according to the comparison result of the safe distance and the actual distance. Compared with the device that determines the obstacle avoidance method of the autonomous driving vehicle only according to the current speed of the obstacle, the device can reduce the probability of collision between the autonomous driving vehicle and the obstacle, and has higher safety.

[0147] It should be noted that the device provided in the above embodiment only uses the division of the above functional modules as an example to implement its functions. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and their specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0148] Figure 8 It is a structural diagram of a server provided in an embodiment of the present application. The server may have relatively large differences due to different configurations or performances, and may include one or more processors 801 and one or more memories 802, wherein the processor 801 may be a central processing unit (CPU), and the one or more memories 802 store at least one computer program, which is loaded and executed by the one or more processors 801, so that the server implements the obstacle avoidance method for the autonomous driving vehicle provided in the above-mentioned various method embodiments. Of course, the server may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output. The server may also include other components for implementing device functions, which will not be described in detail here.

[0149] Fig. 9 1 is a schematic diagram of a terminal structure provided in an embodiment of the present application. The terminal may be a smart phone, a tablet computer, a laptop computer or a desktop computer. The terminal may also be called a user device, a portable terminal, a laptop terminal, a desktop terminal or other names.

[0150] Typically, the terminal includes: a processor 1501 and a memory 1502 .

[0151] The processor 1501 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 1501 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 1501 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 1501 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 1501 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0152] The memory 1502 may include one or more computer-readable storage media, which may be non-transitory. The memory 1502 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 1502 is used to store at least one instruction, which is used to be executed by the processor 1501 so that the terminal implements the autonomous driving vehicle obstacle avoidance method provided in the method embodiment of the present application.

[0153] In some embodiments, the terminal may also optionally include: a peripheral device interface 1503 and at least one peripheral device. The processor 1501, the memory 1502 and the peripheral device interface 1503 may be connected via a bus or a signal line. Each peripheral device may be connected to the peripheral device interface 1503 via a bus, a signal line or a circuit board. Specifically, the peripheral device includes: at least one of a radio frequency circuit 1504, a display screen 1505, a camera assembly 1506, an audio circuit 1507, a positioning assembly 1508 and a power supply 1509.

[0154] The peripheral device interface 1503 may be used to connect at least one peripheral device related to I / O (Input / Output) to the processor 1501 and the memory 1502. In some embodiments, the processor 1501, the memory 1502, and the peripheral device interface 1503 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 1501, the memory 1502, and the peripheral device interface 1503 may be implemented on a separate chip or circuit board, which is not limited in this embodiment.

[0155] The radio frequency circuit 1504 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 1504 communicates with the communication network and other communication devices through electromagnetic signals. The radio frequency circuit 1504 converts the electrical signal into an electromagnetic signal for transmission, or converts the received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 1504 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, and the like. The radio frequency circuit 1504 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes, but is not limited to: a metropolitan area network, various generations of mobile communication networks (2G, 3G, 4G and 5G), a wireless local area network and / or a WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 1504 may also include circuits related to NFC (Near Field Communication), which is not limited in this application.

[0156] The display screen 1505 is used to display a UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 1505 is a touch display screen, the display screen 1505 also has the ability to collect touch signals on the surface or above the surface of the display screen 1505. The touch signal can be input as a control signal to the processor 1501 for processing. At this time, the display screen 1505 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, the display screen 1505 can be one, which is set on the front panel of the terminal; in other embodiments, the display screen 1505 can be at least two, which are respectively set on different surfaces of the terminal or are folded; in other embodiments, the display screen 1505 can be a flexible display screen, which is set on the curved surface or folded surface of the terminal. Even, the display screen 1505 can also be set as a non-rectangular irregular shape, that is, a special-shaped screen. The display screen 1505 can be made of materials such as LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode, organic light-emitting diode).

[0157] The camera assembly 1506 is used to capture images or videos. Optionally, the camera assembly 1506 includes a front camera and a rear camera. Typically, the front camera is disposed on the front panel of the terminal, and the rear camera is disposed on the back of the terminal. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth of field camera, a wide-angle camera, and a telephoto camera, so as to realize the fusion of the main camera and the depth of field camera to realize the background blur function, the fusion of the main camera and the wide-angle camera to realize the panoramic shooting and VR (Virtual Reality) shooting function or other fusion shooting functions. In some embodiments, the camera assembly 1506 may also include a flash. The flash may be a monochrome temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cold light flash, which can be used for light compensation at different color temperatures.

