Obstacle avoidance control method, electronic equipment, medium, obstacle avoidance control system and vehicle

Abstract

The invention discloses an obstacle avoidance control method, electronic equipment, a medium, an obstacle avoidance control system and a vehicle, and the method comprises the steps: determining that an obstacle exists in a planned obstacle avoidance range according to the obstacle information; and determining a target obstacle avoidance strategy according to the obstacle type and the obstacle state. According to the method, accurate obstacle avoidance for different obstacle information can be achieved, it is ensured that the vehicle can effectively cope with various complex obstacle conditions, the autonomous obstacle avoidance capacity of the vehicle in the complex environment is enhanced, the collision risk of the vehicle and the obstacles is reduced, and therefore the safety and intelligence of intelligent driving are improved.

Description

Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to an obstacle avoidance control method, electronic equipment, computer-readable storage medium, obstacle avoidance control system, and vehicle. Background Art

[0002] Existing four-wheel steering obstacle avoidance systems generally employ fixed obstacle avoidance strategies, relying primarily on sensing methods such as ultrasonic radar and panoramic imaging to detect obstacles and avoiding them using pre-set paths or fixed steering patterns. However, these obstacle avoidance strategies are often relatively simple and lack the flexibility to respond to obstacles of varying types, states, and locations. The systems struggle to dynamically adjust to actual conditions and are unable to effectively process obstacle information in complex environments, thus failing to fully utilize the vehicle's autonomous obstacle avoidance capabilities. This can result in poor obstacle avoidance effectiveness, increased collision risk, and a failure to provide adequate driver safety in diverse obstacle scenarios. Summary of the Invention

[0003] The present invention aims to address at least one of the technical problems existing in the prior art. To this end, one objective of the present invention is to provide an obstacle avoidance control method that can achieve precise obstacle avoidance based on different obstacle information, ensuring that the vehicle can effectively cope with various complex obstacle situations, enhancing the vehicle's autonomous obstacle avoidance capabilities in complex environments, reducing the risk of collision between the vehicle and obstacles, and thus improving the safety and intelligence of intelligent driving.

[0004] A second object of the present invention is to provide an electronic device.

[0005] A third object of the present invention is to provide a computer-readable storage medium.

[0006] A fourth objective of the present invention is to provide an obstacle avoidance control system.

[0007] A fifth object of the present invention is to provide a vehicle.

[0008] In order to achieve the above-mentioned purpose, the obstacle avoidance control method of the first embodiment of the present invention includes: determining the existence of an obstacle within the planned obstacle avoidance range based on obstacle information; and determining a target obstacle avoidance strategy based on the obstacle type and obstacle status.

[0009] According to the obstacle avoidance control method of an embodiment of the present invention, by collecting obstacle information, determining the existence of obstacles within the planned obstacle avoidance range, and further determining the target obstacle avoidance strategy based on the obstacle type and obstacle state, it is possible to achieve accurate identification and classification of different obstacles. This method dynamically analyzes the specific position, state, and type of the obstacle, combined with the independent drive characteristics of the vehicle's four-wheel motors, can provide a variety of rotation methods, and then formulate flexible and appropriate obstacle avoidance strategies for each obstacle situation, rather than relying on fixed obstacle avoidance paths or steering modes. This enables the vehicle to autonomously judge and adjust the obstacle avoidance plan in real time in complex environments, especially when facing obstacles of various types, states, and dynamic changes, thereby significantly enhancing the vehicle's autonomous obstacle avoidance capabilities in complex environments, reducing collision risks, and ensuring that the vehicle can avoid obstacles more efficiently and safely in different obstacle scenarios. Therefore, the present invention greatly improves the safety and intelligence level of the intelligent driving system through this flexible and accurate obstacle avoidance control method.

[0010] In some embodiments, the planned obstacle avoidance range includes a first predicted obstacle avoidance completion position, and the first predicted obstacle avoidance completion position is determined based on vehicle surrounding environment information, user input information and vehicle characteristic parameters.

[0011] In some embodiments, determining the presence of an obstacle within the planned obstacle avoidance range based on obstacle information includes: the presence of an obstacle within the first predicted obstacle avoidance completion position, wherein the position of the obstacle is determined based on the obstacle information.

[0012] In some embodiments, the target obstacle avoidance strategy is determined based on the obstacle type and the obstacle state, including: when the obstacle type and the obstacle state meet a first rotation condition, the target obstacle avoidance strategy is a first obstacle avoidance route generated based on a crab mode or a lateral rotation mode according to a first preset angle, and the first obstacle avoidance route is from the vehicle's current position to the first predicted obstacle avoidance completion position.

[0013] In some embodiments, the target obstacle avoidance strategy is determined based on the obstacle type and the obstacle state, including: when the obstacle type and the obstacle state meet a first rotation condition, the target obstacle avoidance strategy is a first obstacle avoidance route generated based on a crab mode or a lateral rotation mode according to a first preset angle, and the first obstacle avoidance route is from the vehicle's current position to the first predicted obstacle avoidance completion position.

[0014] In some embodiments, the obstacle avoidance control method further includes: when the obstacle type and the obstacle state do not satisfy the first rotation condition, determining the target obstacle avoidance route according to the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position.

[0015] In some embodiments, the obstacle state includes the size of the obstacle; and the first rotation condition includes that the obstacle type is a stationary obstacle and the size of the obstacle is less than or equal to a first preset size.

[0016] In some embodiments, the target obstacle avoidance strategy is determined based on the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position, including: when the obstacle avoidance space meets the spatial conditions for bypassing the obstacle, the target obstacle avoidance strategy is a second obstacle avoidance route generated based on an infinite rotation mode or a lateral rotation mode according to a second preset angle, and the second obstacle avoidance route is from the vehicle's current position to the second predicted obstacle avoidance completion position.

[0017] In some embodiments, the second predicted obstacle avoidance completion position is determined based on the first predicted obstacle avoidance completion position and the obstacle information, and there is an overlapping area between the second predicted obstacle avoidance completion position and the first obstacle avoidance rotation completion position.

[0018] In some embodiments, the obstacle avoidance control method further includes: when the obstacle avoidance space does not meet the spatial condition for bypassing the obstacle, the target obstacle avoidance strategy is an optimal route from the current position of the vehicle to a third predicted obstacle avoidance completion position.

[0019] In some embodiments, the third predicted obstacle avoidance completion position is a recommended position determined based on the perception map information, and there is no overlapping area between the third predicted obstacle avoidance completion position and the first predicted obstacle avoidance completion position.

[0020] In some embodiments, the obstacle avoidance control method further includes: when it is determined according to the perception map information that the third predicted obstacle avoidance completion position does not exist within the preset obstacle avoidance range, prompting that there is a risk of collision between the obstacle and the vehicle.

[0021] In some embodiments, the obstacle type includes a dynamic obstacle; the obstacle state includes an obstacle motion state; and determining the target obstacle avoidance strategy based on the obstacle type and obstacle state includes: when the obstacle type is the dynamic obstacle and the obstacle motion state satisfies the second rotation condition, the target obstacle avoidance strategy is the optimal route from the vehicle's current position to the first predicted obstacle avoidance completion position.

[0022] In some embodiments, the determining of the target obstacle avoidance strategy based on the obstacle type and obstacle state further includes: when the obstacle type is the dynamic obstacle and the obstacle motion state does not satisfy the second rotation condition, the target obstacle avoidance strategy is the optimal route from the vehicle's current position to the fourth predicted obstacle avoidance completion position.

[0023] In some embodiments, the fourth predicted obstacle avoidance completion position is a recommended position determined based on the perception map information, and there is no overlapping area between the fourth predicted obstacle avoidance completion position and the first predicted obstacle avoidance completion position.

[0024] In some embodiments, the second rotation condition includes an obstacle leaving a spatial range corresponding to the first predicted obstacle avoidance completion position within a first preset time. The obstacle avoidance control method further includes: in response to a user's confirmation instruction regarding the target obstacle avoidance strategy and / or the predicted obstacle avoidance completion position, the vehicle driving based on the target obstacle avoidance strategy.

[0025] In some embodiments, determining the presence of an obstacle within the planned obstacle avoidance range based on the vehicle's surrounding environment information and the obstacle information includes: when the vehicle is traveling according to the target obstacle avoidance route, determining the presence of an obstacle on the vehicle's forward route based on the vehicle's surrounding environment information and the obstacle information and the obstacle is within the vehicle's safe collision range.

[0026] In some embodiments, the obstacle state includes the size of the obstacle; determining the target obstacle avoidance strategy based on the obstacle type and the obstacle state includes: when the obstacle type is a stationary obstacle and the size of the obstacle is smaller than a second preset size, the target obstacle avoidance strategy includes adopting a lateral rotation mode or a crab mode according to a third preset angle to cross the obstacle.

[0027] In some embodiments, determining the target obstacle avoidance strategy based on the obstacle type and the obstacle state also includes: when the obstacle type is the stationary obstacle and the size of the obstacle is greater than or equal to the second preset size and the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position meets the conditions for bypassing the obstacle, the target obstacle avoidance strategy includes adopting an infinite rotation mode or a lateral rotation mode according to a fourth preset angle to bypass the obstacle.

[0028] In some embodiments, the obstacle avoidance control method also includes: issuing a collision risk prompt when the obstacle type is a stationary obstacle and the size of the obstacle is greater than or equal to the second preset size and the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position does not meet the conditions for bypassing the obstacle.

[0029] In some embodiments, the obstacle state includes the running state of the obstacle; determining the target obstacle avoidance strategy based on the obstacle type and the obstacle state includes: when the obstacle type is a dynamic obstacle and the obstacle motion state satisfies the third rotation condition, the target obstacle avoidance strategy is to adopt the original rotation mode on the target obstacle avoidance route; or, when the obstacle type is a dynamic obstacle and the obstacle motion state does not satisfy the third rotation condition, a collision risk prompt is issued.

[0030] In some embodiments, the third rotation condition is that the obstacle leaves the area where the target obstacle avoidance route is located within a second preset time.

[0031] In some embodiments, the obstacle avoidance control method further includes: before determining the target obstacle avoidance strategy according to the obstacle type and obstacle state, determining the vehicle braking deceleration according to the obstacle type and the relative distance between the obstacle and the vehicle to control the vehicle braking.

[0032] In some embodiments, controlling the vehicle braking based on the obstacle type and the relative distance between the obstacle and the vehicle includes: determining that the obstacle type is a stationary obstacle; when the relative distance is greater than a first safety collision threshold, the vehicle braking deceleration is a first deceleration; when the relative distance is less than or equal to the first safety collision threshold, the vehicle braking deceleration is a second deceleration, and the second deceleration is greater than the first deceleration.

