Vehicle door anti-collision control method, electronic equipment and vehicle

Abstract

The invention provides a vehicle door anti-collision control method, electronic equipment and a vehicle, and relates to the technical field of intelligent vehicle safety, and the vehicle door anti-collision control method comprises the steps that vehicle door motion parameters and obstacle motion parameters are obtained; determining a predicted track gap distance between the vehicle door and the obstacle based on the obtained vehicle door motion parameter and the obstacle motion parameter; based on the predicted track gap distance between the vehicle door and the obstacle, the current collision risk level is judged, and an anti-collision strategy corresponding to the collision risk level is executed; wherein the anti-collision strategy is a strategy for intervening opening of the vehicle door based on the collision risk level so as to reduce the door opening collision risk. According to the method, motion parameters of a vehicle door and an obstacle are fused, a track gap is predicted, risks are evaluated, and graded protection such as prompting, speed limiting and angle limiting is implemented in combination with multi-stage threshold values; meanwhile, the intervention mode is dynamically adjusted, safety and user experience are both considered, and the door opening collision risk is effectively reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent vehicle safety, and in particular to a vehicle door anti-collision control method, an electronic device and a vehicle. BACKGROUND

[0002] With the continuous increase in the number of cars, the use environment of vehicles is becoming increasingly complex, and the vehicle door is prone to collision with surrounding obstacles or other vehicles during opening, resulting in damage to the vehicle body and even causing personal injury. In particular, in urban roads or temporary parking areas, the vehicle door anti-collision problem is particularly prominent. SUMMARY

[0003] Therefore, the present application aims to provide a vehicle door anti-collision control method, an electronic device and a vehicle to solve or partially solve the above problems.

[0004] To achieve the above purpose, the present application provides a vehicle door anti-collision control method, comprising: obtaining vehicle door movement parameters and obstacle movement parameters; determining a predicted trajectory gap distance between the vehicle door and the obstacle based on the obtained vehicle door movement parameters and obstacle movement parameters; judging a current collision risk level based on the predicted trajectory gap distance between the vehicle door and the obstacle, and executing an anti-collision strategy corresponding to the collision risk level; wherein the anti-collision strategy is a strategy for intervening in the opening of the vehicle door based on the collision risk level to reduce the risk of door opening collision.

[0005] Optionally, the determination of the predicted trajectory gap distance between the vehicle door and the obstacle based on the obtained vehicle door movement parameters and obstacle movement parameters comprises: determining a vehicle door predicted movement trajectory based on the vehicle door movement parameters; determining an obstacle trajectory based on the obstacle movement parameters; aligning the vehicle door predicted movement trajectory and the obstacle trajectory in time, and determining the minimum distance between the vehicle door predicted movement trajectory and the obstacle trajectory as the predicted trajectory gap distance.

[0006] Optionally, the determination of the obstacle trajectory based on the obstacle movement parameters comprises: in response to determining that the obstacle is on a straight line section and the movement trend is straight ahead, determining a plurality of predicted positions of the obstacle in a future time window in a straight line direction in combination with the obstacle movement parameters, and determining a straight line type obstacle trajectory based on the plurality of predicted positions; In response to determining that the obstacle is in a straight line segment and the motion trend is a turn, a plurality of predicted positions of the obstacle in a future time window in a direction of a turn angle are determined in combination with the motion parameters of the obstacle, and a curved obstacle trajectory is determined based on the plurality of predicted positions.

[0007] Optionally, the determining of the current collision risk level based on the predicted trajectory gap distance between the vehicle door and the obstacle comprises: In response to the predicted trajectory gap distance being less than or equal to a preset first threshold, it is determined that the current collision risk level is level three. In response to the predicted trajectory gap distance being greater than the preset first threshold and less than or equal to a preset second threshold, it is determined that the current collision risk level is level two. In response to the predicted trajectory gap distance being greater than the preset second threshold and less than or equal to a preset third threshold, it is determined that the current collision risk level is level one.

[0008] Optionally, the executing of the anti-collision strategy corresponding to the collision risk level comprises: In response to determining that the collision risk level is level three, the vehicle door electronic locking mechanism is controlled to be in a locked state to prevent the vehicle door from being opened. In response to determining that the collision risk level is level two, the vehicle door actuator is controlled to apply a reverse damping torque to slow down the opening speed of the vehicle door and delay the opening timing. In response to determining that the collision risk level is level one, the vehicle door ambient light is controlled to emit light in a flashing manner to issue a collision risk prompt.

[0009] Optionally, the obtaining of the motion parameters of the obstacle comprises: Obtaining surrounding space information and road information within a preset range of the vehicle door. Determining an external target and a position parameter and a motion trend of the external target located within the preset range of the vehicle door based on the surrounding space information and the road information. Determining whether the external target is an obstacle based on the position parameter and the motion trend. In response to determining that the external target is an obstacle, the motion parameters of the obstacle are determined.

[0010] Optionally, after the determining of the current collision risk level based on the predicted trajectory gap distance between the vehicle door and the obstacle and the executing of the anti-collision strategy corresponding to the collision risk level, the method further comprises: Packing the collision risk level, the corresponding anti-collision strategy, and trigger time information into an event log. Uploading the event log to a cloud server through a vehicle-mounted communication module. The event log is stored in the cloud and statistical analysis is performed based on historical log data.

[0011] Optionally, the control door actuator to apply a reverse damping torque to slow down the opening speed of the door and delay the opening timing, comprising: Determine the door opening behavior characteristics of the user based on the door movement parameters; Analyze and divide the door opening behavior characteristics of the user, and dynamically adjust the reverse damping torque to slow down the opening speed of the door and delay the opening timing.

[0012] Based on the same inventive concept, the present application also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable by the processor, wherein the processor implements the method as described above when executing the computer program.

[0013] Based on the same inventive concept, the present application also provides a vehicle comprising an electronic device as described above.

[0014] As can be seen from the above, the vehicle door anti-collision control method, electronic device and vehicle provided by the present application, wherein the vehicle door anti-collision control method comprises: obtaining door movement parameters and obstacle movement parameters; determining the predicted trajectory gap distance between the door and the obstacle based on the obtained door movement parameters and obstacle movement parameters; determining the current collision risk level based on the predicted trajectory gap distance between the door and the obstacle, and executing the anti-collision strategy corresponding to the collision risk level; wherein the anti-collision strategy is a strategy for intervening in the opening of the door based on the collision risk level to reduce the door opening collision risk. The present application predicts the door dynamic envelope space and the movement trend of the obstacle based on the obtained door movement parameters and obstacle movement parameters, thereby realizing the calculation and risk assessment of the trajectory gap between the door and the obstacle. At the same time, by executing the corresponding anti-collision strategy for different collision risk levels, the present application realizes differentiated intervention, makes the protection strategy more precise, realizes progressive protection under human-machine cooperation, ensures safety, avoids excessive intervention, and further effectively reduces the risk of collision between the door and the obstacle during the opening of the door. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present application or related art, the following will briefly introduce the drawings needed to be used in the embodiments or related art descriptions. Obviously, the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0016] Figure 1 Flowchart of the vehicle door anti-collision control method of the embodiments of the present application Figure 1 ; Figure 2 Flowchart of a vehicle door anti-collision control method according to an embodiment of the present application Figure 2 ; Figure 3 Flowchart of a vehicle door anti-collision control method according to an embodiment of the present application Figure 3 ; Figure 4 Schematic diagram of a vehicle door anti-collision control device according to an embodiment of the present application Figure 5 Schematic diagram of an electronic device hardware structure according to an embodiment of the present application DETAILED DESCRIPTION

[0017] In order to make the objectives, technical solutions and advantages of the present application clearer, further detailed description will be made to the present application with reference to specific embodiments and accompanying drawings.

