Offset control method and device of vehicle, vehicle and storage medium

Abstract

This application relates to a vehicle offset control method, apparatus, vehicle, and storage medium. The method includes: in autonomous driving mode, acquiring information about at least one target obstacle in at least one direction of the vehicle; acquiring the vehicle's current driving state, and combining the current driving state with the information of each target obstacle to determine the relative motion trend between each target obstacle and the vehicle; generating an optimal offset planning strategy for the vehicle based on the relative motion trend, so as to control the vehicle to perform offset actions based on the optimal offset planning strategy. Embodiments of this application can generate an optimal offset planning strategy for the vehicle based on the relative motion trend between each target obstacle and the vehicle, so as to control the vehicle to avoid obstacles on both sides of the road in advance during driving.

Description

Technical Field

[0001] This application relates to the field of intelligent driving technology for vehicles, and in particular to a vehicle offset control method, device, vehicle, and storage medium. Background Technology

[0002] During vehicle operation, traffic accidents can easily occur when adjacent lanes have vehicles driving over the lane lines, overtaking, or approaching the vehicle, or when there are obstacles or pedestrians on either side of the vehicle, due to factors such as inertia.

[0003] In related technologies, the collision time between a vehicle traveling in an adjacent lane and the vehicle itself can be detected, and the vehicle can be controlled to deviate laterally, thereby avoiding traffic accidents caused by excessively close proximity.

[0004] However, in actual driving, the relevant technology faces diverse road conditions and various types of obstacles encountered by vehicles. Relying solely on the time of collision while ignoring other physical laws makes it difficult to address potential safety hazards during vehicle operation, and thus requires improvement. Summary of the Invention

[0005] This application provides a vehicle offset control method, device, vehicle, and storage medium to solve the technical problem in related technologies that rely solely on judging the collision time while ignoring other physical laws, making it difficult to address safety hazards that may exist during vehicle operation.

[0006] The first aspect of this application provides a vehicle offset control method, comprising the following steps: in an autonomous driving mode, acquiring information on at least one target obstacle in at least one direction of the vehicle; acquiring the current driving state of the vehicle, and combining the current driving state with the information on each target obstacle to determine the relative motion trend between each target obstacle and the vehicle; and generating an optimal offset planning strategy for the vehicle based on the relative motion trend, so as to control the vehicle to perform an offset action based on the optimal offset planning strategy.

[0007] Based on the above technical means, the embodiments of this application can generate the best offset planning strategy for the vehicle based on the relative motion trend between each target obstacle and the vehicle, so as to control the vehicle to avoid obstacles on both sides of the road in advance during driving.

[0008] Optionally, in one embodiment of this application, obtaining information on at least one target obstacle in at least one direction of the vehicle includes: simultaneously acquiring radar data of at least one perceived target in at least one direction of the vehicle and environmental image data in at least one direction of the vehicle; fusing the information data and the environmental image data to obtain fused data of the perceived target, and determining whether the perceived target meets a preset target obstacle determination condition based on the fused data; if the perceived target meets the preset target obstacle determination condition, locking the perceived target as a target obstacle, and obtaining the target obstacle information based on the fused data.

[0009] Based on the above technical means, the embodiments of this application can determine whether the perceived target is a target obstacle by fusing data, and obtain target obstacle information based on the fusing data, thereby facilitating more targeted offset planning for different target obstacles.

[0010] Optionally, in one embodiment of this application, before generating the optimal offset planning strategy for the vehicle based on the relative motion trend, the method further includes: determining the distribution of each of the target obstacles based on the target obstacle information, so as to generate the optimal offset planning strategy for the vehicle based on the distribution and the relative motion trend.

[0011] Based on the above-mentioned technical means, the embodiments of this application can determine the optimal offset planning strategy based on the distribution and relative motion trend of each target obstacle.

[0012] Optionally, in one embodiment of this application, when the distribution is on one side, generating the optimal offset planning strategy for the vehicle based on the relative motion trend includes: determining the type of the target obstacle based on the relative motion trend; if the target obstacle type is static, controlling the vehicle to laterally offset a first preset offset distance to the side away from the target obstacle; if the target obstacle type is dynamic, obtaining the lateral velocity and longitudinal velocity of the target obstacle based on the relative motion trend, and matching the optimal offset planning strategy for the vehicle based on the lateral velocity and the longitudinal velocity.

[0013] Based on the above technical means, the embodiments of this application can perform different offset planning according to the type of target obstacle when there is a target obstacle on one side.

[0014] Optionally, in one embodiment of this application, the optimal offset planning strategy for matching the vehicle based on the lateral speed and the longitudinal speed includes: if the longitudinal speed is less than or equal to a first preset longitudinal speed, then controlling the vehicle to laterally offset a second preset offset distance to the side away from the target obstacle, so that the distance between the vehicle and the target obstacle is greater than the first preset lateral distance; if the longitudinal speed is greater than the first preset longitudinal speed and the lateral speed is zero, then controlling the vehicle to laterally offset a third preset offset distance to the side away from the target obstacle, so that the distance between the vehicle and the target obstacle is greater than the second preset lateral distance; if the longitudinal speed is greater than the first preset longitudinal speed and the lateral speed is not zero, based on the longitudinal speed and the vehicle speed, while controlling the vehicle to laterally offset a fourth preset offset distance to the side away from the target obstacle, simultaneously controlling the vehicle to decelerate to the second preset longitudinal speed.

