Collision detection method, system, device and medium

Abstract

The invention provides a collision detection method, system and device and a medium, and relates to the technical field of vehicles, the method comprises the following steps: determining a first influence quantity of vehicle braking on vehicle longitudinal acceleration according to a relation curve between a braking torque and vehicle longitudinal deceleration and a current braking torque of a vehicle; according to the mapping relation between the suspension compression height and the shock absorber rigidity and the current suspension compression height of the vehicle, the shock absorber rigidity is determined; determining a second influence quantity of the sudden change of the road surface on the longitudinal acceleration of the vehicle according to the damper rigidity and the vehicle mass; according to the first influence quantity, the second influence quantity and the longitudinal acceleration of the vehicle, determining the longitudinal target acceleration of the vehicle after the brake influence and the road surface sudden change influence are corrected; according to the relationship between the target acceleration and a preset threshold value corresponding to the own acceleration direction, determining a collision event confidence coefficient; and according to the collision event confidence, determining whether the vehicle is collided so as to avoid missing detection of the collision event.

Description

Technical Field

[0001] The present application relates to the technical field of vehicles, and specifically relates to a collision detection method, system, device and medium. Background Art

[0002] With the continuous increase in the penetration rate of intelligent connected vehicles, the attribute of a car is no longer simply a means of transportation. Consumers have higher and higher expectations for the intelligent functions of cars, and also have higher and higher requirements for the intelligent services of car brands. Correspondingly, the intelligent level of cars is also getting higher and higher. Although the increasing intelligent level of cars provides better support for avoiding traffic accidents, traffic accidents still cannot be completely eliminated.

[0003] Currently, there is an E-call system for emergency calls after a traffic accident occurs, but it is only triggered for major accidents where the airbag will pop out. When the intelligent assisted driving related functions are turned on, the system can identify limited risks and avoid collisions, but this system does not have an accident recognition function. For the surround view system, although collision recognition can be performed through image recognition technology, when the object being collided is an irregular object, the recognition effect is poor, and due to the limitation of the video frame rate, there is also a problem that accidents with quick contact and separation cannot be recognized. Summary of the Invention

[0004] In view of this, the present application provides a collision detection method, system, device and medium, aiming to solve or partially solve the problems existing in the background art.

[0005] The first aspect of the present application provides a collision detection method, and the method includes: Determine a first influence amount of vehicle braking on the vehicle longitudinal acceleration according to the relationship curve between the braking torque and the vehicle longitudinal deceleration and the current braking torque of the vehicle; Determine the shock absorber stiffness according to the mapping relationship between the suspension compression height and the shock absorber stiffness and the current suspension compression height of the vehicle; Determine a second influence amount of road surface mutation on the vehicle longitudinal acceleration according to the shock absorber stiffness and the vehicle mass; Determine the target acceleration in the vehicle longitudinal direction after correcting the braking influence and the road surface mutation influence according to the first influence amount, the second influence amount and the vehicle longitudinal acceleration; Determine the collision event confidence according to the relationship between the target acceleration and the preset threshold corresponding to the direction of its own acceleration; Determine whether the vehicle has a collision according to the collision event confidence.

[0006] The second aspect of the present application provides a collision detection system, and the system includes: A first influence quantity determination module, configured to determine a first influence quantity of vehicle braking on the vehicle longitudinal acceleration according to a relationship curve between a braking torque and a vehicle longitudinal deceleration and the current braking torque of the vehicle; A shock absorber stiffness determination module, configured to determine a shock absorber stiffness according to a mapping relationship between a suspension compression height and a shock absorber stiffness and the current suspension compression height of the vehicle; A second influence quantity determination module, configured to determine a second influence quantity of a road surface mutation on the vehicle longitudinal acceleration according to the shock absorber stiffness and the vehicle mass; A first acceleration determination module, configured to determine a target acceleration in the vehicle longitudinal direction after correcting for the braking influence and the road surface mutation influence according to the first influence quantity, the second influence quantity, and the vehicle longitudinal acceleration; A confidence determination module, configured to determine a collision event confidence according to a relationship between the target acceleration and a preset threshold corresponding to the direction of its own acceleration; A collision determination module, configured to determine whether a vehicle collision has occurred according to the collision event confidence.

[0007] A third aspect of the present application provides an electronic device, including: a processor, a memory, and a computer program stored on the memory and running on the processor, where when the computer program is executed by the processor, the steps in a collision detection method as described in the first aspect of the present application are implemented.

[0008] A fourth aspect of the present application provides a computer-readable storage medium, on which a computer program is stored, where when the computer program is executed by a processor, the steps in a collision detection method as described in the first aspect of the present application are implemented.

[0009] A collision detection method provided by the present application has the following advantages: A collision detection method provided by an embodiment of the present application first determines a first influence amount of vehicle braking on the vehicle longitudinal acceleration according to the relationship curve between the braking torque and the vehicle longitudinal deceleration and the current braking torque of the vehicle; determines the shock absorber stiffness according to the mapping relationship between the suspension compression height and the shock absorber stiffness and the current suspension compression height of the vehicle; determines a second influence amount of road surface mutation on the vehicle longitudinal acceleration according to the shock absorber stiffness and the vehicle mass; determines the target acceleration in the vehicle longitudinal direction after correcting the braking influence and the road surface mutation influence according to the first influence amount, the second influence amount and the vehicle longitudinal acceleration; determines the collision event confidence according to the relationship between the target acceleration and the preset threshold corresponding to the direction of its own acceleration; and determines whether a collision occurs to the vehicle according to the collision event confidence. Thus, the present application first collects the total acceleration of the vehicle through the IMU of the vehicle, and then corrects the total acceleration based on the state information of the vehicle, excluding the parts of the total acceleration of the vehicle affected by braking and road surface mutation. Finally, a target acceleration in the vehicle longitudinal direction is obtained. By comparing the target acceleration with a preset threshold set in advance, the confidence of the current collision event is determined. A simple way is that when the target acceleration is a positive acceleration (taking a positive value), the higher the degree of exceeding a certain preset threshold, the higher the corresponding confidence; when the target acceleration is a negative acceleration (taking a negative value), the higher the degree of being lower than a certain preset threshold, the higher the corresponding confidence. After the obtained confidence reaches a certain value (such as 90%), it is determined that a collision has occurred to the vehicle. Since the collision detection method provided by the present application determines whether a collision occurs to the vehicle based on the acceleration after eliminating the influence of vehicle braking and ground mutation on the vehicle acceleration, it can avoid the situation where the recognition effect of the surround view system is poor when the collision is an abnormal object, and can avoid the problem that due to the limitation of the number of video frames, an accident with rapid contact and separation cannot be recognized, so as to achieve the purpose of avoiding missed detection of collision events. At the same time, for the problem that it is difficult to distinguish the misoperation working conditions (such as when the user suddenly brakes emergently on the bumpy road surface, resulting in a mutation of the acceleration) in the collision detection method based on the total acceleration of the vehicle itself, the method of the present application for determining whether a collision occurs to the vehicle based on the acceleration after eliminating the influence of vehicle braking and ground mutation on the vehicle acceleration can effectively avoid the situation of misdetecting a collision in such misoperation working conditions. At the same time, based on the detection result, the collision event is reported to the manufacturer service background in a timely manner, and accident handling guidelines, rescue, maintenance service reservation, etc. are provided to the users who have had traffic accidents in a timely manner, which can greatly improve the user satisfaction and enhance the brand technology image. In addition, the collision detection method provided by the present application only needs the IMU of the vehicle to provide the total acceleration of the vehicle for subsequent algorithm correction, without relying on collision sensors, image sensors and radar sensors, and can effectively reduce the system cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] To more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments of the present application. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0011] Figure 1 Flowchart of a collision detection method shown in an embodiment of the present application; Figure 2 Schematic diagram of the relationship curve between the braking torque and the vehicle longitudinal deceleration in a collision detection method shown in an embodiment of the present application; Figure 3 Schematic diagram of the relationship curve between the steering wheel angle and the turning radius in a collision detection method shown in an embodiment of the present application; Figure 4 Another flowchart of a collision detection method shown in an embodiment of the present application; Figure 5 Schematic diagram of acceleration correction in the first scenario of a collision detection method shown in an embodiment of the present application; Figure 6 Schematic diagram of acceleration correction in the second scenario of a collision detection method shown in an embodiment of the present application; Figure 7 Schematic diagram of a collision detection system shown in an embodiment of the present application. Detailed implementation manners

[0012] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application.

[0013] Refer to Figure 1 , Figure 1 which is the flowchart of a collision detection method shown in an embodiment of the present application. As Figure 1 shown, the method includes: Step S1: Determine the first influence amount of vehicle braking on the vehicle longitudinal acceleration according to the relationship curve between the braking torque and the vehicle longitudinal deceleration and the current braking torque of the vehicle.

[0014] In this embodiment, as Figure 2As shown, the present application pre - establishes a relationship curve between the braking torque of the vehicle and the vehicle's longitudinal deceleration. During the normal driving of the vehicle, relevant information collected by the vehicle's sensors is used to determine the current braking torque of the vehicle, and based on the relationship curve pre - established by the present application between the braking torque of the vehicle and the vehicle's longitudinal deceleration, the vehicle's longitudinal deceleration corresponding to the current braking torque of the vehicle is determined. This vehicle's longitudinal deceleration is the first influence quantity on the vehicle's longitudinal acceleration caused by vehicle braking.