[0033] In some embodiments, controlling the vehicle braking according to the obstacle type and the relative distance between the obstacle and the vehicle includes: determining that the obstacle type is a dynamic obstacle; when the relative distance is greater than a second safety collision threshold, the vehicle braking deceleration is a third deceleration; when the relative distance is less than or equal to the second safety collision threshold, the vehicle braking speed is a fourth deceleration, and the fourth deceleration is greater than the third deceleration.

[0034] In order to achieve the above-mentioned purpose, the electronic device of the embodiment of the second aspect of the present invention includes: at least one processor; a memory communicatively connected to the at least one processor; the memory stores a computer program that can be executed by the at least one processor, and when the at least one processor executes the computer program, it implements the obstacle avoidance control method described in the above embodiment.

[0035] In an electronic device according to an embodiment of the present invention, at least one processor executes a computer program that implements the obstacle avoidance control method described in the above embodiment. Based on the vehicle's surrounding environment information and obstacle information, it determines the presence of obstacles within the planned obstacle avoidance range, and further determines a target obstacle avoidance strategy based on the obstacle type and obstacle state, thereby enabling accurate identification and classification of different obstacles. This method dynamically analyzes the specific location, state, and type of obstacles, and combined with the vehicle's four-wheel motor independent drive characteristics, can provide a variety of rotation modes, thereby formulating flexible and appropriate obstacle avoidance strategies for each obstacle situation, rather than relying on fixed obstacle avoidance paths or steering patterns. This enables the vehicle to autonomously determine and adjust obstacle avoidance strategies in real time in complex environments, especially when faced with obstacles of various types, states, and dynamic changes. This significantly enhances the vehicle's autonomous obstacle avoidance capabilities in complex environments, reduces collision risks, and ensures that the vehicle can more efficiently and safely avoid obstacles in different obstacle scenarios. Therefore, through this flexible and accurate obstacle avoidance control method, the present invention significantly improves the safety and intelligence level of intelligent driving systems.

[0036] In order to achieve the above-mentioned purpose, a computer-readable storage medium of an embodiment of the third aspect of the present invention stores a computer program thereon, and when the computer program is executed, the obstacle avoidance control method described in the above embodiment is implemented.

[0037] According to the computer-readable storage medium of an embodiment of the present invention, by adopting the obstacle avoidance control method described in the above embodiment, accurate obstacle avoidance can be achieved for different obstacle information, ensuring that the vehicle can effectively cope with various complex obstacle situations, enhancing the vehicle's autonomous obstacle avoidance capability in complex environments, reducing the risk of collision between the vehicle and obstacles, and thus improving the safety and intelligence of intelligent driving.

[0038] In order to achieve the above-mentioned purpose, an obstacle avoidance control system according to a fourth aspect of an embodiment of the present invention is configured to execute the obstacle avoidance control method described in the above embodiment.

[0039] According to an embodiment of the present invention, the obstacle avoidance control system, by executing the obstacle avoidance control method described in the above embodiment, determines the presence of obstacles within the planned obstacle avoidance range based on the vehicle's surrounding environment information and obstacle information, and further determines the target obstacle avoidance strategy based on the obstacle type and obstacle state, thereby achieving accurate identification and classification of different obstacles. This method dynamically analyzes the specific location, state, and type of the obstacle, combined with the independent drive characteristics of the vehicle's four-wheel motors, to provide a variety of rotation modes, thereby formulating flexible and appropriate obstacle avoidance strategies for each obstacle situation, rather than relying on fixed obstacle avoidance paths or steering modes. This enables the vehicle to autonomously judge and adjust the obstacle avoidance strategy in real time in complex environments, especially when facing obstacles of various types, states, and dynamic changes, thereby significantly enhancing the vehicle's autonomous obstacle avoidance capabilities in complex environments, reducing collision risks, and ensuring that the vehicle can more efficiently and safely avoid obstacles in different obstacle scenarios. Therefore, through this flexible and accurate obstacle avoidance control method, the present invention significantly improves the safety and intelligence level of the intelligent driving system.

[0040] In order to achieve the above-mentioned purpose, the vehicle of the fifth embodiment of the present invention includes the electronic device described in the above embodiment, or the vehicle includes the obstacle avoidance control system described in the above embodiment.

[0041] According to the vehicle of the embodiment of the present invention, by adopting the electronic device described in the above embodiment, or adopting the obstacle avoidance control system described in the above embodiment, based on the vehicle's surrounding environment information and obstacle information, it determines the presence of obstacles within the planned obstacle avoidance range, and further determines the target obstacle avoidance strategy based on the obstacle type and obstacle state, thereby achieving accurate identification and classification of different obstacles. This method dynamically analyzes the specific location, state, and type of the obstacle, combined with the independent drive characteristics of the vehicle's four-wheel motors, can provide a variety of rotation modes, and then formulate flexible and appropriate obstacle avoidance strategies for each obstacle situation, rather than relying on fixed obstacle avoidance paths or steering modes. This enables the vehicle to autonomously judge and adjust the obstacle avoidance plan in real time in complex environments, especially when facing obstacles of various types, states, and dynamic changes, thereby significantly enhancing the vehicle's autonomous obstacle avoidance capabilities in complex environments, reducing collision risks, and ensuring that the vehicle can more efficiently and safely avoid obstacles in different obstacle scenarios. Therefore, the present invention significantly improves the safety and intelligence level of the intelligent driving system through this flexible and accurate obstacle avoidance control method.

[0042] In some embodiments, the vehicle further includes: a sensing device for obtaining vehicle surrounding environment information and obstacle information.

[0043] In some embodiments, the perception device includes: a surround-view camera for collecting information about the vehicle's surrounding environment; and multiple radar devices for collecting information about obstacles.

[0044] In some embodiments, the vehicle further includes an execution device for executing obstacle avoidance operations.

[0045] In some embodiments, the actuator includes at least four motors, a steering device, and a braking device, and the four motors are independently driven.

[0046] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments with reference to the accompanying drawings, in which: Figure 1 is a flow chart of an obstacle avoidance control method according to one embodiment of the present invention; Figure 2 is a schematic diagram of two rotation modes according to an embodiment of the present invention; Figure 3 is a schematic diagram of different obstacle avoidance rotation modes according to one embodiment of the present invention; Figure 4 is a schematic diagram of a side four-wheel steering obstacle avoidance scenario in which there is an obstacle in a parking area or on a parking path according to one embodiment of the present invention; Figure 5 is a schematic diagram of reaching a first predicted obstacle avoidance completion position from a current vehicle position according to one embodiment of the present invention; Figure 6 is a schematic diagram of reaching a second predicted obstacle avoidance completion position from a current vehicle position according to one embodiment of the present invention; Figure 7 is a schematic diagram of reaching a third predicted obstacle avoidance completion position from a current vehicle position according to one embodiment of the present invention; Figure 8 is a flowchart of an obstacle avoidance control method according to one embodiment of the present invention when an obstacle is present at a first predicted obstacle avoidance completion position; Figure 9 is a schematic diagram of an obstacle on an obstacle avoidance route moving from a current position of a vehicle to a first predicted obstacle avoidance completion position according to one embodiment of the present invention; Figure 10 is a schematic diagram of an obstacle on an obstacle avoidance route moving from a current position of a vehicle to a first predicted obstacle avoidance completion position according to one embodiment of the present invention; Figure 11is a schematic diagram showing that the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position does not meet the spatial condition for bypassing the obstacle according to one embodiment of the present invention; Figure 12 is a flowchart of an obstacle avoidance control method according to one embodiment of the present invention when an obstacle exists in a target obstacle avoidance route; Figure 13 is a block diagram of an electronic device according to one embodiment of the present invention; Figure 14 is a block diagram of an obstacle avoidance control system according to one embodiment of the present invention; Figure 15 is a block diagram of a vehicle according to one embodiment of the present invention; Figure 16 is a block diagram of a vehicle according to yet another embodiment of the present invention; Figure 17 The figure is an overall flow chart of a method for controlling vehicle steering and obstacle avoidance according to an embodiment of the present invention.

[0048] Reference numerals: Vehicle 100; Obstacle avoidance control system 1; sensing device 2; execution device 3; Perception module 11; virtual completion state generation module 12; decision module 13; control module 14; communication module 15; surround view camera 21; radar device 22; four motors 31; steering device 32; braking device 33; Ultrasonic radar 211; Laser radar 212; electronic device 110; Processor 111; memory 112. DETAILED DESCRIPTION

[0049] The embodiments of the present invention will be described in detail below. The embodiments described with reference to the accompanying drawings are exemplary. The embodiments of the present invention will be described in detail below.

[0050] Reference below Figures 1-12 An obstacle avoidance control method according to an embodiment of the present invention is described.

[0051] Figure 1 FIG. 1 is a flow chart of an obstacle avoidance control method according to an embodiment of the present invention. Figure 1 As shown, the obstacle avoidance control method of the embodiment of the present invention includes at least steps S1-S2.

[0052] S1, determining whether there is an obstacle within the planned obstacle avoidance range based on the vehicle's surrounding environment information and obstacle information.

[0053] In some embodiments, vehicle surrounding environment information may refer to the geometric and dynamic characteristics of the space surrounding the vehicle. Specifically, this environmental information may include, but is not limited to, road conditions (e.g., whether the road is icy, flooded, or muddy), roadside information (e.g., the shape of the road edge, whether there is a curb or non-lane area, and changes in road width), lane markings, traffic signals, surrounding traffic conditions (e.g., dynamic information about other vehicles), and road characteristics (e.g., road curves and slopes).

[0054] In some embodiments, obstacle information may include but is not limited to: the type of obstacle (such as other vehicles, pedestrians, roadblocks, traffic facilities, etc.), size (length, width, height, etc. of the obstacle), position (the relative position of the obstacle in the vehicle's driving path, and the position in the target parking area), speed, direction, and the relative distance between the obstacle and the vehicle.

[0055] In some embodiments, vehicle surrounding environment information and obstacle information can be obtained in real time through sensing devices such as cameras, ultrasonic radars, and lidars.

[0056] In some embodiments, the planned obstacle avoidance range may refer to an area determined by the vehicle based on the current road environment and obstacle information when making obstacle avoidance decisions. The vehicle will search for potential obstacles in this area and formulate obstacle avoidance strategies. Obstacles within the planned obstacle avoidance range may include obstacles in parking areas that the vehicle may enter, as well as obstacles encountered by the vehicle as it moves along the currently planned route. The purpose of planning the obstacle avoidance range is to guide the vehicle to select a suitable obstacle avoidance path in a complex environment, ensure that the vehicle can make obstacle avoidance decisions within a reasonable range, and avoid deviating from the actual feasible route, thereby effectively improving driving safety.

[0057] S2, determine the target obstacle avoidance strategy according to the obstacle type and obstacle status.

[0058] Specifically, different obstacle avoidance strategies can be employed for different obstacle types and states. By determining the obstacle type and state, and combining them with the independent motor drive characteristics of multiple wheels (for example, three or four wheels), the vehicle can select the optimal rotation method and plan the optimal obstacle avoidance route. This allows the vehicle to dynamically adjust its driving trajectory in complex road environments, effectively avoiding obstacles and minimizing the risk of collision.

