Vehicle collision protection method and device, vehicle and medium

Abstract

The invention provides a vehicle collision protection method and device, a vehicle and a medium. The method is applied to a collision protection system, the collision protection system comprises a sensor and a plurality of crumple modules arranged at different positions of a vehicle, and the method comprises the steps that when the vehicle is collided, initial rigidity information of the crumple modules and pressure distribution information collected by a pressure sensor are obtained, target rigidity information is determined according to the initial rigidity information and the pressure distribution information so as to adjust a collapse module to obtain a target collapse module, vehicle state information collected by an inertial sensor and collision object information collected by a millimeter wave radar are obtained, and the triggering sequence of the target collapse module is determined according to the vehicle state information and the collision object information; and triggering the target crumple module to perform collision protection on the vehicle according to the triggering sequence. According to the method, the rigidity of the crumple module is dynamically adjusted, the triggering sequence of the crumple module is determined through multi-source data fusion, and more reliable and efficient collision protection can be provided in a complex collision scene.

Description

Technical Field

[0001] This application relates to the field of collision protection, and in particular to a vehicle collision protection method, device, vehicle, and medium. Background Technology

[0002] With the continuous growth of car ownership, vehicle density on the road is constantly increasing, and the risk of collisions is rising accordingly. In the modern traffic environment, the frequency of contact between vehicles has increased significantly, especially in congested urban areas and highways, where the probability of minor scrapes and serious collisions has increased dramatically. This trend not only poses a greater threat to the safety of drivers and passengers but also places higher demands on vehicle passive safety systems.

[0003] In existing collision protection systems, collision data acquisition typically relies on a single sensor (such as an accelerometer), lacking multi-source data fusion. This results in weak anti-interference capabilities, insufficient fault tolerance, and susceptibility to environmental noise or sensor failure, thus affecting the reliability of collision protection. Furthermore, the parameter settings of existing collision protection structures are relatively fixed, failing to dynamically adjust according to different collision conditions, making it difficult to provide optimal protection in complex collision scenarios. Summary of the Invention

[0004] In view of the above problems, this application proposes a vehicle collision protection method, device, vehicle and medium.

[0005] In a first aspect of this application, a vehicle collision protection method is provided, applied to a collision protection system, the collision protection system including an inertial sensor, a millimeter-wave radar, a pressure sensor, and a plurality of crumple zones disposed at different locations on the vehicle, the method comprising: When a vehicle collision occurs, the initial stiffness information of the crumple module and the pressure distribution information collected by the pressure sensor at different locations on the vehicle are obtained. The target stiffness information of the collapse module is determined based on the initial stiffness information and the pressure distribution information; The target stiffness information is used to adjust the collapse module to obtain the target collapse module; The vehicle status information collected by the inertial sensor and the collision object information collected by the millimeter-wave radar are acquired. The triggering order of the target crumple module is determined based on the vehicle status information and the collision object information; The target collapse module is triggered according to the triggering sequence, and the vehicle is protected from collision through the target collapse module.

[0006] Optionally, determining the target stiffness information of the collapsible module based on the initial stiffness information and the pressure distribution information includes: The target collision parameters are determined based on the initial stiffness information and the pressure distribution information; If the target collision parameters are within a preset range, the target stiffness information is determined based on the initial stiffness information.

[0007] Optionally, the method further includes: If the target collision parameters are outside the preset range, random stiffness information is generated; The initial stiffness information is replaced with the random stiffness information; Repeat the step of determining the target collision parameters based on the initial stiffness information and the pressure distribution information until the target collision parameters are within a preset range.

[0008] Optionally, the initial stiffness information includes several sets of candidate stiffnesses for the collapsible modules, and determining the target stiffness information based on the initial stiffness information includes: For any set of candidate stiffnesses of the crumple module, the predicted collision parameters are calculated based on the pressure distribution information and the candidate stiffnesses of the crumple module. The candidate stiffnesses of the collapsing modules are sorted in a non-dominated manner according to the predicted collision parameters to obtain several non-dominated levels including at least one set of candidate stiffnesses of the collapsing modules. For any of the non-dominated levels, the crowding parameter of the candidate stiffness of the collapse module is determined based on the predicted collision parameters. Based on the non-dominated level and the crowding parameter, select a number of first stiffnesses of the collapse module from a number of candidate stiffnesses of the collapse module. Based on a preset crossover probability, the first stiffness of several sets of the collapse modules is adjusted to obtain the second stiffness of several sets of the collapse modules. Based on a preset mutation probability, the second stiffness of several sets of the collapse modules is adjusted to obtain several sets of third stiffness of the collapse modules. From several sets of third stiffnesses of the collapse module, a set of third stiffnesses of the collapse module is selected as the target stiffness information based on the non-dominated level and the crowding parameter.

[0009] Optionally, the vehicle status information includes the vehicle yaw rate and vehicle pitch angle, the collision object information includes the relative velocity of the collision object and the collision angle, and determining the triggering order of the target crumple module based on the vehicle status information and the collision object information includes: The collision area is determined based on the collision angle and the vehicle pitch angle. The collision type is determined based on the collision area; The collision energy allocation weight is determined based on the collision type. Obtain the vehicle's moment of inertia; The collision energy is determined based on the vehicle's yaw rate, the relative velocity of the colliding object, the collision angle, and the moment of inertia. The collision energy is allocated to the collision region according to the collision energy allocation weight to obtain the energy absorption information of the collision region. The triggering sequence of the collapse module is determined based on the energy absorption information of the collision area.

[0010] Optionally, the collision protection system further includes a camera, a stiffness adjustment component, and a hydraulic adjustment component. Before acquiring the initial stiffness information of the crumple zone module and the pressure distribution information collected by the pressure sensor at different locations on the vehicle when a collision occurs, the method further includes: Acquire vehicle driving data, historical collision data, and surrounding environment information and driver behavior information collected by the camera; The collision probability is determined based on at least one of the vehicle driving data, the historical collision data, the surrounding environment information, and the driver behavior information; If the collision probability is greater than a preset collision threshold, the stiffness adjustment component and the hydraulic adjustment component are adjusted to a ready-to-trigger state.

[0011] Optionally, the collapse module includes an alloy layer, and adjusting the collapse module using the target stiffness information to obtain the target collapse module includes: The stiffness adjustment component is used to adjust the stiffness of the alloy layer to the stiffness corresponding to the target stiffness information. The adjusted alloy layer corresponding to the collapse module is taken as the target collapse module.

[0012] Optionally, the collision protection system further includes a mechanical inertia valve and a hydraulic adjustment assembly. The mechanical inertia valve is provided with a lever structure for triggering the hydraulic adjustment assembly. The crumple module further includes a hydraulic layer, and the hydraulic adjustment assembly is connected to the hydraulic layer. The method further includes: When the mechanical inertia valve detects that the vehicle's acceleration is greater than a preset threshold, the lever structure triggers the hydraulic adjustment component. The hydraulic pressure of the hydraulic layer is adjusted using the hydraulic adjustment component. The adjusted hydraulic layer and the corresponding collapse module are used as the target collapse module.

[0013] Optionally, the collapse module further includes a pressure detection layer, in which a piezoelectric sensor is disposed, and the method further includes: When a vehicle collision occurs, the collision strain parameters of the crumple module collected by the piezoelectric sensor and the collision acceleration of the vehicle collected by the inertial sensor are acquired. After a vehicle collision, the collapsing strain parameters of the collapsing module collected by the piezoelectric sensor and the collapsing acceleration of the vehicle collected by the inertial sensor are obtained. The crumple strain rate is determined based on the impact strain parameters and the crumple strain parameters. The rate of change of acceleration is determined based on the collision acceleration and the crumpling acceleration; If the collapse strain rate is less than a preset strain rate threshold and the acceleration change rate is less than a preset acceleration change threshold, the alloy layer and the hydraulic layer are reset, and a collision report is generated.

[0014] In a second aspect of this application, a vehicle collision protection device is also provided, applied to a collision protection system, the collision protection system including an inertial sensor, a millimeter-wave radar, a pressure sensor, and a plurality of crumple zones disposed at different locations on the vehicle, the device comprising: The collision pressure acquisition module is used to acquire the initial stiffness information of the crumple module and the pressure distribution information collected by the pressure sensor at different positions on the vehicle when a collision occurs. The target stiffness determination module is used to determine the target stiffness information of the collapse module based on the initial stiffness information and the pressure distribution information. A collapse module adjustment module is used to adjust the collapse module using the target stiffness information to obtain a target collapse module; The collision information acquisition module is used to acquire vehicle status information collected by the inertial sensor and collision object information collected by the millimeter-wave radar; The triggering order determination module is used to determine the triggering order of the target crumple module based on the vehicle status information and the collision object information; The collision protection execution module is used to trigger the target collapse module according to the triggering sequence, and to perform collision protection on the vehicle through the target collapse module.

[0015] In a third aspect of this application, a vehicle is also provided, characterized in that it includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the method described above.

[0016] In a fourth aspect of this application, a computer-readable storage medium is also provided, characterized in that a computer program is stored on the computer-readable storage medium, and the computer program, when executed by a processor, implements the method described above.