[0015] Step S2: Determine the shock absorber stiffness according to the mapping relationship between the suspension compression height and the shock absorber stiffness and the current suspension compression height of the vehicle.

[0016] In this embodiment, the present application also pre - establishes a mapping relationship between the suspension compression height of the vehicle and the shock absorber stiffness. During the normal driving of the vehicle, relevant information collected by the vehicle's sensors is used to determine the suspension compression height of each current suspension of the vehicle, and based on the mapping relationship pre - established by the present application between the suspension compression height of the vehicle and the shock absorber stiffness, the shock absorber stiffness of each shock absorber corresponding to the suspension compression height of each current suspension of the vehicle is determined.

[0017] Step S3: Determine the second influence quantity on the vehicle's longitudinal acceleration caused by road surface mutation according to the shock absorber stiffness and the vehicle mass.

[0018] In this embodiment, based on the vehicle mass and the shock absorber stiffness of each current shock absorber of the vehicle determined in step S2, an acceleration is calculated through a first algorithm. This acceleration is the second influence quantity on the vehicle's longitudinal acceleration caused by road surface mutation. Among them, the expression of the first algorithm is: , where is the second influence quantity, k is the proportionality coefficient, is the suspension height change of the i - th suspension, m is the vehicle mass, is the shock absorber stiffness of the i - th shock absorber.

[0019] Step S4: Determine the target acceleration in the vehicle's longitudinal direction after correcting for the braking influence and the road surface mutation influence according to the first influence quantity, the second influence quantity, and the vehicle's longitudinal acceleration.

[0020] In this embodiment, after the first influence quantity and the second influence quantity of the vehicle are determined through steps S1 to S3, the vehicle's longitudinal acceleration collected by the vehicle's IMU is subtracted by this first influence quantity and the second influence quantity to obtain the target acceleration in the vehicle's longitudinal direction after correcting for the braking influence and the road surface mutation influence.

[0021] In this embodiment, another alternative implementation for determining the target acceleration in the longitudinal direction of the vehicle may be to correct the acceleration in the longitudinal direction of the vehicle collected in real time according to the state information of the vehicle through calculation formulas such as looking up empirical values in a table, and / or quadratic polynomials, and / or piecewise functions, and / or exponential functions, and / or trigonometric functions, etc., to obtain the target acceleration in the longitudinal direction of the vehicle after correcting the braking influence and the influence of road surface mutations.

[0022] Step S5: Determine the collision event confidence level according to the relationship between the target acceleration and the preset threshold corresponding to the direction of its own acceleration.

[0023] In this embodiment, after obtaining the target acceleration in the longitudinal direction of the vehicle after eliminating the braking influence and the influence of road surface mutations through steps S1 to S4, determine the direction of the target acceleration. For the positive target acceleration and the negative target acceleration, this application respectively sets corresponding preset thresholds. For example, the positive preset threshold is 2 and the negative one is -1.2. First, determine the direction of the target acceleration, and then compare the target acceleration with the preset threshold corresponding to the direction of its own acceleration. Based on the relationship between the target acceleration and the preset threshold, determine the collision event confidence level. An alternative implementation is: when the target acceleration is positive, the greater the degree to which the target acceleration exceeds the preset threshold corresponding to the direction of its own acceleration, the higher the collision event confidence level; when the target acceleration is negative, the greater the degree to which the target acceleration is lower than the preset threshold corresponding to the direction of its own acceleration, the higher the collision event confidence level. A simple implementation is to establish a mapping relationship between various degrees to which the positive target acceleration exceeds the preset threshold corresponding to the direction of its own acceleration and each collision event confidence level value, and establish a mapping relationship between various degrees to which the negative target acceleration is lower than the preset threshold corresponding to the direction of its own acceleration and each collision event confidence level value. Based on these two established mapping relationships and the determined target acceleration in the longitudinal direction of the vehicle, determine the corresponding collision event confidence level. Among them, the preset threshold can be set according to the actual scenario and will not be specifically limited here.

[0024] Step S6: Determine whether the vehicle has collided according to the collision event confidence level.

[0025] In this embodiment, based on the collision event confidence level obtained in step S5, determine whether the vehicle has collided currently. An alternative implementation is: preset a threshold (such as 90%), and then determine whether the obtained collision event confidence level is greater than or equal to the threshold. If it is greater than or equal to the threshold, determine that the vehicle has collided currently. At this time, report the collision event of the vehicle to the manufacturer's service background in a timely manner, and provide accident handling guidance, rescue, maintenance service reservation, etc. to the users who have had traffic accidents in a timely manner, so as to achieve the purpose of improving user satisfaction.

[0026] A collision detection method provided by an embodiment of the present application first determines a first influence amount of vehicle braking on the vehicle longitudinal acceleration according to the relationship curve between the braking torque and the vehicle longitudinal deceleration and the current braking torque of the vehicle; determines the shock absorber stiffness according to the mapping relationship between the suspension compression height and the shock absorber stiffness and the current suspension compression height of the vehicle; determines a second influence amount of road surface mutation on the vehicle longitudinal acceleration according to the shock absorber stiffness and the vehicle mass; determines the target acceleration in the vehicle longitudinal direction after correcting the braking influence and the road surface mutation influence according to the first influence amount, the second influence amount and the vehicle longitudinal acceleration; determines the collision event confidence according to the relationship between the target acceleration and a preset threshold corresponding to the direction of its own acceleration; and determines whether a collision occurs to the vehicle according to the collision event confidence. Thus, the present application first collects the total acceleration of the vehicle through the IMU of the vehicle, and then corrects the total acceleration based on the state information of the vehicle, excluding the parts of the total acceleration of the vehicle affected by braking and road surface mutation, and finally obtains a target acceleration in the vehicle longitudinal direction. By comparing the target acceleration with a preset threshold set in advance, the confidence of the current collision event is determined. A simple way is that when the target acceleration is a positive acceleration (taking a positive value), it is determined that the higher the degree of exceeding a certain preset threshold, the higher the corresponding confidence; when the target acceleration is a negative acceleration (taking a negative value), it is determined that the higher the degree of being lower than a certain preset threshold, the higher the corresponding confidence. After the obtained confidence reaches a certain value (such as 90%), it is determined that a collision has occurred to the vehicle. Since the collision detection method provided by the present application determines whether a collision occurs to the vehicle based on the acceleration after eliminating the influence of vehicle braking and ground mutation on the vehicle acceleration, it can avoid the situation where the recognition effect of the surround view system is poor when the collision is an abnormal object, and can avoid the problem that the accident of rapid contact and separation cannot be recognized due to the limitation of the video frame number, so as to achieve the purpose of avoiding missing detection of collision events. At the same time, for the problem that it is difficult to distinguish the misoperation conditions (such as the user suddenly performs emergency braking on the bumpy road surface, resulting in a sudden change in acceleration) in the collision detection method based on the total acceleration of the vehicle itself, the method of the present application for determining whether a collision occurs to the vehicle based on the acceleration after eliminating the influence of vehicle braking and ground mutation on the vehicle acceleration can effectively avoid the situation of misdetecting a collision in such misoperation conditions. At the same time, based on the detection result, the collision event is reported to the manufacturer service background in a timely manner, and accident handling guidance, rescue, maintenance service reservation, etc. are provided to the users who have had traffic accidents in a timely manner, which can greatly improve the user satisfaction and enhance the brand technology image. In addition, the collision detection method provided by the present application only needs the IMU of the vehicle to provide the total acceleration of the vehicle for subsequent algorithm correction, without relying on collision sensors, image sensors and radar sensors, and can effectively reduce the system cost.

[0027] Combined with the above embodiments, in one implementation, the embodiments of the present application further provide a collision detection method. In this collision detection method, step S5 may include steps S51 to S54: Step S51: Compare the target acceleration in the longitudinal direction of the vehicle with the preset threshold corresponding to the direction of its own acceleration.

[0028] In this embodiment, since the acceleration in the longitudinal direction of the vehicle has directions including the forward positive direction and the backward negative direction, the present application sets corresponding preset thresholds for the forward target acceleration and the backward target acceleration respectively. Compare the target acceleration in the longitudinal direction of the vehicle obtained through step S4 with the preset threshold corresponding to the direction of its own acceleration.

[0029] Step S52: When the vehicle has a target acceleration that meets the set conditions, determine the duration from the occurrence moment when the target acceleration in the longitudinal direction of the vehicle continuously meets the set conditions. The set condition is that the absolute value of the target acceleration is greater than the absolute value of the preset threshold corresponding to the direction of its own acceleration.