[0059] According to the obstacle avoidance control method of an embodiment of the present invention, by collecting information about the vehicle's surrounding environment and obstacle information, determining the presence of obstacles within the planned obstacle avoidance range, and further determining the target obstacle avoidance strategy based on the obstacle type and obstacle state, it is possible to accurately identify and classify different obstacles. This method dynamically analyzes the specific location, state, and type of the obstacle, combined with the independent drive characteristics of the vehicle's four-wheel motors, can provide a variety of rotation modes, and then formulate flexible and appropriate obstacle avoidance strategies for each obstacle situation, rather than relying on fixed obstacle avoidance paths or steering modes. This enables the vehicle to autonomously judge and adjust the obstacle avoidance plan in real time in complex environments, especially when facing obstacles of various types, states, and dynamic changes, thereby significantly enhancing the vehicle's autonomous obstacle avoidance capabilities in complex environments, reducing collision risks, and ensuring that the vehicle can avoid obstacles more efficiently and safely in different obstacle scenarios. Therefore, the present invention significantly improves the safety and intelligence level of the intelligent driving system through this flexible and accurate obstacle avoidance control method.

[0060] In some embodiments, the planned obstacle avoidance range includes a first predicted obstacle avoidance completion position, and the first predicted obstacle avoidance completion position is determined based on surrounding environment information, user input information, and vehicle characteristic parameters.

[0061] The first predicted obstacle avoidance completion position can be understood as the target parking position predicted for the vehicle, assuming there are sufficient space and no obstacles, based on ambient information, user input, and vehicle characteristics. Specifically, the first predicted obstacle avoidance completion position represents the target position the user expects the vehicle to safely reach, assuming no obstacles interfere with the vehicle's avoidance process. This position can be depicted by the initial virtual rotation completion state displayed by the vehicle's UI (User Interface) system.

[0062] In some embodiments, the virtual rotation completion state is similar to the final vehicle shape during parking. During parking, the vehicle can adjust its body angle by rotating or reversing to complete the parking task. The virtual rotation completion state is a similar concept, referring to the final vehicle shape when the vehicle arrives at a certain area. Specifically, on the UI (user interface), based on surrounding environmental information, user input information, and vehicle characteristic parameters, the user interface displays the specific position and angle of the vehicle when it arrives at the designated area by virtually displaying the rotated vehicle model shape.

[0063] In some embodiments, the user input information may include the rotation mode, rotation angle, and rotation direction set by the user. Figure 2As shown, the rotation methods can include rotation around a single wheel and rotation around the center of mass. Rotation around a single wheel can refer to the vehicle rotating around a certain wheel. This method is suitable for situations where small adjustments to the path are required. Rotation around the center of mass can refer to the vehicle rotating around its own center of mass, which allows the vehicle to make large adjustments in a small space. Rotation around the center of mass is suitable for larger obstacles or situations where a wider area needs to be avoided. These two rotation methods have no angle restrictions and can be flexibly set according to actual needs. The rotation direction is only available in two options: clockwise and counterclockwise. This input method based on user-defined rotation method, rotation angle and rotation direction enhances user participation.

[0064] In some embodiments, a variety of different obstacle avoidance rotation modes can be generated by different combinations of user-set rotation modes (i.e., rotation around a single wheel and rotation around the center of mass), rotation angles, rotation directions, and rotation torques of the four wheels. Figure 3 As shown, the obstacle avoidance rotation modes may include but are not limited to: crab mode, lateral rotation mode, infinite rotation mode, etc. These obstacle avoidance rotation modes can be adjusted in real time by the vehicle control system, combined with the characteristics of the four-wheel independent motors, to flexibly adapt to various obstacles and environmental changes. For example, Figure 4 As shown, in the side four-wheel steering obstacle avoidance scenario where there are obstacles in the parking area or on the parking path, the obstacles can be avoided through the lateral rotation mode or the infinite rotation mode to successfully park in the parking area.

[0065] In some embodiments, as Figure 3 As shown, crab mode can mean that all four wheels of the vehicle rotate in the same diagonal direction at the same time, so that the vehicle can move in space in a diagonal manner, rather than along the traditional front-to-back axis. Specifically, in crab mode, the angles of the four wheels are the same, but the vehicle does not move in the traditional forward direction, but moves in an oblique direction (such as the northeast direction). The key to this mode is that the four wheels are pushed in the diagonal direction at the same angle and at the same speed, thereby achieving lateral or diagonal translational movement to avoid obstacles in front or behind. For example, if the vehicle is currently facing an obstacle and the lane width is limited, using crab mode allows the vehicle to avoid collision with the obstacle by moving diagonally without changing the direction of the front of the vehicle.

[0066] In some embodiments, as Figure 3As shown, in lateral rotation mode, the front and rear wheels of the vehicle have different steering angles, allowing them to face different directions, thus achieving lateral translation. For example, if the front wheels turn northeast and the rear wheels turn southeast, the vehicle will exhibit lateral translation. This mode is ideal for scenarios where high-precision obstacle avoidance is required in confined spaces, allowing precise avoidance without changing the vehicle's forward direction.

[0067] In some embodiments, as Figure 3 As shown, the infinite rotation mode is a flexible obstacle avoidance method. The vehicle can still move forward or backward simultaneously during the rotation process, allowing the vehicle to avoid obstacles more quickly and flexibly. In infinite rotation mode, the vehicle's rotation angle and movement direction are continuous and flexible, and it can move forward and backward while rotating. In infinite rotation mode, the difference in power output direction and force of different wheels can achieve simultaneous rotation and longitudinal (fore-and-aft) displacement. For example, the left front wheel and left rear wheel turn forward, and the right front wheel and right rear wheel turn backward. The vehicle will move towards the target direction during the rotation. The characteristic of this mode is that it can achieve rotation and translation at the same time.

[0068] In some embodiments, vehicle characteristic parameters may include, but are not limited to, vehicle dimensions (such as vehicle length and width, and vehicle diagonal length), track width, wheelbase, turning radius, chassis height, etc. These vehicle characteristic parameters play an important role in constructing the first predicted obstacle avoidance completion position.

[0069] In some embodiments, determining that there is an obstacle within the planned obstacle avoidance range based on surrounding environment information and obstacle information includes: there is an obstacle within the first predicted obstacle avoidance completion position, wherein the position of the obstacle is determined based on the obstacle information.

[0070] In some embodiments, the system can identify and locate obstacles using point cloud data from lidar, image data from cameras, or distance data from ultrasonic radar. Using the data collected by these sensors, the system can calculate the obstacle's position, distance, and coordinates in space in real time.

[0071] In some embodiments, the presence of an obstacle in the first predicted obstacle avoidance completion position can be understood as an obstacle in the initial virtual rotation completion state displayed on the user interface, that is, there is an obstacle in the target parking area of the vehicle. Based on the obstacle type, position and obstacle state, combined with vehicle characteristic parameters (such as vehicle chassis space information, etc.), the system can determine whether there will be a risk of scratching the chassis or collision between the vehicle and the obstacle when avoiding the obstacle according to the rotation method, rotation angle and rotation direction set by the user, so as to further plan whether to avoid the obstacle or detour. If there is a risk of scratching or collision, it is necessary to combine the independent drive characteristics of the four-wheel motors to provide a variety of rotation methods and re-plan the optimal obstacle avoidance route to adjust the initial virtual rotation completion state. If there is no risk of scratching or collision, the system can continue to move along the original obstacle avoidance path to safely reach the first predicted obstacle avoidance completion position. Depending on the situation of the obstacle in the initial virtual rotation completion state, the system can output different obstacle avoidance strategies. Finally, the best virtual completion state information is highlighted to the user through the user interface (UI). The best virtual completion state information has the following four states: First, the completion state information after the rotation fully meets the user's expectations, that is, there is no obstacle, or there is no risk of collision with the obstacle, or the obstacle can be bypassed through the combined rotation of the four-wheel drive motor.

[0072] Second, the completion state information after the rotation partially meets the user's expectations. That is, there is an obstacle with a collision risk and it cannot be circumvented, but there is sufficient space in the immediate surroundings. The system starts reconstruction and outputs new completion state information that overlaps with the user's expected completion state (the initial virtual rotation completion state).

[0073] Third, the system-recommended completion state after rotation, that is, there is an obstacle with a collision risk that cannot be circumvented, and there is insufficient space in the near periphery, but sufficient space in the far periphery. The system starts reconstruction and outputs the system-recommended completion state information that has no overlapping area with the user's expected completion state (initial virtual rotation completion state).

[0074] Fourth, there is no completion state information, that is, there is an obstacle with a collision risk that cannot be circumvented, and there is no available space within the perception range. The system outputs a no completion state information and prompts the user "Collision risk, unable to complete the rotation."

[0075] Reference below Figure 5-Figure 12 The four states described in the above embodiment are described in detail.

[0076] In some embodiments, a target obstacle avoidance strategy is determined based on the obstacle type and obstacle state, including: when the obstacle type and obstacle state meet the first rotation condition, the target obstacle avoidance strategy is a first obstacle avoidance route generated based on a crab mode or a lateral rotation mode according to a first preset angle, and the first obstacle avoidance route is from the vehicle's current position to a first predicted obstacle avoidance completion position.

[0077] In some embodiments, obstacle types may include stationary obstacles and dynamic obstacles. Stationary obstacles may be fixed in position, have no tendency to move, and do not change over time. Examples include roadblocks, traffic cones, trash cans, rocks, parked vehicles, or any stationary object at the first predicted obstacle avoidance completion location. Dynamic obstacles, on the other hand, are objects that have a tendency to move and whose position changes over time. Examples include pedestrians, cyclists, moving vehicles, and animals.

[0078] In some embodiments, the obstacle status includes the obstacle's dimensions, which can include both its length and height. The obstacle's length describes the obstacle's size in the vehicle's direction of travel, useful for determining whether the vehicle can circumvent the obstacle. The obstacle's height describes the obstacle's vertical dimension, useful for determining whether the vehicle can circumvent the obstacle by climbing over it.

[0079] In some embodiments, the first rotation condition includes that the obstacle type is a stationary obstacle and the size of the obstacle is less than or equal to a first preset size. The first preset size may include a preset length L1, which defines the size limit of the obstacle in the direction of travel. The first preset size may also include a preset height H1, which defines the size limit of the obstacle in the vertical direction. When the length of the obstacle is less than or equal to the preset length L1, and the height of the obstacle is less than or equal to the preset height H1, as Figure 5 As shown, according to the size of the obstacle, the vehicle's surrounding environment information and the rotation mode, and using common path planning algorithms (such as A Algorithm, D Algorithms (e.g., Dijkstra's algorithm) can generate a first obstacle avoidance route. Because the obstacle is sufficiently small in length and height, the vehicle can avoid collisions or scratches by circumventing it along the first obstacle avoidance route using a crab crawl pattern or a lateral rotation pattern at a first preset angle. This allows the vehicle to safely reach the first predicted obstacle avoidance completion position from its current position. At this point, the user interface (UI) can display the first obstacle avoidance route and the first predicted obstacle avoidance completion position (i.e., the initial virtual rotation completion state).