[0017] The embodiments of this application have the following advantages: In this embodiment, when a vehicle collision occurs, the initial stiffness information of the crumple zone module and the pressure distribution information collected by the pressure sensor at different locations on the vehicle are acquired. Based on these initial stiffness and pressure distribution information, the target stiffness information of the crumple zone module is determined. The crumple zone module is then adjusted using this target stiffness information to obtain the target crumple zone module. This application can dynamically adjust the stiffness of the crumple zone module according to the collision conditions. By acquiring the initial stiffness and pressure distribution information, the target stiffness information is determined in real time, and the crumple zone module is adjusted to adapt to different collision scenarios, providing a better protection effect. Vehicle state information collected by inertial sensors and collision object information collected by millimeter-wave radar are acquired. This application integrates multiple sensors such as inertial sensors, millimeter-wave radar, and pressure sensors to achieve multi-source data fusion, significantly improving the system's anti-interference capability and fault tolerance. The triggering order of the target crumple zone module is determined based on the vehicle state information and collision object information. The target crumple zone module is triggered according to the triggering order, and the vehicle is protected from collision using the target crumple zone module. Determining the triggering order of the crumple zone module based on the vehicle state information and collision object information optimizes the energy absorption path, further improving the efficiency and effectiveness of collision protection. It can provide more reliable and efficient collision protection in complex collision scenarios. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.

[0019] Figure 1 This is a flowchart illustrating the steps of a vehicle collision protection method according to an embodiment of this application; Figure 2 This is a logic flowchart of a genetic algorithm provided in one embodiment of this application; Figure 3 This is a logic flowchart of a collision protection method provided in one embodiment of this application; Figure 4 This is a schematic diagram of the structure of a vehicle collision protection device provided in one embodiment of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the various embodiments of this application will be described in detail below with reference to the accompanying drawings. However, those skilled in the art will understand that many technical details have been presented in the various embodiments of this application to enable readers to better understand this application. However, the technical solutions claimed in this application can be implemented even without these technical details and various changes and updates based on the following embodiments. The division of the various embodiments below is for the convenience of description and should not constitute any limitation on the specific implementation of this application. The various embodiments can be combined with and referenced by each other without contradiction.

[0021] Existing vehicle crumple zones (such as front longitudinal beams and bumper energy-absorbing boxes) typically employ fixed geometries or single materials, limiting their energy absorption efficiency to a predetermined deformation pattern. Although novel energy-absorbing solutions such as honeycomb structures and multi-stage folding designs exist, these structures still cannot dynamically adjust their energy absorption characteristics based on differences in collision direction, speed, and mass.

[0022] Furthermore, the stiffness of existing collision protection structures, i.e., energy-absorbing structures, is relatively fixed and cannot dynamically adapt to different collision scenarios. For example, existing crumple zones (such as honeycomb aluminum materials and corrugated steel beams) rely on preset geometric deformation patterns, and their structural mechanical properties cannot be dynamically adjusted according to collision parameters. When the collision direction, velocity, or mass changes, the energy absorption efficiency will decrease significantly.

[0023] Therefore, this application provides a vehicle collision protection method, device, vehicle, and medium that can dynamically adjust the stiffness of the crumple zone according to collision conditions. By acquiring initial stiffness information and pressure distribution information, it determines the target stiffness information in real time and adjusts the crumple zone to adapt to different collision scenarios, providing better protection. Furthermore, it integrates multiple sensors such as inertial sensors, millimeter-wave radar, and pressure sensors, achieving multi-source data fusion and significantly improving the system's anti-interference capability and fault tolerance. By determining the triggering sequence of the crumple zone through vehicle status information and collision object information, it optimizes the energy absorption path, further improving the efficiency and effectiveness of collision protection. It can provide more reliable and efficient collision protection in complex collision scenarios.

[0024] Reference Figure 1 The diagram shows a flowchart of the steps of a vehicle collision protection method provided in an embodiment of this application.

[0025] In this embodiment, the vehicle collision protection method can be applied to a collision protection system, which includes an inertial sensor, millimeter-wave radar, a pressure sensor, and several crumple zones located at different positions on the vehicle. In this embodiment, the collision protection system can protect the vehicle when a collision occurs.

[0026] It should be noted that a collision protection system can be an intelligent safety system integrating multiple sensors and actuators. It can rapidly respond and take protective measures in the event of a collision by monitoring the vehicle's status and external environment in real time, thereby reducing the risk of occupant injury and vehicle damage. In the embodiments of this application, the collision protection system may include data acquisition devices such as inertial sensors, millimeter-wave radar, pressure sensors, cameras, and strain sensors, as well as actuators such as stiffness adjustment components, hydraulic adjustment components, mechanical inertia valves, and hydraulic adjustment components.

[0027] An inertial sensor can be a device used to measure motion parameters such as acceleration, angular velocity, and tilt angle of an object, and may include accelerometers and gyroscopes. In the embodiments of this application, the inertial sensor can be used to monitor the dynamic changes of a vehicle in real time, providing vehicle status information for collision detection.

[0028] Millimeter-wave radar is a sensor that uses millimeter-wave electromagnetic waves for detection and ranging, and it features high precision and strong anti-interference capabilities. In this embodiment, millimeter-wave radar can be used to detect collision objects around a vehicle and obtain collision object information.

[0029] A pressure sensor can be a device used to measure pressure changes, capable of detecting the impact force or pressure changes generated during a vehicle collision. In the embodiments of this application, the pressure sensor can be used to capture mechanical information at the moment of collision to obtain pressure distribution information.

[0030] A crumple module is a structure designed to absorb and disperse impact energy during a collision. It can be installed in various parts of a vehicle, such as distributed throughout the body. Upon impact, the crumple module deforms or folds to reduce the impact force transmitted to the passenger compartment, thereby improving vehicle safety. Furthermore, adjacent crumple modules can be connected by shear-weakening rivets. In practical implementation, the structure of a crumple module can be divided into an alloy layer, a hydraulic layer, and a pressure sensing layer.

[0031] In a specific implementation, taking a crumple module comprising an alloy layer, a hydraulic layer, and a pressure detection layer as an example, an alloy layer can be placed on the side of the crumple module furthest from the vehicle. This alloy layer can be a three-dimensional mesh structure formed by 2mm thick SMA (Shape Memory Alloy) wire mesh weaving, providing higher structural strength and stability, better dispersing collision loads, and improving energy absorption efficiency. In this embodiment, the stiffness of the alloy layer can be adjusted by triggering deformation of the shape memory alloy through localized heating.

[0032] Furthermore, in the alloy layer, the mesh density of the SMA mesh on the side of the alloy layer away from the vehicle is greater than that on the side closer to the vehicle. During a collision, the side that first contacts the impact object has smaller mesh openings, providing higher rigidity and initial impact resistance. The other side has larger mesh openings, reducing rigidity and allowing subsequent modules to gradually collapse, achieving staged energy absorption.

[0033] In the middle layer of the collapse module, a hydraulic layer can be provided. This hydraulic layer can be a hydraulic cavity filled with other buffer solutions. The stiffness of the hydraulic layer can be adjusted by filling or releasing the buffer solution. Furthermore, the hydraulic layer can include several hydraulic cavities for containing the buffer solution.

[0034] A pressure detection layer can be set on the side of the crumple module closest to the vehicle. The pressure detection layer can be equipped with a piezoelectric sensor. In this embodiment, the pressure detection layer can be used to monitor the collision strain parameters and crumple strain parameters of the crumple module in real time.

[0035] Furthermore, in the alloy layer, the mesh density of the SMA mesh on the side of the alloy layer away from the vehicle is greater than that on the side closer to the vehicle. During a collision, the side that first contacts the impact object has smaller mesh openings, providing higher rigidity and initial impact resistance. The other side has larger mesh openings, reducing rigidity and allowing subsequent modules to gradually collapse, achieving staged energy absorption.

[0036] Furthermore, if there are adjacent collapse modules around a collapse module, they can be connected by shear-weakening rivets.

[0037] The method may specifically include the following steps: Step 101: When a vehicle collision occurs, acquire the initial stiffness information of the crumple module and the pressure distribution information collected by the pressure sensor at different locations on the vehicle.

[0038] In this embodiment, when a vehicle collision occurs, the initial stiffness information of the crumple zone module and the pressure distribution information collected by pressure sensors at different locations on the vehicle can be obtained. The initial stiffness information represents the original stiffness state of the crumple zone module before the collision. Simultaneously, through pressure sensors distributed at different locations on the vehicle, the system can collect pressure distribution information for various parts of the vehicle during the collision.

[0039] Step 102: Determine the target stiffness information of the collapsible module based on the initial stiffness information and the pressure distribution information.

[0040] In this embodiment, the target stiffness information of the crumple module can be determined based on the initial stiffness information and the pressure distribution information. The target stiffness information represents the target stiffness state of the crumple module that enables it to provide collision protection during a collision.

[0041] In practical implementation, by analyzing the initial stiffness information of several crumple modules during a collision and the pressure distribution information collected on the vehicle, a set of optimal stiffness corresponding to the optimal energy absorption and dispersion of several crumple modules during the collision process can be calculated, and this set of optimal stiffness can be used as the target stiffness state of several crumple modules.