[0030] In this embodiment, when the vehicle has a target acceleration in the longitudinal direction that meets the set conditions, determine the duration from the moment when the target acceleration that meets the set conditions appears, and the subsequent target acceleration in the longitudinal direction of the vehicle continuously meets the set conditions. Among them, the set condition is that the absolute value of the target acceleration is greater than the absolute value of the preset threshold corresponding to the direction of its own acceleration, that is, when the vehicle has a target acceleration whose absolute value is greater than the absolute value of the preset threshold corresponding to the direction of its own acceleration, starting from the moment when the target acceleration appears, determine whether the target acceleration of the vehicle continuously meets the set conditions. If so, monitor and determine how long it lasts. For example, the vehicle determines the target acceleration in real time, compares each determined target acceleration with the preset threshold corresponding to the direction of its own acceleration. When a target acceleration whose absolute value is greater than the preset threshold corresponding to the direction of its own acceleration appears at a certain moment t0, starting from this moment t0, determine the relationship between the subsequent target acceleration and the preset threshold corresponding to the direction of its own acceleration. If the absolute values of all the target accelerations determined during the period from moment t0 to the end of 1 second are greater than the absolute value of the preset threshold corresponding to the direction of its own acceleration, and at the same time, after 1 second, a target acceleration whose absolute value is less than or equal to the absolute value of the preset threshold corresponding to the direction of its own acceleration is determined, then determine that the duration during which the target acceleration in the longitudinal direction of the vehicle continuously meets the set conditions is 1 second.

[0031] Step S53: Determine the maximum target acceleration of the vehicle during the duration according to the duration.

[0032] In this embodiment, after determining the duration during which the target acceleration in the vehicle longitudinal direction continuously satisfies the set condition through step S52, a maximum target acceleration among all the target accelerations determined during this duration is determined. Among them, when the acceleration direction of the target acceleration is positive, the maximum target acceleration among all the target accelerations refers to the one with the largest acceleration value; when the acceleration direction of the target acceleration is negative, the maximum target acceleration among all the target accelerations refers to the one with the largest absolute value of the acceleration value.

[0033] Step S54: Determine the collision event confidence level according to the duration and the relationship between the maximum target acceleration and the preset threshold corresponding to its own acceleration direction.

[0034] In this embodiment, after determining the duration during which the target acceleration in the vehicle longitudinal direction continuously satisfies the set condition and the maximum target acceleration during this duration through steps S52 and S53, based on the duration and the relationship between the maximum target acceleration and the preset threshold corresponding to its own acceleration direction, the collision event confidence level of the vehicle currently having a collision event is determined. An optional implementation method is: establish a first mapping relationship between the duration and the degree of exceeding of the absolute value of the maximum target acceleration over the absolute value of the preset threshold corresponding to its own acceleration direction and the collision event confidence level. After determining the duration and the maximum target acceleration, first determine the degree of exceeding of the absolute value of the maximum target acceleration over the absolute value of the preset threshold corresponding to its own acceleration direction, and then based on this degree of exceeding and the determined duration, by querying this first mapping relationship, determine the collision event confidence level (such as 80%) in the first mapping relationship that corresponds to both the degree of exceeding and the duration, and determine the determined collision event confidence level (i.e., 80%) as the collision event confidence level of the vehicle currently having a collision.

[0035] Combined with the above embodiments, in one implementation, the embodiments of the present application further provide a collision detection method. In this collision detection method, step S6 may include: comparing the collision event confidence level with the upper and lower limits of the confidence threshold range respectively; when the collision event confidence level is greater than or equal to the upper limit of the confidence threshold range, determining that a vehicle collision event has occurred; when the collision event confidence level is less than or equal to the lower limit of the confidence threshold range, determining that no vehicle collision event has occurred; when the collision event confidence level is within the confidence threshold range, obtaining the control actions performed on the vehicle within the target duration range, where the target duration range is: a set duration range before and after the determination moment when the collision event confidence level is determined; determining whether there is a target control action among the performed control actions, where the target control action is a control action related to the collision event; correcting the collision event confidence level according to the performed target control action; and determining whether a vehicle collision has occurred according to the corrected collision event confidence level.

[0036] In this embodiment, after obtaining the collision event confidence level that the vehicle currently has a collision event, it is further determined whether the vehicle actually has a collision event currently. Specifically, the present application pre-sets a confidence threshold range, which can be set according to the actual application scenario and will not be specifically limited here, such as (80%, 90%). First, the obtained collision event confidence level is compared with the upper and lower limits of the confidence threshold range respectively. When the collision event confidence level is greater than or equal to the upper limit of the confidence threshold range, it is determined that a vehicle collision event has occurred. At this time, the collision event of the vehicle is reported to the manufacturer service background in a timely manner, and accident handling guidance, rescue, maintenance service reservation, etc. are provided to the user who has had a traffic accident in a timely manner, so as to achieve the purpose of improving user satisfaction. When the collision event confidence level is less than or equal to the lower limit of the confidence threshold range, it is determined that no vehicle collision event has occurred. At this time, a new round of determination of whether the vehicle has a collision event is continued.

[0037] When the confidence level of the collision event is within the confidence threshold range (for example, between 80% and 90% within the confidence threshold range, and not equal to 80% and not equal to 90%), this is a suspected collision event with a high probability. In this case, the present application will correct the confidence level of the collision event in this situation. The specific correction process is as follows: Obtain the control actions performed by the user on the vehicle within the target duration range. The target duration range is a set duration range before and after the determination moment when the confidence level of the collision event is determined. The set duration range can be set according to the actual application scenario and is not specifically limited here. For example, a total of 5 seconds from 2.5 seconds before the determination moment to 2.5 seconds after the determination moment. Then determine whether there is a target control action among all the control actions performed within the target duration range. The target control action is a control action related to the collision event, that is, if a collision event actually occurs, generally a target control action will be performed on the vehicle. The target control action at least includes switching to the parking gear, pulling up the handbrake, turning on the hazard lights, opening the door, and emergency braking. If there is a target control action, the confidence level of the collision event is corrected upwards. At the same time, the relevance of different types of target control actions to the collision event is different. Therefore, the correction amplitude of the confidence level of the collision event by different types of target control actions is different. The higher the relevance, the higher the correction amplitude. Then, based on the corrected confidence level of the collision event, it is finally determined whether the vehicle has collided. The determination method is still to compare the corrected confidence level of the collision event with the upper and lower limits of the confidence threshold range. When the comparison result at this time is that the corrected confidence level of the collision event is greater than or equal to the upper limit of the confidence threshold range, it is determined that the vehicle has a collision event. If the comparison result at this time is that the corrected collision event is less than the upper limit of the confidence threshold range, it is directly determined that the vehicle has not had a collision event, and the confidence level of the collision event will not be corrected again. That is, in one round of collision event determination process of the present application, the confidence level of the collision event will only be corrected once. If the corrected confidence level of the collision event is less than the upper limit of the confidence threshold range, it is directly determined that there is no collision event.

[0038] Combined with the above embodiments, in one implementation manner, the embodiment of the present application further provides a collision detection method. In this collision detection method, the method further includes: during the correction process of the confidence level of the collision event after determining the duration, determining whether the vehicle appears again with a target acceleration that meets the set conditions; in the case of reappearance, exiting the correction process, and re-determining the confidence level of the collision event according to the relationship between the reappearing target acceleration and the preset threshold corresponding to its own acceleration direction; and determining whether the vehicle has collided according to the re-determined confidence level of the collision event.

[0039] In this embodiment, in order to quickly identify a collision event that has occurred, the present application provides an implementation for a special scenario. This special scenario is that in many scenarios where a collision is about to occur, users may make some incorrect control actions on the vehicle in a hurry, and thus the above implementation of a collision detection method provided by the present application identifies it as a suspected collision event and further corrects the confidence level of the collision event. In this scenario, a real collision may occur soon, and at this time, the above implementation of a collision detection method provided by the present application may still be in the process of correcting the confidence level of the collision event corresponding to the suspected collision event and cannot quickly identify this real collision. To solve this problem, the present application provides another implementation: during the process of correcting the confidence level of the collision event after determining the confidence level of the collision event based on the duration (this correction process refers to the correction process based on whether to execute the target control action in the above implementation), determine whether the vehicle reappears with a target acceleration that meets the set conditions. If it reappears, then exit the current correction process, and promptly determine the confidence level of the collision event based on the relationship between the currently reappearing target acceleration and the preset threshold corresponding to the direction of its own acceleration, and determine whether the vehicle has a collision based on the re-determined confidence level of the collision event. Among them, the method for determining the confidence level of the collision event by promptly determining the relationship between the currently reappearing target acceleration and the preset threshold corresponding to the direction of its own acceleration can be the same as the determination method in the implementation of step S5 above, or can be the same as the determination methods in the implementations of steps S51 to S54 above. Here, the implementation for determining whether the vehicle has a collision based on the re-determined confidence level of the collision event can be the same as the implementation of step S6 above, or can be the same as another implementation of step S6 above. For example, starting from a certain moment t0, it is determined that the duration for which the target acceleration in the longitudinal direction of the vehicle continuously meets the set conditions is 1 second. After 1 second, the target acceleration of the vehicle no longer meets the set conditions. At this time, a confidence level of the collision event is calculated after 1 second, and this confidence level of the collision event meets the situation of a suspected collision event. Therefore, the confidence level of the collision event is corrected accordingly. During the correction process, the vehicle obtains another target acceleration that meets the set conditions through real-time determination. At this time, the correction process will end, and based on the target acceleration that meets the set conditions determined during this correction process, the confidence level of the collision event is re-determined, and it is determined whether the vehicle has a collision based on the re-determined confidence level of the collision event.