[0080] In some embodiments, the first preset angle can be set based on factors such as the size of the obstacle, the current speed of the vehicle, the road width, the relative position of the obstacle and the vehicle, the obstacle avoidance space, the size of the vehicle, and the lateral movement capability.

[0081] In some embodiments, the obstacle avoidance control method further includes: when the obstacle type and the obstacle state do not satisfy the first rotation condition, determining a target obstacle avoidance route according to the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position.

[0082] Specifically, if the obstacle type is not a stationary obstacle and the obstacle's size is greater than a first preset size (i.e., the obstacle's length is greater than the preset length L1, or the obstacle's height is greater than the preset length H1), there is a risk of chassis scraping or collision between the obstacle and the vehicle. In this case, the system needs to determine the size of the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position and determine the target obstacle avoidance route based on the size of the obstacle avoidance space. The obstacle avoidance space refers to the area within which the vehicle can move during obstacle avoidance and can be determined based on information about the surrounding environment and the obstacle.

[0083] In some embodiments, the system uses sensory data (such as lidar, cameras, and ultrasonic radar) to perceive the surrounding environment in real time. Based on this sensory data, it calculates a feasible path between the vehicle's current position and the target location and defines an obstacle avoidance volume. The obstacle avoidance volume is a three-dimensional area that can take into account the size of the vehicle, the size of the obstacle, and the distance between them.

[0084] In some embodiments, a target obstacle avoidance strategy is determined based on the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position, including: when the obstacle avoidance space meets the spatial conditions for bypassing obstacles, the target obstacle avoidance strategy is a second obstacle avoidance route generated based on an infinite rotation mode or a lateral rotation mode according to a second preset angle, and the second obstacle avoidance route is from the current position of the vehicle to the second predicted obstacle avoidance completion position.

[0085] Specifically, if Figure 6 As shown in Figure 2, when the obstacle avoidance space meets the spatial conditions for bypassing obstacles, the obstacle avoidance algorithm is used according to the size of the obstacle, the vehicle's surrounding environment information and the rotation mode, and the commonly used path planning algorithm (such as A Algorithm, D Algorithms (e.g., Dijkstra's algorithm) can generate a second obstacle avoidance route. Although the obstacle is long or tall, posing a risk of chassis scraping or collision with the vehicle, the sufficient obstacle avoidance space allows the vehicle to circumvent the obstacle along the second obstacle avoidance route by using a continuous rotation mode or a lateral rotation mode at a second preset angle, avoiding collision or scraping. This allows the vehicle to safely reach the second predicted obstacle avoidance completion position from its current position. At this point, the user interface (UI) can display the second obstacle avoidance route and the second predicted obstacle avoidance completion position (i.e., the new virtual rotation completion state).

[0086] In some embodiments, the second preset angle can be set based on factors such as the size of the obstacle, the current speed of the vehicle, the road width, the relative position of the obstacle and the vehicle, the obstacle avoidance space, the size of the vehicle, and the lateral movement capability.

[0087] In some embodiments, the second predicted obstacle avoidance completion position is determined based on the first predicted obstacle avoidance completion position and obstacle information, such as Figure 6 As shown, the second predicted obstacle avoidance completion position overlaps with the first obstacle avoidance rotation completion position. This means that to avoid collision with the obstacle, the obstacle avoidance route is dynamically adjusted to the second obstacle avoidance route. Ultimately, the vehicle arrives at a location adjacent to the user's desired parking area, with some overlap between the two areas, thus maximally meeting the user's parking needs.

[0088] In some embodiments, the size of the overlap region can be adjusted based on multiple factors, including the size and position of the obstacle, the size of the vehicle, the available avoidance space, and real-time changes in the environment during the avoidance process. The overlap region can be rectangular, circular, elliptical, or other complex geometric shapes to accommodate different obstacle avoidance scenarios and path planning requirements.

[0089] In some embodiments, the obstacle avoidance control method further includes: when the obstacle avoidance space does not meet the spatial conditions for bypassing the obstacle, the target obstacle avoidance strategy is the optimal route from the current position of the vehicle to the third predicted obstacle avoidance completion position.

[0090] Specifically, when the obstacle type is a stationary obstacle and the size of the obstacle is greater than the first preset size, that is, the length of the obstacle is greater than the preset length L1, or the height of the obstacle is greater than the preset length H1, there is a risk of chassis scratches or collision between the obstacle and the vehicle. At this time, the system needs to determine the size of the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position. If the obstacle avoidance space does not meet the spatial conditions for bypassing the obstacle, that is, the obstacle avoidance space is too small and there is not enough obstacle avoidance space near the obstacle, the original target obstacle avoidance strategy will be adjusted, that is, according to the current obstacle avoidance space conditions and obstacle information, combined with the diverse rotation methods provided by the four-wheel motors, using the path planning algorithm (such as A , Dijkstra algorithm, etc.) to calculate a new obstacle avoidance route, which is the optimal route from the vehicle's current position to the third predicted obstacle avoidance completion position. The user interface (UI) can then display the optimal route and the third predicted obstacle avoidance completion position (i.e., the new virtual rotation completion state).

[0091] The optimal route is the one that balances vehicle speed, path safety, and accuracy, given the current obstacle avoidance space and obstacle distribution. This can be the most efficient obstacle avoidance path in the shortest possible time, or it can be a path that can be executed within a larger space to ensure safety and effectiveness during obstacle avoidance.

[0092] In some embodiments, the third predicted obstacle avoidance completion position is a recommended position determined based on the perception map information, and the third predicted obstacle avoidance completion position does not overlap with the first predicted obstacle avoidance completion position. The perception map information can be real-time data collected by vehicle sensors (such as lidar, ultrasonic radar, and cameras), processed to generate map information. This information may include road geometry, the specific location of obstacles, and dynamic changes in the surrounding environment. Perception maps help improve path planning accuracy, especially in complex or dynamic environments.

[0093] In some embodiments, the recommended position is a more suitable obstacle avoidance completion position recommended by the system based on factors such as perceived map information, current obstacle avoidance space, vehicle characteristic parameters, obstacle size and position, etc. The recommended position can be one or more, and there is no specific limitation here.

[0094] In some embodiments, the third predicted obstacle avoidance completion location does not overlap with the first predicted obstacle avoidance completion location. This means that the third predicted obstacle avoidance completion location and the first predicted obstacle avoidance completion location do not intersect. This is because the obstacle avoidance space at the first predicted obstacle avoidance completion location does not meet the spatial requirements for bypassing the obstacle, and the user's initially desired parking area does not meet the vehicle's parking requirements. Therefore, the system recommends a third predicted obstacle avoidance completion location that is farther away from the first predicted obstacle avoidance completion location to ensure safe parking.

[0095] For example, if Figure 7 As shown, there are other vehicles parked in front and behind the first predicted obstacle avoidance completion position, and there is a large obstacle in the first predicted obstacle avoidance completion position. At this time, the obstacle avoidance space does not meet the spatial conditions for bypassing the obstacle. That is to say, when the vehicle enters the first predicted obstacle avoidance completion position through the diverse rotation methods provided by the four-wheel motors, it will scratch and collide with the obstacle. Moreover, since there are other vehicles parked in front and behind the first predicted obstacle avoidance completion position, the system can recommend nearby empty parking spaces or spacious areas of other vehicles as the third predicted obstacle avoidance completion position based on factors such as the perceived map information, the current obstacle avoidance space, vehicle characteristic parameters, and the size and position of the obstacle.

[0096] In some embodiments, the obstacle avoidance control method further includes: when it is determined based on the perception map information that there is no third predicted obstacle avoidance completion position within the preset obstacle avoidance range, prompting that there is a risk of collision between the obstacle and the vehicle.

[0097] Specifically, if the data in the perception map indicates that the third predicted obstacle avoidance completion position cannot be found within the preset obstacle avoidance range, the system will prompt the driver or control system that there is a collision risk. This prompt can be issued through the vehicle display, sound alarm, vibration feedback, etc., reminding the user or the autonomous driving system to take the next step. The prompt content may include "Unable to circumvent the obstacle" or "There is a collision risk, please take over", ensuring that the driver can take other necessary measures in a timely manner.

[0098] In some embodiments, obstacle types also include dynamic obstacles, which may include, but are not limited to, other moving vehicles, pedestrians, bicycles, and animals. The obstacle state includes the obstacle's motion state, which refers to the obstacle's current dynamic behavior characteristics, including but not limited to its speed, direction, distance, acceleration, and other dynamic characteristics. By monitoring these characteristics, the system can determine the obstacle's behavior pattern in real time and optimize the obstacle avoidance strategy.

[0099] In some embodiments, a target obstacle avoidance strategy is determined based on the obstacle type and obstacle state, including: when the obstacle type is a dynamic obstacle and the obstacle motion state satisfies a second rotation condition, the target obstacle avoidance strategy is the optimal route from the vehicle's current position to the first predicted obstacle avoidance completion position.

[0100] Among them, the second rotation condition includes the obstacle leaving the spatial range corresponding to the first predicted obstacle avoidance completion position within the first preset time. The spatial range can be an area surrounding the first predicted obstacle avoidance completion position. This area can be a rectangle, circle or other shape, which is used to define whether the obstacle is located in the area, and then determine whether it is necessary to avoid or take other measures. If the obstacle is within the range, the vehicle needs to avoid collision with the obstacle. If the obstacle leaves the range, it means that the vehicle can continue to travel along the optimal route from the current position of the vehicle to the first predicted obstacle avoidance completion position.

[0101] In some embodiments, the first preset time may be the time range used to determine whether an obstacle has left the spatial range corresponding to the first predicted obstacle avoidance completion position. If the obstacle leaves this area within this time range, the second rotation condition is met, meaning the vehicle can continue along the originally planned route without adjusting the obstacle avoidance path. The first preset time can be set based on the actual environment and obstacle avoidance requirements and is not specifically limited here.

[0102] Specifically, when the obstacle type is a dynamic obstacle and the obstacle leaves the spatial range corresponding to the first predicted obstacle avoidance completion position within the first preset time, the path planning algorithm (such as A , Dijkstra algorithm, etc.) to calculate an optimal route from the vehicle's current position to the first predicted obstacle avoidance completion position. At this point, the user interface (UI) can display the optimal route and the first predicted obstacle avoidance completion position (i.e., the initial virtual rotation completion state).