[0042] Step 103: Adjust the collapsing module using the target stiffness information to obtain the target collapsing module.

[0043] In this embodiment, the stiffness of the crumple module can be adjusted using target stiffness information, and the adjusted crumple module can be used as the target crumple module. In a specific implementation, the structure of the crumple module can be divided into an alloy layer, a hydraulic layer, and a pressure detection layer.

[0044] In practice, the stiffness of the crumple module can be adjusted in real time by changing the stiffness of the alloy layer of the crumple module and changing the hydraulic pressure of the hydraulic layer of the crumple module.

[0045] Step 104: Obtain the vehicle status information collected by the inertial sensor and the collision object information collected by the millimeter-wave radar.

[0046] In this embodiment, vehicle state information collected by the inertial sensor and collision object information collected by the millimeter-wave radar can be acquired. The vehicle state information may include state parameters such as vehicle yaw rate and vehicle pitch angle. The collision object information may include parameters such as the relative velocity of the collision object and the collision angle.

[0047] Step 105: Determine the triggering order of the target crumple module based on the vehicle status information and the collision object information.

[0048] In this embodiment, the triggering order of the target crumple modules can be determined based on vehicle status information and collision object information. The triggering order of the target crumple modules refers to the crumple sequence of the target crumple modules that maximizes the safety of the vehicle occupants during a collision.

[0049] In practical implementation, the triggering sequence of the target crumple zone modules can be determined through comprehensive analysis of vehicle status information and collision object information. This intelligent triggering sequence decision-making enables more effective absorption of collision energy and protects the safety of vehicle occupants.

[0050] Step 106: Trigger the target crumple module according to the triggering sequence, and use the target crumple module to perform collision protection on the vehicle.

[0051] In this embodiment of the application, the target collapse module can be triggered in the order of triggering, and the vehicle can be protected from collision through the target collapse module.

[0052] In practical implementation, if the triggering order is determined, the system can trigger the target crumple modules sequentially according to the triggering order. The stiffness of the target crumple module can be adjusted in real time by changing the stiffness of the alloy layer of the crumple module and changing the hydraulic pressure of the hydraulic layer of the crumple module, thereby absorbing collision energy and reducing the impact force transmitted to the vehicle structure and occupants.

[0053] In this embodiment, when a vehicle collision occurs, the initial stiffness information of the crumple zone module and the pressure distribution information collected by the pressure sensor at different locations on the vehicle are acquired. Based on these initial stiffness and pressure distribution information, the target stiffness information of the crumple zone module is determined. The crumple zone module is then adjusted using this target stiffness information to obtain the target crumple zone module. This application can dynamically adjust the stiffness of the crumple zone module according to the collision conditions. By acquiring the initial stiffness and pressure distribution information, the target stiffness information is determined in real time, and the crumple zone module is adjusted to adapt to different collision scenarios, providing a better protection effect. Vehicle state information collected by inertial sensors and collision object information collected by millimeter-wave radar are acquired. This application integrates multiple sensors such as inertial sensors, millimeter-wave radar, and pressure sensors to achieve multi-source data fusion, significantly improving the system's anti-interference capability and fault tolerance. The triggering order of the target crumple zone module is determined based on the vehicle state information and collision object information. The target crumple zone module is triggered according to the triggering order, and the vehicle is protected from collision using the target crumple zone module. Determining the triggering order of the crumple zone module based on the vehicle state information and collision object information optimizes the energy absorption path, further improving the efficiency and effectiveness of collision protection. It can provide more reliable and efficient collision protection in complex collision scenarios.

[0054] In one optional embodiment of this application, step 102 further includes the following steps: S111, Determine the target collision parameters based on the initial stiffness information and the pressure distribution information; S112, if the target collision parameters are within a preset range, then the target stiffness information is determined based on the initial stiffness information.

[0055] It should be noted that target collision parameters can refer to collision-related parameters calculated based on initial stiffness information and pressure distribution information. Among them, target collision parameters may include occupant compartment intrusion, peak acceleration, and stiffness adjustment cost, etc.

[0056] In this embodiment, target collision parameters can be determined based on initial stiffness information and pressure distribution information. If the target collision parameters are within a preset range, it indicates that the initial stiffness information can meet the constraints such as occupant compartment intrusion, peak acceleration, and stiffness adjustment cost, and the target stiffness information can be further determined based on the initial stiffness information.

[0057] In practical implementation, when the stiffness of the crumple module is adjusted in real time by changing the stiffness of the alloy layer, the stiffness adjustment cost can be reflected as the heating energy consumption corresponding to the heating power used to heat the alloy layer. The preset range of the target collision parameters can be set as follows: crew compartment intrusion less than or equal to 100mm, peak acceleration less than or equal to 40g, and alloy layer heating energy consumption less than 200J.

[0058] This application determines target collision parameters by combining initial stiffness information and pressure distribution information, and optimizes the target stiffness information according to a preset range, enabling precise control and optimization of the collision process. This not only effectively reduces occupant compartment intrusion and peak acceleration, but also reduces energy consumption during stiffness adjustment. In one optional embodiment of this application, the method further includes: S121, If ​​the target collision parameters are outside the preset range, random stiffness information is generated; S122, replace the initial stiffness information with the random stiffness information; S123, repeat the step of determining the target collision parameters based on the initial stiffness information and the pressure distribution information until the target collision parameters are within a preset range.

[0059] In this embodiment, if the target collision parameters are outside the preset range, it indicates that the initial stiffness information cannot meet the constraints such as passenger compartment intrusion, peak acceleration, and stiffness adjustment cost. In this case, random stiffness information can be generated and used to replace the initial stiffness information. The process of determining the target collision parameters based on the initial stiffness information and pressure distribution information is repeated until the target collision parameters are within the preset range, that is, until the initial stiffness information can meet the constraints such as passenger compartment intrusion, peak acceleration, and stiffness adjustment cost. The random stiffness information can represent the stiffness state of a randomly generated crumple zone.

[0060] When the target collision parameters exceed a preset range, this application indicates that the initial stiffness information cannot meet constraints such as occupant compartment intrusion, peak acceleration, and stiffness adjustment costs. At this point, random stiffness information is generated and used to replace the initial stiffness information, and the target collision parameters are recalculated. This process continues until the target collision parameters fall within the preset range, ensuring that the initial stiffness information meets all constraints. In this way, the collision protection system can find the optimal solution among multiple possible stiffness configurations, thereby improving collision safety and energy efficiency while reducing energy consumption during stiffness adjustment. This method not only enhances the adaptability and robustness of the collision protection system but also provides more flexibility and possibilities for optimizing collision performance.

[0061] In an optional embodiment of this application, the initial stiffness information includes several sets of candidate stiffnesses for the collapsible modules, and step S112 further includes the following steps: S131, For any set of candidate stiffnesses of the crumple module, calculate the predicted collision parameters based on the pressure distribution information and the candidate stiffnesses of the crumple module; S132, according to the predicted collision parameters, sort the candidate stiffness of the several groups of the collapse module in a non-dominated manner to obtain several non-dominated levels including at least one group of candidate stiffness of the collapse module. S133, for any of the non-dominated levels, determine the crowding parameter of the candidate stiffness of the collapse module based on the predicted collision parameters; S134, select a number of first stiffnesses of the collapse module from a number of candidate stiffnesses of the collapse module according to the non-dominated level and the crowding parameter. S135, Based on the preset crossover probability, adjust the first stiffness of several sets of the collapse modules to obtain the second stiffness of several sets of the collapse modules. S136, Based on a preset mutation probability, adjust the second stiffness of several sets of the collapse modules to obtain several sets of third stiffness of the collapse modules. S137, From a plurality of groups of third stiffnesses of the collapse module, select a group of third stiffnesses of the collapse module according to the non-dominated level and the crowding parameter, as the target stiffness information.

[0062] In this embodiment, the initial stiffness information includes several sets of candidate stiffnesses for crumple modules. For the several crumple modules located at different positions on the vehicle, the initial stiffness corresponding to each of the several crumple modules can be used as a set of candidate stiffnesses. In this embodiment, for any set of candidate stiffnesses for crumple modules, predicted collision parameters can be calculated based on pressure distribution information and the candidate stiffnesses. The predicted collision parameters can refer to collision-related parameters predicted based on the initial stiffness information and pressure distribution information, and may include predicted passenger compartment intrusion, predicted peak acceleration, and predicted stiffness adjustment cost. It is understood that the predicted passenger compartment intrusion, predicted peak acceleration, and predicted stiffness adjustment cost are the predicted passenger compartment intrusion, peak acceleration, and stiffness adjustment cost. Furthermore, the predicted collision parameters are calculated for any set of candidate stiffnesses for crumple modules based on pressure distribution information and the candidate stiffnesses.

[0063] In this embodiment, several sets of candidate crumple module stiffnesses can be non-dominated according to the predicted collision parameters to obtain several non-dominated levels including at least one set of candidate crumple module stiffnesses. The non-dominated level can refer to the non-dominated front ranking, which, in a multi-objective optimization problem, describes the relative merits of different stiffness configurations. Specifically, the non-dominated level can be used to distinguish which candidate crumple module stiffnesses perform better in terms of cabin intrusion, peak acceleration, and stiffness adjustment cost. Candidate crumple module stiffnesses with better performance have smaller non-dominated levels. If there are two non-dominated levels, the candidate crumple module stiffness with the smaller non-dominated level will not be completely dominated by the candidate crumple module stiffness with the larger non-dominated level.