[0018] It should be noted that, unless otherwise defined, technical terms or scientific terms used in the embodiments of the present application should be understood as their common meanings to those skilled in the art to which the present application belongs. The terms "first", "second" and similar terms used in the embodiments of the present application do not represent any order, number or importance, but are only used to distinguish different components. The terms "include" or "contain" and similar terms mean that the elements or objects before the terms cover the elements or objects listed after the terms and their equivalents, and do not exclude other elements or objects. The terms "connect" or "connected" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms "upper", "lower", "left", "right" and the like are only used to represent relative positional relationships, and when the absolute positions of the described objects change, the relative positional relationships may also change accordingly.

[0019] As described in the background, with the continuous growth of the number of cars, the urban road and parking environment is becoming increasingly complex. When the vehicle is temporarily parked on both sides of the road or enters a narrow parking space, the opening of the vehicle door often forms a potential conflict with the surrounding vehicles, bicycles, electric vehicles and even pedestrians. Once the passenger fails to timely perceive the surrounding environment and recklessly pushes open the door, it is easy to cause traffic accidents such as "door kill", which not only causes damage to the vehicle itself, but also can cause serious personal injury. This risk is particularly prominent in urban roads, community entrances and underground garages, and has become a problem that needs to be solved in the safe use of vehicles.

[0020] In view of the above, some vehicles currently begin to be equipped with door anti-collision auxiliary functions, trying to reduce the collision probability in the door opening process by monitoring the environment around the vehicle body through sensors. For example, ultrasonic sensors or millimeter wave radars are used to detect obstacles on one side of the door, and the relative relationship between the obstacles and the door is determined through distance and speed information, so as to trigger an alarm or limit the opening of the door. In addition, some vehicle models introduce a slow opening mechanism or a mechanical limiting structure, trying to reduce the impact of collision by slowing down the opening speed of the door.

[0021] However, the present inventors have found that the related art is mostly based on the judgment of static or single parameters in application, and cannot truly solve the anti-collision demand in a complex dynamic environment. For example, the risk of obstacles is determined by a simple distance threshold. This way can theoretically indicate the proximity between the obstacles and the door, but it ignores the fact that the opening of the door is a continuous dynamic process, and the "dynamic envelope space" formed by the rotation of the door will gradually expand with the opening angle. If only static distance is relied on for measurement, it is impossible to predict in advance whether the obstacles will appear in the future path of the door opening, resulting in delayed warning or missed risk judgment.

[0022] In view of the above problems, the present inventors propose a new improved scheme: preventing door collision by actively sensing collision risks and effectively intervening. Specifically, before and during the opening of the door, the system can collect the motion parameters of the obstacles and the road environment information in real time, and then further determine the motion trend, establish a dynamic prediction model, and calculate the interaction between the opening angle of the door and the possible trajectory of the obstacles. Based on the prediction results, the system can dynamically adjust the opening speed, angle range of the door, or limit the door from continuing to open when necessary, thereby realizing a "early prediction + active intervention" protection mechanism. Compared with the related art, this scheme not only improves the recognition accuracy of dynamic obstacles in complex scenarios, but also matches the control according to the door opening behavior and the motion trend of the obstacles, reduces false positives and omissions, and significantly improves the intelligent level and practical value of door anti-collision.

[0023] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0024] In some embodiments, with reference to Figure 1 The present application provides a door anti-collision control method, comprising: S100, acquiring door motion parameters and obstacle motion parameters; In this step, the dynamic state of the door and the obstacles can be collected and processed by the vehicle controller to construct the input information required for subsequent prediction.

[0025] Exemplarily, when acquiring the door motion parameter, the door motion parameter comprises an opening angle, an opening angular velocity, an opening angular acceleration, an opening direction, and a displacement angle change trend of the door.

[0026] To realize the acquisition of the above parameters, the vehicle controller can call the angle sensor arranged at the door hinge to collect the real-time angle value; detect the magnetic field change of the door shaft through the Hall sensor to reflect the door opening speed; or use the acceleration sensor installed on the door to acquire the acceleration components of the door in different directions, so as to comprehensively determine the dynamic opening characteristics of the door.

[0027] Optionally, the vehicle controller can also combine the historical door opening trajectory to predict the subsequent motion trend of the door (such as continuing to accelerate opening, maintaining the opening angle, or decelerating closing).

[0028] Exemplarily, when acquiring the obstacle motion parameter, the obstacle motion parameter comprises the current position, the running speed, the acceleration, the motion direction, and the motion trend characteristics of the obstacle.

[0029] The vehicle controller can perceive the surrounding space through the vehicle-mounted radar, ultrasonic sensor, or camera, identify the target obstacle, and track the position information of the obstacle at continuous time points. Based on the position change of the obstacle in the time sequence, the controller can calculate the speed and acceleration of the obstacle, and further judge the motion direction of the obstacle (such as approaching the door, moving away from the door, or passing parallel to the door).

[0030] Further, the reasonable motion trend of the obstacle can also be determined in combination with the road environment data (such as the lane line, the curb line, or the sidewalk direction).

[0031] By simultaneously acquiring the door motion parameter and the obstacle motion parameter, the vehicle controller can establish the dynamic state model of the two, and provide a data basis for subsequent prediction of the relative motion relationship between the door and the obstacle. This dual parameter acquisition method not only improves the prediction accuracy, but also effectively avoids the misjudgment or delay problem caused by relying on only the state of a single object.

[0032] S200, determining a predicted trajectory gap distance between the door and the obstacle based on the acquired door motion parameter and obstacle motion parameter; In this step, the vehicle controller calculates the angle change of the door within a future preset time window based on the opening angle, angular velocity, and angular acceleration of the door, and generates an envelope space formed by the rotation of the door in combination with the geometric size of the door. The envelope space can accurately represent the three-dimensional region that the door can occupy in the opening process, thereby reflecting the dynamic trajectory of the door.

