Method for Responding to Vehicle Collision Risk, Readable Storage Medium and Program Product

Abstract

The present invention provides a method for coping with vehicle collision risks, a readable storage medium, and a program product. The method includes: when it is determined that a vehicle is about to collide with a target object, determining a target position on the vehicle based on vehicle motion state information of the vehicle and object motion state information of the target object, wherein the degree of vehicle damage corresponding to the target position is no higher than the degree of vehicle damage corresponding to other collision positions; and adjusting the driving path of the vehicle so that the vehicle collides with the target object at the target position.

Description

Technical Field

[0001] The present invention relates to the automotive field, and in particular to a method for coping with vehicle collision risks, a readable storage medium, and a program product. Background Art

[0002] In the field of automotive safety, active safety technologies aim to avoid collisions or reduce the probability of accidents, such as automatic emergency braking, electronic stability control, and adaptive cruise control; while passive safety technologies focus on protecting occupants after a collision, such as airbags and collision energy-absorbing structures. In recent years, the collaborative optimization of active and passive safety has gradually become a major development direction in this field. For example, the proactive information from the active safety system can be used to adjust the seatbelt pretensioning or airbag triggering logic in advance to improve the response efficiency of passive safety devices. However, existing technologies are still at the macro level of "predicting whether a collision will occur" or "selecting the general direction of the collision." They do not further consider the specific degree of damage to the vehicle when a collision occurs, and thereby determine a safer response method. Summary of the Invention

[0003] In view of this, the present invention provides a method for dealing with vehicle collision risks, a readable storage medium, and a program product to address the deficiencies in the related art.

[0004] Specifically, the present invention is achieved through the following technical solutions:

[0005] According to a first aspect of the present invention, a method for coping with vehicle collision risk is provided, the method comprising:

[0006] In a case where it is determined that a vehicle and a target object are about to collide, determining a target position on the vehicle based on vehicle motion state information of the vehicle and object motion state information of the target object, wherein a degree of vehicle damage corresponding to the target position is no greater than degrees of vehicle damage corresponding to other collision positions;

[0007] The driving path of the vehicle is adjusted so that the vehicle collides with the target object at the target position.

[0008] According to a second aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the steps of the method according to the first aspect.

[0009] According to a third aspect of the present invention, a mobile charging device is provided, comprising a control module and an energy storage module, wherein the control module comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the steps of the method of the first aspect are implemented when the processor executes the program through the cooperation between the control module and the energy storage module.

[0010] When the vehicle in this specification is determined to be about to collide with a target object, it can actively select a target position where the vehicle damage is minimal, and control the collision point by adjusting the driving path. Specifically, the target position can be determined based on the vehicle motion state information of the vehicle and the object motion state information of the target object, and the degree of vehicle damage corresponding to the target position is no higher than the degree of vehicle damage corresponding to other collision positions. At the same time, the vehicle can adjust its own driving path so that the vehicle collides with the target object at the previously determined target position, directing the collision impact force to the target position where the degree of vehicle damage is no higher than that of other collision positions, thereby reducing the degree of vehicle damage and injuries to the occupants, and effectively improving the safety of the vehicle when responding to collision risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] To more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present invention, and those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0012] Figure 1 This is a flow chart of a method for coping with vehicle collision risk shown in an embodiment disclosed in the present invention;

[0013] Figure 2 is a schematic diagram of a safety collision model shown in an embodiment disclosed in the present invention;

[0014] Figure 3 is a schematic diagram of various collision scenarios shown in the disclosed embodiment of the present invention;

[0015] Figure 4 This is a schematic diagram of the architecture of a vehicle collision risk response system shown in an embodiment disclosed in the present invention;

[0016] Figure 5 is a schematic structural diagram of an electronic device shown in an embodiment of the present invention;

[0017] Figure 6 This is a block diagram of a device for coping with vehicle collision risks shown in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] Exemplary embodiments are described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent like or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with certain aspects of the present invention.

[0019] The terms used in this invention are for the purpose of describing specific embodiments only and are not intended to limit the invention. The singular forms "a," "the," and "the" used in this invention and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0020] It should be understood that although the terms "first," "second," "third," etc. may be used in the present invention to describe various information, such information should not be limited to these terms. These terms are merely used to distinguish information of the same type from one another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present invention. Depending on the context, the term "if" as used herein may be interpreted as "when," "when," or "in response to determining."