[0064] In this embodiment, for any non-dominated level, a crowding parameter for the candidate stiffness of the collapsible module can be determined based on the predicted collision parameters. The crowding parameter can be an index used to evaluate the uniformity of solution distribution in a multi-objective optimization problem. It can be used in conjunction with the non-dominated level to find a balanced candidate stiffness for the collapsible module among multiple candidate stiffnesses. In this embodiment, the crowding parameter reflects the degree of balance among the candidate stiffnesses of the collapsible module.

[0065] In this embodiment, several sets of first stiffness for collapse modules can be selected from several sets of candidate stiffness for collapse modules based on the non-dominated front level and the crowding parameter. That is, several sets of first stiffness for collapse modules can be selected from several sets of candidate stiffness for collapse modules based on the non-dominated front level and the crowding parameter. The number of sets of candidate stiffness for collapse modules and the number of sets of first stiffness for collapse modules are the same; that is, if there are 5 sets of candidate stiffness for collapse modules, then 5 sets of first stiffness for collapse modules are selected. During selection, candidate stiffness for collapse modules with smaller non-dominated levels are preferred, and when the non-dominated levels are the same, candidate stiffness for collapse modules with larger crowding parameters are selected as the first stiffness for collapse modules. Each set of first stiffness for collapse modules contains stiffness information corresponding to one or more collapse modules. When using a genetic algorithm to determine the target stiffness information, the first stiffness for collapse modules can represent the parent stiffness information selected from the candidate stiffness for collapse modules.

[0066] In this embodiment, the first stiffness of several sets of collapse modules can be adjusted based on a preset crossover probability to obtain several sets of second stiffness of collapse modules. The crossover probability can be set according to actual needs, and the second stiffness of the collapse module is the stiffness information corresponding to one or more collapse modules obtained by crossover of the first stiffness of the collapse modules.

[0067] In this embodiment, the second stiffness of several sets of collapse modules can be adjusted based on a preset mutation probability to obtain several sets of third stiffness of collapse modules. The mutation probability can be set according to actual needs, and the third stiffness of the collapse module is the stiffness information corresponding to one or more collapse modules obtained by mutating the first stiffness of the collapse module.

[0068] In this embodiment, a set of third stiffnesses for collapse modules can be selected from several sets of third stiffnesses based on the non-dominated level and congestion parameter as the target stiffness information. Alternatively, the set of third stiffnesses with the smallest non-dominated level and the largest congestion parameter can be selected as the target stiffness information. It is understood that the target stiffness information can also be selected from several sets of candidate stiffnesses, several sets of first stiffnesses, several sets of second stiffnesses, and several sets of third stiffnesses for collapse modules, based on the smallest non-dominated level and the largest congestion parameter.

[0069] In the specific implementation, you can refer to Figure 2 Obtain target stiffness information. Figure 2 A flowchart illustrating the logic of a genetic algorithm according to an embodiment of this application is shown. In a specific implementation, the non-dominated sorting genetic algorithm (NSGA-II) can be used to determine the target stiffness information.

[0070] The process begins with a genetic algorithm to initialize the population and obtain random stiffness information. This random stiffness information can be the initial stiffness information used in this application.

[0071] Then, an fitness assessment is performed on the random stiffness information to calculate the crew compartment intrusion, peak acceleration, and stiffness adjustment cost corresponding to the random stiffness information. In this embodiment, target collision parameters can be calculated based on initial stiffness information and pressure distribution information.

[0072] Then it is determined whether the passenger compartment intrusion, peak acceleration, and stiffness adjustment cost all meet the constraints. If the values ​​of passenger compartment intrusion, peak acceleration, and stiffness adjustment cost do not meet the constraints, the random stiffness information is reacquired.

[0073] If the values ​​of passenger compartment intrusion, peak acceleration, and stiffness adjustment cost can meet the constraints of passenger compartment intrusion, peak acceleration, and stiffness adjustment cost, that is, in this embodiment of the application, the target collision parameters are within a preset range, then proceed to the next step.

[0074] In this embodiment, the candidate stiffness of the collapse module can be sorted according to the predicted collision parameters. The dominance relationship between each group of candidate stiffness of the collapse module and the other groups of candidate stiffness of the collapse module is calculated. If a group of candidate stiffness of the collapse module A is not inferior to another group of candidate stiffness of the collapse module B in all types of candidate collision parameters, and this group of candidate stiffness of the collapse module A is superior to the other group of candidate stiffness of the collapse module B in at least one type of candidate collision parameter, then A dominates B. Based on the dominance relationship, a non-dominated level is generated, and the non-dominated level of the collapse module candidate stiffness with better performance is smaller. If there are two non-dominated levels, Front 1 and Front 2, the collapse module candidate stiffness corresponding to Front 1 with a smaller non-dominated level will not be completely dominated by the collapse module candidate stiffness corresponding to Front 2 with a larger non-dominated level. Front 1 can be regarded as the optimal non-dominated level. The determination method between any two other non-dominated levels is the same as described above, and finally several non-dominated levels will be obtained.

[0075] Crowding degree calculation is performed by sorting the candidate stiffnesses of collapsible modules within the same non-dominated level in ascending order according to the values ​​of the predicted collision parameters. The crowding degree parameter for each group of candidate stiffnesses is then calculated. Specifically, for each predicted collision parameter, assuming there are three groups of candidate stiffnesses C, D, and E sorted in ascending order according to their predicted collision parameter values, the crowding degree parameter for candidate stiffness D is equal to the difference between the candidate collision parameter values ​​of candidate stiffness E and candidate stiffness C. The overall crowding degree parameter for candidate stiffness D is the sum of the crowding degrees for candidate stiffness D under each predicted collision parameter.

[0076] When selecting the parent stiffness combination, candidates for the collapse module with a smaller non-dominated level can be selected. When the non-dominated levels are the same, several groups of candidates for the collapse module with larger crowding parameters are selected as the parent stiffness combination, which are the several groups of first stiffnesses of the collapse module in the embodiments of this application.

[0077] A cross operation is performed to simulate binary cross operation on several selected groups of candidate stiffnesses of the collapse modules, thereby obtaining several groups of second stiffnesses of the collapse modules in this embodiment of the application.

[0078] A mutation operation is performed on the second stiffness of several sets of collapsible modules after crossover, according to a preset mutation probability, to obtain several sets of third stiffness of collapsible modules in this embodiment of the application.

[0079] When selecting the stiffness combination for the offspring, the third stiffness of the collapsible module can be used as the stiffness combination for the offspring.

[0080] The algorithm checks if the maximum number of iterations has been reached. If not, it regenerates the random stiffness information and repeats the above steps. If the maximum number of iterations has been reached, it proceeds to the next step. In a specific implementation, the maximum number of iterations can be set to 50.

[0081] The optimal stiffness combination can be selected from several sets of third stiffness of the collapsible modules, choosing the set of third stiffness of the collapsible modules with the smallest non-dominated level and the largest crowding parameter as the optimal stiffness combination, which is the target stiffness information in the embodiments of this application.

[0082] Then, the real-time control section can be implemented, and the heating power can be determined based on the optimal stiffness combination. That is, when the stiffness of the collapse module is adjusted in real time by changing the stiffness of the alloy layer of the collapse module, the heating power for heating the alloy layer can be determined based on the optimal stiffness combination.

[0083] Heating commands are issued to heat the alloy layer based on the heating power. These heating commands can be real-time heating power commands for each collapse module.

[0084] Then, it can be determined whether the collision has terminated. If the collision has not terminated, the collision-related sensor data is updated, and the fitness assessment of the random stiffness information or target stiffness information is performed again. If the collision has terminated, the process ends.

[0085] This application introduces a non-dominated sorting genetic algorithm, combining candidate collision parameters, non-dominated hierarchy, and crowding parameters to achieve multi-objective optimization of the crumple zone stiffness. It effectively balances multiple objectives such as occupant compartment intrusion, peak acceleration, and stiffness adjustment costs, ensuring occupant safety while reducing energy consumption during stiffness adjustment during a collision. Through hierarchical sorting and crowding calculation, the system can select a uniformly distributed and optimal stiffness configuration, avoiding solution concentration and local optima problems. Furthermore, crossover and mutation operations enhance the diversity of stiffness configurations, improving the algorithm's robustness and adaptability. The final selected stiffness information can be applied in real-time to vehicle collision control, improving overall safety and energy efficiency.

[0086] In one optional embodiment of this application, the vehicle state information includes the vehicle yaw rate and the vehicle pitch angle, the collision object information includes the relative velocity of the collision object and the collision angle, and step 105 further includes the following steps: S141, determine the collision area based on the collision angle and the vehicle pitch angle; S142, determine the collision type based on the collision area; S143, determine the collision energy allocation weight according to the collision type; S144, obtain the vehicle's moment of inertia; S145, determine the collision energy based on the vehicle yaw rate, the relative velocity of the colliding object, the collision angle, and the moment of inertia; S146, Distribute the collision energy to the collision region according to the collision energy distribution weight to obtain collision region energy absorption information; S147, determine the triggering sequence of the collapse module based on the energy absorption information of the collision area.