[0103] In some embodiments, determining the target obstacle avoidance strategy based on the obstacle type and obstacle state also includes: when the obstacle type is a dynamic obstacle and the obstacle motion state does not meet the second rotation condition, the target obstacle avoidance strategy is the optimal route from the vehicle's current position to the fourth predicted obstacle avoidance completion position.

[0104] Specifically, if the obstacle type is a dynamic obstacle and the obstacle fails to leave the spatial range corresponding to the first predicted obstacle avoidance completion position within the first preset time, the system will abandon the optimal route from the vehicle's current position to the first predicted obstacle avoidance completion position for safety reasons due to the large activity area of the dynamic obstacle. In this case, the target obstacle avoidance strategy with insufficient obstacle avoidance space can be adopted, that is, based on the current obstacle avoidance space conditions and obstacle information, combined with the diverse rotation modes provided by the four-wheel motors, using a path planning algorithm (such as A , Dijkstra algorithm, etc.) to recalculate a new obstacle avoidance route, which is the optimal route from the vehicle's current position to the fourth predicted obstacle avoidance completion position. The user interface (UI) may then display the optimal route and the fourth predicted obstacle avoidance completion position (i.e., the adjusted new virtual rotation completion state).

[0105] In some embodiments, the fourth predicted obstacle avoidance completion position is a recommended position determined based on the perception map information, and there is no overlap between the fourth predicted obstacle avoidance completion position and the first predicted obstacle avoidance completion position. This means that the fourth predicted obstacle avoidance completion position does not intersect with the first predicted obstacle avoidance completion position, meaning that there is no guarantee that the vehicle can safely enter the user's originally desired parking area (i.e., the first predicted obstacle avoidance completion position) or its immediate surroundings. Therefore, the system recommends a fourth predicted obstacle avoidance completion position that is farther from the first predicted obstacle avoidance completion position to ensure safe parking and avoid collisions or scrapes.

[0106] In some embodiments, the obstacle avoidance control method further includes: in response to a user confirmation instruction regarding the target obstacle avoidance strategy and / or predicted obstacle avoidance completion position, the vehicle driving according to the target obstacle avoidance strategy. The user confirmation instruction may be a confirmation signal sent by the driver or in-vehicle user to the system through some interactive method (e.g., a touch screen, voice command, button, etc.), indicating the user's agreement or confirmation of the system's automatically generated target obstacle avoidance strategy and / or predicted obstacle avoidance completion position. This confirmation instruction serves to inform the system that the user agrees and authorizes the vehicle to perform obstacle avoidance operations according to a specific obstacle avoidance strategy, ensuring that the user has ultimate control over the obstacle avoidance process.

[0107] For example, by setting a "Confirm" button in the user interface (UI), the UI highlights the final obstacle avoidance route and the vehicle's rotation method (which can be presented through animation effects). In this interface, the vehicle's final virtual rotation state is also highlighted. After the user clicks the "Confirm" button, the system can take over the vehicle's lateral, longitudinal, and steering control, accurately controlling the vehicle to move along the planned obstacle avoidance route using the specified rotation method until the vehicle completely overlaps with the final virtual rotation state. Upon completion, the system can provide feedback to the user through the UI, indicating that the obstacle avoidance operation has been successfully completed.

[0108] Figure 8 FIG. 1 is a flow chart of an obstacle avoidance control method according to an embodiment of the present invention in which an obstacle is present at a first predicted obstacle avoidance completion position. Figure 8 As shown, the process of the obstacle avoidance control method in which an obstacle exists at the first predicted obstacle avoidance completion position according to the embodiment of the present invention at least includes steps S10 to S40.

[0109] S10, the user arbitrarily sets the rotation mode, rotation angle and rotation direction.

[0110] S11 , determining a first predicted obstacle avoidance completion position based on surrounding environment information, user input information, and vehicle characteristic parameters, that is, constructing an initial virtual rotation completion state.

[0111] S12, performing path planning based on the vehicle's surrounding environment information and the coordinate information of the virtual rotation completion state in combination with the set rotation method.

[0112] S13: Determine whether an obstacle exists in the first predicted obstacle avoidance completion position based on the vehicle surrounding environment information and the obstacle information.

[0113] S20: Determine that the obstacle type is a stationary obstacle.

[0114] S21, when the size of the obstacle is less than or equal to the first preset size, a first obstacle avoidance route is generated according to the crab crawl mode or the lateral rotation mode according to the first preset angle, combined with the path planning algorithm. The first obstacle avoidance route is from the current position of the vehicle to the first predicted obstacle avoidance completion position.

[0115] S22 , a user interface (UI) may prompt a first obstacle avoidance route and a first predicted obstacle avoidance completion position.

[0116] S23, when the size of the obstacle is larger than the first preset size and the obstacle avoidance space meets the spatial conditions for bypassing the obstacle, a second obstacle avoidance route is generated according to the infinite rotation mode or the lateral rotation mode according to the second preset angle, combined with the path planning algorithm. The second obstacle avoidance route is from the current position of the vehicle to the second predicted obstacle avoidance completion position.

[0117] S24 , the user interface (UI) may prompt a second obstacle avoidance route and a second predicted obstacle avoidance completion position.

[0118] S25, when the size of the obstacle is larger than the first preset size and the obstacle avoidance space does not meet the spatial conditions for bypassing the obstacle, based on the diverse rotation modes provided by the four-wheel motors and combined with the path planning algorithm, an optimal route is generated from the vehicle's current position to the third predicted obstacle avoidance completion position determined by the perception map information.

[0119] S26 , a user interface (UI) may prompt the optimal route and the third predicted obstacle avoidance completion position.

[0120] S27: When it is determined based on the perception map information that the third predicted obstacle avoidance completion position does not exist within the preset obstacle avoidance range, a prompt is given that there is a collision risk between the obstacle and the vehicle.

[0121] S30: Determine that the obstacle type is a dynamic obstacle.

[0122] S31, when the obstacle leaves the spatial range corresponding to the first predicted obstacle avoidance completion position within the first preset time, based on the diverse rotation modes provided by the four-wheel motors and combined with the path planning algorithm, an optimal route from the vehicle's current position to the first predicted obstacle avoidance completion position is generated.

[0123] S32: A user interface (UI) may prompt the optimal route and the first predicted obstacle avoidance completion position.

[0124] S33: When the obstacle fails to leave the spatial range corresponding to the first predicted obstacle avoidance completion position within the first preset time, a new obstacle avoidance route is recalculated based on the diverse rotation modes provided by the four-wheel motors and the path planning algorithm. This route is the optimal route from the vehicle's current position to the fourth predicted obstacle avoidance completion position determined by the perception map information.

[0125] S34 , a user interface (UI) may prompt the optimal route and the fourth predicted obstacle avoidance completion position.

[0126] S40 , in response to a user's confirmation instruction regarding the target obstacle avoidance strategy and / or the predicted obstacle avoidance completion position, the vehicle drives based on the target obstacle avoidance strategy.

[0127] In general, when it is determined that there is an obstacle within the first predicted obstacle avoidance completion position, based on the obstacle type and obstacle state, combined with the vehicle's four-wheel motor independent drive characteristics, a variety of rotation methods can be provided, and then a flexible and appropriate obstacle avoidance strategy can be formulated for each obstacle situation, rather than relying on a fixed obstacle avoidance path or steering mode. This enables the vehicle to independently judge and adjust the obstacle avoidance plan in complex environments, especially when facing obstacles of various types, states and dynamic changes, thereby significantly enhancing the vehicle's autonomous obstacle avoidance capabilities in complex environments and reducing the risk of collision.

[0128] In some embodiments, determining whether there is an obstacle within the planned obstacle avoidance range is based on the vehicle's surrounding environment information and obstacle information, including: when the vehicle is traveling according to the target obstacle avoidance route, determining whether there is an obstacle on the vehicle's forward route and that the obstacle is within the vehicle's safe collision range based on the vehicle's surrounding environment information and obstacle information.

[0129] Specifically, in response to the user's confirmation of the target obstacle avoidance strategy and / or the predicted obstacle avoidance completion position, the system controls the vehicle along a predetermined trajectory while acquiring real-time information about the vehicle's position and surrounding environment via onboard sensors. If an obstacle is detected within the vehicle's forward path and within the vehicle's safe collision range, the system determines whether there is a risk of collision with the chassis or collision with the obstacle based on the obstacle's type, location, and positional relationship with the vehicle, combined with vehicle parameters such as chassis spatial information. This determines whether the vehicle will avoid the obstacle or adopt a detour strategy. If there is a risk of collision or collision, the system utilizes the independent drive characteristics of the four-wheel motors to provide a variety of rotation methods and replans the optimal obstacle avoidance route. If there is no risk of collision or collision, the system can continue along the original obstacle avoidance route. Therefore, based on the position of the obstacle within the vehicle's forward path, the system predicts the risk of collision with the vehicle in real time, enabling the implementation of different obstacle avoidance strategies.

[0130] In some embodiments, the obstacle state includes the size of the obstacle, and determining the target obstacle avoidance strategy based on the obstacle type and the obstacle state includes: when the obstacle type is a stationary obstacle and the size of the obstacle is smaller than a second preset size, the target obstacle avoidance strategy includes adopting a lateral rotation mode or a crab mode according to a third preset angle to cross the obstacle.

[0131] Specifically, the second preset size may include a preset length L2, which is used to define the size limit of the obstacle in the driving direction. The second preset size may also include a preset height H2, which is used to define the size limit of the obstacle in the vertical direction. When the length of the obstacle is less than or equal to the preset length L2, and the height of the obstacle is less than or equal to the preset height H2, as Figure 9As shown, according to the size of the obstacle, the vehicle's surrounding environment information and the rotation mode, and using common path planning algorithms (such as A Algorithm, D Algorithms (such as the Dijkstra algorithm) can generate an optimal obstacle avoidance route. Because obstacles are small in length and height, there's no risk of collision, but no risk of scratches. Crab mode or a lateral rotation mode at a third preset angle can be used to traverse obstacles along the optimal obstacle avoidance route, avoiding collisions or scratches.

[0132] In some embodiments, the third preset angle can be set based on factors such as the size of the obstacle, the current speed of the vehicle, the road width, the relative position of the obstacle and the vehicle, the obstacle avoidance space, the size of the vehicle, and the lateral movement capability.

[0133] In some embodiments, determining the target obstacle avoidance strategy based on the obstacle type and obstacle state also includes: when the obstacle type is a stationary obstacle and the size of the obstacle is greater than or equal to a second preset size and the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position meets the conditions for bypassing the obstacle, the target obstacle avoidance strategy includes adopting an infinite rotation mode or a lateral rotation mode according to a fourth preset angle to bypass the obstacle.