[0033] Meanwhile, the vehicle controller predicts the future position of the obstacle according to the current position, speed, acceleration and moving direction of the obstacle. For different types of obstacles, the controller can adopt different prediction models: for example, for pedestrians, a motion model based on gait or linear extrapolation can be adopted; for vehicles or cyclists, the trajectory prediction is corrected in combination with road constraint conditions (such as lane lines, driving rules). Thus, the possible motion trajectory region of the obstacle within a future time window can be obtained.

[0034] After obtaining the door envelope space (predicted motion trajectory of the door) and the motion trajectory of the obstacle, the vehicle controller performs spatial comparison on the two. If there is no intersection between the two, the minimum Euclidean distance of the nearest point is taken as the predicted trajectory gap distance; if there is an overlapping or intersecting region, the gap distance is recorded as zero, indicating that a future collision may occur.

[0035] Optionally, the nearest distance at different time instants can also be calculated to obtain a “predicted trajectory gap distance curve varying with time”, to support more detailed risk assessment.

[0036] By comparing the predicted trajectory gap distance with a preset safety threshold. If the predicted trajectory gap distance is always greater than the preset safety threshold, it is considered that the door opening process will not interfere with the obstacle; if the predicted trajectory gap distance is less than or gradually approaches the preset safety threshold, it indicates that there is a potential collision risk, and the controller will output risk information to the subsequent warning or intervention module. In this way, not only the dynamic opening process of the door is considered, but also the future motion trend of the obstacle is taken into account, effectively overcoming the shortcomings of the judgment based on only the static distance.

[0037] S300, based on the predicted trajectory gap distance between the door and the obstacle, judging the current collision risk level, and executing a collision avoidance strategy corresponding to the collision risk level; The collision avoidance strategy is a strategy of interfering with the opening of the door based on the collision risk level to reduce the opening-door collision risk.

[0038] Illustratively, in this step, the vehicle controller compares the predicted trajectory gap distance with a preset safety threshold / multi-level risk threshold to distinguish different risk levels. Specifically, the controller can divide the risk level into three categories: safe level, dangerous level and collision level, to realize risk assessment.

[0039] When the predicted trajectory gap distance is greater than the preset safety threshold, the vehicle controller determines that the current is the safe level, and considers that the door opening will not interfere with the obstacle, at which time the system does not trigger any intervention measure to ensure the normal use experience of the user.

[0040] When the predicted trajectory gap distance is close to or less than the preset safety threshold, the controller determines a danger level, and the system timely adjusts the opening speed of the vehicle door according to the specific predicted trajectory gap distance, for example, by means of a prompt sound, light flashing or a moderate adjustment of the opening speed of the vehicle door, so as to provide more sufficient reaction time for the user.

[0041] Optionally, the danger level can be further divided into multiple levels (for example, level 1, level 2, level 3, and so on) to achieve a more smooth risk assessment.

[0042] When the predicted trajectory gap distance is less than or equal to 0, the controller determines a collision level, indicating that there is a risk of collision if the vehicle door continues to open. At this time, the vehicle controller will execute an anti-collision strategy, for example, directly locking the vehicle door to prevent the vehicle door from further opening.

[0043] Through the above multi-level risk judgment and corresponding anti-collision strategies, the system can gradually enhance the protection control of the vehicle door while ensuring the freedom of user operation, thereby realizing a hierarchical and progressive safety protection, avoiding the inconvenience caused by false triggering, and improving the reliability and timeliness of anti-collision.

[0044] The embodiment provides a vehicle door anti-collision control method, including: acquiring a vehicle door motion parameter and an obstacle motion parameter; determining a predicted trajectory gap distance between the vehicle door and the obstacle based on the acquired vehicle door motion parameter and the obstacle motion parameter; judging a current collision risk level based on the predicted trajectory gap distance between the vehicle door and the obstacle, and executing an anti-collision strategy corresponding to the collision risk level; wherein the anti-collision strategy is a strategy of interfering with the opening of the vehicle door based on the collision risk level to reduce the risk of door collision. The embodiment predicts the dynamic envelope space of the vehicle door and the motion trend of the obstacle based on the acquired vehicle door motion parameter and the obstacle motion parameter, thereby realizing the calculation and risk assessment of the trajectory gap between the vehicle door and the obstacle. Meanwhile, the embodiment realizes differentiated intervention by executing corresponding anti-collision strategies for different collision risk levels, so that the protection strategy is more precise, realizes progressive protection under human-machine cooperation, ensures safety, avoids excessive intervention, and further effectively reduces the risk of collision between the vehicle door and the obstacle during the opening process of the vehicle door.

[0045] In some embodiments, with reference to Figure 2 , the S200 determines the predicted trajectory gap distance between the vehicle door and the obstacle based on the acquired vehicle door motion parameter and the obstacle motion parameter, including: S201, determining a predicted motion trajectory of the vehicle door based on the vehicle door motion parameter; Exemplarily, the current door motion parameters are acquired: current opening angle θ0(rad), angular velocity ω0(rad / s), angular acceleration α0(rad / s2, which can be estimated by the difference of historical angular velocity), hinge position h (coordinate vector in the vehicle coordinate system), door geometry description (door outer edge, multiple key points p i on the door boundary away from the hinge, i = 1, 2, 3,..., N).

[0046] If it is a sliding door, replace it with translation parameters: current position x 01 , linear velocity v 01 , linear acceleration a 01 , and door contour point set p i .

[0047] Further, the prediction time window and sampling are set, specifically, the prediction time window T pred is set (for example: 2 s, which can be adaptive according to vehicle type / speed), and the sampling interval Δt (example: 0.05-0.1 s) is set.

[0048] Generate time series t k = kΔt, k = 0, 1, 2,..., N, .

[0049] Further, based on the motion model, the trajectory is generated, specifically, for the swing door, angular motion prediction is adopted:

[0050] At each time t k , the rotation matrix (around the hinge axis, usually the vertical axis of the vehicle or the local hinge axis) is calculated:

[0051] And the predicted position of the i-th key point on the door is obtained: In addition, if the door is a sliding door, linear translation prediction is adopted: In summary, at each , several key points of the door are connected to form a polygon or a set of sample points representing the door contour at that time; if continuous envelope is required, the contours of each can be taken and the union set can be calculated to approximately obtain the "dynamic envelope space" of the door, i.e. the predicted motion trajectory of the door.

[0052] Optionally, if further accurate data is required to reduce the influence of angular velocity / position measurement noise and model error, the covariance matrix The characterization is performed and can also be used in the subsequent distance determination for risk probability calculation.

[0053] S202, determining a trajectory of the obstacle based on the obstacle motion parameter; Exemplarily, the vehicle controller / vehicle can perceive the surrounding environment through various sensors (such as a camera, a millimeter wave radar, an ultrasonic wave, etc.), obtain observation information of the obstacle at time t0, including position x0, velocity estimate v0, acceleration estimate a0, target category (pedestrian, bicycle, electric vehicle, motor vehicle, or static object), shape approximation (point, circle, rectangle, or boundary polygon), and motion trend.