[0015] Based on the above technical means, the embodiments of this application can perform different offset planning according to the longitudinal and lateral velocities of the target obstacle when there is a target obstacle on one side and the target obstacle is of a dynamic type.

[0016] Optionally, in one embodiment of this application, when the distribution is on both sides, generating the optimal offset planning strategy for the vehicle based on the relative motion trend includes: identifying the lane line of the vehicle's current driving lane to obtain a preset safe distance between the vehicle and the lane line; obtaining the lateral distances between the vehicle and multiple target obstacles based on the relative motion trend; and calculating a fifth preset offset distance for the vehicle based on the lateral distances, so as to control the vehicle to perform the offset action at the fifth preset offset distance while maintaining the preset safe distance.

[0017] Based on the above technical means, the embodiments of this application can perform corresponding offset planning based on the lane lines and the lateral distance between the vehicle and the target obstacles on both sides when there are target obstacles on both sides.

[0018] A second aspect of this application provides a vehicle offset control device, comprising: an acquisition module, configured to acquire information on at least one target obstacle in at least one direction of the vehicle in an autonomous driving mode; a first determination module, configured to acquire the current driving state of the vehicle and, in combination with the current driving state and the information on each target obstacle, determine the relative motion trend between each target obstacle and the vehicle; and a control module, configured to generate an optimal offset planning strategy for the vehicle based on the relative motion trend, so as to control the vehicle to perform an offset action based on the optimal offset planning strategy.

[0019] Optionally, in one embodiment of this application, the acquisition module includes: a sensing unit, configured to sense radar data of at least one sensing target in at least one direction of the vehicle while simultaneously acquiring environmental image data in at least one direction of the vehicle; a fusion unit, configured to fuse the information data and the environmental image data to obtain fused data of the sensing target, and determine whether the sensing target meets a preset target obstacle determination condition based on the fused data; and a locking unit, configured to lock the sensing target as a target obstacle when the sensing target meets the preset target obstacle determination condition, and obtain the target obstacle information based on the fused data.

[0020] Optionally, in one embodiment of this application, it further includes: a second determining module, configured to determine the distribution of each of the target obstacles based on the target obstacle information, so as to generate the optimal offset planning strategy for the vehicle based on the distribution and the relative motion trend.

[0021] Optionally, in one embodiment of this application, the control module is used to determine the type of the target obstacle based on the relative motion trend; when the type of the target obstacle is static, control the vehicle to laterally deviate a first preset offset distance away from the target obstacle; when the type of the target obstacle is dynamic, obtain the lateral velocity and longitudinal velocity of the target obstacle based on the relative motion trend, and match the optimal offset planning strategy of the vehicle based on the lateral velocity and the longitudinal velocity.

[0022] Optionally, in one embodiment of this application, the control module includes: a first control unit, configured to control the vehicle to laterally deviate a second preset offset distance away from the target obstacle when the longitudinal speed is less than or equal to a first preset longitudinal speed, so that the distance between the vehicle and the target obstacle is greater than the first preset lateral distance; a second control unit, configured to control the vehicle to laterally deviate a third preset offset distance away from the target obstacle when the longitudinal speed is greater than the first preset longitudinal speed and the lateral speed is zero, so that the distance between the vehicle and the target obstacle is greater than the second preset lateral distance; and a third control unit, configured to control the vehicle to laterally deviate a fourth preset offset distance away from the target obstacle while simultaneously controlling the vehicle to decelerate to the second preset longitudinal speed when the longitudinal speed is greater than the first preset longitudinal speed and the lateral speed is not zero, based on the longitudinal speed and the vehicle speed.

[0023] Optionally, in one embodiment of this application, the control module is further configured to identify the lane line of the vehicle's current driving lane to obtain a preset safe distance between the vehicle and the lane line; obtain the lateral distances between the vehicle and a plurality of target obstacles based on the relative motion trend; and calculate a fifth preset offset distance of the vehicle based on the lateral distance, so as to control the vehicle to perform the offset action at the fifth preset offset distance while maintaining the preset safe distance.

[0024] A third aspect of this application provides a vehicle, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle offset control method as described in the above embodiments.

[0025] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle offset control method described above.

[0026] The beneficial effects of the embodiments of this application are as follows:

[0027] (1) The embodiments of this application can generate the best offset planning strategy for the vehicle based on the relative motion trend between each target obstacle and the vehicle, so as to control the vehicle to avoid obstacles on both sides of the road in advance during the driving process.

[0028] (2) The embodiments of this application can determine whether the perceived target is a target obstacle by fusing data, and obtain target obstacle information based on the fusing data, thereby facilitating more targeted offset planning for different target obstacles;

[0029] (3) In this embodiment of the application, different offset plans can be made according to the longitudinal speed and lateral speed of the target obstacle, while adjusting the longitudinal speed of the vehicle to deal with scenarios such as overtaking or occupying the lane by the target obstacle.