[0158] The audio circuit 1507 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, and convert the sound waves into electrical signals and input them into the processor 1501 for processing, or input them into the RF circuit 1504 to achieve voice communication. For the purpose of stereo acquisition or noise reduction, there may be multiple microphones, which are respectively arranged at different parts of the terminal. The microphone may also be an array microphone or an omnidirectional acquisition microphone. The speaker is used to convert the electrical signal from the processor 1501 or the RF circuit 1504 into sound waves. The speaker may be a traditional film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert the electrical signal into sound waves audible to humans, but also convert the electrical signal into sound waves inaudible to humans for purposes such as ranging. In some embodiments, the audio circuit 1507 may also include a headphone jack.

[0159] The positioning component 1508 is used to locate the current geographical location of the terminal to implement navigation or LBS (Location Based Service).

[0160] The power supply 1509 is used to power various components in the terminal. The power supply 1509 can be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power supply 1509 includes a rechargeable battery, the rechargeable battery can support wired charging or wireless charging. The rechargeable battery can also be used to support fast charging technology.

[0161] In some embodiments, the terminal further includes one or more sensors 1510 , including but not limited to: an acceleration sensor 1511 , a gyroscope sensor 1512 , a pressure sensor 1513 , a fingerprint sensor 1514 , an optical sensor 1515 , and a proximity sensor 1516 .

[0162] The acceleration sensor 1511 can detect the magnitude of acceleration on the three coordinate axes of the coordinate system established by the terminal. For example, the acceleration sensor 1511 can be used to detect the components of gravity acceleration on the three coordinate axes. The processor 1501 can control the display screen 1505 to display the user interface in a horizontal view or a vertical view according to the gravity acceleration signal collected by the acceleration sensor 1511. The acceleration sensor 1511 can also be used for collecting game or user motion data.

[0163] The gyro sensor 1512 can detect the body direction and rotation angle of the terminal, and the gyro sensor 1512 can cooperate with the acceleration sensor 1511 to collect the user's 3D actions on the terminal. The processor 1501 can implement the following functions based on the data collected by the gyro sensor 1512: motion sensing (such as changing the UI according to the user's tilt operation), image stabilization during shooting, game control, and inertial navigation.

[0164] The pressure sensor 1513 can be set in the side frame of the terminal and / or the lower layer of the display screen 1505. When the pressure sensor 1513 is set in the side frame of the terminal, the user's holding signal of the terminal can be detected, and the processor 1501 performs left and right hand recognition or shortcut operation according to the holding signal collected by the pressure sensor 1513. When the pressure sensor 1513 is set in the lower layer of the display screen 1505, the processor 1501 controls the operability controls on the UI interface according to the user's pressure operation on the display screen 1505. The operability controls include at least one of a button control, a scroll bar control, an icon control, and a menu control.

[0165] The fingerprint sensor 1514 is used to collect the user's fingerprint, and the processor 1501 identifies the user's identity based on the fingerprint collected by the fingerprint sensor 1514, or the fingerprint sensor 1514 identifies the user's identity based on the collected fingerprint. When the user's identity is identified as a trusted identity, the processor 1501 authorizes the user to perform relevant sensitive operations, which include unlocking the screen, viewing encrypted information, downloading software, paying, and changing settings. The fingerprint sensor 1514 can be set on the front, back or side of the terminal. When a physical button or manufacturer logo is set on the terminal, the fingerprint sensor 1514 can be integrated with the physical button or manufacturer logo.

[0166] The optical sensor 1515 is used to collect the ambient light intensity. In one embodiment, the processor 1501 can control the display brightness of the display screen 1505 according to the ambient light intensity collected by the optical sensor 1515. Specifically, when the ambient light intensity is high, the display brightness of the display screen 1505 is increased; when the ambient light intensity is low, the display brightness of the display screen 1505 is reduced. In another embodiment, the processor 1501 can also dynamically adjust the shooting parameters of the camera component 1506 according to the ambient light intensity collected by the optical sensor 1515.