[0021] An embodiment of the method for coping with vehicle collision risk of the present invention is described in detail below with reference to the accompanying drawings.

[0022] Figure 1 This is a flowchart of a method for coping with vehicle collision risk according to an exemplary embodiment disclosed in the present invention, which may include the following steps:

[0023] Step 202, when it is determined that the vehicle is about to collide with the target object, determine the target position on the vehicle based on the vehicle motion state information of the vehicle and the object motion state information of the target object, and the vehicle damage level corresponding to the target position is not higher than the vehicle damage levels corresponding to other collision positions.

[0024] When a vehicle detects that it is about to collide with a target object, the collision is currently determined to be an unavoidable risk for the vehicle. At this point, the vehicle's own motion state information and the target object's motion state information can be acquired in real time to determine a collision contact point with a degree of damage no greater than that of other collision positions as the target position. In other words, the target position must satisfy the requirement that the degree of damage to the vehicle corresponding to the target position is less than or equal to that of other candidate collision positions, thereby achieving active optimization of the collision position. The vehicle's motion state information and the object's motion state information can include at least one of position, velocity, acceleration, and heading angle, and the vehicle's motion state information and the object's motion state information can be detected and acquired by corresponding onboard sensors in the vehicle. Of course, the acquisition operation actually begins during the process of determining whether the vehicle and the target object are about to collide.

[0025] The present application will provide a quantitative judgment standard for determining whether the vehicle and the target object are about to collide.

[0026] In one embodiment, a decision control unit (DCU) or autonomous driving domain controller in a vehicle may obtain first motion state information of the vehicle, second motion state information of candidate objects in the vehicle's surroundings, and road environment information based on the vehicle's onboard sensors. The DCU may determine a collision probability between the vehicle and the candidate objects based on the first motion state information, the second motion state information, and the road environment information. If the collision probability reaches a preset probability threshold, the DCU may identify the candidate objects as the target objects and determine that a collision is imminent between the vehicle and the target objects. The onboard sensors may include, for example, millimeter-wave radars, cameras, lidars, and inertial measurement units. The first motion state information collected by the onboard sensors may include, for example, the vehicle's speed, acceleration, yaw rate, and heading angle. The second motion state information may include, for example, the real-time location, speed, motion direction, and size characteristics of the candidate objects in the vehicle's surroundings. Furthermore, the road environment information may include, for example, lane line distribution, curvature, shoulder boundaries, traffic sign locations, and road friction coefficient.

[0027] After obtaining the vehicle's first motion state information, the candidate object's second motion state information, and the road environment information, at least one drivable path for the vehicle can be generated based on the road environment information. This drivable path covers the set of trajectories that the vehicle can reach through braking, steering, or acceleration in its current motion state. For example, the at least one drivable path may include a conservative path representing deceleration in the current lane and an aggressive path representing lane change avoidance. Simultaneously, the motion trajectory of the candidate object within a preset duration can be predicted based on the first and second motion state information to identify points of spatial overlap between the at least one drivable path for the vehicle and the object's motion trajectory within the preset duration, and the number and temporal distribution characteristics of these spatial overlap points can be used to calculate the collision probability.

[0028] Specifically, using the first motion state information and the second motion state information, at least one safe path that meets the vehicle's motion capabilities can be generated through a kinematic model or a machine learning trajectory prediction algorithm, and the motion trajectory of each candidate object within a preset time period, such as the next 2 to 5 seconds, can be predicted, and the key spatiotemporal nodes on the trajectory can be marked. At the same time, spatiotemporal conflict detection can be performed on each vehicle's drivable path and the predicted trajectory of each candidate object, that is, the intersection of the corresponding vehicle's drivable path and the object's trajectory can be calculated by a geometric projection method, and it can be determined whether the intersection meets the following conditions at the same time to be determined as a spatial overlap point: 1. Time synchronization condition, that is, the time difference between the time the vehicle arrives at the path overlap point and the time the candidate object arrives at the trajectory overlap point is less than a preset threshold, such as ±0.3 seconds; 2. Spatial overlap condition: There is physical overlap between the vehicle and the candidate object in the area occupied by the overlap point. This process can provide the outer dimensions of the vehicle and the object to establish a collision box model for detection. This statement does not limit this. Ultimately, the probability of collision between the vehicle and each candidate is calculated based on the number of spatial overlap points corresponding to each vehicle's drivable path and their temporal distribution characteristics, or by dynamically adjusting the weights of each candidate. For example, the greater the number of overlap points and the closer the time window is to the current moment, the higher the collision probability. These probability values are mapped to a range of 0-100% using a normalization algorithm. When the probability value of a candidate exceeds a preset threshold, it is identified as a target for collision optimization.