[0030] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0031] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0032] Figure 1 This is a flowchart of a vehicle offset control method according to an embodiment of this application;

[0033] Figure 2This is a schematic diagram illustrating the principle of a vehicle offset control method according to an embodiment of this application;

[0034] Figure 3 This is a flowchart of a vehicle offset control method according to an embodiment of this application;

[0035] Figure 3a This is a partially enlarged schematic diagram of a flowchart of a vehicle offset control method according to an embodiment of this application. Figure 1 ;

[0036] Figure 3b This is a partially enlarged schematic diagram of a flowchart of a vehicle offset control method according to an embodiment of this application. Figure 2 ;

[0037] Figure 4 This is a schematic diagram of the structure of a vehicle offset control device according to an embodiment of this application;

[0038] Figure 5 This is a structural schematic diagram of a vehicle provided according to an embodiment of this application.

[0039] Among them, 10-vehicle offset control device; 100-acquisition module; 200-first determination module; 300-control module. Detailed Implementation

[0040] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0041] The following description, with reference to the accompanying drawings, describes a vehicle offset control method, apparatus, vehicle, and storage medium according to embodiments of this application. Addressing the technical problem mentioned in the background section of the related art, which relies solely on determining the collision time while ignoring other physical laws, making it difficult to address safety hazards present during vehicle operation, this application provides a vehicle offset control method. In this method, embodiments of this application, in autonomous driving mode, combine the vehicle's current driving state and information about each target obstacle to determine the relative motion trend between each target obstacle and the vehicle. Based on this relative motion trend, an optimal offset planning strategy for the vehicle is generated, thereby controlling the vehicle to execute offset actions based on the optimal offset planning strategy. A comprehensive logical judgment is used to determine whether the vehicle needs to offset and to determine the offset plan, ensuring that the vehicle maintains a safe distance from target obstacles during operation, thus improving vehicle driving safety. This solves the technical problem in the related art where relying solely on determining the collision time while ignoring other physical laws makes it difficult to address safety hazards present during vehicle operation.

[0042] Specifically, Figure 1 This is a schematic flowchart of a vehicle offset control method provided in an embodiment of this application.

[0043] like Figure 1 As shown, the vehicle's offset control method includes the following steps:

[0044] In step S101, in autonomous driving mode, information on at least one target obstacle in at least one direction of the vehicle is acquired.

[0045] In actual implementation, the embodiments of this application can use the vehicle's built-in sensors to obtain information on at least one target obstacle in at least one direction of the vehicle when the vehicle is in autonomous driving mode, thereby obtaining all-round perception information around the vehicle. The target obstacle information may include: target obstacle images, movement data, etc.

[0046] Optionally, in one embodiment of this application, obtaining information on at least one target obstacle in at least one direction of the vehicle includes: simultaneously acquiring radar data of at least one perceived target in at least one direction of the vehicle and environmental image data in at least one direction of the vehicle; fusing the information data and environmental image data to obtain fused data of the perceived target, and determining whether the perceived target meets preset target obstacle determination conditions based on the fused data; if the perceived target meets the preset target obstacle determination conditions, locking the perceived target as a target obstacle, and obtaining target obstacle information based on the fused data.

[0047] Specifically, embodiments of this application can utilize sensors to perceive radar data of targets in various directions of the vehicle and collect corresponding environmental image data, such as target images and lane line images, thereby performing data fusion and determining whether the target meets the preset target obstacle determination conditions based on the fused data. The preset target obstacle determination conditions can be that the target is located near the lane line currently being driven by the vehicle. It is understood that in the vehicle's autonomous driving mode, the vehicle can activate the centering function to keep the vehicle driving in the middle of the lane. Therefore, embodiments of this application can predict the vehicle's driving trajectory based on the centering function and determine that stationary targets such as guardrails and curbs located outside the lane line of the driving trajectory, which are not affected by wind or inertia generated when the vehicle passes, do not meet the preset target obstacle determination conditions. Specifically, the preset target obstacle determination conditions can be set by those skilled in the art according to factors such as road type, road construction status, vehicle type, and the inertial influence of vehicle speed on objects on both sides during driving, and no specific limitations are made here.

[0048] For example, in this embodiment, a 4D front millimeter-wave radar can be installed in the center of the lower grille of the front bumper at the very front of the vehicle; four millimeter-wave angular radars can be installed on the left and right sides of the front and rear bumpers; a front-view camera can be installed behind the rearview mirror inside the windshield; five panoramic cameras can be installed above the left and right rearview mirrors, left and right fenders, and the rear license plate; a panoramic controller can be installed at the rear of the trunk; and a domain controller can be installed on the side of the trunk. The 4D front millimeter-wave radar and four millimeter-wave angular radars mounted on the front bumper detect the perceived target and send the detection results to the domain controller. Six vision cameras detect target information (such as vehicles, pedestrians, cyclists) and lane environment (lane lines, curbs, guardrails, cones, cardboard boxes, etc.) in the environmental image data around the vehicle within a 360° range and send the data to the panoramic controller for fusion and output of continuous perception information to the domain controller. The domain controller receives the perception information, performs fusion processing, and locks onto the target obstacle.

[0049] In step S102, the current driving state of the vehicle is obtained, and the relative motion trend between each target obstacle and the vehicle is determined by combining the current driving state with the information of each target obstacle.