[0040] Combined with the above embodiments, in one implementation, the embodiments of the present application further provide a collision detection method. In this collision detection method, the method further includes: determining the current turning radius of the vehicle according to the relationship curve between the steering wheel angle and the turning radius and the current steering wheel angle of the vehicle; determining a third influence amount of the vehicle steering on the lateral acceleration of the vehicle according to the turning radius and the current speed of the vehicle; determining the target lateral acceleration of the vehicle after correcting the steering influence according to the third influence amount and the lateral acceleration of the vehicle; determining a fourth influence amount of the vehicle steering on the yaw acceleration of the vehicle according to the third influence amount and the current speed of the vehicle; determining the target acceleration of the vehicle yaw rotation after correcting the steering influence according to the fourth influence amount and the yaw acceleration of the vehicle; determining the confidence level of the collision event according to the relationship between the target acceleration and the preset threshold corresponding to the direction of its own acceleration, including: determining the first collision event confidence level according to the relationship between the target lateral acceleration of the vehicle and the lateral setting threshold corresponding to the direction of its own acceleration; determining the second collision event confidence level according to the relationship between the target longitudinal acceleration of the vehicle and the longitudinal setting threshold corresponding to the direction of its own acceleration; determining the third collision event confidence level according to the relationship between the combined target acceleration of the vehicle and the combined setting threshold corresponding to the direction of its own acceleration, where the combined target acceleration is the acceleration synthesized by the target lateral acceleration of the vehicle and the target longitudinal acceleration of the vehicle; determining the fourth collision event confidence level according to the relationship between the target acceleration of the vehicle yaw rotation and the yaw setting threshold corresponding to the direction of its own acceleration; determining the maximum confidence level among the first collision event confidence level, the second collision event confidence level, the third collision event confidence level, and the fourth collision event confidence level as the final collision event confidence level of the vehicle.

[0041] In this embodiment, as Figure 3 shown, the present application pre - establishes a relationship curve between the steering wheel angle and the turning radius. During the normal driving of the vehicle, the current steering wheel angle of the vehicle is determined by collecting relevant information through the vehicle sensors, and based on the relationship curve between the steering wheel angle and the turning radius of the vehicle pre - established in the present application, the current turning radius of the vehicle corresponding to the current steering wheel angle of the vehicle is determined. According to the turning radius and the current speed of the vehicle, an acceleration is calculated through a second algorithm, and this acceleration is determined as the third influence amount of the vehicle steering on the lateral acceleration of the vehicle. Among them, the expression of the second algorithm is: , where, is the third influencing quantity, R is the turning radius, and V is the current speed of the vehicle. Subtract the current lateral acceleration of the vehicle obtained by the vehicle IMU from this third influencing quantity to obtain the target acceleration in the lateral direction of the vehicle after correcting the influence of vehicle steering. At the same time, divide the current third influencing quantity of the vehicle by the current speed of the vehicle to obtain the fourth influencing quantity of vehicle steering on the yaw acceleration of the vehicle, and then subtract this fourth influencing quantity from the current yaw acceleration of the vehicle obtained by the vehicle IMU to obtain the target acceleration of the vehicle yaw rotation after correcting the influence of vehicle steering. Here, two target accelerations under new acceleration types will be obtained.

[0042] In this embodiment, when a certain implementation manner of the present application obtains the target accelerations under the above two new acceleration types, another implementation manner of step S5 is as follows: For the target acceleration in the vehicle lateral acceleration type, the present application will determine a first collision event confidence level according to the relationship between the target acceleration in the vehicle lateral direction and the lateral setting threshold corresponding to its own acceleration direction. The determination method is similar to the implementation manners of steps S51 to S54 above. Two lateral setting thresholds corresponding to the acceleration direction will be set for the target acceleration in the vehicle lateral direction respectively, and then the target acceleration in the vehicle lateral direction will be compared with the lateral preset threshold corresponding to its own acceleration direction; when the target acceleration in the vehicle lateral direction that meets the set conditions appears, determine the duration from the appearance moment when the target acceleration in the vehicle lateral direction continuously meets the set conditions. The set condition is that the absolute value of the target acceleration in the vehicle lateral direction is greater than the absolute value of the lateral preset threshold corresponding to its own acceleration direction; according to this duration, determine the maximum target acceleration in the vehicle lateral direction during this duration; according to this duration and the relationship between the maximum target acceleration and the lateral preset threshold corresponding to its own acceleration direction, determine a first collision event confidence level.

[0043] Similarly, for the target acceleration under the type of vehicle longitudinal acceleration, the present application will determine a second collision event confidence level according to the relationship between the target acceleration in the vehicle longitudinal direction and the longitudinal setting threshold corresponding to the direction of its own acceleration. The determination method is the same as the implementation manners of the above steps S51 to S54. Two longitudinal setting thresholds corresponding to the acceleration direction are set for the target acceleration in the vehicle longitudinal direction, and then the target acceleration in the vehicle longitudinal direction is compared with the longitudinal preset threshold corresponding to the direction of its own acceleration; when a target acceleration that meets the set conditions appears in the vehicle longitudinal direction, the duration during which the target acceleration in the vehicle longitudinal direction continuously meets the set conditions is determined starting from the appearance moment. The set condition is that the absolute value of the target acceleration in the vehicle longitudinal direction is greater than the absolute value of the longitudinal preset threshold corresponding to the direction of its own acceleration; according to this duration, the maximum target acceleration in the vehicle longitudinal direction during this duration is determined; according to this duration and the relationship between the maximum target acceleration and the longitudinal preset threshold corresponding to the direction of its own acceleration, a second collision event confidence level is determined.

[0044] The present application first calculates a combined target acceleration by using the square root method for the target acceleration in the vehicle lateral direction and the target acceleration in the vehicle longitudinal direction. Similarly, the present application will determine a third collision event confidence level according to the relationship between the combined target acceleration of the vehicle and the combined setting threshold corresponding to the direction of its own acceleration. The determination method is similar to the implementation manners of the above steps S51 to S54. Among them, the direction of the combined target acceleration is the same as the target acceleration in the vehicle longitudinal direction at the same moment. Two combined setting thresholds corresponding to the acceleration direction are set for the combined target acceleration of the vehicle, and then the combined target acceleration is compared with the combined preset threshold corresponding to the direction of its own acceleration; when a combined target acceleration that meets the set conditions appears in the vehicle, the duration during which the combined target acceleration continuously meets the set conditions is determined starting from the appearance moment. The set condition is that the absolute value of the combined target acceleration is greater than the absolute value of the combined preset threshold corresponding to the direction of its own acceleration; according to this duration, the maximum combined target acceleration in the vehicle longitudinal direction during this duration is determined; according to this duration and the relationship between the maximum combined target acceleration and the combined preset threshold corresponding to the direction of its own acceleration, a third collision event confidence level is determined.

[0045] Similarly, for the target acceleration in the vehicle yaw acceleration type, the present application will determine a fourth collision event confidence level according to the relationship between the target acceleration of the vehicle yaw rotation and the yaw setting threshold corresponding to the direction of its own acceleration. The determination method is similar to the implementation manners of the above steps S51 to S54. Among them, the direction of the target acceleration of the vehicle yaw rotation is the same as the target acceleration in the vehicle lateral direction at the same moment. The present application will set two longitudinal setting thresholds corresponding to the acceleration direction for the target acceleration in the vehicle longitudinal direction respectively, and then compare the target acceleration of the vehicle yaw rotation with the yaw preset threshold corresponding to the direction of its own acceleration; in the case where the target acceleration of the vehicle yaw rotation that satisfies the set conditions appears, determine the duration from the appearance moment when the target acceleration of the vehicle yaw rotation continuously satisfies the set conditions. The set condition is that the absolute value of the target acceleration of the vehicle yaw rotation is greater than the absolute value of the yaw preset threshold corresponding to the direction of its own acceleration; according to this duration, determine the maximum target acceleration of the vehicle yaw rotation within this duration; according to this duration, and the relationship between the maximum target acceleration and the yaw preset threshold corresponding to the direction of its own acceleration, determine a fourth collision event confidence level.

[0046] In this embodiment, compare the obtained first collision event confidence level, second collision event confidence level, third collision event confidence level and fourth collision event confidence level, and select the largest one of them as the final collision event confidence level of the vehicle. Then use this final collision event confidence level to participate in step S6 and the optional implementation manners of step S6 to determine whether the vehicle has a collision.

[0047] Combined with the above embodiments, in one implementation manner, the embodiment of the present application also provides a collision detection method. In this collision detection method, the method further includes: during the correction process of the collision event confidence level after determining the duration, whether a target acceleration that satisfies the set conditions appears again under at least one acceleration type of the vehicle; in the case of reappearance, exit the correction process, and according to the relationship between the reappearing target acceleration and the setting threshold under the acceleration type to which it belongs corresponding to the direction of its own acceleration, re-determine the collision event confidence level under the acceleration type to which the reappearing target acceleration belongs; in the case of obtaining multiple collision event confidence levels after re-determination, determine the largest confidence level among the re-determined multiple collision event confidence levels as the final new collision event confidence level of the vehicle; according to the final new collision event confidence level of the vehicle, determine whether the vehicle has a collision.