[0029] In addition to the above methods, the dynamic safety corridor method can also be used to establish a time-varying vehicle safety path corridor, calculate the time-space intersection area with the probability trajectory cluster of the alternative object, and then quantify the collision risk based on the time-space density of the intersection area, or discretize the future time and space into a three-dimensional probability grid through the probability grid mapping method, and generate a collision probability heat map by superimposing the joint probability density of the conflict grid units to perform time-space conflict detection. This is not limited in this manual.

[0030] The following combination Figure 3 The following scenarios are exemplified by the following examples: The vehicle can start to judge whether the vehicle and the target object are about to collide when it recognizes the following scenarios. Figure 3 As shown, assuming the target object is a vehicle, common collision scenarios include but are not limited to: (a) the ego vehicle (hereinafter referred to as vehicle A in the figure) colliding with another vehicle (hereinafter referred to as vehicle B in the figure) during lane change. In this case, the ego vehicle is susceptible to blind spot interference or prediction errors during lane change. If the dynamics of vehicles in the adjacent lane are not accurately monitored, a side collision may easily occur if the following vehicle accelerates and the distance between them is insufficient; (b) the ego vehicle collides with another vehicle in a curve. In this case, due to the limited field of view in the curve, the vehicle may understeer / oversteer or fail to detect the trajectory of oncoming / same-direction vehicles in a timely manner, resulting in path conflict; (c) the ego vehicle collides with a guardrail in a curve. In this case, if the curve radius is too small or the speed is too high, the vehicle may deviate from the lane and collide with the guardrail if the steering angle is not adjusted or braked in advance; (d) the ego vehicle collides with another vehicle crossing the intersection. In this case, if the ego vehicle fails to predict the movement intention of the vehicle through V2X, cameras, etc. when the vehicle cuts in laterally, a right-angle collision may easily occur; (e) When the vehicle is approaching an oncoming vehicle in urban conditions, due to the narrow roads or mixed traffic, if the vehicle's crossing of the line is not recognized in real time, a head-on collision may occur due to insufficient avoidance space.

[0031] As mentioned above, there can actually be multiple candidate targets. When the DCU or the autonomous driving domain controller detects vulnerable road users (VRUs) such as pedestrians, cyclists, and e-scooter users among the candidate targets, a targeted protection priority strategy can be designed. This strategy uses onboard visual sensors or vehicle-to-everything (V2X) communication to obtain candidate target identification information, such as pedestrian outline recognition and non-motor vehicle feature classification. If a candidate target is identified as a vulnerable road user, it is removed from the candidate list, retaining only non-vulnerable targets such as vehicles and fixed obstacles. This process is implemented using a preset weighting algorithm. For example, if the candidate targets include pedestrians and other vehicles, even if the pedestrian collision probability is higher than that of the vehicle, the system will still prioritize pedestrians as targets and instead optimize the collision point with non-vulnerable targets. This minimizes the risk of injury to vulnerable groups if a collision is unavoidable. After the removal operation, the system recalculates the collision probability of the remaining candidate objects and, based on the updated list of candidate objects, selects the candidate that causes the least damage to the vehicle as the target object. It then makes subsequent collision location decisions and route adjustments. This mechanism ensures that even in complex ethical dilemma scenarios, system decisions comply with traffic safety ethics and social responsibility requirements.

[0032] At this point, the situation that the vehicle and the target object are about to collide has been determined. At this point, the solution in this specification can efficiently determine the target position on the vehicle based on a method of a preset safety collision model.

[0033] In one embodiment, the target position is determined based on a safety collision model, vehicle motion state information, and object motion state information. The safety collision model can be used to characterize the relationship between the damage level and collision parameters for each collision region of the vehicle at different collision angles and locations. Specifically, the safety collision model can be constructed based on vehicle structural finite element analysis, historical collision test data, and dynamic damage simulation data. This model then provides a parameterized mapping relationship to establish collision parameters, which may include collision angle, relative velocity, and contact area. These parameters are quantitatively associated with the damage level of each vehicle region, such as passenger compartment intrusion, stress thresholds of key components, and deformation efficiency of energy-absorbing structures. During the actual determination of the target position, the DCU, the autonomous driving domain controller, or other independent computing module can first calculate the expected collision parameters at the time of the collision using kinematic equations based on the vehicle's real-time motion state information and the target object's motion state information. These expected collision parameters may include parameters such as collision angle deviation and contact surface normal vector direction. These expected collision parameters are then input into the safety collision model for damage simulation calculations.