[0050] As one possible approach, embodiments of this application can obtain the current driving state of the vehicle, and then combine the current driving state with information about each target obstacle to obtain the relative motion trend between each target obstacle and the vehicle.

[0051] For example, in this embodiment of the application, the distance and speed difference between the front radar and the target obstacle can be detected, and the domain controller data processing unit can calculate the lateral and longitudinal distances of the target obstacle. At the same time, intersection position compensation processing can be added to determine whether to enter the intersection. Thus, by visually monitoring the lane lines ahead and combining the current driving status of the vehicle, the expected trajectory of the vehicle can be determined, and the relative motion trend between each target obstacle and the vehicle can be determined.

[0052] In step S103, an optimal offset planning strategy for the vehicle is generated based on the relative motion trend, so as to control the vehicle to perform offset actions based on the optimal offset planning strategy.

[0053] Furthermore, embodiments of this application can generate an optimal offset planning strategy for the vehicle based on the relative motion trend, thereby controlling the vehicle to perform offset actions based on the optimal offset planning strategy, using comprehensive logic to determine whether the vehicle needs to offset, and determining the offset plan, so that the vehicle can maintain a safe distance from the target obstacle during driving, thereby improving the vehicle's driving safety.

[0054] Optionally, in one embodiment of this application, before generating the optimal offset planning strategy for the vehicle based on the relative motion trend, the method further includes: determining the distribution of each target obstacle based on the target obstacle information, so as to generate the optimal offset planning strategy for the vehicle based on the distribution and the relative motion trend.

[0055] In actual implementation, the embodiments of this application can determine the distribution of each target obstacle by using target obstacle information before generating the optimal offset planning strategy for the vehicle based on the relative motion trend. That is, it can determine the specific location of the target obstacle on the vehicle. Thus, based on the difference between the target obstacle and the vehicle's location and the relative motion trend between the target obstacle and the vehicle, the optimal offset planning strategy for the vehicle can be obtained.

[0056] Optionally, in one embodiment of this application, when the distribution is on one side, the optimal offset planning strategy for the vehicle is generated based on the relative motion trend, including: determining the type of the target obstacle based on the relative motion trend; if the type of the target obstacle is static, controlling the vehicle to laterally offset a first preset offset distance to the side away from the target obstacle; if the type of the target obstacle is dynamic, obtaining the lateral velocity and longitudinal velocity of the target obstacle based on the relative motion trend, and matching the optimal offset planning strategy for the vehicle based on the lateral velocity and longitudinal velocity.

[0057] In some embodiments, the type of target obstacle can be determined based on the relative motion trend. When the relative motion trend is that the vehicle is shortening the distance to the target obstacle at the current speed, i.e. one side is stationary and the other side is moving, the type of target obstacle can be determined to be static. In this case, the vehicle can be controlled to laterally deflect a first preset offset distance, such as 30cm, away from the target obstacle to avoid collision between the vehicle and the target obstacle, and to prevent the target obstacle from being knocked over by wind pressure as the vehicle passes by.

[0058] When the relative motion trend is such that the distance between the vehicle and the target obstacle does not decrease with the vehicle's current speed, meaning both are in motion, the lateral and longitudinal velocities of the target obstacle can be obtained based on the relative motion trend. Thus, the optimal offset planning strategy for the vehicle can be matched based on the lateral and longitudinal velocities.

[0059] Optionally, in one embodiment of this application, the optimal offset planning strategy for matching the vehicle based on lateral and longitudinal speeds includes: if the longitudinal speed is less than or equal to a first preset longitudinal speed, controlling the vehicle to laterally offset a second preset offset distance to the side away from the target obstacle, so that the distance between the vehicle and the target obstacle is greater than the first preset lateral distance; if the longitudinal speed is greater than the first preset longitudinal speed and the lateral speed is zero, controlling the vehicle to laterally offset a third preset offset distance to the side away from the target obstacle, so that the distance between the vehicle and the target obstacle is greater than the second preset lateral distance; if the longitudinal speed is greater than the first preset longitudinal speed and the lateral speed is not zero, based on the longitudinal speed and the vehicle speed, controlling the vehicle to laterally offset a fourth preset offset distance to the side away from the target obstacle while controlling the vehicle to decelerate to the second preset longitudinal speed.

[0060] In other words, if the longitudinal speed is less than or equal to the first preset longitudinal speed, the target obstacle can be determined to be a pedestrian, cyclist, stray animal, etc. In this embodiment, the vehicle can be controlled to laterally deviate a second preset offset distance away from the target obstacle, so that the distance between the vehicle and the target obstacle is greater than the first preset lateral distance, such as 1m. The first preset longitudinal speed can be set by those skilled in the art according to the actual situation, and no specific restrictions are made here.

[0061] If the longitudinal speed is greater than the first preset longitudinal speed, the target obstacle can be determined to be an obstacle vehicle. When the lateral speed of the obstacle vehicle is zero, it can be determined that the obstacle vehicle has no intention to approach the vehicle laterally. In this embodiment, the vehicle offset can be controlled based on factors such as the direction of movement of the obstacle vehicle and whether the obstacle vehicle is crossing the line. For example, if there is an oncoming vehicle or a vehicle coming from behind in the adjacent lane, and the vehicle speed is greater than the current vehicle speed, the vehicle is controlled to offset laterally by a third preset offset distance to the side away from the target obstacle, so that the distance between the vehicle and the target obstacle is greater than 1m. If there is an oncoming vehicle or a vehicle coming from behind in the adjacent lane, and the vehicle speed is less than the current vehicle speed, and the obstacle vehicle is crossing the line, the vehicle is controlled to offset laterally by a third preset offset distance to the side away from the target obstacle, so that the distance between the vehicle and the target obstacle is greater than 1m.