[0054] Subsequently, the vehicle controller inputs the historical observation data into a tracking algorithm (such as Kalman filtering, extended Kalman filtering, or multi-sensor fusion tracking) to generate a robust trajectory state estimate, , and its covariance Σ obs to reflect the motion state and uncertainty of the obstacle.

[0055] Further, in the trajectory prediction stage, the vehicle controller selects a suitable motion model according to the target category and historical behavior. Optionally, for pedestrians or slow-moving targets, a constant velocity (CV) or random walk model can be used; for bicycles and electric vehicles, a constant acceleration (CA) model or a motion model with steering can be used; and a static obstacle is considered to have a constant position and a speed of zero.

[0056] The motion of the obstacle can be described by a motion equation in vector form, for example:

[0057] If a filter prediction (Kalman prediction) is used, a Kalman prediction step can be used: ,

[0058] where F is the state transition matrix and Q is the process noise covariance.

[0059] Further, to facilitate the calculation of the trajectory gap between the vehicle door and the obstacle, as in S201, the vehicle controller generates a set of obstacle prediction points k from the predicted trajectory at discrete time points t , which can cover the obstacle outline points or only use the center point and add a radius or envelope expansion. The obstacle can be further approximated as a point (with a radius), a circle, a rectangle, or a polygon boundary, thereby simplifying the distance calculation.

[0060] S203, time progress alignment is performed on the door predicted motion trajectory and the obstacle trajectory, and a minimum distance between the door predicted motion trajectory and the obstacle trajectory is determined as the predicted trajectory gap distance.

[0061] Exemplarily, in this step, the vehicle controller first aligns the door predicted motion trajectory and the obstacle trajectory in time sequence, ensuring that the two trajectories are compared at the same time point. Specifically, the predicted positions of the door in the future time period are one-to-one corresponding to the predicted positions of the obstacle at the same time point, so that the spatial relationship between the door and the obstacle at each time point can be evaluated, that is, the two trajectories are compared at the same time sequence t k Resampling is performed on the above (both S201 and S202 are performed at the same t k If the original sampling is different, interpolation (linear interpolation or spline) is used to obtain consistent time point positions.

[0062] Further, the controller calculates the minimum distance between the door and the obstacle at each aligned time point, which can be determined based on the distance between the door edge point and the obstacle outline point. By comparing the minimum distances at all time points in the entire prediction time window, the smallest distance is selected as the predicted trajectory gap distance.

[0063] The predicted trajectory gap distance can intuitively reflect the minimum spatial allowance of the door in the opening process and the possible collision with the obstacle, providing an accurate reference for subsequent collision risk level judgment and anti-collision strategy execution. Through this time progress alignment and minimum distance calculation, the vehicle controller can effectively predict potential collisions before the door is opened, achieving active protection.

[0064] This embodiment realizes active prediction and intervention of possible collisions in the door opening process by grasping the spatial information of potential collision risks in advance. Compared with the traditional method based on static distance or single time point judgment, this embodiment improves the accuracy of collision prediction, can timely identify small and fast obstacles, and takes into account the dynamic opening process of the door, making the protection measures more scientific and reasonable, avoiding false positives or lag. In addition, it also provides a reliable basis for subsequent collision risk level judgment and anti-collision strategy execution, improving the safety and intelligent level of the vehicle during use.

[0065] In some embodiments, S202 determines the obstacle trajectory based on the obstacle motion parameters, comprising: In response to determining that the obstacle is on a straight road segment and the motion trend is straight ahead, a plurality of predicted positions of the obstacle in the future time window in the straight line direction are determined in combination with the obstacle motion parameters, and a straight line type obstacle trajectory is determined based on the plurality of predicted positions; In response to determining that the obstacle is on a straight road segment and the motion trend is turning, a plurality of predicted positions of the obstacle in a future time window in a turning angle direction are determined in combination with the motion parameters of the obstacle, and a curved obstacle trajectory is determined based on the plurality of predicted positions.

[0066] Exemplarily, this step further determines the motion trend and generates the obstacle trajectory based on the motion parameters of the obstacle, which can be performed by a vehicle controller or a vehicle door control unit. The vehicle controller first acquires the real-time motion parameters of the obstacle, including position, direction, speed, acceleration, etc., and then determines the motion trend (straight or turning) of the obstacle, while analyzing in combination with the type of road where the obstacle is located (such as a straight road segment or a curved road segment). The determination can be combined with the data collected by the camera, radar or ultrasonic sensor, as well as the trend analysis of historical trajectory data, so as to determine the motion type, direction and future behavior mode of the obstacle.

[0067] Exemplarily, when the vehicle controller determines that the obstacle is on a straight road segment and the motion trend is straight, the system will calculate a plurality of predicted positions of the obstacle in a future time window according to the current position, speed and acceleration of the obstacle. These predicted positions are arranged in time sequence to form a continuous trajectory of the obstacle along a straight path, and the generated straight trajectory can accurately reflect the future motion direction of the obstacle and can be used for subsequent gap distance calculation with the vehicle door trajectory.

[0068] Exemplarily, if the vehicle controller determines that the obstacle has a turning trend on the straight road segment, the system will predict a plurality of positions of the obstacle along the turning path in a future time window in combination with the current position, speed, acceleration and turning angle information of the obstacle. These predicted points are connected in a curved sequence to form a curved obstacle trajectory, so that the trajectory prediction can fit the actual turning characteristics of the obstacle and provide a more accurate data basis for collision risk assessment.

[0069] The generated straight or curved trajectory can be further represented as a set of discrete trajectory points or a polygon envelope, and a buffer radius or uncertainty area can be expanded around the trajectory points according to the size of the obstacle or the uncertainty of the trajectory, so as to improve the reliability and safety of the anti-collision strategy.

[0070] The above method enables the vehicle controller to adaptively generate the continuous motion trajectory of the obstacle in the future, whether the obstacle is straight or turning, and provides reliable prediction for the vehicle door anti-collision control.

[0071] In some embodiments, the S300 determines the current collision risk level based on the predicted trajectory gap distance between the vehicle door and the obstacle, including: In response to the predicted trajectory gap distance being less than or equal to a preset first threshold, it is determined that the current collision risk level is level three. In response to the predicted trajectory gap distance being greater than a preset first threshold and less than or equal to a preset second threshold, it is determined that the current collision risk level is level two; In response to the predicted trajectory gap distance being greater than a preset second threshold and less than or equal to a preset third threshold, it is determined that the current collision risk level is level one.

[0072] Illustratively, this step is used to judge the collision risk level based on the predicted trajectory gap distance between the vehicle door and the obstacle. First, the predicted trajectory gap distance obtained in step S203 is obtained, which reflects the minimum space allowance between the vehicle door and the obstacle during the opening process, for example, the shortest distance between the edge of the vehicle door and the outer contour of the obstacle within the predicted time window is 0.25 meters.