[0048] In this embodiment, when the maximum confidence level among multiple confidence levels is determined as the confidence level of the vehicle's final collision event and participates in the determination of whether the vehicle has a collision, the collision detection method provided by this application further includes: during the process of correcting the maximum collision event confidence level after obtaining the maximum collision event confidence level based on the duration (the correction process refers to the correction process based on whether to execute the target control action in the above embodiment), determine whether at least one of all target accelerations under various acceleration types of the vehicle (including the target acceleration in the lateral direction of the vehicle, the target acceleration in the longitudinal direction of the vehicle, the combined target acceleration, and the target acceleration of the vehicle's yaw rotation) reappears and satisfies the set condition (for example, assume that a combined target acceleration and a target acceleration of the vehicle's yaw rotation both satisfy the corresponding set conditions simultaneously). If it reappears, then exit the current correction process, and promptly re-determine the corresponding collision event confidence level based on the relationship between the currently reappearing target acceleration that satisfies the corresponding set condition and the preset threshold corresponding to its own acceleration direction. It should be understood that if there are multiple target accelerations that satisfy the set condition and reappear among all target accelerations under various acceleration types of the vehicle (such as including a combined target acceleration and a target acceleration of the vehicle's yaw rotation simultaneously), then correspondingly, promptly based on the relationship between the currently reappearing target accelerations that satisfy the set condition (that is, the combined target acceleration and the target acceleration of the vehicle's yaw rotation that reappear simultaneously) and the preset thresholds corresponding to their own acceleration directions (that is, the combined preset threshold corresponding to the own acceleration direction of the combined target acceleration and the yaw preset threshold corresponding to the own acceleration direction of the target acceleration of the vehicle's yaw rotation), the re-determined corresponding collision event confidence levels will also include multiple (that is, including the third collision event confidence level corresponding to the combined target acceleration and the fourth collision event confidence level corresponding to the target acceleration of the vehicle's yaw rotation). This application will determine the maximum confidence level among the re-determined multiple collision event confidence levels as the vehicle's final new collision event confidence level, and determine whether the vehicle has a collision based on the re-determined vehicle's final new collision event confidence level. Among them, the method of promptly re-determining the corresponding collision event confidence level based on the relationship between the currently reappearing target acceleration that satisfies the set condition and the preset threshold corresponding to its own acceleration direction is the same as the method of determining the first collision event confidence level, the second collision event confidence level, the third collision event confidence level, and the fourth collision event confidence level, and is determined based on the acceleration type corresponding to the currently reappearing target acceleration that satisfies the set condition. Here, the implementation manner of determining whether the vehicle has a collision based on the re-determined vehicle's final new collision event confidence level can be the same as the implementation manner of step S6 above, or can be the same as another implementation manner of step S6 above.

[0049] Combined with the above embodiments, in one implementation, the embodiments of the present application further provide a collision detection method. In this collision detection method, the method further includes: pre-defining that the positive value of the lateral acceleration is the acceleration received by the vehicle to the right, the positive value of the longitudinal acceleration is the acceleration received by the vehicle forward, and the positive value of the combined acceleration is the acceleration received by the vehicle from the rear side; in the case of determining that a vehicle collision event occurs, according to the acceleration type corresponding to the final collision event confidence of the vehicle and the positive or negative value of the corresponding target acceleration, determine the collision type of the collision event; when the corresponding acceleration type is the lateral acceleration and the value of the target acceleration in the vehicle's lateral direction is positive, determine that the collision type is the left collision type; when the corresponding acceleration type is the lateral acceleration and the value of the target acceleration in the vehicle's lateral direction is negative, determine that the collision type is the right collision type; when the corresponding acceleration type is the longitudinal acceleration and the value of the target acceleration in the vehicle's longitudinal direction is positive, determine that the collision type is the rear-end collision type; when the corresponding acceleration type is the longitudinal acceleration and the value of the target acceleration in the vehicle's longitudinal direction is negative, determine that the collision type is the frontal collision type; when the corresponding acceleration type is the combined acceleration and the value of the combined target acceleration is positive, determine that the collision type is the rear-side collision type; when the corresponding acceleration type is the combined acceleration and the value of the combined target acceleration is negative, determine that the collision type is the front-side collision type; when the corresponding acceleration type is the yaw acceleration, determine that the collision type is the complex collision type.

[0050] In this embodiment, in order to determine the collision type of the collision when it is determined that a vehicle has a collision, a collision detection method provided by the present application further includes: pre-defining that the positive value of the vehicle's lateral acceleration is the acceleration received by the vehicle to the right, the positive value of the vehicle's longitudinal acceleration is the acceleration received by the vehicle forward, and the positive value of the combined acceleration is the acceleration received by the vehicle forward. Then, in the case of determining that a vehicle collision occurs, based on the acceleration type corresponding to the final collision event confidence of the vehicle (such as the lateral acceleration) and the positive or negative value of the target acceleration corresponding to the final collision event confidence of the vehicle (i.e., the target acceleration in the vehicle's lateral direction), determine the collision type of the collision event. For example, if the final collision event confidence of the vehicle obtained is determined based on the target acceleration in the vehicle's lateral direction corresponding to the vehicle's lateral acceleration type, in the case of determining that a vehicle collision occurs, based on this lateral acceleration type and the positive or negative value of the target acceleration in the vehicle's lateral direction, determine the collision type of the collision event.

[0051] When it is determined that a collision has occurred, and the type of acceleration based on which the confidence level of the vehicle's final collision event is determined is lateral acceleration and the value of the target acceleration in the lateral direction of the vehicle is positive, the collision type is determined to be the left collision type; when it is determined that a collision has occurred, and the type of acceleration based on which the confidence level of the vehicle's final collision event is determined is lateral acceleration and the value of the target acceleration in the lateral direction of the vehicle is negative, the collision type is determined to be the right collision type; when it is determined that a collision has occurred, and the type of acceleration based on which the confidence level of the vehicle's final collision event is determined is longitudinal acceleration and the value of the target acceleration in the longitudinal direction of the vehicle is positive, the collision type is determined to be the rear-end collision type; when it is determined that a collision has occurred, and the type of acceleration based on which the confidence level of the vehicle's final collision event is determined is longitudinal acceleration and the value of the target acceleration in the longitudinal direction of the vehicle is negative, the collision type is determined to be the frontal collision type; when it is determined that a collision has occurred, and the type of acceleration based on which the confidence level of the vehicle's final collision event is determined is combined acceleration and the value of the combined target acceleration is positive, the collision type is determined to be the rear-side collision type; when it is determined that a collision has occurred, and the type of acceleration based on which the confidence level of the vehicle's final collision event is determined is combined acceleration and the value of the combined target acceleration is negative, the collision type is determined to be the front-side collision type; when it is determined that a collision has occurred, and the type of acceleration based on which the confidence level of the vehicle's final collision event is determined is yaw acceleration, the collision type is determined to be the complex collision type.

[0052] Combined with the above embodiments, in one implementation, the embodiments of the present application further provide a collision detection method. In this collision detection method, the method further includes: determining and saving the identity information of the in-vehicle user to the local according to the collected image data of the in-vehicle user; when it is determined that the vehicle currently has a collision and the collision type that has occurred is obtained, continuously sending a collision event notification for a preset duration to trigger the in-vehicle image acquisition device to collect video data inside and outside the vehicle; synchronously saving the collected video data inside and outside the vehicle and the flag bit of the collision type to the local and the cloud, and saving the identity information of the in-vehicle user to the cloud.

[0053] In this embodiment, after the user gets in the vehicle and starts the vehicle, image data of all users in the vehicle is collected. Based on the collected image data, the identity information of all users in the vehicle is determined, and the identity information of all current users in the vehicle and the personal health information of all users are stored from the persistent storage database to a specific storage location. The specific storage location stores the identity information of all current users in the vehicle and the personal health information of all users. The information stored in the specific storage location will be cleared after the user finishes using the vehicle. And when a user gets in the vehicle and starts the vehicle next time, a new round of determination and storage of the identity information of all current users in the vehicle and the personal health information of all users to the specific storage location is performed. Among them, the user identity information corresponding to the image data and the personal health information of the user corresponding to the user identity information are actively recorded and stored in the persistent storage database by the main user who owns the vehicle. The personal health information corresponding to the user can facilitate rescue personnel to take timely and correct rescue measures in the event of a sudden collision event. In the case where it is determined that the vehicle has collided and the collision type of the collision has been determined, in order to prevent the vehicle from not receiving the collision event notification due to the sending of other event notifications, resulting in the vehicle being unable to collect corresponding countermeasures in time. At this time, this application will continuously send collision event notifications for a preset duration to ensure as much as possible to trigger the in-vehicle image acquisition device to collect in-vehicle and out-of-vehicle video data, and trigger the operation of synchronously saving the collected in-vehicle and out-of-vehicle video data and the flag bit of the collision type to local and cloud, and trigger the cloud upload of the identity information and personal health information of all current users in the vehicle stored in the specific storage location. Thereby providing accident handling guidance, rescue, maintenance service reservation, etc. to the users who have had a traffic accident in a timely manner, so as to improve user satisfaction.