[0167] The proximity sensor 1516, also known as a distance sensor, is usually arranged on the front panel of the terminal. The proximity sensor 1516 is used to collect the distance between the user and the front of the terminal. In one embodiment, when the proximity sensor 1516 detects that the distance between the user and the front of the terminal is gradually decreasing, the processor 1501 controls the display screen 1505 to switch from the screen-on state to the screen-off state; when the proximity sensor 1516 detects that the distance between the user and the front of the terminal is gradually increasing, the processor 1501 controls the display screen 1505 to switch from the screen-off state to the screen-on state.

[0168] Those skilled in the art will understand that Fig. 9 The structure shown in the figure does not constitute a limitation on the terminal, and may include more or less components than those shown in the figure, or combine certain components, or adopt a different component arrangement.

[0169] In an exemplary embodiment, a computer device is also provided, the computer device comprising a processor and a memory, wherein at least one computer program is stored in the memory. The at least one computer program is loaded and executed by one or more processors, so that the computer device implements any of the above-mentioned autonomous driving vehicle obstacle avoidance methods.

[0170] In an exemplary embodiment, a computer-readable storage medium is also provided, in which at least one computer program is stored. The at least one computer program is loaded and executed by a processor of a computer device so that the computer implements any of the above-mentioned autonomous driving vehicle obstacle avoidance methods.

[0171] In one possible implementation, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0172] In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs any of the above-mentioned methods for avoiding obstacles in an autonomous driving vehicle.

[0173] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions. For example, the first distance involved in this application is obtained with full authorization.

[0174] It should be understood that the "plurality" mentioned in this article refers to two or more. "And / or" describes the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0175] It should be noted that the terms "first", "second", etc. (if any) in the specification and claims of the present application are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. The implementations described in the above exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0176] The above description is only an exemplary embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. An obstacle avoidance method for an autonomous driving vehicle, characterized in that: The method comprises: Based on the current scene of the autonomous driving vehicle being an obstacle avoidance scene, the obstacle avoidance scene refers to the presence of obstacles in the front area in the target direction when the autonomous driving vehicle is driving in the target direction; Determine a right-of-way result of the autonomous driving vehicle for an adjacent lane, indicate that the autonomous driving vehicle has the right-of-way of the adjacent lane based on the right-of-way result, calculate a first distance between the autonomous driving vehicle and an obstacle behind the autonomous driving vehicle according to a first parameter, the obstacle behind the autonomous driving vehicle and the autonomous driving vehicle are traveling in the target direction, and the obstacle is located behind the autonomous driving vehicle in the target direction; Based on the first distance being smaller than the actual distance, determining that the obstacle avoidance method of the autonomous driving vehicle is to rush over the obstacle behind the autonomous driving vehicle; based on the first distance being larger than the actual distance, determining that the obstacle avoidance method of the autonomous driving vehicle is to yield to the obstacle behind the autonomous driving vehicle, the actual distance being the distance between the autonomous driving vehicle and the obstacle behind the autonomous driving vehicle, the first distance being the distance at which the autonomous driving vehicle brakes at the minimum acceleration, the obstacle behind the autonomous driving vehicle accelerates at the minimum acceleration within the shortest reaction time, and decelerates at the maximum acceleration after the reaction time without collision; Based on the indication from the right of way result that the autonomous driving vehicle does not have the right of way of the adjacent lane, determine whether the obstacle behind the autonomous driving vehicle has the right of way of the adjacent lane; if the obstacle behind the autonomous driving vehicle has the right of way of the adjacent lane, calculate the second distance between the autonomous driving vehicle and the obstacle behind the autonomous driving vehicle according to the second parameter; based on the second distance being less than the actual distance, determine that the obstacle avoidance method of the autonomous driving vehicle is to rush over the obstacle behind the autonomous driving vehicle; based on the second distance being greater than the actual distance, determine that the obstacle avoidance method of the autonomous driving vehicle is to give way to the obstacle behind the autonomous driving vehicle; the second distance is the distance at which the autonomous driving vehicle brakes with the maximum acceleration, the obstacle behind the autonomous driving vehicle accelerates with the maximum acceleration within the longest reaction time, and decelerates with the minimum acceleration after the reaction time without collision; Control the automatic driving vehicle to perform obstacle avoidance driving according to the obstacle avoidance method.

2. The method according to claim 1, characterized in that The determining of the right of way result of the autonomous driving vehicle for the adjacent lane includes: Determining a proportion of adjacent lanes occupied by the automated driving vehicle; Based on the proportion of the adjacent lane occupied by the autonomous driving vehicle, the right of way result of the autonomous driving vehicle for the adjacent lane is determined.