[0087] It should be noted that the yaw rate of a vehicle can refer to the angular velocity of the vehicle rotating about its vertical axis (usually the Z-axis). In the embodiments of this application, it can represent the rotational motion of the vehicle in the horizontal plane at the time of a collision.

[0088] The vehicle pitch angle refers to the angular change between the front and rear axles of a vehicle. In this embodiment, it can represent the attitude change of the vehicle during a collision. A positive value indicates that the front of the vehicle has lifted, and a negative value indicates that the front of the vehicle has sunk.

[0089] The relative velocity between the colliding objects refers to the difference in relative velocity between the vehicle and the colliding object. It reflects the velocity relationship between the two at the moment of collision and, in the embodiments of this application, can be used to assess the severity of the collision.

[0090] The collision angle refers to the contact angle between a vehicle and a colliding object at the moment of impact. It reflects the location and direction of the collision and, in this embodiment, can be used to assess the vehicle's trajectory and the extent of damage after the collision.

[0091] The moment of inertia of a vehicle refers to the physical quantity that resists rotational motion when the vehicle rotates around its center of mass. It depends on the vehicle's mass distribution, i.e., how the mass is distributed relative to the axis of rotation. A larger moment of inertia makes it more difficult for the vehicle to change its rotational state when subjected to torque, and vice versa. In the embodiments of this application, it can be used to evaluate the yaw, pitch, and roll motions of a vehicle after a collision.

[0092] In this embodiment, the collision area can be determined based on the collision angle and the vehicle pitch angle, that is, the specific location where the collision occurred can be determined. The collision area can represent the region where the vehicle and the object in contact during the collision, and the collision energy can represent the energy generated by the collision between the vehicle and the object.

[0093] In this embodiment, the collision type can be determined based on the collision area, where the collision type can refer to frontal collision, side collision, offset collision, and rear-end collision, etc. Then, the collision energy allocation weight can be determined based on the collision type.

[0094] In practical implementation, collision energy distribution weights can be determined based on preset weight mapping relationships. These preset weight mapping relationships reflect the relationship between collision type and collision energy distribution weights. For example, in a frontal collision, the vehicle's front longitudinal beams and bumper energy-absorbing boxes can be set as high-weight areas, the firewall and A-pillars as medium-weight areas, and the side panels as low-weight areas. In a side collision, the B-pillars, door anti-collision beams, and sills can be set as high-weight areas, the seat crossbeams as medium-weight areas, and the roof longitudinal beams as low-weight areas. In an offset collision, the impact-side A-pillars and front longitudinal beams can be set as high-weight areas, the sill beams as medium-weight areas, and the non-impact-side longitudinal beams as low-weight areas. In a rear-end collision, the rear longitudinal beams and rear anti-collision beams can be set as high-weight areas, the C-pillars as medium-weight areas, and the trunk floor as low-weight areas. Other methods can also be used to set high-weight, medium-weight, and low-weight areas.

[0095] Specifically, the collision energy allocation weight for high-weight regions is greater than 0.6, the collision energy allocation weight for medium-weight regions is greater than 0.2 and less than 0.4, and the collision energy allocation weight for low-weight regions is less than 0.2. Furthermore, the sum of the collision energy allocation weights for high-weight, medium-weight, and low-weight regions equals 1.

[0096] In this embodiment of the application, the vehicle's moment of inertia can be obtained, and the collision energy can be determined based on the vehicle's yaw rate, the relative velocity of the colliding object, the collision angle, and the moment of inertia.

[0097] In practical implementation, the following formula can also be used to calculate the collision energy:

[0098] in, Let m represent the collision energy (J), m represent the vehicle mass (kg), and v represent the relative velocity of the colliding objects (m / s). Indicates the collision angle (degrees). The moment of inertia of a vehicle (kg· ), This indicates the vehicle's yaw rate (rad / s).

[0099] In this embodiment, collision energy can be allocated to the collision area according to the collision energy allocation weight to obtain collision area energy absorption information. This collision area energy absorption information represents the energy that needs to be absorbed in the collision area. The triggering sequence of the collapse module can then be determined based on this collision area energy absorption information.

[0100] In the specific implementation, the energy absorption information of the collision area can be arranged in descending order from high to low, and the collision area corresponding to the energy absorption information of the collision area can be obtained. The target collapse module in the collision area is triggered in the order of energy absorption information from high to low, so as to obtain the triggering order of the collapse module.

[0101] This application, by accurately identifying the collision zone, can prioritize the triggering of crumple zones located within that zone, ensuring effective absorption and dispersion of collision energy and reducing intrusion into the passenger compartment and the transmission of impact force. By comprehensively considering vehicle yaw rate, pitch angle, relative velocity of the collision object, collision angle, and moment of inertia, this application can more accurately assess collision energy, thereby improving the precision and reliability of collision analysis. Simultaneously, based on the magnitude of the collision energy, the triggering sequence of the crumple zones can be rationally allocated, achieving refined control of energy absorption. This dynamic triggering strategy not only improves the targeting of collision protection but also reduces unnecessary energy consumption, enhancing the overall safety and economy of the vehicle.

[0102] In one optional embodiment of this application, the collision protection system further includes a camera, a stiffness adjustment component, and a hydraulic adjustment component. Prior to step 101, the method further includes the following steps: S151, acquire vehicle driving data, historical collision data, and surrounding environment information and driver behavior information collected by the camera; S152, determine the collision probability based on at least one of the vehicle driving data, the historical collision data, the surrounding environment information, and the driver behavior information; S153, if the collision probability is greater than the preset collision threshold, adjust the stiffness adjustment component and the hydraulic adjustment component to the ready-to-trigger state.

[0103] In this embodiment, vehicle driving data, historical collision data, and surrounding environment information and driver behavior information collected by a camera can be acquired. Then, a collision probability is determined based on at least one of these three data. If the collision probability exceeds a preset collision threshold, the stiffness adjustment component and the hydraulic adjustment component are adjusted to a ready-to-trigger state. The stiffness adjustment component is used to adjust the stiffness of the alloy layer, and the hydraulic adjustment component is used to adjust the hydraulic pressure of the hydraulic layer.

[0104] The vehicle driving data may include the vehicle's dynamic state, including information such as acceleration, steering angle, and yaw rate obtained through IMU (Inertial Measurement Unit), wheel speed sensor, and EPS (Electric Power Steering).

[0105] Historical collision data can include historical accident data or collision frequency statistics for similar scenarios from a cloud database.

[0106] Surrounding environment information can include traffic environment and road information. It can be information such as the location, speed and type of obstacles identified by sensing cameras, lidar, and V2X (Vehicle-to-Everything) or information such as curve curvature, slope and lane boundary determined by high-precision maps and GPS.

[0107] Driver behavior information can include operational intentions, which can be predicted and determined by information such as steering wheel torque and pedal travel.

[0108] In a practical implementation, the preset collision threshold can be set to 80%. The collision time can be determined based on at least one of vehicle driving data, historical collision data, surrounding environment information, and driver behavior information. When the collision time (Time to Collision, TTC) is less than 0.5 seconds, the collision probability can be considered to be greater than 80%.

[0109] In practical implementation, collision time is determined based on vehicle driving data. This can be achieved by acquiring real-time dynamic states such as vehicle acceleration, steering angle, and yaw rate using IMU, wheel speed sensors, and EPS. Combined with the current vehicle speed and direction, the vehicle's trajectory in the next few seconds can be predicted. By obtaining the relative speed and distance between the vehicle and the obstacle, and assuming the collision time equals distance divided by relative speed, the collision time can be estimated.

[0110] In practical implementation, collision time is determined based on historical collision data. This can be achieved by statistically analyzing the collision frequency and typical collision times of similar scenarios using a cloud database. The system compares the current scenario with historical data and can use the collision times from the historical data as a reference for the predicted collision time.

[0111] In practical implementation, the collision time is determined based on surrounding environmental information. The location, speed, and type of obstacles can be obtained through cameras, LiDAR, or V2X. Combined with curvature and slope data from high-precision maps, the collision risk is dynamically calculated. If the vehicle in front suddenly decelerates, the system calculates the Time to Collision (TTC) based on the speed difference and distance between the two vehicles. If a large curve curvature is detected in the high-precision map, the system can estimate the potential time of lane departure based on the vehicle's current speed, and comprehensively predict the collision time.

[0112] In practice, collision time is determined based on driver behavior information. This can be achieved by monitoring steering wheel torque and pedal travel to predict driver intent, and by combining this with the driver's operational efficiency to predict collision time.

[0113] In the specific implementation, the stiffness adjustment component and the hydraulic adjustment component are adjusted to a ready-to-trigger state. Since the stiffness adjustment component can be an electric heating component that heats the alloy layer to change its stiffness, and the electric heating component may include a capacitor, the capacitor in the stiffness adjustment component can be pre-charged. Since the hydraulic adjustment component may include a buffer storage area for storing buffer solution, the buffer storage area can be pre-pressurized.