[0054] Combined with the above embodiments, in one implementation, the embodiment of the present application also provides a collision detection method. In this collision detection method, the method further includes: collecting various state information of the vehicle, where the various state information at least includes braking torque, suspension compression height, steering wheel angle, and speed; determining whether the collected various state information meets preset conditions, where the preset conditions at least include state information collected during the vehicle power-on process, state information collected during the system restart process, the signal value of the state information is invalid, and the state information is intermittently lost; in the case where the state information meets the preset conditions, replacing the collected value of the state information with a preset default value corresponding to the type of the state information; performing corresponding formula conversion on the collected state information that requires formula conversion; performing time-step filtering processing on the collected state information belonging to high-frequency signals according to the scheduling period.

[0055] In this embodiment, to ensure that the relevant status information collected by the vehicle sensors can be used to correctly correct the acceleration of the vehicle, this application will preprocess various types of collected status information. Specifically: determine whether the various types of collected status information meet the preset conditions, and the preset conditions at least include: determining that the preset conditions are met when the status information is the status information collected during the vehicle power-on process; determining that the preset conditions are met when the status information is the status information collected during the system restart process; determining that the preset conditions are met when the signal value of the status information is invalid; determining that the preset conditions are met when the status information is intermittently lost. A preset default value is preset for each type of status information. When the status information meets the preset conditions, the collected value of the status information is replaced with the preset default value corresponding to the type to which the status information belongs. For the status information that needs to be formula-converted among the collected status information, the corresponding formula conversion is performed, and at the same time, according to the scheduling period, time-step filtering processing is performed on the status information belonging to the high-frequency signal among the collected status information. Then, all the relevant preprocessed status information is used to correct the acceleration of the vehicle. Among them, the various types of status information at least include braking torque, suspension compression height, steering wheel angle, and speed, etc.

[0056] In this embodiment, Figure 4 Another flowchart of a collision detection method shown in an embodiment of this application is as Figure 4As shown in the figure, the entire implementation process of a collision detection method provided by this application can be as follows: First, obtain the relevant state information of the vehicle. Based on the obtained relevant state information, correct the acceleration of the current vehicle to obtain the target acceleration in the longitudinal direction of the vehicle after correcting the influence of vehicle braking and road surface mutation. Then, determine whether the target acceleration of the vehicle meets the set conditions. If the target acceleration of the vehicle does not meet the set conditions, it is determined that no collision event has occurred. At this time, directly end the execution of the subsequent steps and start a new round of determination of whether a collision has occurred. If the target acceleration of the vehicle meets the set conditions, further determine the duration for which the target acceleration of the vehicle meets the set conditions, and then determine the collision event confidence level based on the relationship between this duration and the relationship between the maximum target acceleration of the vehicle and the set threshold within this duration. Then, further determine the relationship between this collision event confidence level and the upper and lower limits of the confidence level threshold range. If it is determined that this collision event confidence level is greater than or equal to the upper limit of the confidence level threshold range, it is determined that a collision event has occurred to the vehicle. At this time, end the determination of whether a collision has occurred, and then report the subsequent collision event and relevant information to the cloud platform. If it is determined that this collision event confidence level is less than or equal to the lower limit of the confidence level threshold range, it is determined that no collision has occurred to the vehicle. At this time, directly end the execution of the subsequent steps and start a new round of determination of whether a collision has occurred. If it is determined that this collision event confidence level is within the confidence level threshold range (the values within this range do not include the upper and lower limits of the confidence level threshold range), further determine whether a target control action has been performed on the vehicle within the target duration. If no target control action has been performed on the vehicle within the target duration, no correction of the collision event confidence level is performed. At this time, it is determined that no collision has occurred, and then end the execution of the subsequent steps and start a new round of determination of whether a collision has occurred. If a target control action has been performed on the vehicle within the target duration, then correct the collision event confidence level to obtain the corrected collision event confidence level. At this time, determine whether the corrected collision event confidence level is greater than or equal to the upper limit of the confidence level threshold range. If the corrected collision event confidence level is greater than or equal to the upper limit of the confidence level threshold range, it is determined that a collision has occurred, and then report the subsequent collision event and relevant information to the cloud platform. If the corrected collision event confidence level is less than the upper limit of the confidence level threshold range, it is determined that no collision has occurred. At this time, directly end the execution of the subsequent steps and start a new round of determination of whether a collision has occurred.

[0057] In this embodiment, Figure 5 is a schematic diagram of acceleration correction in the first scenario of a collision detection method shown in an embodiment of this application. As Figure 5 shown, Figure 5Shown is the first scenario where a collision occurs during a driver's misoperation. Assume that in this scenario, the vehicle changes lanes to an adjacent lane of its own lane and collides with a vehicle in front in that adjacent lane (the vehicle itself rear-ends the vehicle in front). At the same time, during this process, the user performs a braking control on the vehicle. At this time, the vehicle itself has a forward acceleration, and this collision generates a backward acceleration on the vehicle itself. At this time, the total acceleration of the vehicle is Figure 5 the solid line A1 in Figure 5 . At this time, the absolute value of the total acceleration of the vehicle itself will not exceed the preset threshold. If no correction is made, correspondingly, it will not be recognized that a collision has occurred to the vehicle itself, resulting in this collision being missed. By using a collision detection method provided by the present application to correct the total acceleration of the vehicle itself to eliminate the influence of vehicle braking and the influence of ground mutation on vehicle acceleration, the remaining target acceleration is like the dotted line B1 in

[0058] In this embodiment, Figure 6 is a schematic diagram of acceleration correction in the second scenario of a collision detection method shown in an embodiment of the present application. As shown in Figure 6 Figure 6 Shown is the second scenario where ground mutation affects the total acceleration of the vehicle. Assume that in this scenario, the user suddenly brakes when the vehicle passes through a sudden change in the road surface such as a speed bump. Figure 6 In Figure 6 , A2 represents the total acceleration of the vehicle, and B2 represents the target acceleration of the vehicle after correction. If A2 is not corrected, the absolute value of the total acceleration of the vehicle will exceed the absolute value of the preset threshold corresponding to the direction of its own acceleration, and the exceeding amplitude is relatively large. Therefore, it will be misjudged as a collision event. However, in fact, it is caused by the user suddenly braking when the vehicle passes through a speed bump, which is a misoperation condition and should not be triggered. Therefore, by using a collision detection method provided by the present application to correct the total acceleration of the vehicle itself to eliminate the influence of braking and ground mutation on vehicle acceleration, the remaining target acceleration is like the dotted line B2 in

[0059] ​In this embodiment, a collision detection method provided by the present application does not rely on a collision acceleration sensor or a collision pressure sensor. Instead, through the IMU and vehicle status information, it uses confidence evaluation to detect collision events, featuring high detection accuracy and low misjudgment probability. It has very good safety redundancy and can almost avoid all misoperation cases of airbag ignition strategies. At the same time, it is not used for the ignition control of the occupant restraint system, but mainly for the manufacturer to master the clues of collision events, and is used for post-accident customer care, rescue, repair appointment, risk analysis and other services.

[0060] Based on the same inventive concept, an embodiment of the present application provides a collision detection system, as Figure 7 shown. The collision detection system 700 includes: A first influence quantity determination module 701, configured to determine a first influence quantity of vehicle braking on the vehicle longitudinal acceleration according to the relationship curve between the braking torque and the vehicle longitudinal deceleration and the current braking torque of the vehicle; A shock absorber stiffness determination module 702, configured to determine the shock absorber stiffness according to the mapping relationship between the suspension compression height and the shock absorber stiffness and the current suspension compression height of the vehicle; A second influence quantity determination module 703, configured to determine a second influence quantity of road surface mutation on the vehicle longitudinal acceleration according to the shock absorber stiffness and the vehicle mass; A first acceleration determination module 704, configured to determine the target acceleration in the vehicle longitudinal direction after correcting the braking influence and the road surface mutation influence according to the first influence quantity, the second influence quantity and the vehicle longitudinal acceleration; A confidence determination module 705, configured to determine the collision event confidence according to the relationship between the target acceleration and a preset threshold corresponding to its own acceleration direction; A collision determination module 706, configured to determine whether the vehicle has collided according to the collision event confidence.

[0061] Optionally, the confidence determination module 705 includes: A first comparison module, configured to compare the target acceleration in the vehicle longitudinal direction with a preset threshold corresponding to its own acceleration direction; A duration determination module, configured to determine the duration from the occurrence moment when the target acceleration in the vehicle longitudinal direction continuously satisfies the set condition in the case that the vehicle has a target acceleration that meets the set condition, where the set condition is that the absolute value of the target acceleration is greater than the absolute value of the preset threshold corresponding to its own acceleration direction; A maximum target acceleration determination module, configured to determine the maximum target acceleration of the vehicle during the duration according to the duration; A collision event confidence determination sub-module, configured to determine a collision event confidence according to the duration and the relationship between the maximum target acceleration and a preset threshold corresponding to the direction of its own acceleration.