[0034] At this point, the collision position in multiple predefined candidate collision areas on the vehicle surface can be traversed. The collision position can be determined by the center point of the area or other custom points, such as Figure 2 The safety collision model dynamically assesses the damage level of each area under the expected collision parameters (e.g., the front energy absorption zones A1-A3, the side anti-collision beam coverage zones B1-A6, and the rear crumple zones C1-C3). The target location is ultimately selected in the area with the lowest damage. Furthermore, this safety collision model features an online update function, adjusting relevant model parameters based on real-time data collected by onboard sensors, such as changes in vehicle load and battery position, to ensure that the optimized collision location accurately matches the current physical state of the vehicle.

[0035] Of course, if the target object itself, like the aforementioned vehicle, is a conventional model such as a sedan, sport utility vehicle (SUV), or multi-purpose vehicle (MPV), or a specialized model such as a bus or truck, the target object's corresponding model can be incorporated into the vehicle's damage assessment, with additional focus on the target object's damage. For example, if the target object is an SUV, the vehicle can access a pre-stored SUV collision characteristic database containing parameters such as chassis height, front anti-collision beam position, and mass distribution, and then combine this with the vehicle's own safety collision model for a bidirectional damage assessment. Alternatively, if the target object is a van, after identifying its highly rigid rear cargo box, the reinforced B-pillar structure in the vehicle's side impact zone can be prioritized as the target location. By actively guiding the collision point away from a direct impact with the van's rear bumper and instead utilizing the offset contact between the van's cargo box side panel and the vehicle's B-pillar, the collision energy is dispersed to non-lethal structural areas on both sides, achieving bidirectional optimization of occupant protection for both vehicles.

[0036] In the process of determining the above-mentioned target positions, this manual can also further screen the existing target positions in combination with the situation of the passengers in the vehicle, thereby avoiding the passengers in the vehicle from being impacted by the target positions to the greatest extent and ensuring the personal safety of the passengers in the vehicle.

[0037] In one embodiment, occupant distribution information of the vehicle's occupants can be generated based on the vehicle's onboard sensors, and a set of candidate target locations can be determined based on this occupant distribution information. Subsequent processes can determine the target location on the vehicle from the set of candidate target locations based on the vehicle's motion state information and the target object's motion state information, as described above. In this embodiment, the onboard sensors can include seat pressure sensors, an in-cabin camera array, an infrared thermal imaging module, and other devices to collect occupant distribution information, including the precise seat coordinates, sitting height, and seat belt restraint status of the driver and passengers. Based on this information, a three-dimensional mapping model of the occupant safety protection zone can be established. Then, based on the vehicle's structural topology data, a spatial correlation analysis is performed between each collision zone on the vehicle's exterior surface and the corresponding location within the vehicle to generate a set of candidate target locations. This eliminates all external collision zones that directly overlap with the occupant's location within the vehicle. For example, if there is a passenger in the right rear seat, the right rear quarter panel area is excluded. This ensures that the internal projection area corresponding to each target location in the set of candidate target locations exceeds a preset safety distance threshold from the nearest occupant. Therefore, the situation where the internal projection area of any of the above-mentioned target positions is more than a preset safety distance threshold from the nearest occupant represented by the occupant distribution information can be called a mismatch between the occupant distribution information and any of the above-mentioned target positions, and it can be concluded that the above-mentioned occupant distribution information does not match any of the target positions in the above-mentioned target position set.

[0038] Those skilled in the art will understand that when it is detected that all seats in the vehicle are occupied, the exclusion rule based on a single occupant position can be canceled, and instead the above-mentioned safety collision model can be used to calculate the comprehensive injury index of the occupants in the vehicle corresponding to each collision area, such as the weighted sum of the head injury criterion HIC value, chest compression, leg force peak, etc., and finally generate a priority list of candidate positions sorted in ascending order of injury index. Alternatively, priority can be given to areas with the highest vehicle structural crashworthiness scores, such as the connection between the front longitudinal beam and the chassis. Even if the associated occupant injury index is not the lowest, active safety linkage can be achieved by, for example, triggering the corresponding side airbag inflation in advance, locking the electric seat rearward, and other actions, thereby compensating for the corresponding protection effect.