[0062] If the longitudinal speed is greater than the first preset longitudinal speed, the target obstacle can be determined to be an obstacle vehicle. If the lateral speed is not zero, and the longitudinal speed of the obstacle vehicle is greater than the current speed of the vehicle, it can be determined that the obstacle vehicle intends to approach the vehicle laterally, i.e., to overtake. In this embodiment, based on the longitudinal speed of the target obstacle and the current speed of the vehicle, the vehicle can be controlled to laterally deviate a fourth preset offset distance away from the target obstacle while simultaneously decelerating to a second preset longitudinal speed to facilitate overtaking by the obstacle vehicle and prevent collision. The second preset longitudinal speed and the fourth preset offset distance can be set by those skilled in the art based on factors such as the obstacle vehicle's speed and size, and are not specifically limited here.

[0063] Optionally, in one embodiment of this application, when the distribution is on both sides, the optimal offset planning strategy for the vehicle is generated based on the relative motion trend, including: identifying the lane line of the vehicle's current driving lane to obtain a preset safe distance between the vehicle and the lane line; obtaining the lateral distance between the vehicle and multiple target obstacles based on the relative motion trend; and calculating a fifth preset offset distance for the vehicle based on the lateral distance, so as to control the vehicle to perform an offset action at the fifth preset offset distance while maintaining the preset safe distance.

[0064] In other embodiments, when the target obstacles are distributed on both sides of the vehicle, the embodiments of this application can identify the lane lines of the vehicle's current driving lane, obtain the preset safe distance between the vehicle and the lane lines, and obtain the lateral distances between the vehicle and multiple target obstacles based on the relative motion trend. Based on the lateral distance, the fifth preset offset distance of the vehicle is calculated, so as to control the vehicle to perform an offset action at the fifth preset offset distance while maintaining the preset safe distance.

[0065] When there are obstacle vehicles crossing the line on both sides of the vehicle, making it impossible for the vehicle to maintain the preset safe distance, the embodiments of this application can control the vehicle speed to change based on the speed of the obstacle vehicle on either side, so as to get rid of the situation where there are target obstacles on both sides. For example, when the speed of the target obstacle vehicle is greater than the current speed of the vehicle, the vehicle is controlled to decelerate, and when the speed of the target obstacle vehicle is less than the current speed of the vehicle, the vehicle is controlled to accelerate.

[0066] gather Figure 2 and Figure 3 As shown, the working principle of the vehicle offset control method of this application embodiment is explained in detail with reference to one embodiment.

[0067] like Figure 2 As shown, in practical applications, the embodiments of this application can be implemented based on the following functional components: detection control unit, vehicle information monitoring unit, data processing unit, and data execution unit.

[0068] The data detection and control unit may include: a front millimeter-wave radar (installed at the lower grille of the front bumper at the very front of the vehicle) for detecting vehicle and pedestrian target information, four millimeter-wave angle radars (mounted on the left and right sides of the front and rear bumpers), one forward-view camera (mounted on the windshield behind the rearview mirror), and five panoramic cameras (mounted above the left and right rearview mirrors, left and right fenders, and the rear license plate), wheel speed sensors (mounted on the wheel hubs of the four wheels) for providing vehicle speed information, a sensor for providing yaw rate information (mounted in the EPBi actuator), and a steering angle sensor (mounted in the steering mechanism) for providing steering wheel angle information.

[0069] The data processing unit may include: a panoramic controller (mounted at the bottom of the rear of the trunk) that fuses and outputs data from six cameras, covering a 360° range of the vehicle; and a domain controller (mounted on the right side of the rear of the trunk) that fuses and outputs radar and camera-perceived targets for data calculation and outputting control strategies.

[0070] The data execution unit may include: an EPS (Electric Power Steering) control unit for lateral distance control, an integrated electronic parking brake system for longitudinal distance control, and an EMS (Engine-Management-System) power control unit.

[0071] This embodiment of the application can be equipped with a 4D front millimeter-wave radar in the center of the lower grille of the front bumper at the very front of the vehicle, four millimeter-wave angular radars on the left and right sides of the front and rear bumpers, a front-view camera behind the rearview mirror inside the windshield, five panoramic cameras above the left and right rearview mirrors, left and right fenders, and the rear license plate, a panoramic controller at the rear of the trunk, and a domain controller on the side of the trunk. The 4D front millimeter-wave radar and four millimeter-wave angular radars mounted on the front grille of the vehicle detect the perceived target and send the detection results to the domain controller. Six vision cameras detect target information (such as vehicles, pedestrians, cyclists) and lane environment (lane lines, curbs, guardrails, cones, cardboard boxes, etc.) in the environmental image data around the vehicle within a 360° range, and send it to the panoramic controller to fuse and output continuous perception information to the domain controller. The domain controller receives the perception information, performs fusion processing, and locks onto the target obstacle.