[0114] This application dynamically assesses collision probability by integrating vehicle driving data, historical collision data, surrounding environmental information, and driver behavior information. When the collision probability exceeds a preset threshold, it proactively adjusts the stiffness adjustment component and hydraulic adjustment component to a ready-to-trigger state, thereby achieving proactive prevention and protection against collision risks. This significantly improves vehicle safety and reduces the occurrence of collision accidents. Furthermore, through accurate collision probability calculation and a rapid response mechanism, it ensures the system's high efficiency and reliability.

[0115] In an optional embodiment of this application, the collapse module includes an alloy layer, and step 103 further includes the following steps: S161, The stiffness of the alloy layer is adjusted to the stiffness corresponding to the target stiffness information using the stiffness adjustment component; S162, the collapsing module corresponding to the adjusted alloy layer is taken as the target collapsing module.

[0116] In this embodiment of the application, a stiffness adjustment component can be used to adjust the stiffness of the alloy layer to the stiffness corresponding to the target stiffness information, and the collapsing module corresponding to the adjusted alloy layer can be used as the target collapsing module.

[0117] In a specific implementation, since the stiffness adjustment component can be an electric heating component that heats the alloy layer to change its stiffness, the heating power of the alloy layer can be determined according to the target stiffness information. The stiffness adjustment component heats the alloy layer according to the heating power, and the completion of heating is regarded as adjusting the stiffness of the alloy layer to the stiffness corresponding to the target stiffness information.

[0118] Existing collision protection structures heavily rely on electronic control systems, which are susceptible to response delays and failures. For example, current dynamic energy absorption technologies are controlled by an ECU (Electronic Control Unit), but due to sensor signal transmission and algorithm calculations, system response delays are typically high. Furthermore, circuit failures (such as power outages caused by a collision) can directly lead to the failure of the adjustment function. Additionally, current technologies lack mechanical redundancy triggering mechanisms, and the electronic systems themselves are inherently prone to response delays and failures. This dependence and vulnerability make it difficult for existing collision protection structures to ensure stable safety performance in the diverse collision scenarios of real-world traffic environments.

[0119] Therefore, in addition to adjusting the stiffness of the alloy layer by the electronic control system, this application introduces a mechanical triggering mechanism of mechanical inertia valve and hydraulic adjustment component to form mechanical redundancy protection, which effectively solves the problems of response delay and failure risk of the electronic control system.

[0120] In one optional embodiment of this application, the collision protection system further includes a mechanical inertia valve and a hydraulic adjustment assembly. The mechanical inertia valve is provided with a lever structure for triggering the hydraulic adjustment assembly. The crumple module further includes a hydraulic layer, and the hydraulic adjustment assembly is connected to the hydraulic layer. The method further includes: S171, when the mechanical inertia valve detects that the vehicle's acceleration is greater than a preset threshold, the lever structure triggers the hydraulic adjustment component; S172, The hydraulic pressure of the hydraulic layer is adjusted using the hydraulic adjustment component; S173, the collapsing module corresponding to the adjusted hydraulic layer is taken as the target collapsing module.

[0121] In this embodiment, when the mechanical inertia valve detects that the vehicle's acceleration is greater than a preset threshold, the lever structure can trigger the hydraulic adjustment component to adjust the hydraulic pressure of the hydraulic layer, and the collapsing module corresponding to the adjusted hydraulic layer is used as the target collapsing module.

[0122] In practical implementation, the hydraulic regulating component can control the buffer solution in the hydraulic layer to change its stiffness via a mechanical inertia valve. The hydraulic regulating component may include a mechanical inertia valve comprising a dual-mass ball and a lever structure. The primary mass ball can be 50g of tungsten carbide, used to detect longitudinal acceleration. When the longitudinal acceleration exceeds a threshold, the primary mass ball displaces and contacts the lever structure. The secondary mass ball can be 20g of aluminum, used to detect lateral acceleration. When the lateral acceleration exceeds a threshold, the secondary mass ball displaces and contacts the lever structure. Since the hydraulic regulating component may include a buffer solution storage area for storing the buffer solution, after the lever structure triggers the hydraulic regulating component, it can control the buffer solution to flow from the buffer solution storage area into the hydraulic chamber in the hydraulic layer, thereby adjusting the hydraulic pressure of the hydraulic layer.

[0123] In addition to adjusting the stiffness of the alloy layer, this application introduces a mechanical triggering mechanism using a mechanical inertia valve and a hydraulic adjustment assembly, forming a mechanical redundancy protection that effectively solves the problems of response delay and failure risk in the electronic control system. The mechanical inertia valve can quickly trigger the hydraulic adjustment assembly upon detecting high acceleration, enabling rapid adjustment of the hydraulic layer and ensuring reliable protection at the moment of impact. This mechanical triggering mechanism not only improves the system's response speed and stability but also enhances the reliability of collision protection, providing dual protection for vehicle safety performance.

[0124] In one optional embodiment of this application, the method further includes: S181, when the mechanical inertia valve detects that the vehicle's acceleration is greater than a preset threshold, after adjusting the hydraulic pressure of the hydraulic layer using the hydraulic adjustment component, the stiffness of the alloy layer in the target crumple module is adjusted using the stiffness adjustment component.

[0125] In this embodiment of the application, when the mechanical inertia valve detects that the vehicle's acceleration is greater than a preset threshold, after adjusting the hydraulic pressure of the hydraulic layer using a hydraulic adjustment component, the stiffness of the alloy layer in the target crumple module can be adjusted using a stiffness adjustment component.

[0126] This embodiment of the application achieves dual control of the collision protection system by combining a mechanical inertia valve and a hydraulic adjustment component. It can rapidly trigger the hydraulic adjustment component under high acceleration conditions, and further optimize the stiffness of the alloy layer through the stiffness adjustment component, ensuring effective energy absorption during a collision. Simultaneously, the purely physical triggering mechanism of the mechanical inertia valve is isolated from the ECU control logic, avoiding the risks of electronic system response delays and failures, thus improving the system's reliability and safety and providing more comprehensive protection for vehicle collision protection.

[0127] In one optional embodiment of this application, the collapse module further includes a pressure detection layer, in which a piezoelectric sensor is disposed, and the method further includes: S191, when a vehicle collision occurs, acquire the collision strain parameters of the crumple module collected by the piezoelectric sensor and the collision acceleration of the vehicle collected by the inertial sensor. S192, after a vehicle collision, acquire the crumple strain parameters of the crumple module collected by the piezoelectric sensor and the crumple acceleration of the vehicle collected by the inertial sensor. S193, Determine the crumpling strain rate based on the collision strain parameter and the crumpling strain parameter; S194, determine the rate of change of acceleration based on the collision acceleration and the crumpling acceleration; S195, if the collapse strain rate is less than a preset strain rate threshold and the acceleration change rate is less than a preset acceleration change threshold, reset the alloy layer and the hydraulic layer and generate a collision report.

[0128] It should be noted that a piezoelectric sensor can be a sensor based on the piezoelectric effect, capable of converting mechanical stress or pressure into an electrical signal. The piezoelectric effect refers to the phenomenon where certain materials (such as quartz, piezoelectric ceramics, etc.) generate an electric charge when subjected to mechanical stress, thereby producing a voltage. Piezoelectric sensors can be used to measure physical quantities such as pressure, strain, and acceleration. In the embodiments of this application, the piezoelectric sensor can be disposed in the pressure detection layer of the crumple zone module to collect strain parameters of the vehicle during and after a collision.

[0129] In this embodiment, when a vehicle collision occurs, the collision strain parameters of the crumple zone collected by the piezoelectric sensor and the collision acceleration of the vehicle collected by the inertial sensor can be acquired. Then, after the collision, the crumple strain parameters of the crumple zone collected by the piezoelectric sensor and the crumple acceleration of the vehicle collected by the inertial sensor are acquired. The crumple strain rate is determined based on the collision strain parameters and the crumple strain parameters. The acceleration change rate is determined based on the collision acceleration and the crumple acceleration. If the crumple strain rate is less than a preset strain rate threshold and the acceleration change rate is less than a preset acceleration change threshold, the alloy layer and the hydraulic layer are reset, and a collision report is generated.

[0130] This application introduces piezoelectric sensors to monitor the strain parameters of the crumple module in real time during a collision. Combined with acceleration data collected by inertial sensors, it accurately assesses the crumple strain rate and acceleration change rate during the collision. When the crumple strain rate and acceleration change rate fall below preset thresholds, the collision process can be automatically determined to have ended, the alloy and hydraulic layers can be reset, and a collision report can be generated. This judgment mechanism based on strain and acceleration change rate not only improves the intelligence level of the collision protection system but also ensures rapid system recovery and data recording after a collision, providing more comprehensive protection for vehicle safety performance.

[0131] In the specific implementation, you can refer to Figure 3 To provide collision protection for vehicles, Figure 3 A logic flowchart of a collision protection method provided in one embodiment of this application is shown.

[0132] The logic of collision protection is divided into a perception layer, an execution layer, a dynamic control layer, and a post-processing layer.