[0073] Specifically, according to a preset threshold rule, the collision risk level is divided into three levels, level two and level one. When the predicted trajectory gap distance is less than or equal to the first threshold (for example, 0.3 meters), it is determined as level three collision risk, and immediate intervention measures need to be taken to prevent collision; when the gap distance is greater than the first threshold but less than or equal to the second threshold (for example, 0.3-0.6 meters), it is determined as level two collision risk, and a prompt can be provided to the driver or passenger, but the intervention measure can be moderate; when the gap distance is greater than the second threshold and less than or equal to the third threshold (for example, 0.6-1.0 meters), it is determined as level one collision risk, and the system can only provide a light prompt without active intervention.

[0074] The above method can accurately divide the collision risk level when a collision is likely to occur according to the actual value of the predicted trajectory gap distance, providing a reliable basis for subsequent execution of corresponding anti-collision strategies, thereby realizing active protection and safety control during the opening process of the vehicle door.

[0075] In some embodiments, the S300 executes the anti-collision strategy corresponding to the collision risk level, including: In response to determining that the collision risk level is level three, the vehicle door electronic locking mechanism is controlled to be in a locked state to prevent the vehicle door from opening; In response to determining that the collision risk level is level two, the vehicle door actuator is controlled to apply a reverse damping torque to slow down the opening speed of the vehicle door and delay the opening time; In response to determining that the collision risk level is level one, the vehicle door ambient light is controlled to emit light in a flashing manner to issue a collision risk prompt.

[0076] Exemplarily, when the vehicle controller judges that the predicted trajectory gap distance is less than or equal to a first threshold (for example, ≤0.3 meters), that is, the collision risk level is level three, the system immediately controls the vehicle door electronic locking mechanism to enter a locking state, preventing the vehicle door from being opened. In this state, even if the passenger tries to open the vehicle door, the electronic locking mechanism will generate resistance, so that the vehicle door remains closed, thereby preventing a collision with the obstacle. At the same time, a prompt message can be displayed on the dashboard or near the vehicle door, informing the passenger that the vehicle door cannot be opened at the moment, to further improve safety.

[0077] Exemplarily, when the predicted trajectory gap distance is greater than the first threshold but less than or equal to a second threshold (for example, 0.3-0.6 meters), that is, the collision risk level is level two, the vehicle controller controls the vehicle door actuator to apply a reverse damping torque, thereby slowing down the opening speed of the vehicle door. The actuator dynamically calculates the required damping torque according to the current angle and opening speed of the vehicle door, generates a certain reverse force when the passenger applies force to open the vehicle door, and delays the opening time of the vehicle door. This strategy not only provides enough time for the passenger to perceive the potential risk, but also reduces the possibility of the vehicle door hitting the obstacle, while reducing the risk of damage to the vehicle door itself.

[0078] Exemplarily, when the predicted trajectory gap distance is greater than the second threshold and less than or equal to a third threshold (for example, 0.6-1.0 meters), that is, the collision risk level is level one, the vehicle controller provides a visual prompt by controlling the vehicle door ambient light to flash in red, reminding the passenger to pay attention to the surrounding obstacles. At this time, there is no need to limit the opening of the vehicle door, nor to apply a damping torque, and the flashing frequency of the ambient light can be adjusted according to the gap distance, for example, the smaller the gap, the faster the flashing frequency, to enhance the warning effect.

[0079] The above-mentioned three-level protection strategy enables the vehicle to automatically judge the collision risk level according to the predicted trajectory gap distance and execute corresponding safety intervention measures, realizing a hierarchical protection from active prevention, deceleration intervention to visual prompt. Compared with the traditional single static protection method, this scheme has significant technical progress: improving the safety of the vehicle door opening process, adapting to different obstacle types and passenger operation differences, and balancing safety and user experience, to realize fine and intelligent vehicle door anti-collision control.

[0080] In some embodiments, with reference to Figure 3 , the S100 obtains obstacle motion parameters, including: S101, obtaining surrounding space information within a preset range of the vehicle door and road information; S102, determining an external target located within the preset range of the vehicle door and its position parameter and motion trend based on the surrounding space information and the road information; S103, judging whether the external target is an obstacle based on the position parameter and the motion trend; S104, in response to determining that the external target is an obstacle, determining a motion parameter of the obstacle.

[0081] Exemplarily, the method of the present embodiment is described as follows: The vehicle controller collects the surrounding space information within the preset range of the vehicle door in real time through sensors (such as millimeter wave radar, ultrasonic radar, laser radar, vehicle-mounted camera, etc.) configured on the vehicle body, and obtains the road information where the vehicle is currently located by combining with navigation map, lane line recognition and other data, such as road type (straight road, curved road, intersection, etc.), road width and number of lanes. In this way, it can ensure that the vehicle door anti-collision system has a comprehensive perception basis for the surrounding environment.

[0082] Subsequently, based on the obtained surrounding space information and road information, the space targets within the preset range of the vehicle door are identified and classified. For example, when a bicycle approaching is detected on one side of the vehicle door, the system will extract the real-time position parameters of the target (including relative vehicle body coordinates, driving direction), and further analyze its motion trend (such as straight driving, deceleration, turning, approaching or moving away from the vehicle, etc.) by combining the possible driving trajectory of the target in the road environment.

[0083] On this basis, the identified target is determined as an obstacle. Specifically, if the motion trend of the target indicates that its future trajectory may enter the vehicle door opening area, the target will be determined as an obstacle. For example, when a pedestrian is detected approaching the vehicle door along the sidewalk on the side of the vehicle, the system will determine that the pedestrian may enter the vehicle door activity range in the future, and therefore determine it as an obstacle; while if the target is an electric vehicle moving away from the vehicle, it will not be determined as an obstacle.

[0084] Finally, in response to the case where the external target is determined as an obstacle, the vehicle controller will generate the motion parameter of the obstacle based on its position parameter and motion trend. The motion parameter includes the current position, speed, acceleration, driving direction, and possible turning angle of the obstacle, etc. These parameters will be used as input data for subsequent obstacle trajectory prediction and vehicle door collision risk assessment, to ensure the accuracy and real-time performance of the anti-collision control strategy.

[0085] The embodiment realizes all-around dynamic perception of the surrounding environment before the door is opened, and accurately identifies potential obstacles. Through the fusion of door surrounding space information and road information, the integrity of the detection range is ensured, and the perception blind area is avoided; through the joint analysis of the position parameters and motion trend of external targets, the accurate identification of fast-moving small targets such as pedestrians, bicycles and electric vehicles is realized; through the obstacle judgment based on the prediction result, irrelevant fixed objects are effectively filtered, and the false alarm rate is reduced; on this basis, the motion parameters of the obstacles are further extracted, providing reliable input for trajectory prediction and risk assessment, thereby improving the real-time, accuracy and foresight of the door anti-collision, and significantly improving the safety and use experience of the user.