[0062] Optionally, the collision determination module 706 includes: A second comparison module, configured to compare the collision event confidence with the upper and lower limits of a confidence threshold range respectively; A first collision determination module, configured to determine that a vehicle collision event occurs when the collision event confidence is greater than or equal to the upper limit of the confidence threshold range; A second collision determination module, configured to determine that no vehicle collision event occurs when the collision event confidence is less than or equal to the lower limit of the confidence threshold range; A control action acquisition module, configured to acquire control actions performed on the vehicle within a target duration when the collision event confidence is within the confidence threshold range, where the target duration range is a set duration range before and after the determination moment when the collision event confidence is determined; A target control action determination module, configured to determine whether there is a target control action among the performed control actions, where the target control action is a control action related to a collision event; A confidence correction module, configured to correct the collision event confidence according to the performed target control action; A collision determination sub-module, configured to determine whether a vehicle collision occurs according to the corrected collision event confidence.

[0063] Optionally, the collision detection system 700 further includes: A target acceleration determination module, configured to determine whether a target acceleration that meets the set conditions appears again in the vehicle during the correction process of the collision event confidence after the duration; A collision event confidence determination module, configured to exit the correction process when it appears again, and re-determine the collision event confidence according to the relationship between the target acceleration that appears again and a preset threshold corresponding to the direction of its own acceleration; A collision determination module 706, configured to determine whether a vehicle collision occurs according to the re-determined collision event confidence.

[0064] Optionally, the collision detection system 700 further includes: A turning radius determination module, configured to determine the current turning radius of the vehicle according to the relationship curve between the steering wheel angle and the turning radius and the current steering wheel angle of the vehicle; A third influence amount determination module, configured to determine a third influence amount of the vehicle steering on the vehicle lateral acceleration according to the turning radius and the current speed of the vehicle; A target lateral acceleration determination module for a vehicle, configured to determine a target lateral acceleration of the vehicle after correcting for steering influence based on the third influence quantity and the lateral acceleration of the vehicle; A fourth influence quantity determination module for a vehicle, configured to determine a fourth influence quantity of vehicle steering on the yaw acceleration of the vehicle based on the third influence quantity and the current speed of the vehicle; A target acceleration determination module for vehicle yaw rotation, configured to determine a target acceleration of vehicle yaw rotation after correcting for steering influence based on the fourth influence quantity and the yaw acceleration of the vehicle; The confidence determination module 705 is configured to determine a first collision event confidence based on the relationship between the target lateral acceleration of the vehicle and the lateral set threshold corresponding to its own acceleration direction; and is configured to determine a second collision event confidence based on the relationship between the target longitudinal acceleration of the vehicle and the longitudinal set threshold corresponding to its own acceleration direction; and is configured to determine a third collision event confidence based on the relationship between the combined target acceleration of the vehicle and the combined set threshold corresponding to its own acceleration direction, where the combined target acceleration is the acceleration synthesized from the target lateral acceleration of the vehicle and the target longitudinal acceleration of the vehicle; and is configured to determine a fourth collision event confidence based on the relationship between the target acceleration of vehicle yaw rotation and the yaw set threshold corresponding to its own acceleration direction; and is configured to determine that the maximum confidence among the first collision event confidence, the second collision event confidence, the third collision event confidence, and the fourth collision event confidence is the final collision event confidence of the vehicle.

[0065] Optionally, the collision detection system 700 further includes: A target acceleration determination module, configured to determine whether a target acceleration that meets the set conditions appears again under at least one acceleration type of the vehicle during the correction process of the collision event confidence after the duration; The confidence determination module 705 is configured to, in the case of a reappearance, exit the correction process and re-determine the collision event confidence under the acceleration type to which the reappearing target acceleration belongs based on the relationship between the reappearing target acceleration and the set threshold under the acceleration type to which its own acceleration belongs corresponding to its own acceleration direction; and is configured to, in the case of obtaining multiple collision event confidences after re-determination, determine the maximum confidence among the multiple re-determined collision event confidences as the final new collision event confidence of the vehicle; A collision determination module 706, configured to determine whether a vehicle collision occurs based on the final new collision event confidence of the vehicle.

[0066] Optionally, the collision detection system 700 further includes: A predefined module for predefined positive values of lateral acceleration as the vehicle is subjected to an acceleration to the right, predefined positive values of longitudinal acceleration as the vehicle is subjected to an acceleration forward, and predefined positive values of resultant acceleration as the vehicle is subjected to an acceleration from the rear side; A collision type determination module for, when it is determined that a vehicle collision event has occurred, determining the collision type of the collision event according to the acceleration type corresponding to the final collision event confidence level of the vehicle and the positive or negative value of the corresponding target acceleration; and for, when the corresponding acceleration type is lateral acceleration and the value of the target acceleration in the vehicle's lateral direction is positive, determining the collision type as a left-side collision type; and for, when the corresponding acceleration type is lateral acceleration and the value of the target acceleration in the vehicle's lateral direction is negative, determining the collision type as a right-side collision type; and for, when the corresponding acceleration type is longitudinal acceleration and the value of the target acceleration in the vehicle's longitudinal direction is positive, determining the collision type as a rear-end collision type; and for, when the corresponding acceleration type is longitudinal acceleration and the value of the target acceleration in the vehicle's longitudinal direction is negative, determining the collision type as a frontal collision type; and for, when the corresponding acceleration type is resultant acceleration and the value of the corresponding resultant target acceleration is positive, determining the collision type as a rear-side collision type; and for, when the corresponding acceleration type is resultant acceleration and the value of the corresponding resultant target acceleration is negative, determining the collision type as a front-side collision type; and for, when the corresponding acceleration type is yaw acceleration, determining the collision type as a complex collision type.

[0067] Optionally, the collision detection system 700 further includes: An identity information determination module for determining and saving the identity information of the in-vehicle user to the local according to the acquired image data of the in-vehicle user; An event trigger module for, when it is determined that the vehicle is currently in a collision and the collision type that has occurred is obtained, continuously sending a collision event notification for a preset duration to trigger the in-vehicle image acquisition device to acquire in-vehicle and out-of-vehicle video data; A storage module for synchronously saving the acquired in-vehicle and out-of-vehicle video data and the flag bit of the collision type to the local and the cloud, and saving the identity information of the in-vehicle user to the cloud.

[0068] Optionally, the collision detection system 700 further includes: A status information acquisition module for acquiring various status information of the vehicle, where the various status information at least includes braking torque, suspension compression height, steering wheel angle, and speed; A preprocessing module is used to determine whether various types of collected status information meet preset conditions. The preset conditions at least include status information collected during the vehicle power-on process, status information collected during the system restart process, invalid signal values of the status information, and intermittent loss of the status information. Moreover, it is used to replace the collected value of the status information with a preset default value corresponding to the type of the status information when the status information meets the preset conditions. Additionally, it is used to perform corresponding formula conversions on the collected status information that requires formula conversions. Furthermore, it is used to perform time-step filtering on the collected status information belonging to high-frequency signals according to the scheduling period.

[0069] Based on the same inventive concept, an embodiment of the present application provides an electronic device, including: a processor, a memory, and a computer program stored on the memory and running on the processor. When the computer program is executed by the processor, it implements the steps in a collision detection method as described in the first aspect of the present application.

[0070] Based on the same inventive concept, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps in a collision detection method as described in the first aspect of the present application.

[0071] For the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple. For related parts, refer to the partial description of the method embodiment.

[0072] It should be noted that for the method embodiment, for simplicity of description, it is all expressed as a series of action combinations. However, those skilled in the art should know that the embodiments of the present application are not limited by the described action sequence, because according to the embodiments of the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential for the embodiments of the present application.

[0073] Each embodiment in this specification is described in a progressive manner. The key point of each embodiment is to illustrate the differences from other embodiments. The same or similar parts among the embodiments can be referred to each other.

[0074] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the embodiments of the present application can take the form of all-hardware embodiments, all-software embodiments, or embodiments combining software and hardware aspects. Moreover, the embodiments of the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code.

[0075] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of methods, terminal devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing terminal devices to generate a machine, so that the instructions executed by the processors of the computer or other programmable data processing terminal devices generate means for implementing the functions specified in one Figure 1 process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0076] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implement the functions specified in one Figure 1 process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0077] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable terminal device provide steps for implementing the functions specified in one Figure 1 process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0078] Although the preferred embodiments of the embodiments of the present application have been described, those skilled in the art can make additional changes and modifications once they know the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications falling within the scope of the embodiments of the present application.

[0079] Finally, it should also be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or terminal device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or terminal device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or terminal device comprising the said element.