[0039] Step 204 : Adjust the driving path of the vehicle so that the vehicle collides with the target object at the target position.

[0040] Based on the target position determined in the previous step, the vehicle control system can generate a path adjustment command, thereby shifting the vehicle's actual trajectory toward the target position. This path adjustment can be achieved through the coordinated action of vehicle actuators, such as the electronic stability program, electric power steering system, and drive motor, ensuring that the vehicle is guided to the target position and makes contact with the target object before a collision occurs. This allows the vehicle to absorb collision energy in its optimal crashworthiness zone, directly reducing structural damage and occupant safety risks.

[0041] Specifically, the process of adjusting the driving path of the vehicle described above can be further broken down in this specification.

[0042] In one embodiment, the vehicle's adjusted path parameters can first be determined based on the target position. Then, path adjustment instructions based on braking, steering, and drive dimensions are generated based on the adjusted path parameters, and the path adjustment instructions are executed to adjust the driving path. The adjusted path parameters can be calculated in real time using a vehicle dynamics model and may include specific values such as a target lateral offset, longitudinal velocity change rate, heading angle correction, and path curvature constraints. These parameters can meet vehicle kinematic feasibility and current road environment constraints, such as a maximum lateral acceleration of no more than 0.5g and no crossing of a solid lane or shoulder. The path adjustment instructions based on braking, steering, and drive dimensions can be understood as multi-dimensional path adjustment instructions, i.e., different instructions are issued to the vehicle's braking system, steering system, and drive system, respectively, to ensure that the vehicle adjusts its driving path according to the path adjustment instructions, thereby reducing the possibility of accidental collision with the target object.

[0043] Furthermore, as previously mentioned, "an imminent collision between the vehicle and the target object" is merely a result for the vehicle at a specific moment in time; it does not necessarily mean that the vehicle and the target object will actually collide. Therefore, while adjusting the vehicle's driving path, it is possible to periodically determine whether the vehicle and the target object are about to collide. Specifically, the vehicle's and the target object's motion state information is recollected at predetermined intervals, and the latest collision probability between the vehicle and the target object is recalculated based on the updated data. Upon detecting that the recalculated collision probability is below a predetermined probability threshold, the vehicle and the target object are determined to be no longer in an unavoidable collision state. At this point, the vehicle can immediately terminate the collision with the target object at the target location and adjust its driving path to actively avoid the target object, thereby minimizing the risk to the vehicle. Of course, if the determination still indicates an imminent collision between the vehicle and the target object, the vehicle can continue on the previously adjusted driving path.

[0044] It's worth noting that the aforementioned occupant distribution information can also be used to assist in the aforementioned driving path decisions. For example, if the occupant distribution information indicates that only the driver's seat is occupied, and if there's insufficient space to avoid an oncoming vehicle or a truck, the electric power steering can be used to fine-tune the vehicle's direction to the left, directing the collision point to the passenger side or right rear door area. The electronic stability program (ESP) can also be triggered to coordinate braking and assist vehicle rotation, reducing the impact on the driver's side. If a lateral vehicle is encountered, such as a right-angle collision at an intersection, instantaneous acceleration can be used to shift the collision point backward to the rear crumple zone, reducing stress on the passenger compartment. If both the front passenger and driver are occupied, the vehicle can exclude the side panels based on the real-time occupant distribution. Steering and braking can be used to coordinate vehicle rotation, locking the collision point to the rear door or rear energy absorption zone, and triggering the side airbags to inflate early. Furthermore, when the vehicle is fully loaded, priority is given to collisions at positions corresponding to collision pillars such as the A-pillar and B-pillar, while triggering the linkage of all vehicle airbags and the rearward locking function of the seats; if the road environment restricts path adjustment, the areas with the highest collision resistance, such as the connection between the front longitudinal beam and the chassis, are forcibly locked, and the occupant injury index is comprehensively evaluated through the above-mentioned safety collision model to ensure maximum energy dispersion and occupant safety when a collision is inevitable.