[0086] In some embodiments, the S300, based on the predicted trajectory gap distance between the door and the obstacle, determines the current collision risk level, and after executing the anti-collision strategy corresponding to the collision risk level, further comprises: packaging the collision risk level, the corresponding anti-collision strategy and the trigger time information to form an event log; uploading the event log to a cloud server through a vehicle-mounted communication module; storing the event log in the cloud and statistically analyzing based on historical log data.

[0087] Exemplarily, after completing the collision risk judgment and executing the corresponding anti-collision strategy, the system generates an event log and uploads and manages it. Specifically, first, the relevant information is packaged in the vehicle to generate a structured event log. The event log at least includes event unique ID, trigger time, vehicle identification (desensitization processing), trigger position, door state (angle, angular velocity), predicted trajectory gap distance and its occurrence time point, determined collision risk level, actually executed anti-collision strategy and parameters (such as locking, damping torque, light frequency), involved obstacle information, key sensors and their confidence, system version, artificial intervention situation and other diagnostic information. The log can adopt a structured format (such as JSON), and local clock and synchronous UTC timestamp are recorded at the same time to ensure time sequence consistency.

[0088] After the log is generated, the vehicle side executes serialization, signature and caching. The log is serialized into JSON, the sensitive fields such as vehicle identification are hashed or desensitized, and the digital signature is made through the device private key to ensure the integrity and source credibility. The log can also be compressed to save bandwidth. For high-priority events (such as level three risk), the system will preferentially attempt real-time uploading; if the network is unavailable or the event level is low, the log will be written into the local persistent queue, and the uploading retry will be performed by using the backoff or periodic batch strategy. All logs carry a unique message ID to support idempotent processing and deduplication.

[0089] On the vehicle side, the system can transmit through cellular networks (4G / 5G), Wi-Fi, or V2X, and adopt different strategies according to the priority of the event. For level three events, the system will immediately upload through an encrypted channel and require cloud confirmation, and if it fails, it will enable a backup low-bandwidth channel (such as SMS) to notify; level two events can be uploaded in real time or with a small delay in batches; level one events can be delayed to upload in idle periods or in Wi-Fi environments to reduce communication overhead. The upload process uses a reliable message protocol (such as MQTT QoS2 or HTTPS POST) to ensure that the cloud returns a receipt and returns the event ID, thereby ensuring the reliability of message delivery.

[0090] After the cloud receives the log, it first performs signature verification and field checking, and then writes it to a hierarchical storage system. The original event log is archived in chronological order for easy tracing and evidence collection; key information is written to a structured database to support fast queries; high-frequency time series data such as vehicle door angle curves, minimum distance (predicted trajectory gap distance) over time are stored in a time series database for playback and analysis. At the same time, the cloud will record metadata such as upload time, vehicle authentication status, and processing results, and sensitive information involving individuals or vehicles will be desensitized or access-controlled to meet compliance and privacy protection requirements.

[0091] In addition, the cloud can also support real-time alerts, statistical aggregation, and model optimization. For example, vehicles that frequently experience level three events or high-risk areas are warned; statistical analysis of different vehicle models, firmware versions, and geographic locations is performed to generate heat maps and trend reports; combining external feedback to compare false positive and false negative rates to form system performance evaluation indicators; and using high-confidence events as training samples to improve obstacle prediction models and adaptive threshold mechanisms. Analysis results can be provided to product, safety, or engineering teams through dashboards, visual reports, and other means, and used for compliance reports.

[0092] It should be noted that, to ensure privacy and compliance, the entire transmission process can be end-to-end encrypted, with vehicle-side private keys stored in a hardware security module, and the cloud ensuring data security through strict access control and audit strategies. Sensitive information such as precise GPS or VIN can be blurred or stored hierarchically according to regulations. The system also establishes data retention and deletion mechanisms, such as saving original logs for only 90 days, while statistical results can be saved for several years to meet different compliance and regulatory requirements.

[0093] Optionally, the system also needs to have the reliability guarantee under the network interruption and abnormal scenarios. When the communication is interrupted, the vehicle will cache the log in the local queue and retry in the order of priority. When the storage is close to the upper limit, low-priority events can be discarded, and the discarding situation is recorded to ensure that high-priority events are not lost. The uploading adopts an idempotent mechanism, and the vehicle end will delete the local cache only after the cloud end returns an acknowledgement (ACK), avoiding repeated reporting. In this way, even in the case of network anomalies or system anomalies, the integrity and reliability of critical events can still be guaranteed.

[0094] By forming a structured event log of the collision risk and the protection action and reporting it to the cloud, the embodiment realizes real-time protection at the vehicle end, global perception at the cloud end, and closed-loop optimization: the vehicle can take graded protection measures locally, the cloud can statistically analyze high-risk areas based on historical data, evaluate and improve sensor fusion and prediction models, and support remote optimization and safety management, thereby continuously reducing the false positive / negative rate, improving system reliability and user experience, and providing strong data support for product upgrading, after-sales maintenance, and regulatory compliance.

[0095] In some embodiments, the control of the vehicle door actuator to apply a reverse damping torque to slow down the opening speed of the vehicle door and delay the opening timing comprises: determining the door opening behavior characteristics of the user based on the vehicle door motion parameters; analyzing and dividing the door opening behavior characteristics of the user, and dynamically adjusting the reverse damping torque to slow down the opening speed of the vehicle door and delay the opening timing.

[0096] In terms of vehicle door anti-collision adjustment, there is a contradiction in the related art that the user cannot protect in time when opening the door quickly, and the slow opening of the door causes excessive prompts, resulting in a risk of collision between the vehicle door and obstacles during the opening process.

[0097] To address the above problems, the vehicle controller of the embodiment of the application obtains the motion parameters such as the opening angle, angular velocity, and angular acceleration of the vehicle door in real time through the angle sensor, angular velocity sensor, or torque sensor set at the vehicle door hinge, to represent the opening speed and force of the user.

[0098] Secondly, based on the above vehicle door motion parameters, the vehicle controller predicts the motion trend of the vehicle door within a preset time window in the future. For example, when the vehicle door angular velocity is greater than 50° / s and the angular acceleration is positive, it indicates that the user is opening the door quickly, and the vehicle door will be opened significantly within 1s; when the vehicle door angular velocity is less than 10° / s and the angular acceleration is close to zero, it indicates that the user is opening the door slowly, and the vehicle door will only move slowly within 3s in the future.

[0099] Further, the vehicle controller combines the predicted door movement trend with the obstacle trajectory to re-evaluate the risk and dynamically adjust the anti-collision intervention mode.