[0134] Specifically, if Figure 10 As shown, when the obstacle type is a stationary obstacle and the size of the obstacle is greater than or equal to the second preset size and the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position meets the conditions for bypassing the obstacle, according to the size of the obstacle, the vehicle's surrounding environment information and the rotation mode, and using a common path planning algorithm (such as A Algorithm, D Algorithms (e.g., Dijkstra's algorithm) can generate an optimal obstacle avoidance route. Although the obstacle is long and tall, posing a risk of chassis scraping or collision with the vehicle, the sufficient obstacle avoidance space allows the vehicle to circumvent the obstacle by using either the infinite rotation mode or the lateral rotation mode at a fourth preset angle along the second obstacle avoidance route, avoiding collision or scraping.

[0135] In some embodiments, the fourth preset angle can be set based on factors such as the size of the obstacle, the current speed of the vehicle, the road width, the relative position of the obstacle and the vehicle, the obstacle avoidance space, the size of the vehicle, and the lateral movement capability.

[0136] In some embodiments, the obstacle avoidance control method further includes: issuing a collision risk prompt when the obstacle type is a stationary obstacle and the size of the obstacle is greater than or equal to a second preset size and the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position does not meet the conditions for bypassing the obstacle.

[0137] Specifically, if the obstacle type is stationary and its size is greater than or equal to a second preset size (i.e., the obstacle's length is greater than the preset length L2, or the obstacle's height is greater than the preset length H2), there is a risk of chassis scratches or collision between the obstacle and the vehicle. At this point, the system needs to determine the size of the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position. If the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position does not meet the conditions for bypassing the obstacle, that is, the obstacle avoidance space is too small and the vehicle cannot bypass the obstacle, the system prompts "Unable to bypass obstacle" or "Collision risk, please take over", and the VOT (Vehicle Origin Turn) function will exit.

[0138] For example, if Figure 11 As shown in the figure, there are other vehicles parked in front of and behind the first predicted obstacle avoidance completion position, and there is a large obstacle on the route from the vehicle's current position to the first predicted obstacle avoidance completion position. At this time, the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position does not meet the spatial conditions for bypassing the obstacle. In other words, although the vehicle can use the various rotation methods of the four-wheel motors to advance toward the first predicted obstacle avoidance completion position, it still cannot avoid the obstacles on the forward route. In this case, the vehicle will scrape or collide with the obstacle. Therefore, based on this analysis result, the system can issue a collision risk warning to prompt the driver to intervene manually.

[0139] In some embodiments, the obstacle state includes the running state of the obstacle. Determining the target obstacle avoidance strategy based on the obstacle type and the obstacle state includes: when the obstacle type is a dynamic obstacle and the obstacle motion state satisfies a third rotation condition, the target obstacle avoidance strategy is to adopt an existing rotation mode on the target obstacle avoidance route.

[0140] Among them, the third rotation condition is that the obstacle leaves the area where the target obstacle avoidance route is located within the second preset time. The first preset time may refer to the time range based on which to judge whether the obstacle has left the area where the target obstacle avoidance route is located. Within this time range, if the obstacle leaves this area, the third rotation condition is met, which means that the vehicle can continue to drive along the originally planned target obstacle avoidance route using the original rotation mode until the vehicle completely coincides with the preset virtual rotation completion state, that is, the vehicle reaches the first predicted obstacle avoidance completion position from the current vehicle position. After arriving, the system can provide feedback to the user through the UI, indicating that the obstacle avoidance operation has been successfully completed.

[0141] In some embodiments, when the obstacle type is a dynamic obstacle and the obstacle motion state does not satisfy the third rotation condition, a collision risk prompt is performed.

[0142] Specifically, when the obstacle type is a dynamic obstacle and the obstacle fails to leave the area where the target obstacle avoidance route is located within the second preset time, due to the large activity area of the dynamic obstacle, for safety reasons, the system will abandon the original rotation mode and abandon the optimal route from the vehicle's current position to the first predicted obstacle avoidance completion position. The vehicle will not be able to bypass the obstacle. Therefore, the system will prompt "Unable to bypass the obstacle" or "There is a risk of collision, please take over", and the VOT (Vehicle Origin Turn) function will exit.

[0143] In some embodiments, the obstacle avoidance control method further includes: determining the vehicle's braking deceleration based on the obstacle type and its state, in order to control vehicle braking, before determining the target obstacle avoidance strategy based on the obstacle type and state. Precisely controlling the braking deceleration can help the vehicle safely stop in the shortest possible time and distance in emergency situations (e.g., when the relative distance between the vehicle and the obstacle is small), thereby effectively avoiding collision with the obstacle. Furthermore, in non-emergency situations (e.g., when the relative distance between the vehicle and the obstacle is large), the system can rationally control the braking deceleration to bring the vehicle to a slow stop, avoiding unnecessary drastic deceleration or excessive braking, thereby improving ride comfort while ensuring smooth and safe braking.

[0144] In some embodiments, controlling the vehicle to stop based on the obstacle type and the relative distance between the obstacle and the vehicle includes: determining that the obstacle type is a stationary obstacle, and when the relative distance is greater than a first collision safety threshold, braking the vehicle to a first deceleration; and when the relative distance is less than or equal to the first collision safety threshold, braking the vehicle to a second deceleration, the second deceleration being greater than the first deceleration.

[0145] Specifically, when the relative distance between the static obstacle and the vehicle is greater than the first collision safety threshold, the obstacle is relatively far away, providing ample time and distance for the vehicle to decelerate smoothly. The system deems the collision risk level to be moderate and sets the vehicle's braking deceleration to the first (slower) deceleration. This means a comfortable braking is achieved using a slower deceleration to ensure smooth driving and avoid the discomfort caused by unnecessary sudden braking. When the relative distance between the static obstacle and the vehicle is less than or equal to the first collision safety threshold, the obstacle is relatively close, and the system deems the collision risk level to be high, necessitating an emergency braking stop to prevent a collision. Therefore, the system sets the vehicle's braking deceleration to the second (higher) deceleration for faster deceleration and stopping, prioritizing the safety of the vehicle and its occupants and preventing a collision.

[0146] In some embodiments, the first safety collision threshold is a key parameter used to determine whether the vehicle enters an emergency braking state. The first safety collision threshold can be set based on the vehicle's speed, road conditions, braking performance, vehicle load, etc. The first deceleration is used for smooth braking in non-emergency situations. The first deceleration can be set based on ride comfort, current vehicle speed, braking performance, vehicle load, etc. The second deceleration is used to decelerate as quickly as possible in an emergency situation. The second deceleration can be set based on road conditions, current vehicle speed, maximum braking system performance, vehicle load, etc., without specific limitations herein.

[0147] In some embodiments, controlling the vehicle to stop based on the obstacle type and the relative distance between the obstacle and the vehicle includes: determining that the obstacle type is a dynamic obstacle, and when the relative distance is greater than a second collision safety threshold, braking the vehicle to a third deceleration; and when the relative distance is less than or equal to the second collision safety threshold, braking the vehicle to a fourth deceleration, the fourth deceleration being greater than the third deceleration.

[0148] Specifically, when the relative distance between the dynamic obstacle and the vehicle is greater than the second collision safety threshold, the dynamic obstacle is relatively far away, allowing the vehicle sufficient time and distance to decelerate smoothly. At this point, the system deems the collision risk level to be moderate and sets the vehicle's braking deceleration rate to the third (slower) deceleration rate. This means a slower deceleration rate is used for comfortable braking, ensuring a smooth ride and avoiding the discomfort caused by unnecessary sudden braking. When the relative distance between the dynamic obstacle and the vehicle is less than or equal to the first collision safety threshold, the dynamic obstacle is relatively close, and the system deems the collision risk level to be high, requiring emergency braking to prevent a collision. Therefore, the system sets the vehicle's braking deceleration rate to the fourth (higher) deceleration rate for faster deceleration and stopping, prioritizing the safety of the vehicle and its occupants and preventing a collision.

[0149] In some embodiments, the second safety collision threshold is also a key parameter used to determine whether the vehicle enters an emergency braking state. The second safety collision threshold can be set based on the vehicle's speed, road conditions, braking performance, vehicle load, etc. The third deceleration is used for smooth braking in non-emergency situations and can be set based on ride comfort, current vehicle speed, braking performance, vehicle load, etc. The fourth deceleration is used to decelerate as quickly as possible in an emergency situation and can be set based on road conditions, current vehicle speed, maximum braking system performance, vehicle load, etc., without specific limitations herein.

[0150] Figure 12 FIG. 1 is a flow chart of an obstacle avoidance control method according to an embodiment of the present invention when an obstacle exists in a target obstacle avoidance route. Figure 12As shown, the process of the obstacle avoidance control method when an obstacle exists in a target obstacle avoidance route according to the embodiment of the present invention at least includes steps S100 to S312.

[0151] S100: The vehicle drives along a target obstacle avoidance route.

[0152] S101 , determining, based on vehicle surrounding environment information and obstacle information, that an obstacle exists on a target obstacle avoidance route and that the obstacle is within a safe collision range of the vehicle.

[0153] S200: Determine that the obstacle type is a stationary obstacle.

[0154] S201: When the relative distance is greater than a first safety collision threshold, the vehicle braking deceleration is a first deceleration.

[0155] S202: When the relative distance is less than or equal to the first safety collision threshold, the vehicle braking deceleration is a second deceleration.

[0156] S210: When the size of the stationary obstacle is smaller than a second preset size, it is determined that there is no risk of scratching the vehicle chassis.

[0157] S211: adopting a lateral rotation mode or a crab crawl mode according to a third preset angle to cross a stationary obstacle.

[0158] S220: When the size of the stationary obstacle is greater than or equal to the second preset size, determine whether the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position satisfies a condition for bypassing the obstacle.

[0159] S221: Use the infinite rotation mode or the lateral rotation mode according to the fourth preset angle to bypass the obstacle.

[0160] S230: When the size of the stationary obstacle is greater than or equal to the second preset size, it is determined that the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position does not meet the condition for bypassing the obstacle.

[0161] S231, prompts "Unable to bypass obstacle" or "Risk of collision, please take over".

[0162] S300: Determine that the obstacle type is a dynamic obstacle.

[0163] S301: When the relative distance is greater than the second safety collision threshold, the vehicle braking deceleration is a third deceleration.

[0164] S302: Determine whether the obstacle's motion state satisfies a third rotation condition, where the third rotation condition is that the obstacle leaves the area where the target obstacle avoidance route is located within a second preset time.

[0165] S303: The target obstacle avoidance strategy is to adopt the original rotation mode on the target obstacle avoidance route.

[0166] S310: When the relative distance is less than or equal to the second safety collision threshold, the vehicle braking speed is a fourth deceleration.

[0167] S311, determining that the obstacle fails to leave the area where the target obstacle avoidance route is located within a second preset time.

[0168] S312, prompts "Unable to bypass obstacle" or "Risk of collision, please take over".