[0045] The following combination Figure 4 The schematic diagram of the architecture of the algorithm for dealing with vehicle collision risk shown in FIG. explains the above-mentioned method for dealing with vehicle collision risk. Figure 4 Regarding the various models and modules described in this article, it's important to note that onboard sensors 402 can be independent hardware devices, including millimeter-wave radar, cameras, lidar, inertial measurement units, seat pressure sensors, in-cabin camera arrays, and infrared thermal imaging modules. These sensors are deployed directly on the vehicle to collect information about the vehicle's motion state, the object's motion state, and the road environment. The driving path planning model 404, target location selection model 406, and driving path decision model 408 can be deployed on the DCU, autonomous driving domain controller, or independent onboard computing hardware with sufficient computing power, depending on actual needs. The path adjustment module 410 can be deployed on the corresponding electronic control unit (ECU) of the vehicle's actuators to implement its functionality and execute corresponding path adjustment instructions.

[0046] Specifically, Figure 4The diagram shows the architecture of the vehicle collision risk response system. The core function of the onboard sensors 402 in the diagram is to collect data. These sensors collect information about the vehicle's first motion state, the second motion state of surrounding candidate objects, and road environment information, and provide this information to the driving path planning model 404. Based on the acquired road environment information, the onboard sensor model 404 generates a set of possible vehicle paths, makes a preliminary judgment about whether a collision between the vehicle and the target object is imminent, and provides path basis for the collision probability calculation module in the target location selection model 406 and the driving path decision model 408, respectively. The collision probability calculation module in the target location selection model 406 obtains motion state information about the vehicle and candidate objects based on information from the driving path planning model 404, calculates the collision probability between the two, and determines the target object. The occupant distribution information generation module utilizes information from the seat pressure sensors, in-cabin cameras, and other devices in the onboard sensors 402 to generate information about the occupant distribution within the vehicle. This information is used to screen a set of safe candidate target locations, assisting the safe collision model in determining the target location. The safety collision model, based on the target object determined by the collision probability calculation module and the candidate target position set from the occupant distribution information generation module, performs vehicle structural analysis and collision test data construction, characterizing the relationship between collision angle and position and vehicle damage. Using the vehicle and object motion state information input by the collision probability calculation module, it assesses the damage level of each collision area, selects the target position with the least damage, and outputs this to the driving path decision model 408. This allows the driving path decision model 408 to calculate the adjusted vehicle path parameters based on the target position determined by the target position selection model, generate path adjustment instructions for braking, steering, and driving, and output the planned final driving path to the path adjustment module 410. Ultimately, the path adjustment module 410 executes these path adjustment instructions, namely, by collaboratively adjusting the vehicle trajectory through actuators such as the electronic stability program and the steering system, causing the vehicle to deviate toward the target position.

[0047] Figure 5 This is a schematic structural diagram of an electronic device in an exemplary embodiment. Figure 5 At the hardware level, the electronic device includes a processor 502, an internal bus 510, a network interface 504, a memory 506, and a non-volatile memory 508, and may also include other necessary hardware. The processor reads the corresponding computer program from the non-volatile memory into the internal memory and then runs it, forming a risk code detection device at the logical level. Of course, in addition to software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of software and hardware. In other words, the execution of the following processing flow is not limited to individual logic units and can also be hardware or logic devices.

[0048] Figure 6A block diagram of a vehicle collision risk response device is shown in an embodiment of the present invention. Figure 6 , the device can be used for Figure 5 In the device shown, to implement the technical solution of the present invention, the device includes:

[0049] a target position determining unit 602 for determining, when it is determined that a vehicle and a target object are about to collide, a target position on the vehicle based on vehicle motion state information of the vehicle and object motion state information of the target object, wherein the vehicle damage level corresponding to the target position is no greater than the vehicle damage levels corresponding to other collision positions;

[0050] The driving path adjustment unit 604 is configured to adjust the driving path of the vehicle so that the vehicle collides with the target object at the target position.

[0051] Optionally, the device further includes:

[0052] a collision probability processing unit, configured to obtain first motion state information of the vehicle, second motion state information of candidate objects around the vehicle, and road environment information based on an onboard sensor of the vehicle;

[0053] determining a collision probability between the vehicle and the candidate object based on the first motion state information, the second motion state information, and the road environment information;

[0054] When the collision probability reaches a preset probability threshold, the candidate object is used as the target object, and it is determined that the vehicle and the target object are about to collide.

[0055] Optionally, the collision probability processing unit is specifically configured to:

[0056] generating at least one vehicle drivable path based on the road environment information;

[0057] Predicting a motion trajectory of the candidate object within a preset duration based on the first motion state information and the second motion state information, so as to identify a spatial overlap point between the at least one drivable vehicle path and the object motion trajectory within the preset duration;

[0058] The collision probability is calculated based on the number and time distribution characteristics of the spatial coincidence points.