[0100] Exemplarily, a fast door opening scenario: when the door angular velocity is greater than or equal to 50° / s, it is determined that there is a medium or higher collision risk, and a reverse damping torque greater than 20 N·m is immediately applied to the door actuator or the electronic locking mechanism of the door is controlled to enter the locking state to forcibly slow down or stop the door opening; A slow door opening scenario: when the door angular velocity is less than or equal to 10° / s, it is determined that there is a low collision risk, and only a slight damping torque less than 5 N·m is applied to the door actuator to remind the user to avoid excessive intervention; A medium-speed door opening scenario: when the door angular velocity is between 10-50° / s, the system adjusts the reverse damping torque in real time according to the change trend of the predicted trajectory gap, for example, dynamically changes in the range of 5-20 N·m, to balance safety and comfort.

[0101] The above method, the system can not only respond in time when the obstacle approaches, but also flexibly adjust the intervention strategy according to the actual door opening habit of the user, thereby solving the contradiction between "fast door opening and not enough protection" and "slow door opening and excessive prompting" in the related art, and significantly improving the intelligence and human-computer interaction experience of the door anti-collision control.

[0102] It should be noted that the method of the embodiments of the present application can be executed by a single device, such as a computer or a server. The method of the embodiments of the present application can also be applied to a distributed scenario and completed by multiple devices cooperating with each other. In this distributed scenario, one of the multiple devices can only execute one or more steps in the method of the embodiments of the present application, and the multiple devices can interact with each other to complete the method.

[0103] It should be noted that some embodiments of the present application have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than the order described above and still achieve the desired result. In addition, the processes depicted in the figures do not necessarily require the particular order shown or sequential order to achieve the desired results. In certain implementations, multitasking and parallel processing can be advantageous.

[0104] Based on the same inventive concept, referring to Figure 4 Corresponding to any of the above-mentioned embodiment methods, the present application further provides a door anti-collision control device, comprising: an acquisition module 410, an analysis module 420 and an execution module 430. The acquisition module 410 is configured to acquire a door movement parameter and an obstacle movement parameter; The analysis module 420 is configured to determine a predicted trajectory gap distance between the door and the obstacle based on the acquired door movement parameter and obstacle movement parameter; The execution module 430 is configured to determine a current collision risk level based on the predicted trajectory gap distance between the door and the obstacle, and execute an anti-collision strategy corresponding to the collision risk level.

[0105] Further, the acquisition module 410 is further configured to: acquire surrounding space information within a preset range of the door and road information; determine an external target and its position parameter and movement trend within the preset range of the door based on the surrounding space information and road information; determine whether the external target is an obstacle based on the position parameter and movement trend; in response to determining that the external target is an obstacle, determine the movement parameter of the obstacle.

[0106] Further, the analysis module 420 is further configured to: determine a door predicted movement trajectory based on the door movement parameter; determine an obstacle trajectory based on the obstacle movement parameter; align the door predicted movement trajectory and the obstacle trajectory in time, and determine the minimum distance between the door predicted movement trajectory and the obstacle trajectory as the predicted trajectory gap distance.

[0107] Further, the analysis module 420 is further configured to: in response to determining that the obstacle is on a straight road segment and the movement trend is straight ahead, determine a plurality of predicted positions of the obstacle in a future time window in a straight line direction based on the obstacle movement parameter, and determine a straight line type obstacle trajectory based on the plurality of predicted positions; in response to determining that the obstacle is on a straight road segment and the movement trend is turning, determine a plurality of predicted positions of the obstacle in a future time window in a turning angle direction based on the obstacle movement parameter, and determine a curve type obstacle trajectory based on the plurality of predicted positions.

[0108] Further, the execution module 430 is further configured to: in response to the predicted trajectory gap distance being less than or equal to a preset first threshold value, determine that the current collision risk level is level three; in response to the predicted trajectory gap distance being greater than the preset first threshold value and less than or equal to a preset second threshold value, determine that the current collision risk level is level two; In response to the predicted trajectory gap distance being greater than a preset second threshold and less than or equal to a preset third threshold, it is determined that the current collision risk level is level one.

[0109] Further, the execution module 430 is further configured to: In response to determining that the collision risk level is level three, the vehicle door electronic locking mechanism is controlled to be in a locked state to prevent the vehicle door from being opened; In response to determining that the collision risk level is level two, the vehicle door actuator is controlled to apply a reverse damping torque to slow down the opening speed of the vehicle door and delay the opening timing; In response to determining that the collision risk level is level one, the vehicle door ambient light is controlled to emit light in a flashing manner to issue a collision risk prompt.

[0110] Further, the execution module 430 is further configured to: Determine the user's door opening behavior characteristics based on the vehicle door motion parameters; Analyze and divide the user's door opening behavior characteristics, and dynamically adjust the reverse damping torque to slow down the opening speed of the vehicle door and delay the opening timing.

[0111] Further, the execution module 430 is further configured to: Pack the collision risk level, the corresponding anti-collision strategy and the trigger time information into an event log; Upload the event log to a cloud server through a vehicle-mounted communication module; Store the event log in the cloud and statistically analyze based on historical log data.

[0112] For the convenience of description, the above device is described as various modules respectively described in function. Of course, in the implementation of the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0113] The device of the above embodiment is used to implement the corresponding vehicle door anti-collision control method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be described here.

[0114] Based on the same inventive concept, corresponding to any of the above embodiment methods, the present application also provides an electronic device, comprising 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 door anti-collision control method of any one of the above embodiments.

[0115] Figure 5A more specific electronic device hardware structure schematic diagram provided by the embodiment is shown. The device can include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other through the bus 1050 for internal communication.

[0116] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, and is configured to execute related programs to implement the technical solutions provided by the embodiments of the present specification.

[0117] The memory 1020 can be implemented by a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, etc. The memory 1020 can store an operating system and other application programs. When the technical solutions provided by the embodiments of the present specification are implemented by software or firmware, the related program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0118] The input / output interface 1030 is configured to connect an input / output module to realize information input and output. The input / output module can be configured as a component in the device (not shown in the figure) or can be externally connected to the device to provide corresponding functions. The input device can include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device can include a display, a speaker, a vibrator, an indicator light, etc.

[0119] The communication interface 1040 is configured to connect a communication module (not shown in the figure) to realize the communication interaction between the device and other devices. The communication module can realize communication through a wired manner (such as USB, network cable, etc.) or through a wireless manner (such as mobile network, WIFI, Bluetooth, etc.).

[0120] The bus 1050 includes a channel to transmit information between various components (such as the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040) of the device.

[0121] It should be noted that although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040 and the bus 1050, in the specific implementation process, the device can also include other components necessary for normal operation. In addition, those skilled in the art can understand that the above device can also only contain components necessary to implement the embodiments of the present application, and does not necessarily contain all the components shown in the figure.

[0122] The electronic device of the above embodiment is used to implement the corresponding vehicle door anti-collision control method in any of the preceding embodiments, and has the beneficial effects of the corresponding method embodiments, which are not repeated here.

[0123] Based on the same inventive concept, the present application also provides a non-transitory computer readable storage medium, which stores computer instructions for causing the computer to execute the vehicle door anti-collision control method according to any of the above embodiments.