[0072] In this embodiment, the distance and speed difference between the target obstacle and the front radar can be detected, and the domain controller data processing unit can calculate the lateral and longitudinal distances of the target obstacle. At the same time, intersection position compensation processing can be added to determine whether to enter the intersection. Thus, by monitoring the lane lines ahead visually and combining the current driving status of the vehicle, the expected trajectory of the vehicle can be determined, and the relative motion trend between each target obstacle and the vehicle can be determined.

[0073] Furthermore, the embodiments of this application can solve the following seven scenarios:

[0074] 1. There are guardrails, curbs, cones or other obstacles beside the vehicle's driving lane.

[0075] 2. There are oncoming or rearward vehicles, and the distance between the vehicle and the obstacle vehicle is less than 1m.

[0076] 3. Oncoming or following vehicles are traveling at a speed greater than the vehicle's speed, indicating lateral movement.

[0077] 4. Oncoming or following vehicles are driving over the lane lines.

[0078] 5. A car is driving on the lane line in the adjacent lane.

[0079] 6. There are pedestrians or cyclists on one side of the vehicle lane.

[0080] 7. Targets appear simultaneously in both lanes of the vehicle's own lane: There are clear lane lines in the lane; vehicles on both sides have lateral target speeds.

[0081] Furthermore, such as Figure 3 As shown, embodiments of this application may include the following steps:

[0082] in, Figure 3a and Figure 3b for Figure 3 A partially enlarged schematic diagram of the flowchart shown.

[0083] S1: When the vehicle is driving in autonomous driving mode, activate the lane centering function.

[0084] S2: Identify targets using radar and cameras, identify lane lines using cameras, and predict the vehicle's trajectory using the steering wheel angle and yaw rate of the entire vehicle. If the conditions are met, control the vehicle to center itself within the lane.

[0085] S3: The sensing and detection unit detects whether there are target obstacles around the vehicle. If there are no target obstacles, the vehicle continues to drive in the center.

[0086] S4: When a target obstacle, such as a guardrail, curb, cone, or cardboard box, is detected on one side of the vehicle, the vehicle is laterally controlled to deviate from the target by L1 (at least 30cm, calibrable).

[0087] S5: When there is oncoming traffic in the adjacent lane or when there is rearward traffic in the adjacent lane and the speed of the vehicle is greater than the vehicle's speed, the lateral distance between the obstructing vehicle and the vehicle is <1m (can be calibrated):

[0088] If there is a lateral tendency for the vehicle to approach the obstacle vehicle, the vehicle's lateral path planning will shift to the other side by L1 (at least 30cm, which can be calibrated) to move away from the obstacle vehicle in the adjacent lane.

[0089] If an obstructing vehicle in the adjacent lane is driving on the lane line (such as a double yellow line, with the lane line on the side of the lane as the judgment target), the vehicle's lateral path planning will shift to the other side to maintain a distance L2 (at least 1m, which can be calibrated) from the obstructing vehicle.

[0090] S6: When an obstacle vehicle in the adjacent lane is driving on the lane line and the vehicle's speed is greater than the actual speed of the obstacle vehicle, the distance to the vehicle in front is judged to be greater than t1s (one grid time interval can be calibrated as 2s) based on the relative speed. The vehicle is then controlled to shift to the other side to maintain a lateral distance L3 (at least 60cm can be calibrated) from the obstacle vehicle. In this case, if there is also an obstacle vehicle in the adjacent lane that is close to the lane line or has a lateral movement speed, the vehicle's longitudinal speed is adjusted, and the deceleration is controlled to a1 (for comfort, it is recommended to control it at -2m / s, which can be calibrated). The vehicle is decelerated as comfortably as possible until the relative longitudinal distance to the obstacle vehicle in front is more than one grid time interval t1s.

[0091] S7: When a large vehicle is traveling in the adjacent lane, control the vehicle path planning to shift to the other side to maintain a lateral distance L2 (at least 1m can be calibrated) from the large vehicle.

[0092] S8: When there are pedestrians or cyclists on one side of the lane, control the vehicle to shift to the other lane line, maintaining a distance of L2 (at least 1m) from the pedestrians or cyclists.

[0093] S9: When the above traffic conditions combine and occur simultaneously in both lanes of this lane, the following procedures should be followed:

[0094] When a clear lane line is identified, the minimum distance between the vehicle edge and the lane line during lateral offset is required to be L3 (at least 30cm can be calibrated). This priority is higher than the offset logic of other moving or stationary targets.

[0095] When both sides are moving targets that cause the vehicle to deviate laterally, such as oncoming vehicles, large vehicles in the side lane, and vehicles in the side lane crossing the line, and these situations occur simultaneously on both sides of the lane line, the vehicle will deviate to the right by D1 according to the left target and to the left by D2 according to the right target. The total rightward deviation is D = D1 - D2, where a negative D indicates a deviation in the opposite direction.

[0096] S10: After the offset ends, the sensing and detection module continues to detect and enters the next cycle.