[0169] In general, when an obstacle is determined to be on the target avoidance route, or within the first predicted avoidance completion position, the vehicle's four-wheel motors independently drive the vehicle, providing a variety of rotation methods based on the obstacle type and state. This allows for a flexible and appropriate avoidance strategy to be developed for each obstacle situation, rather than relying on a fixed avoidance path or steering pattern. Furthermore, emergency and slow braking methods are provided based on the obstacle type and the relative distance between the obstacle and the vehicle, and the target avoidance route is replanned, maximizing the effectiveness of intelligent driving.

[0170] Reference below Figure 13 An electronic device according to an embodiment of the present invention is described.

[0171] Figure 13 is a block diagram of an electronic device according to an embodiment of the present invention, such as Figure 13 As shown, the electronic device according to the embodiment of the present invention includes at least one processor and a memory.

[0172] In some embodiments, the at least one processor may be a single processor, or may be multiple processors, such as two, three, or five processors. The processor may be a single-core or multi-core processor responsible for executing the obstacle avoidance control method stored in the memory. The processor may be a central processing unit (CPU), graphics processing unit (GPU), or digital signal processor (DSP) in the electronic device, etc. The specific configuration depends on the design and application of the electronic device.

[0173] In some embodiments, a memory is a device used to store data and programs, and can be a random access memory (RAM), read-only memory (ROM), flash memory, or other storage medium. It is communicatively connected to at least one processor to provide computing programs and store runtime data.

[0174] In some embodiments, a computer program executable by at least one processor is stored in the memory, and when the at least one processor executes the computer program, the obstacle avoidance control method described in the above embodiment is implemented.

[0175] In an electronic device according to an embodiment of the present invention, at least one processor executes a computer program that implements the obstacle avoidance control method described in the above embodiment. Based on the vehicle's surrounding environment information and obstacle information, it determines the presence of obstacles within the planned obstacle avoidance range, and further determines a target obstacle avoidance strategy based on the obstacle type and obstacle state, thereby enabling accurate identification and classification of different obstacles. This method dynamically analyzes the specific location, state, and type of obstacles, and combined with the vehicle's four-wheel motor independent drive characteristics, can provide a variety of rotation modes, thereby formulating flexible and appropriate obstacle avoidance strategies for each obstacle situation, rather than relying on fixed obstacle avoidance paths or steering patterns. This enables the vehicle to autonomously determine and adjust obstacle avoidance strategies in real time in complex environments, especially when faced with obstacles of various types, states, and dynamic changes. This significantly enhances the vehicle's autonomous obstacle avoidance capabilities in complex environments, reduces collision risks, and ensures that the vehicle can more efficiently and safely avoid obstacles in different obstacle scenarios. Therefore, through this flexible and accurate obstacle avoidance control method, the present invention significantly improves the safety and intelligence level of intelligent driving systems.

[0176] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed, the obstacle avoidance control method described in the above embodiment is implemented.

[0177] The computer-readable storage medium of the embodiments of the present invention may include, but is not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which are not listed here one by one.

[0178] According to the computer-readable storage medium of an embodiment of the present invention, by adopting the obstacle avoidance control method described in the above embodiment, accurate obstacle avoidance can be achieved for different obstacle information, ensuring that the vehicle can effectively cope with various complex obstacle situations, enhancing the vehicle's autonomous obstacle avoidance capability in complex environments, reducing the risk of collision between the vehicle and obstacles, and thus improving the safety and intelligence of intelligent driving.

[0179] Reference below Figure 14 An obstacle avoidance control system according to an embodiment of the present invention is described.

[0180] Figure 14is a block diagram of an obstacle avoidance control system according to an embodiment of the present invention, as shown in FIG. Figure 14 As shown, the obstacle avoidance control system includes: a perception module, a virtual completion state generation module, a decision module, a control module and a communication module.

[0181] In some embodiments, the perception module is connected to the virtual completion state generation module and the decision module respectively, and is used to receive the vehicle surrounding environment information and obstacle information detected in real time by perception devices such as cameras, ultrasonic radars, and lidars, and transmit the acquired data to the virtual completion state generation module and the decision module.

[0182] In some embodiments, the virtual completion state generation module is connected to the decision module to receive the vehicle surrounding environment information and obstacle information transmitted by the perception module, combine the user input information and vehicle characteristic parameters, construct the initial virtual rotation completion state, and transmit the coordinate information of the completion state to the decision module to provide a reference for obstacle avoidance route planning.

[0183] In some embodiments, the decision module is used to receive information data transmitted by the perception module and the completion state coordinate information transmitted by the virtual completion state generation module to perform obstacle avoidance route planning and formulate obstacle avoidance strategies, determine the optimal obstacle avoidance route and the best rotation method, thereby ensuring that the vehicle can safely avoid obstacles.

[0184] In some embodiments, the control module is connected to the decision module and is used to control the vehicle to perform automatic driving and obstacle avoidance operations according to the obstacle avoidance instructions generated by the decision module.

[0185] In some embodiments, the communication module is used to enable data interaction between the obstacle avoidance control system and other vehicles or infrastructure, ensuring information sharing and collaborative work during the rotational obstacle avoidance process, thereby improving the accuracy and safety of obstacle avoidance decisions.

[0186] In some embodiments, the obstacle avoidance control system is used to execute the obstacle avoidance control method described in the above embodiments.

[0187] According to an embodiment of the present invention, the obstacle avoidance control system, by executing the obstacle avoidance control method described in the above embodiment, determines the presence of obstacles within the planned obstacle avoidance range based on the vehicle's surrounding environment information and obstacle information, and further determines the target obstacle avoidance strategy based on the obstacle type and obstacle state, thereby achieving accurate identification and classification of different obstacles. This method dynamically analyzes the specific location, state, and type of the obstacle, combined with the independent drive characteristics of the vehicle's four-wheel motors, to provide a variety of rotation modes, thereby formulating flexible and appropriate obstacle avoidance strategies for each obstacle situation, rather than relying on fixed obstacle avoidance paths or steering modes. This enables the vehicle to autonomously judge and adjust the obstacle avoidance strategy in real time in complex environments, especially when facing obstacles of various types, states, and dynamic changes, thereby significantly enhancing the vehicle's autonomous obstacle avoidance capabilities in complex environments, reducing collision risks, and ensuring that the vehicle can more efficiently and safely avoid obstacles in different obstacle scenarios. Therefore, through this flexible and accurate obstacle avoidance control method, the present invention significantly improves the safety and intelligence level of the intelligent driving system.

[0188] Reference below Figure 15 and Figure 16 A vehicle according to an embodiment of the present invention is described.

[0189] Figure 15 is a block diagram of a vehicle according to one embodiment of the present invention, as shown Figure 15 As shown, the vehicle includes the electronic device described in the above embodiments.

[0190] Figure 16 is a block diagram of a vehicle according to yet another embodiment of the present invention, Figure 16 As shown, the vehicle includes the obstacle avoidance control system described in the above embodiment.

[0191] According to the vehicle of the embodiment of the present invention, by adopting the electronic device described in the above embodiment, or adopting the obstacle avoidance control system described in the above embodiment, based on the vehicle's surrounding environment information and obstacle information, it determines the presence of obstacles within the planned obstacle avoidance range, and further determines the target obstacle avoidance strategy based on the obstacle type and obstacle state, thereby achieving accurate identification and classification of different obstacles. This method dynamically analyzes the specific location, state, and type of the obstacle, combined with the independent drive characteristics of the vehicle's four-wheel motors, can provide a variety of rotation modes, and then formulate flexible and appropriate obstacle avoidance strategies for each obstacle situation, rather than relying on fixed obstacle avoidance paths or steering modes. This enables the vehicle to autonomously judge and adjust the obstacle avoidance plan in real time in complex environments, especially when facing obstacles of various types, states, and dynamic changes, thereby significantly enhancing the vehicle's autonomous obstacle avoidance capabilities in complex environments, reducing collision risks, and ensuring that the vehicle can more efficiently and safely avoid obstacles in different obstacle scenarios. Therefore, the present invention significantly improves the safety and intelligence level of the intelligent driving system through this flexible and accurate obstacle avoidance control method.

[0192] In some embodiments, as Figure 16 As shown, the vehicle further includes a sensing device, which can be used to obtain vehicle surrounding environment information and obstacle information.

[0193] In some embodiments, the vehicle surrounding environment information may include, but is not limited to: road conditions, curb information, lane markings, traffic signals, surrounding traffic conditions, and road condition characteristics.

[0194] In some embodiments, the obstacle information may include, but is not limited to: the type, size, position, speed, direction of the obstacle, and the relative distance between the obstacle and the vehicle.

[0195] In some embodiments, the perception device includes a surround-view camera and multiple radar devices. The surround-view cameras can be fisheye cameras, each of which can be installed at different locations on the vehicle (e.g., front, rear, left, or right). These cameras are used to obtain information about the vehicle's surroundings and obstacles, enabling comprehensive environmental detection and obstacle recognition. Each fisheye camera has an ultra-wide-angle 190° field of view, covering a full 360° range around the vehicle, making it suitable for panoramic perception and obstacle detection.

[0196] In some embodiments, multiple radar devices are used to collect obstacle information. These multiple radar devices may include ultrasonic radar and lidar. Ultrasonic radar operates by emitting high-frequency ultrasonic waves. When the ultrasonic waves hit an obstacle, they are reflected back. The sensor calculates the distance to the obstacle based on the time difference between the reflected waves and the obstacle.

[0197] In some embodiments, the number of ultrasonic radars may be multiple, for example, 12, and the installation locations of the 12 ultrasonic radars may be the front and rear bumpers or the front and rear wheel arches of the vehicle.

[0198] In some embodiments, one or more LiDAR sensors can be configured, depending on the specific vehicle configuration. LiDAR sensors can be mounted on the roof or bumper for precise long-range sensing. LiDAR sensors emit high-precision laser beams and measure the return time or phase difference to calculate the distance to obstacles. LiDAR sensors offer higher accuracy, faster response times, and longer detection ranges.

[0199] In some embodiments, as Figure 16 As shown, the vehicle also includes an actuator for executing obstacle avoidance maneuvers. Specifically, the control module in the obstacle avoidance control system can send control instructions to the actuator based on the obstacle avoidance instructions generated by the decision module. After receiving the instructions, the actuator performs the corresponding steering and braking operations to ensure accurate execution of the obstacle avoidance maneuver.

[0200] In some embodiments, the actuator includes at least four motors, a steering device, and a braking device. The four motors are independently driven, enabling more flexible power distribution and improving the vehicle's dynamic control capabilities. Specifically, each wheel is driven by a separate motor, enabling independent control of forward, reverse, acceleration, and deceleration, resulting in superior vehicle posture adjustment capabilities and a faster, more extreme rotation experience through various rotation combinations.

[0201] In some embodiments, the steering device may include a steering wheel for adjusting the vehicle's direction of travel to accommodate different obstacle avoidance requirements. The braking device may include a throttle and brakes for providing necessary acceleration, deceleration, or parking functions during obstacle avoidance to improve safety.