[0124] The computer readable medium of the present embodiment includes permanent and non-permanent, removable and non-removable media, which can be realized by any method or technology to store information. The information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are 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 memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0125] The computer instructions stored in the storage medium of the above embodiment are used to cause the computer to execute the vehicle door anti-collision control method according to any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which are not repeated here.

[0126] Based on the same inventive concept, the present application also provides a vehicle comprising the electronic device as described above.

[0127] The vehicle has the same beneficial effects as the electronic device in the above embodiment, and is not repeated here.

[0128] It can be understood that, before using the technical solutions of various embodiments in the present application, the user will be informed of the type, use range, use scenario, etc. of the personal information involved in a proper manner, and the authorization of the user will be obtained.

[0129] For example, in response to receiving the active request of the user, the user is sent prompt information to explicitly prompt the user that the operation requested to be performed will require obtaining and using the personal information of the user. Thus, the user can voluntarily choose whether to provide the personal information to the software or hardware such as an electronic device, an application program, a server or a storage medium, etc. performing the operation of the technical solutions of the present application according to the prompt information.

[0130] As an optional but non-limiting implementation manner, in response to accepting the active request of the user, the manner of sending the prompt information to the user may, for example, be a pop-up window manner, and the prompt information may, for example, be presented in the form of text in the pop-up window. In addition, the pop-up window may also carry selection controls for the user to select "agree" or "disagree" to provide the personal information to the electronic device.

[0131] It can be understood that the above notification and obtaining of the authorization of the user are only illustrative, and do not limit the implementation manners of the present application, and other manners meeting the relevant laws and regulations can also be applied to the implementation manners of the present application.

[0132] Those skilled in the art will understand that the discussion of any of the above embodiments is merely exemplary, and is not intended to suggest that the scope of the present application (including claims) is limited to these examples; the above embodiments or technical features among different embodiments can also be combined, steps can be implemented in any order, and there are many other changes to the aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of brevity. Therefore, the true scope of the present application should be defined only by the claims.

[0133] In addition, in order to simplify the description and discussion, and so as not to make the embodiments of the present application difficult to understand, the known power / ground connections of integrated circuit (IC) chips and other components can or can not be shown in the provided drawings. In addition, the devices can be shown in the form of block diagrams in order to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented for the embodiments of the present application (i.e. these details should be fully within the understanding of those skilled in the art). Where specific details (e.g. circuits) are set forth in order to describe an illustrative embodiment of the present application, it will be apparent to those skilled in the art that the embodiments of the present application can be practiced without these specific details or with variations on these specific details. Therefore, these descriptions should be considered as illustrative rather than limiting.

[0134] While the present application has been described in connection with certain embodiments thereof, many modifications, substitutions, changes, and of forms will be apparent to those of ordinary skill in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) can use the embodiments discussed.

[0135] Embodiments of the present application are intended to cover all such alterations, modifications, and variations as they can come within the scope of the appended claims. Accordingly, although specific embodiments have been furthered in connection with the present application, any omission, substitution, or change, in principle and in form, made to the present application should be included in the scope of the present application.

Claims

1. A vehicle door collision avoidance control method characterized by comprising: The method comprises: acquiring door movement parameters and obstacle movement parameters; determining a predicted trajectory gap distance between the door and the obstacle based on the acquired door movement parameters and obstacle movement parameters; judging a current collision risk level based on the predicted trajectory gap distance between the door and the obstacle, and executing an anti-collision strategy corresponding to the collision risk level; wherein the anti-collision strategy is a strategy of intervening in the opening of the door based on the collision risk level to reduce the risk of door collision.

2. The vehicle door collision avoidance control method according to claim 1, characterized by, The method of determining the predicted trajectory gap distance between the door and the obstacle based on the acquired door movement parameters and obstacle movement parameters comprises: determining a door predicted movement trajectory based on the door movement parameters; determining an obstacle trajectory based on the obstacle movement parameters; aligning the door predicted movement trajectory and the obstacle trajectory in time progress, and determining the minimum distance between the door predicted movement trajectory and the obstacle trajectory as the predicted trajectory gap distance.

3. The vehicle door collision avoidance control method according to claim 2, characterized by, The method of determining the obstacle trajectory based on the obstacle movement parameters comprises: in response to determining that the obstacle is on a straight road segment and the movement trend is straight, determining a plurality of predicted positions of the obstacle in a future time window in a straight line direction in combination with the obstacle movement parameters, and determining a straight line type obstacle trajectory based on the plurality of predicted positions; in response to determining that the obstacle is on a straight road segment and the movement trend is turning, determining a plurality of predicted positions of the obstacle in a future time window in a turning angle direction in combination with the obstacle movement parameters, and determining a curve type obstacle trajectory based on the plurality of predicted positions.

4. The vehicle door collision avoidance control method according to claim 1, characterized by, The method of judging the current collision risk level based on the predicted trajectory gap distance between the door and the obstacle comprises: in response to the predicted trajectory gap distance being less than or equal to a preset first threshold, determining that the current collision risk level is level three; in response to the predicted trajectory gap distance being greater than the preset first threshold and less than or equal to a preset second threshold, determining that the current collision risk level is level two; in response to the predicted trajectory gap distance being greater than the preset second threshold and less than or equal to a preset third threshold, determining that the current collision risk level is level one.

5. The vehicle door collision avoidance control method according to claim 4, characterized by, The method of executing the anti-collision strategy corresponding to the collision risk level comprises: in response to determining that the collision risk level is level three, controlling the door electronic locking mechanism to be in a locked state to prevent the door from being opened; in response to determining that the collision risk level is level two, controlling the door actuator to apply a reverse damping torque to slow down the opening speed of the door and delay the opening timing; in response to determining that the collision risk level is level one, controlling the door ambient light to emit light in a flashing manner to issue a collision risk prompt.

6. The vehicle door collision avoidance control method according to claim 1, characterized by, The method of acquiring the obstacle movement parameters comprises: acquiring surrounding space information within a preset range of the door and road information; determining an external target located within the preset range of the door and its position parameters and movement trend based on the surrounding space information and the road information; judging whether the external target is an obstacle based on the position parameters and the movement trend; in response to determining that the external target is an obstacle, determining the movement parameters of the obstacle.

7. The vehicle door collision avoidance control method according to claim 1, characterized by, The method further comprises: packaging the collision risk level, the corresponding anti-collision strategy and the triggering time information to form an event log; uploading the event log to a cloud server through a vehicle-mounted communication module; storing the event log in the cloud and performing statistical analysis based on historical log data.

8. The vehicle door collision avoidance control method according to claim 5, characterized by, The method further comprises: determining the user's door opening behavior characteristics based on the door movement parameters; analyzing and dividing the user's door opening behavior characteristics, and dynamically adjusting the reverse damping torque to slow down the opening speed of the door and delay the opening timing.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the method of any one of claims 1 to 7 when executing the program.

10. A vehicle characterized by comprising: The electronic device of claim 9 is included.

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