[0097] According to the vehicle offset control method proposed in this application, in autonomous driving mode, the method combines the vehicle's current driving state and information about each target obstacle to determine the relative motion trend between the vehicle and each obstacle. Based on this relative motion trend, an optimal offset planning strategy is generated for the vehicle. The method then controls the vehicle to execute offset actions based on this optimal offset planning strategy. A comprehensive logical judgment is used to determine whether the vehicle needs to offset and to determine the offset plan, ensuring that the vehicle maintains a safe distance from target obstacles during driving, thereby improving driving safety. This solves the technical problem in related technologies that rely solely on collision time while ignoring other physical laws, making it difficult to address safety hazards present during vehicle operation.

[0098] Next, with reference to the accompanying drawings, a vehicle offset control device according to an embodiment of this application is described.

[0099] Figure 4 This is a block diagram of a vehicle offset control device according to an embodiment of this application.

[0100] like Figure 4 As shown, the vehicle's offset control device 10 includes: an acquisition module 100, a first determination module 200, and a control module 300.

[0101] Specifically, the acquisition module 100 is used to acquire information about at least one target obstacle in at least one direction of the vehicle in autonomous driving mode.

[0102] The first determining module 200 is used to obtain the current driving state of the vehicle and, in combination with the current driving state and the information of each target obstacle, determine the relative motion trend between each target obstacle and the vehicle.

[0103] The control module 300 is used to generate the optimal offset planning strategy for the vehicle based on the relative motion trend, so as to control the vehicle to perform offset actions based on the optimal offset planning strategy.

[0104] Optionally, in one embodiment of this application, the acquisition module 100 includes: a sensing unit, a fusion unit, and a locking unit.

[0105] The sensing unit is used to sense radar data of at least one target in at least one direction of the vehicle, while simultaneously acquiring environmental image data in at least one direction of the vehicle.

[0106] The fusion unit is used to fuse information data and environmental image data to obtain fused data of the perceived target, and to determine whether the perceived target meets the preset target obstacle determination conditions based on the fused data.

[0107] The locking unit is used to lock the perceived target as a target obstacle when the perceived target meets the preset target obstacle determination conditions, and to obtain target obstacle information based on the fused data.

[0108] Optionally, in one embodiment of this application, the vehicle offset control device 10 further includes a second determining module.

[0109] The second determination module is used to determine the distribution of each target obstacle based on the target obstacle information, so as to generate the optimal offset planning strategy for the vehicle based on the distribution and relative motion trend.

[0110] Optionally, in one embodiment of this application, the control module 300 is used to determine the type of the target obstacle based on the relative motion trend; when the type of the target obstacle is static, control the vehicle to laterally deviate a first preset offset distance away from the target obstacle; when the type of the target obstacle is dynamic, obtain the lateral velocity and longitudinal velocity of the target obstacle based on the relative motion trend, and match the vehicle's optimal offset planning strategy based on the lateral velocity and longitudinal velocity.

[0111] Optionally, in one embodiment of this application, the control module 300 includes: a first control unit, a second control unit, and a third control unit.

[0112] The first control unit is used to control the vehicle to laterally deflect a second preset offset distance away from the target obstacle when the longitudinal speed is less than or equal to the first preset longitudinal speed, so that the distance between the vehicle and the target obstacle is greater than the first preset lateral distance.

[0113] The second control unit is used to control the vehicle to laterally deflect a third preset offset distance away from the target obstacle when the longitudinal speed is greater than the first preset longitudinal speed and the lateral speed is zero, so that the distance between the vehicle and the target obstacle is greater than the second preset lateral distance.

[0114] The third control unit is used to control the vehicle to deflect laterally away from the target obstacle by a fourth preset offset distance based on the longitudinal speed and the vehicle speed when the longitudinal speed is greater than the first preset longitudinal speed and the lateral speed is not zero, while controlling the vehicle to decelerate to the second preset longitudinal speed.

[0115] Optionally, in one embodiment of this application, the control module 300 is further configured to identify the lane lines of the vehicle's current driving lane to obtain a preset safe distance between the vehicle and the lane lines; obtain the lateral distances between the vehicle and multiple target obstacles based on the relative motion trend; and calculate a fifth preset offset distance of the vehicle based on the lateral distance, so as to control the vehicle to perform an offset action at the fifth preset offset distance while maintaining the preset safe distance.

[0116] It should be noted that the foregoing explanation of the vehicle offset control method embodiment also applies to the vehicle offset control device of this embodiment, and will not be repeated here.

[0117] According to the vehicle offset control device proposed in this application embodiment, in autonomous driving mode, by combining the vehicle's current driving state and information about each target obstacle, the relative motion trend between the vehicle and each target obstacle is determined. Based on this relative motion trend, an optimal offset planning strategy for the vehicle is generated, thereby controlling the vehicle to execute offset actions based on the optimal offset planning strategy. A comprehensive logic is used to determine whether the vehicle needs to offset and to determine the offset plan, ensuring that the vehicle maintains a safe distance from target obstacles during driving, thus improving vehicle driving safety. This solves the technical problem in related technologies that rely solely on judging the collision time while ignoring other physical laws, making it difficult to address safety hazards present during vehicle operation.

[0118] Figure 5 A schematic diagram of the structure of a vehicle provided in an embodiment of this application. The vehicle may include:

[0119] The memory 501, the processor 502, and the computer program stored on the memory 501 and capable of running on the processor 502.

[0120] When the processor 502 executes the program, it implements the vehicle offset control method provided in the above embodiments.