[0202] Figure 17 FIG. 1 is an overall flow chart of a method for controlling a vehicle to avoid obstacles while turning according to an embodiment of the present invention. Figure 17 As shown, the overall process of the vehicle steering obstacle avoidance control method includes at least steps S400-S403.

[0203] At S400, the user enters the VOT function interface and selects the rotation fulcrum, which can be the center of mass or located on a certain tire. The user determines the required rotation angle and direction by sliding or manually inputting, thus achieving user-customized VOT rotation.

[0204] S401, the obstacle avoidance control system constructs an initial virtual rotation completion state based on the vehicle's surrounding environment information and user input information in combination with vehicle characteristic parameters.

[0205] In step S402, the possibility and risk of a collision caused by the VOT rotation are determined based on the initial virtual rotation completion state information, combined with the obstacle information and vehicle surrounding environment information output by the perception module. The virtual rotation completion state is adjusted in a timely manner according to the obstacle type, and the user is informed through the HMI (Human Machine Interface).

[0206] S403, after the user confirms the final virtual rotation completion state, the control module controls the torque of the four wheels according to the planning results to achieve crab walking, lateral movement or infinite rotation operations. When the vehicle coincides with the final virtual rotation completion state, the rotation is completed and the user is informed.

[0207] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "illustrative embodiments," "example," "specific example," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example.

[0208] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the claims and their equivalents.

Claims

1. An obstacle avoidance control method, characterized in that: include: Determine the existence of obstacles within the planned obstacle avoidance range based on obstacle information; Determine the target obstacle avoidance strategy based on obstacle type and obstacle status.

2. The obstacle avoidance control method according to claim 1, characterized in that: The planned obstacle avoidance range includes a first predicted obstacle avoidance completion position, which is determined based on vehicle surrounding environment information, user input information, and vehicle characteristic parameters.

3. The obstacle avoidance control method according to claim 2, characterized in that: The determining that there is an obstacle within the planned obstacle avoidance range based on the obstacle information includes: there is an obstacle within the first predicted obstacle avoidance completion position, wherein the position of the obstacle is determined based on the obstacle information.

4. The obstacle avoidance control method according to claim 3, characterized in that: The target obstacle avoidance strategy is determined according to the obstacle type and obstacle state, including: When the obstacle type and the obstacle state meet the first rotation condition, the target obstacle avoidance strategy is a first obstacle avoidance route generated based on a crab mode or a lateral rotation mode according to a first preset angle, and the first obstacle avoidance route is a path from the vehicle's current position to the first predicted obstacle avoidance completion position.

5. The obstacle avoidance control method according to claim 4, characterized in that: The obstacle avoidance control method further includes: When the obstacle type and the obstacle state do not satisfy the first rotation condition, the target obstacle avoidance route is determined according to the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position.

6. The obstacle avoidance control method according to claim 4 or 5, characterized in that: The obstacle state includes the size of the obstacle; The first rotation condition includes that the obstacle type is a stationary obstacle and the size of the obstacle is less than or equal to a first preset size.

7. The obstacle avoidance control method according to claim 5, characterized in that: The determining the target obstacle avoidance strategy according to the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position includes: When the obstacle avoidance space meets the spatial conditions for bypassing the obstacle, the target obstacle avoidance strategy is a second obstacle avoidance route generated based on an infinite rotation mode or a lateral rotation mode according to a second preset angle, and the second obstacle avoidance route is a path from the current position of the vehicle to the second predicted obstacle avoidance completion position.

8. The obstacle avoidance control method according to claim 7, characterized in that: The second predicted obstacle avoidance completion position is determined based on the first predicted obstacle avoidance completion position and the obstacle information, and there is an overlapping area between the second predicted obstacle avoidance completion position and the first obstacle avoidance rotation completion position.

9. The obstacle avoidance control method according to claim 7, characterized in that: The obstacle avoidance control method further includes: When the obstacle avoidance space does not satisfy the spatial condition for bypassing the obstacle, the target obstacle avoidance strategy is an optimal route from the current position of the vehicle to a third predicted obstacle avoidance completion position.

10. The obstacle avoidance control method according to claim 9, characterized in that: The third predicted obstacle avoidance completion position is a recommended position determined based on the perception map information, and there is no overlapping area between the third predicted obstacle avoidance completion position and the first predicted obstacle avoidance completion position.

11. The obstacle avoidance control method according to claim 9, characterized in that: The obstacle avoidance control method further includes: When it is determined according to the perception map information that the third predicted obstacle avoidance completion position does not exist within the preset obstacle avoidance range, a prompt is given that there is a collision risk between the obstacle and the vehicle.

12. The obstacle avoidance control method according to claim 3, characterized in that: The obstacle types include dynamic obstacles; The obstacle state includes the obstacle motion state; The target obstacle avoidance strategy is determined according to the obstacle type and obstacle state, including: When the obstacle type is the dynamic obstacle and the obstacle motion state satisfies the second rotation condition, the target obstacle avoidance strategy is an optimal route from the current position of the vehicle to the first predicted obstacle avoidance completion position.

13. The obstacle avoidance control method according to claim 12, characterized in that: The method of determining the target obstacle avoidance strategy according to the obstacle type and obstacle state further includes: When the obstacle type is the dynamic obstacle and the obstacle motion state does not satisfy the second rotation condition, the target obstacle avoidance strategy is an optimal route from the current position of the vehicle to a fourth predicted obstacle avoidance completion position.

14. The obstacle avoidance control method according to claim 13, characterized in that: The fourth predicted obstacle avoidance completion position is a recommended position determined based on the perception map information, and there is no overlapping area between the fourth predicted obstacle avoidance completion position and the first predicted obstacle avoidance completion position.

15. The obstacle avoidance control method according to claim 12 or 13, characterized in that: The second rotation condition includes that the obstacle leaves the spatial range corresponding to the first predicted obstacle avoidance completion position within a first preset time.

16. The obstacle avoidance control method according to claim 9 or 13, characterized in that: The obstacle avoidance control method further includes: In response to a user's confirmation instruction regarding a target obstacle avoidance strategy and / or a predicted obstacle avoidance completion position, the vehicle travels based on the target obstacle avoidance strategy.

17. The obstacle avoidance control method according to any one of claims 2-5 or 7-14, characterized in that: The determining of the presence of an obstacle within the planned obstacle avoidance range based on the vehicle's surrounding environment information and obstacle information includes: When the vehicle travels along a target obstacle avoidance route, it is determined based on the vehicle surrounding environment information and the obstacle information that an obstacle exists on the vehicle's forward route and that the obstacle is within a safe collision range of the vehicle.

18. The obstacle avoidance control method according to claim 17, characterized in that: The obstacle state includes the size of the obstacle; Determining a target obstacle avoidance strategy according to the obstacle type and the obstacle state includes: When the obstacle type is a stationary obstacle and the size of the obstacle is smaller than a second preset size, the target obstacle avoidance strategy includes adopting a lateral rotation mode or a crab crawl mode according to a third preset angle to cross the obstacle.

19. The obstacle avoidance control method according to claim 18, characterized in that: Determining a target obstacle avoidance strategy according to the obstacle type and the obstacle state further includes: When the obstacle type is the stationary obstacle and the size of the obstacle is greater than or equal to the second preset size and the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position meets the conditions for bypassing the obstacle, the target obstacle avoidance strategy includes adopting an infinite rotation mode or a lateral rotation mode according to a fourth preset angle to bypass the obstacle.

20. The obstacle avoidance control method according to claim 19, characterized in that: The obstacle avoidance control method further includes: When the obstacle type is a stationary obstacle and the size of the obstacle is greater than or equal to the second preset size and the obstacle avoidance space corresponding to the first predicted obstacle avoidance completion position does not meet the conditions for bypassing the obstacle, a collision risk prompt is issued.

21. The obstacle avoidance control method according to claim 17, characterized in that: The obstacle state includes the operating state of the obstacle; The determining of the target obstacle avoidance strategy according to the obstacle type and the obstacle state includes: When the obstacle type is a dynamic obstacle and the obstacle motion state satisfies the third rotation condition, the target obstacle avoidance strategy is to adopt the original rotation mode on the target obstacle avoidance route; Alternatively, when the obstacle type is a dynamic obstacle and the obstacle motion state does not satisfy the third rotation condition, a collision risk prompt is issued.

22. The obstacle avoidance control method according to claim 21, characterized in that: The third rotation condition is that the obstacle leaves the area where the target obstacle avoidance route is located within a second preset time.

23. The obstacle avoidance control method according to claim 17, characterized in that: The obstacle avoidance control method further includes: Before determining the target obstacle avoidance strategy according to the obstacle type and obstacle state, the vehicle braking deceleration is determined according to the obstacle type and the relative distance between the obstacle and the vehicle to control the vehicle to brake.

24. The obstacle avoidance control method according to claim 23, characterized in that: The controlling the vehicle to stop according to the obstacle type and the relative distance between the obstacle and the vehicle includes: Determining that the obstacle type is a stationary obstacle; When the relative distance is greater than a first safety collision threshold, the vehicle braking deceleration is a first deceleration; When the relative distance is less than or equal to the first safety collision threshold, the vehicle braking deceleration is a second deceleration, and the second deceleration is greater than the first deceleration.

25. The obstacle avoidance control method according to claim 23, characterized in that: The controlling the vehicle to stop according to the obstacle type and the relative distance between the obstacle and the vehicle includes: Determining that the obstacle type is a dynamic obstacle; When the relative distance is greater than a second safety collision threshold, the vehicle braking deceleration is a third deceleration; When the relative distance is less than or equal to the second safety collision threshold, the vehicle braking speed is a fourth deceleration, and the fourth deceleration is greater than the third deceleration.

26. An electronic device, characterized in that: include: at least one processor; a memory communicatively coupled to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, and when the at least one processor executes the computer program, the obstacle avoidance control method according to any one of claims 1 to 25 is implemented.

27. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, the obstacle avoidance control method according to any one of claims 1 to 25 is implemented.

28. An obstacle avoidance control system, characterized in that: The obstacle avoidance control system is used to execute the obstacle avoidance control method described in any one of claims 1-25.

29. A vehicle, characterized in that: The vehicle includes the electronic device according to claim 27, or the vehicle includes the obstacle avoidance control system according to claim 28.

30. The vehicle according to claim 29, characterized in that The vehicle further comprises: The sensing device is used to obtain information about the vehicle's surrounding environment and obstacles.

31. The vehicle according to claim 30, characterized in that The sensing device comprises: A surround-view camera, used to collect information about the vehicle's surroundings; Multiple radar devices are used to collect the obstacle information.

32. The vehicle of claim 29, wherein: The vehicle further includes an execution device, which is used to execute obstacle avoidance operation.

33. The vehicle according to claim 32, characterized in that The execution device comprises at least four motors, a steering device and a braking device, and the four motors are independently driven.

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