[0080] The above has introduced in detail a collision detection method, system, device and medium provided by the present application. Specific examples are used in this text to elaborate on the principle and implementation manner of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A collision detection method, characterized in that: The method comprises: Determining a first influence amount of vehicle braking on the vehicle longitudinal acceleration according to a relationship curve between braking torque and vehicle longitudinal deceleration and a current braking torque of the vehicle; Determine the shock absorber stiffness according to the mapping relationship between the suspension compression height and the shock absorber stiffness and the current suspension compression height of the vehicle; Determining a second influence amount of the sudden change in road surface on the longitudinal acceleration of the vehicle according to the stiffness of the shock absorber and the mass of the vehicle; Determine, according to the first influence amount, the second influence amount and the longitudinal acceleration of the vehicle, a target longitudinal acceleration of the vehicle after correcting the influence of braking and the influence of sudden road changes; Determining the collision event confidence level according to the relationship between the target acceleration and a preset threshold value corresponding to the direction of the own acceleration; It is determined whether a collision occurs in the vehicle according to the collision event confidence.

2. A collision detection method according to claim 1, characterized in that: Determining the collision event confidence level according to the relationship between the target acceleration and the preset threshold corresponding to the direction of the own acceleration includes: Comparing the target acceleration in the longitudinal direction of the vehicle with a preset threshold corresponding to the direction of its own acceleration; When the vehicle has a target acceleration that satisfies a set condition, determining the duration of time that the target acceleration in the longitudinal direction of the vehicle continues to satisfy the set condition from the time of occurrence, wherein the set condition is that the absolute value of the target acceleration is greater than the absolute value of a preset threshold value corresponding to the direction of the vehicle's own acceleration; Determining a maximum target acceleration of the vehicle within the duration according to the duration; The confidence level of the collision event is determined according to the duration and the relationship between the maximum target acceleration and a preset threshold corresponding to the direction of the own acceleration.

3. A collision detection method according to claim 2, characterized in that: Determining whether a collision occurs between vehicles according to the collision event confidence level includes: Comparing the collision event confidence with the upper and lower limits of the confidence threshold range respectively; When the collision event confidence is greater than or equal to an upper limit of a confidence threshold range, determining that a collision event occurs on the vehicle; When the collision event confidence is less than or equal to the lower limit of the confidence threshold range, determining that the vehicle has not experienced a collision event; When the collision event confidence is within the confidence threshold range, obtaining a control action performed on the vehicle within a target duration range, wherein the target duration range is: a set duration range before and after the moment when the collision event confidence is determined; determining whether there is a target control action in the executed control actions, the target control action being a control action related to the collision event; Correcting the confidence of the collision event according to the executed target control action; Whether the vehicle has collided is determined based on the corrected collision event confidence level.

4. A collision detection method according to claim 3, characterized in that: The method further comprises: After determining the duration, during the correction process of the confidence level of the collision event, whether the vehicle again reaches the target acceleration that satisfies the set condition; In the event of a recurrence, the correction process is exited, and the confidence level of the collision event is re-determined based on the relationship between the recurring target acceleration and the preset threshold corresponding to the direction of the own acceleration; It is determined whether the vehicle has collided based on the re-determined collision event confidence level.

5. A collision detection method according to claim 3, characterized in that: The method further comprises: Determine the current turning radius of the vehicle according to the relationship curve between the steering wheel angle and the turning radius and the current steering wheel angle of the vehicle; Determining a third influence amount of the vehicle steering on the vehicle lateral acceleration according to the turning radius and the current speed of the vehicle; Determining a target lateral acceleration of the vehicle after correcting the steering influence according to the third influence amount and the lateral acceleration of the vehicle; Determining a fourth influence amount of the vehicle steering on the vehicle yaw acceleration according to the third influence amount and the current speed of the vehicle; Determining a target acceleration of the yaw rotation of the vehicle after correcting the steering influence according to the fourth influence amount and the yaw acceleration of the vehicle; Determining the collision event confidence level according to the relationship between the target acceleration and the preset threshold corresponding to the direction of the own acceleration includes: Determining the first collision event confidence level according to a relationship between a target lateral acceleration of the vehicle and a lateral set threshold value corresponding to the direction of the vehicle's own acceleration; Determining the second collision event confidence level according to a relationship between a target longitudinal acceleration of the vehicle and a longitudinal set threshold value corresponding to the direction of the vehicle's own acceleration; Determining a third collision event confidence level according to a relationship between a synthetic target acceleration of the vehicle and a synthetic set threshold value corresponding to the direction of the vehicle's own acceleration, wherein the synthetic target acceleration is an acceleration synthesized from a lateral target acceleration of the vehicle and a longitudinal target acceleration of the vehicle; determining a fourth collision event confidence level according to a relationship between a target acceleration of the vehicle's yaw rotation and a yaw setting threshold corresponding to the direction of the vehicle's own acceleration; The maximum confidence among the first collision event confidence, the second collision event confidence, the third collision event confidence and the fourth collision event confidence is determined as a final collision event confidence of the vehicle.

6. A collision detection method according to claim 5, characterized in that: The method further comprises: In the process of correcting the confidence of the collision event after determining the duration, whether a target acceleration meeting the set condition appears again under at least one acceleration type of the vehicle; In the case of a recurrence, the correction process is exited, and the confidence level of the collision event under the acceleration type to which the recurring target acceleration belongs is re-determined based on the relationship between the recurring target acceleration and the set threshold value under the acceleration type to which the own acceleration direction belongs; In the case of re-determining a plurality of collision event confidences, determining the maximum confidence among the re-determined plurality of collision event confidences as the final new collision event confidence of the vehicle; Whether the vehicle has collided is determined based on the final new collision event confidence of the vehicle.

7. A collision detection method according to claim 5, characterized in that: The method further comprises: A positive value of the predefined lateral acceleration means that the vehicle is subjected to rightward acceleration, a positive value of the predefined longitudinal acceleration means that the vehicle is subjected to forward acceleration, and a positive value of the predefined combined acceleration means that the vehicle is subjected to rear lateral acceleration; When it is determined that a collision event occurs with the vehicle, the collision type of the collision event is determined according to the acceleration type corresponding to the final collision event confidence of the vehicle and the positive or negative value of the corresponding target acceleration; When the corresponding acceleration type is lateral acceleration and the corresponding lateral target acceleration value of the vehicle is positive, determining that the collision type is a left collision type; When the corresponding acceleration type is lateral acceleration and the corresponding lateral target acceleration value of the vehicle is negative, the collision type is determined to be a right collision type; When the corresponding acceleration type is longitudinal acceleration and the corresponding target acceleration value of the vehicle longitudinal direction is positive, determining that the collision type is a rear-end collision type; When the corresponding acceleration type is longitudinal acceleration and the corresponding target acceleration value of the vehicle longitudinal direction is negative, the collision type is determined to be a forward collision type; When the corresponding acceleration type is a synthetic acceleration and the value of the corresponding synthetic target acceleration is positive, the collision type is determined to be a rear side collision type; When the corresponding acceleration type is a synthetic acceleration and the value of the corresponding synthetic target acceleration is negative, the collision type is determined to be a front side collision type; When the corresponding acceleration type is yaw acceleration, it is determined that the collision type is a complex collision type.

8. A collision detection method according to claim 1, characterized in that: The method further comprises: According to the collected image data of the user in the car, determine and save the identity information of the user in the car locally; When it is determined that the vehicle is currently in collision and the type of collision is obtained, a collision event notification is continuously sent for a preset time to trigger the vehicle-mounted image acquisition device to collect video data inside and outside the vehicle; The collected video data inside and outside the car and the flag of the collision type are saved locally and in the cloud simultaneously, and the identity information of the user in the car is also saved in the cloud.

9. A collision detection method according to claim 1, characterized in that: The method further comprises: Collecting various status information of the vehicle, wherein the various status information at least includes braking torque, suspension compression height, steering wheel angle and speed; Determine whether the various types of status information collected meet preset conditions, where the preset conditions at least include status information collected during vehicle power-on, status information collected during system restart, invalid signal value of status information, and intermittent loss of status information; When the status information meets the preset conditions, the collected value of the status information is replaced by a preset default value corresponding to the type of the status information; Perform corresponding formula conversion on the collected status information that needs formula conversion; According to the scheduling cycle, the collected state information belonging to the high-frequency signal is subjected to time step filtering.

10. A collision detection system, characterized in that: The system comprises: A first influence amount determination module, used to determine a first influence amount of vehicle braking on the vehicle longitudinal acceleration according to a relationship curve between braking torque and vehicle longitudinal deceleration and a current braking torque of the vehicle; A shock absorber stiffness determination module, used for determining the shock absorber stiffness according to a mapping relationship between the suspension compression height and the shock absorber stiffness and a current suspension compression height of the vehicle; A second influence amount determination module is used to determine a second influence amount of the sudden change of the road surface on the longitudinal acceleration of the vehicle according to the stiffness of the shock absorber and the mass of the vehicle; A first acceleration determination module is used to determine a target acceleration in the longitudinal direction of the vehicle after correcting the braking effect and the road surface mutation effect according to the first influence amount, the second influence amount and the longitudinal acceleration of the vehicle; A confidence determination module, used to determine the confidence of the collision event according to the relationship between the target acceleration and the preset threshold corresponding to the direction of the own acceleration; The collision determination module is used to determine whether the vehicle collides according to the collision event confidence.

11. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and running on the processor, wherein when the computer program is executed by the processor, the steps in a collision detection method according to any one of claims 1 to 9 are implemented.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the collision detection method according to any one of claims 1 to 9 are implemented.

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