[0133] Firstly, at the perception layer, various data can be collected through sensors. In this embodiment, these data may include vehicle status information collected by inertial sensors, collision object information collected by millimeter-wave radar, surrounding environment information and driver behavior information collected by cameras, as well as vehicle driving data, or directly acquired historical collision data.

[0134] In this embodiment of the application, the collision probability can be determined based on at least one of vehicle driving data, historical collision data, surrounding environment information, and driver behavior information.

[0135] The system determines whether the collision probability is greater than a threshold. If the collision probability is less than or equal to the preset collision threshold, the low-power mode of the collision protection system can be maintained.

[0136] If the collision probability is greater than the preset collision threshold, the pre-trigger system can be activated.

[0137] Secondly, at the execution layer, capacitor charging can be performed. Since the stiffness adjustment component can be an electrically heated component that heats the alloy layer to change its stiffness, and the electrically heated component can include a capacitor, the capacitor in the stiffness adjustment component can be pre-charged. Hydraulic pre-pressurization can also be performed. Since the hydraulic adjustment component can include a buffer storage area for storing buffer solution, the buffer storage area can be pre-pressurized.

[0138] When a vehicle collision occurs, it can be triggered via both mechanical and electronic methods.

[0139] During mechanical triggering, when the mechanical inertia valve detects that the vehicle's acceleration exceeds a preset threshold, the hydraulic adjustment component can control the buffer solution in the hydraulic layer to change its stiffness via the mechanical inertia valve. The hydraulic adjustment component may include a mechanical inertia valve comprising a dual-mass ball and a lever structure. The primary mass ball can be 50g of tungsten steel, used to detect longitudinal acceleration. When the longitudinal acceleration exceeds the acceleration threshold, the primary mass ball will displace and contact the lever structure. The secondary mass ball can be 20g of aluminum, used to detect lateral acceleration. When the lateral acceleration exceeds the acceleration threshold, the secondary mass ball will displace and contact the lever structure. Since the hydraulic adjustment component may include a buffer solution storage area for storing the buffer solution, after the lever structure triggers the hydraulic adjustment component, the component can control the buffer solution to flow from the buffer solution storage area into the hydraulic chamber in the hydraulic layer, thereby adjusting the hydraulic pressure in the hydraulic layer.

[0140] In the electronically controlled triggering process, pressure distribution detection can be performed first. In this embodiment, pressure distribution information collected by pressure sensors at different locations on the vehicle and the initial stiffness information of the crumple module can be obtained. Then, a genetic algorithm is used to determine the target stiffness information of the crumple module based on the initial stiffness information and pressure distribution information. Next, vehicle state information collected by inertial sensors and collision object information collected by millimeter-wave radar are obtained. The triggering sequence of the target crumple module is determined based on the vehicle state information and collision object information, thereby achieving stiffness adjustment triggering.

[0141] Then, in the dynamic control layer, real-time energy absorption control can be performed. In this embodiment, the stiffness of the alloy layer of the crumple module can be adjusted by a stiffness adjustment component, and the hydraulic layer of the crumple module can be hydraulically adjusted by a hydraulic adjustment component, thereby obtaining the target crumple module. Furthermore, the initial stiffness information and pressure distribution information fed back by the sensors can be acquired in real time. After determining the target collision parameters based on the initial stiffness information and pressure distribution information, the target stiffness information is determined.

[0142] Finally, in the post-processing layer, it can be determined whether the collision has terminated. If the collision has not terminated, that is, if the collapse strain rate is greater than or equal to the preset strain rate threshold, or the acceleration change rate is greater than or equal to the preset acceleration change threshold, the initial stiffness information and pressure distribution information fed back by the sensor can be reacquired. Then, after determining the target collision parameters based on the initial stiffness information and pressure distribution information, the target stiffness information is re-determined.

[0143] If the collision is terminated, that is, when the collapse strain rate is less than the preset strain rate threshold and the acceleration change rate is less than the preset acceleration change threshold, the alloy layer and hydraulic layer can be reset by the collision protection system and a collision report can be generated.

[0144] Reference Figure 4 This illustration shows a structural schematic diagram of a vehicle collision protection device according to an embodiment of this application, applied to a collision protection system. The collision protection system includes an inertial sensor, a millimeter-wave radar, a pressure sensor, and several crumple zones disposed at different locations on the vehicle. The device includes: The collision pressure acquisition module 401 is used to acquire the initial stiffness information of the crumple module and the pressure distribution information collected by the pressure sensor at different positions of the vehicle when a collision occurs. The target stiffness determination module 402 is used to determine the target stiffness information of the collapse module based on the initial stiffness information and the pressure distribution information. Collapse module adjustment module 403 is used to adjust the collapse module using the target stiffness information to obtain the target collapse module; The collision information acquisition module 404 is used to acquire vehicle status information acquired by the inertial sensor and collision object information acquired by the millimeter-wave radar; Trigger sequence determination module 405 is used to determine the trigger sequence of the target crumple module based on the vehicle status information and the collision object information; The collision protection execution module 406 is used to trigger the target collapse module according to the triggering sequence, and to perform collision protection on the vehicle through the target collapse module.

[0145] In one optional embodiment of this application, the target stiffness determination module 402 includes: The collision parameter determination submodule is used to determine the target collision parameters based on the initial stiffness information and the pressure distribution information; The target stiffness determination submodule is used to determine the target stiffness information based on the initial stiffness information if the target collision parameters are within a preset range.

[0146] In one optional embodiment of this application, the apparatus further includes: The random stiffness generation submodule is used to generate random stiffness information if the target collision parameters are outside the preset range. An initial stiffness replacement submodule is used to replace the initial stiffness information with the random stiffness information; The collision parameter iteration submodule is used to repeat the step of determining the target collision parameters based on the initial stiffness information and the pressure distribution information until the target collision parameters are within a preset range.

[0147] In one optional embodiment of this application, the target stiffness determination submodule includes: The candidate parameter determination unit is used to calculate and predict collision parameters based on the pressure distribution information and the candidate stiffness of the crumple module for any set of candidate stiffness of the crumple module. The stiffness category determination unit is used to perform non-dominated sorting of several groups of candidate stiffness of the collapse module according to the predicted collision parameters, so as to obtain several non-dominated levels including at least one group of candidate stiffness of the collapse module. A crowding determination unit is used to determine the crowding parameters of the candidate stiffness of the collapse module based on the predicted collision parameters for any of the non-dominated levels. The first stiffness determination unit is used to select several sets of first stiffnesses of the collapse module from several sets of candidate stiffnesses of the collapse module according to the non-dominated level and the crowding parameter. The second stiffness determination unit is used to adjust the first stiffness of several sets of the collapse modules based on a preset crossover probability to obtain the second stiffness of several sets of the collapse modules. The third stiffness determination unit is used to adjust the second stiffness of several sets of the collapse module based on a preset mutation probability to obtain the third stiffness of several sets of the collapse module. The target stiffness determination unit is used to select a set of third stiffnesses of the collapse module from several sets of third stiffnesses of the collapse module, based on the non-dominated level and the crowding parameter, as the target stiffness information.

[0148] In one optional embodiment of this application, the vehicle state information includes the vehicle yaw rate and the vehicle pitch angle, the collision object information includes the relative velocity of the collision object and the collision angle, and the trigger sequence determination module 405 includes: The collision area determination submodule is used to determine the collision area based on the collision angle and the vehicle pitch angle. The collision type determination submodule is used to determine the collision type based on the collision area; The weight allocation determination submodule is used to determine the collision energy allocation weights based on the collision type. The moment of inertia acquisition submodule is used to acquire the vehicle's moment of inertia. The collision energy determination submodule is used to determine the collision energy based on the vehicle's yaw rate, the relative velocity of the colliding object, the collision angle, and the moment of inertia. An energy distribution submodule is used to distribute the collision energy to the collision region according to the collision energy distribution weight, thereby obtaining energy absorption information of the collision region. The trigger sequence determination submodule is used to determine the trigger sequence of the collapse module based on the energy absorption information of the collision area.

[0149] In one optional embodiment of this application, the collision protection system further includes a camera, a stiffness adjustment component, and a hydraulic adjustment component. Before acquiring the initial stiffness information of the crumple zone module and the pressure distribution information collected by the pressure sensor at different locations on the vehicle when a collision occurs, the device further includes: The information collection module is used to acquire vehicle driving data, historical collision data, and surrounding environment information and driver behavior information collected by the camera; The collision probability determination module is used to determine the collision probability based on at least one of the vehicle driving data, the historical collision data, the surrounding environment information, and the driver behavior information. The pending trigger mode adjustment module is used to adjust the stiffness adjustment component and the hydraulic adjustment component to a pending trigger state when the collision probability is greater than a preset collision threshold.

[0150] In one optional embodiment of this application, the collapse module adjustment module 403 includes: The alloy layer stiffness adjustment submodule is used to adjust the stiffness of the alloy layer to the stiffness corresponding to the target stiffness information using the stiffness adjustment component. The first target acquisition submodule is used to take the collapsing module corresponding to the adjusted alloy layer as the target collapsing module.