[0121] Furthermore, the vehicle also includes:

[0122] Communication interface 503 is used for communication between memory 501 and processor 502.

[0123] The memory 501 is used to store computer programs that can run on the processor 502.

[0124] The memory 501 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0125] If the memory 501, processor 502, and communication interface 503 are implemented independently, then the communication interface 503, memory 501, and processor 502 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 5 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0126] Optionally, in a specific implementation, if the memory 501, processor 502, and communication interface 503 are integrated on a single chip, then the memory 501, processor 502, and communication interface 503 can communicate with each other through an internal interface.

[0127] Processor 502 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0128] This embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle offset control method described above.

[0129] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0130] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0131] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0132] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0133] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0134] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0135] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0136] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for controlling vehicle offset, characterized in that, Includes the following steps: In autonomous driving mode, acquire information on at least one target obstacle in at least one direction of the vehicle; The current driving state of the vehicle is obtained, and the relative motion trend between each target obstacle and the vehicle is determined by combining the current driving state with the information of each target obstacle. as well as The optimal offset planning strategy for the vehicle is generated based on the relative motion trend, so as to control the vehicle to perform offset actions based on the optimal offset planning strategy; The step of obtaining information on at least one target obstacle in at least one direction of the vehicle includes: While sensing radar data of at least one perceived target in at least one direction of the vehicle, environmental image data of at least one direction of the vehicle is also acquired. The radar data and the environmental image data are fused to obtain fused data of the perceived target, and the perceived target is judged based on the fused data to determine whether the perceived target meets the preset target obstacle determination conditions; If the perceived target meets the preset target obstacle determination conditions, then the perceived target is locked as a target obstacle, and the target obstacle information is obtained based on the fused data; Before generating the optimal offset planning strategy for the vehicle based on the relative motion trend, the following steps are also included: Based on the target obstacle information, the distribution of each target obstacle is determined, and based on the distribution and the relative motion trend, the optimal offset planning strategy for the vehicle is generated. When the distribution is on both sides, the step of generating the optimal offset planning strategy for the vehicle based on the relative motion trend includes: Identify the lane lines of the vehicle's current driving lane to obtain a preset safe distance between the vehicle and the lane lines; Based on the relative motion trend, the lateral distances between the target obstacles and the vehicle are obtained respectively; The fifth preset offset distance of the vehicle is calculated based on the lateral distance, so as to control the vehicle to perform the offset action at the fifth preset offset distance while maintaining the preset safety distance.

2. The method according to claim 1, characterized in that, When the distribution is concentrated on one side, the optimal offset planning strategy for generating the vehicle based on the relative motion trend includes: Based on the relative motion trend, the type of the target obstacle is determined; If the target obstacle is of static type, the vehicle is controlled to laterally deviate a first preset offset distance away from the target obstacle. If the target obstacle is a dynamic type, the lateral and longitudinal velocities of the target obstacle are obtained based on the relative motion trend, and the optimal offset planning strategy for the vehicle is matched based on the lateral and longitudinal velocities.

3. The method according to claim 2, characterized in that, The optimal offset planning strategy for matching the vehicle based on the lateral velocity and the longitudinal velocity includes: If the longitudinal speed is less than or equal to the first preset longitudinal speed, the vehicle is controlled to laterally deviate a second preset offset distance away from the target obstacle, so that the distance between the vehicle and the target obstacle is greater than the first preset lateral distance. If the longitudinal speed is greater than the first preset longitudinal speed and the lateral speed is zero, then the vehicle is controlled to laterally deviate a third preset offset distance away from the target obstacle, so that the distance between the vehicle and the target obstacle is greater than the second preset lateral distance. If the longitudinal speed is greater than the first preset longitudinal speed and the lateral speed is not zero, based on the longitudinal speed and the vehicle speed, the vehicle is controlled to laterally deviate a fourth preset offset distance away from the target obstacle, while the vehicle is controlled to decelerate to the second preset longitudinal speed.

4. A vehicle offset control device, characterized in that, The offset control device is used to implement the offset control method as described in any one of claims 1-3, and the offset control device includes: The acquisition module is used to acquire information about at least one target obstacle in at least one direction of the vehicle in autonomous driving mode. The determination module is used to acquire the current driving state of the vehicle, and, in conjunction with the current driving state and information about each target obstacle, determine the relative motion trend between each target obstacle and the vehicle; and The control module is used to generate the optimal offset planning strategy for the vehicle based on the relative motion trend, so as to control the vehicle to perform offset actions based on the optimal offset planning strategy.

5. The offset control device according to claim 4, characterized in that, The acquisition module includes: The sensing unit is used to sense radar data of at least one sensing target in at least one direction of the vehicle, while simultaneously acquiring environmental image data of the vehicle in at least one direction. The fusion unit is used to fuse the radar data and the environmental image data to obtain fused data of the perceived target, and to determine whether the perceived target meets the preset target obstacle determination conditions based on the fused data; The locking unit is used to lock the perceived target as a target obstacle when the perceived target meets the preset target obstacle determination conditions, and to obtain the target obstacle information based on the fused data.

6. A vehicle, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the vehicle offset control method as described in any one of claims 1-5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the vehicle offset control method as described in any one of claims 1-5.

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