3. The method according to claim 1 or 2, characterized in that: The method further comprises: Based on the right-of-way result indicating that the autonomous driving vehicle does not have the right-of-way of the adjacent lane, and the obstacle also does not have the right-of-way of the adjacent lane, calculating a first distance between the autonomous driving vehicle and the obstacle according to a first parameter; The obstacle avoidance method of the autonomous driving vehicle is determined according to the comparison result between the first distance and the actual distance.

4. The method according to claim 1, characterized in that: The first parameter includes , , , represents the distance traveled within the obstacle reaction time; Indicates the distance traveled after the obstacle reaction time; Indicates the distance traveled by the autonomous driving vehicle; The calculating a first distance between the autonomous driving vehicle and the obstacle according to the first parameter includes: Based on the , , Calculate a first distance between the autonomous driving vehicle and the obstacle according to the following formula; d= Wherein, the d represents the first distance.

5. The method according to claim 4, characterized in that Said ; Among them, the represents the speed of the obstacle; represents the minimum acceleration within the acceleration value range when the obstacle accelerates; and p represents the minimum reaction time within the obstacle reaction time value range after the autonomous driving vehicle brakes.

6. The method according to claim 4, characterized in that Said , ; Among them, the represents the speed of the obstacle; represents the minimum acceleration in the acceleration value range when the obstacle accelerates; p represents the minimum reaction time in the obstacle reaction time value range after the autonomous driving vehicle brakes; represents the maximum acceleration within the acceleration value range when braking after the obstacle reaction time; represents the speed of the autonomous driving vehicle; Indicates the minimum acceleration within the acceleration value range when the autonomous driving vehicle brakes.

7. An obstacle avoidance device for an autonomous driving vehicle, characterized in that: The device comprises: A calculation module is used to determine the right-of-way result of the autonomous driving vehicle for an adjacent lane based on the current scene of the autonomous driving vehicle being an obstacle avoidance scene, where the obstacle avoidance scene refers to the presence of an obstacle in a front area in a target direction during the autonomous driving vehicle's driving in the target direction; calculate a first distance between the autonomous driving vehicle and an obstacle behind the autonomous driving vehicle according to a first parameter based on the right-of-way result indicating that the autonomous driving vehicle has the right of way of the adjacent lane, where the obstacle behind the autonomous driving vehicle is in a state where the autonomous driving vehicle is driving in the target direction and the obstacle is located behind the autonomous driving vehicle in the target direction; a determination module, configured to determine that the obstacle avoidance method of the autonomous driving vehicle is to rush the obstacle behind the autonomous driving vehicle based on the first distance being less than the actual distance; and to determine that the obstacle avoidance method of the autonomous driving vehicle is to yield to the obstacle behind the autonomous driving vehicle based on the first distance being greater than the actual distance, wherein the actual distance is the distance between the autonomous driving vehicle and the obstacle behind the autonomous driving vehicle, and the first distance is the distance at which the autonomous driving vehicle brakes at the minimum acceleration, the obstacle behind the autonomous driving vehicle accelerates at the minimum acceleration within the shortest reaction time, and decelerates at the maximum acceleration after the reaction time without collision; The determination module is further configured to determine whether the obstacle behind the autonomous driving vehicle has the right of way of the adjacent lane based on the right of way result indicating that the autonomous driving vehicle does not have the right of way of the adjacent lane; if the obstacle behind the autonomous driving vehicle has the right of way of the adjacent lane, calculate the second distance between the autonomous driving vehicle and the obstacle behind the autonomous driving vehicle according to the second parameter; based on the second distance being less than the actual distance, determine that the obstacle avoidance method of the autonomous driving vehicle is to rush over the obstacle behind the autonomous driving vehicle; based on the second distance being greater than the actual distance, determine that the obstacle avoidance method of the autonomous driving vehicle is to give way to the obstacle behind the autonomous driving vehicle; the second distance is the distance at which the autonomous driving vehicle brakes at the maximum acceleration, the obstacle behind the autonomous driving vehicle accelerates at the maximum acceleration within the longest reaction time, and decelerates at the minimum acceleration after the reaction time without collision; A control module is used to control the autonomous driving vehicle to perform obstacle avoidance driving according to the obstacle avoidance method.

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