[0151] In one optional embodiment of this application, the collision protection system further includes a mechanical inertia valve and a hydraulic adjustment assembly. The mechanical inertia valve is provided with a lever structure for triggering the hydraulic adjustment assembly. The crumple module further includes a hydraulic layer, and the hydraulic adjustment assembly is connected to the hydraulic layer. The device further includes: A hydraulic adjustment trigger submodule is used to trigger the hydraulic adjustment component by the lever structure when the mechanical inertia valve detects that the vehicle's acceleration is greater than a preset threshold. A hydraulic layer stiffness adjustment submodule is used to adjust the hydraulic pressure of the hydraulic layer using the hydraulic adjustment component; The second target acquisition submodule is used to take the collapsing module corresponding to the adjusted hydraulic layer as the target collapsing module.

[0152] In one optional embodiment of this application, the collapse module further includes a pressure detection layer, in which a piezoelectric sensor is disposed, and the device further includes: The first parameter acquisition module is used to acquire the collision strain parameters of the crumple module collected by the piezoelectric sensor and the collision acceleration of the vehicle collected by the inertial sensor when a vehicle collision occurs. The first parameter acquisition module is used to acquire the crumple strain parameters of the crumple module collected by the piezoelectric sensor and the crumple acceleration of the vehicle collected by the inertial sensor after a vehicle collision. A strain rate determination module is used to determine the crumple strain rate based on the impact strain parameters and the crumple strain parameters. An acceleration change rate determination module is used to determine the acceleration change rate based on the collision acceleration and the crumpling acceleration. The post-processing module is used to reset the alloy layer and the hydraulic layer and generate a collision report when the collapse strain rate is less than a preset strain rate threshold and the acceleration change rate is less than a preset acceleration change threshold.

[0153] One embodiment of this application also provides a vehicle that may include a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the method described above.

[0154] An embodiment of this application also provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, it implements the method described above.

[0155] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0156] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0157] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, embodiments of this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of this application can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0158] This application describes embodiments with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0159] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0160] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0161] Although preferred embodiments of the present application have been described, those skilled in the art, upon learning the basic inventive concept, can make other modifications and updates to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all modifications and updates falling within the scope of the embodiments of the present application.

[0162] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes the aforementioned element.

[0163] The above provides a detailed description of the vehicle collision protection method, device, vehicle, and medium. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A vehicle collision protection method, characterized in that, The method, applied to a collision protection system including an inertial sensor, millimeter-wave radar, a pressure sensor, and several crumple zones located at different positions on the vehicle, includes: When a vehicle collision occurs, the initial stiffness information of the crumple module and the pressure distribution information collected by the pressure sensor at different locations on the vehicle are obtained. The target stiffness information of the collapse module is determined based on the initial stiffness information and the pressure distribution information; The target stiffness information is used to adjust the collapse module to obtain the target collapse module; The vehicle status information collected by the inertial sensor and the collision object information collected by the millimeter-wave radar are acquired. The triggering order of the target crumple module is determined based on the vehicle status information and the collision object information; The target collapse module is triggered according to the triggering sequence, and the vehicle is protected from collision through the target collapse module.

2. The method according to claim 1, characterized in that, Determining the target stiffness information of the collapsible module based on the initial stiffness information and the pressure distribution information includes: The target collision parameters are determined based on the initial stiffness information and the pressure distribution information; If the target collision parameters are within a preset range, the target stiffness information is determined based on the initial stiffness information.

3. The method according to claim 2, characterized in that, The method further includes: If the target collision parameters are outside the preset range, random stiffness information is generated; The initial stiffness information is replaced with the random stiffness information; Repeat the step of determining the target collision parameters based on the initial stiffness information and the pressure distribution information until the target collision parameters are within a preset range.

4. The method according to claim 2, characterized in that, The initial stiffness information includes several sets of candidate stiffnesses for the collapsible modules. Determining the target stiffness information based on the initial stiffness information includes: For any set of candidate stiffnesses of the crumple module, the predicted collision parameters are calculated based on the pressure distribution information and the candidate stiffnesses of the crumple module. The candidate stiffnesses of the collapsing modules are sorted in a non-dominated manner according to the predicted collision parameters to obtain several non-dominated levels including at least one set of candidate stiffnesses of the collapsing modules. For any of the non-dominated levels, the crowding parameter of the candidate stiffness of the collapse module is determined based on the predicted collision parameters. Based on the non-dominated level and the crowding parameter, select a number of first stiffnesses of the collapse module from a number of candidate stiffnesses of the collapse module. Based on a preset crossover probability, the first stiffness of several sets of the collapse modules is adjusted to obtain the second stiffness of several sets of the collapse modules. Based on a preset mutation probability, the second stiffness of several sets of the collapse modules is adjusted to obtain several sets of third stiffness of the collapse modules. From several sets of third stiffnesses of the collapse module, a set of third stiffnesses of the collapse module is selected as the target stiffness information based on the non-dominated level and the crowding parameter.

5. The method according to claim 1, characterized in that, The vehicle status information includes the vehicle yaw rate and vehicle pitch angle; the collision object information includes the relative velocity of the collision object and the collision angle; determining the triggering sequence of the target crumple module based on the vehicle status information and the collision object information includes: The collision area is determined based on the collision angle and the vehicle pitch angle. The collision type is determined based on the collision area; The collision energy allocation weight is determined based on the collision type. Obtain the vehicle's moment of inertia; The collision energy is determined based on the vehicle's yaw rate, the relative velocity of the colliding object, the collision angle, and the moment of inertia. The collision energy is allocated to the collision region according to the collision energy allocation weight to obtain the energy absorption information of the collision region. The triggering sequence of the collapse module is determined based on the energy absorption information of the collision area.

6. The method according to claim 1, characterized in that, The collision protection system further includes a camera, a stiffness adjustment component, and a hydraulic adjustment component. Before acquiring the initial stiffness information of the crumple zone module and the pressure distribution information collected by the pressure sensor at different locations on the vehicle when a collision occurs, the method further includes: Acquire vehicle driving data, historical collision data, and surrounding environment information and driver behavior information collected by the camera; The collision probability is determined based on at least one of the vehicle driving data, the historical collision data, the surrounding environment information, and the driver behavior information; If the collision probability is greater than a preset collision threshold, the stiffness adjustment component and the hydraulic adjustment component are adjusted to a ready-to-trigger state.

7. The method according to claim 6, characterized in that, The collapsing module includes an alloy layer. Adjusting the collapsing module using the target stiffness information to obtain the target collapsing module includes: The stiffness adjustment component is used to adjust the stiffness of the alloy layer to the stiffness corresponding to the target stiffness information. The adjusted alloy layer corresponding to the collapse module is taken as the target collapse module.

8. The method according to claim 7, characterized in that, The collision protection system further includes a mechanical inertia valve and a hydraulic adjustment assembly. The mechanical inertia valve is provided with a lever structure for triggering the hydraulic adjustment assembly. The crumple module further includes a hydraulic layer, and the hydraulic adjustment assembly is connected to the hydraulic layer. The method further includes: When the mechanical inertia valve detects that the vehicle's acceleration is greater than a preset threshold, the lever structure triggers the hydraulic adjustment component. The hydraulic pressure of the hydraulic layer is adjusted using the hydraulic adjustment component. The adjusted hydraulic layer and the corresponding collapse module are used as the target collapse module.

9. The method according to claim 8, characterized in that, The collapse module further includes a pressure detection layer, in which a piezoelectric sensor is disposed; the method further includes: When a vehicle collision occurs, the collision strain parameters of the crumple module collected by the piezoelectric sensor and the collision acceleration of the vehicle collected by the inertial sensor are acquired. After a vehicle collision, the collapsing strain parameters of the collapsing module collected by the piezoelectric sensor and the collapsing acceleration of the vehicle collected by the inertial sensor are obtained. The crumple strain rate is determined based on the impact strain parameters and the crumple strain parameters. The rate of change of acceleration is determined based on the collision acceleration and the crumpling acceleration; If the collapse strain rate is less than a preset strain rate threshold and the acceleration change rate is less than a preset acceleration change threshold, the alloy layer and the hydraulic layer are reset, and a collision report is generated.

10. A vehicle collision protection device, characterized in that, An application in a collision protection system, the collision protection system including an inertial sensor, millimeter-wave radar, a pressure sensor, and several crumple zones disposed at different locations on the vehicle, the device comprising: The collision pressure acquisition module is used to acquire the initial stiffness information of the crumple module and the pressure distribution information collected by the pressure sensor at different positions on the vehicle when a collision occurs. The target stiffness determination module is used to determine the target stiffness information of the collapse module based on the initial stiffness information and the pressure distribution information. A collapse module adjustment module is used to adjust the collapse module using the target stiffness information to obtain a target collapse module; The collision information acquisition module is used to acquire vehicle status information collected by the inertial sensor and collision object information collected by the millimeter-wave radar; The triggering order determination module is used to determine the triggering order of the target crumple module based on the vehicle status information and the collision object information; The collision protection execution module is used to trigger the target collapse module according to the triggering sequence, and to perform collision protection on the vehicle through the target collapse module.

11. A vehicle, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the method as described in any one of claims 1-9.

12. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, which, when executed by a processor, implements the method as described in any one of claims 1-9.

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