[0059] Optionally, the method further includes:

[0060] The vulnerable group removing unit is configured to remove the vulnerable road user group from the candidate objects when there are multiple candidate objects and a vulnerable road user group exists among the multiple candidate objects.

[0061] Optionally, the target position determining unit 602 is specifically configured to:

[0062] The target position is determined based on a safety collision model, vehicle motion state information, and object motion state information. The safety collision model is used to characterize the correspondence between the degree of damage to each collision area and the collision parameters of the vehicle under different collision angles and different collision positions.

[0063] Optionally, the target position determining unit 602 is specifically configured to:

[0064] generating occupant distribution information of occupants in the vehicle according to onboard sensors of the vehicle;

[0065] determining a set of candidate target positions based on the occupant distribution information, wherein the occupant distribution information does not match any target position in the set of target positions;

[0066] A target position on the vehicle is determined from the candidate target position set according to the vehicle motion state information of the vehicle and the object motion state information of the target object.

[0067] Optionally, the transposition further includes:

[0068] a driving path readjustment unit, configured to periodically determine whether a collision between the vehicle and a target object is imminent while adjusting the driving path of the vehicle;

[0069] If the judgment result is negative, the driving path of the vehicle is adjusted to avoid a collision between the vehicle and the target object.

[0070] Optionally, the driving path adjustment unit 604 is specifically configured to:

[0071] determining adjusted path parameters of the vehicle according to the target position;

[0072] Path adjustment instructions for braking, turning, and driving dimensions are generated according to the vehicle's adjusted path parameters, and the path adjustment instructions are executed to adjust the driving path.

[0073] The implementation process of the functions and effects of each unit in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method, and will not be repeated here.

[0074] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to the partial description of the method embodiments. The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this specification. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0075] Based on the same concept as the above method, this specification also provides an electronic device, including: a processor; a memory for storing processor-executable instructions; wherein the processor implements the steps of the method described in any of the above embodiments by running the executable instructions.

[0076] Based on the same concept as the above method, this specification also provides a computer-readable storage medium on which computer instructions are stored. When the instructions are executed by a processor, the steps of the method described in any of the above embodiments are implemented.

[0077] Based on the same concept as the above method, this specification also provides a computer program product, including a computer program / instruction, which implements the steps of the method described in any of the above embodiments when executed by a processor.

[0078] Embodiments of the subject matter and functional operations described in this specification may be implemented in the following: digital electronic circuits, tangibly embodied computer software or firmware, computer hardware including the structures disclosed in this specification and their structural equivalents, or a combination of one or more of them. Embodiments of the subject matter described in this specification may be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on a tangible, non-transitory program carrier to be executed by a data processing device or to control the operation of the data processing device. Alternatively or additionally, the program instructions may be encoded on an artificially generated propagation signal, such as a machine-generated electrical, optical, or electromagnetic signal, which is generated to encode information and transmit it to a suitable receiver device for execution by the data processing device. The computer storage medium may be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of one or more of them.

[0079] The processes and logic flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform the corresponding functions by operating on input data and generating output. The processes and logic flows can also be performed by, and apparatus can be implemented as, special-purpose logic circuitry, such as an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit).

[0080] Computers suitable for executing computer programs include, for example, general-purpose and / or special-purpose microprocessors, or any other type of central processing unit. Typically, the central processing unit will receive instructions and data from a read-only memory and / or random access memory. The basic components of a computer include a central processing unit for implementing or executing instructions and one or more memory devices for storing instructions and data. Typically, a computer will also include one or more mass storage devices for storing data, such as magnetic disks, magneto-optical disks, or optical disks, or the computer will be operably coupled to such mass storage devices to receive data from them or to transmit data to them, or both. However, a computer does not necessarily have such devices. In addition, a computer can be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device such as a universal serial bus (USB) flash drive, to name a few.

[0081] Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and storage devices, including, for example, semiconductor memory devices (e.g., EPROM, EEPROM, and flash memory devices), magnetic disks (e.g., internal hard disks or removable disks), magneto-optical disks, and CD ROM and DVD-ROM disks. The processor and memory can be supplemented by, or incorporated in, special purpose logic circuitry.

[0082] Although this specification includes many specific implementation details, these should not be interpreted as limiting the scope of any invention or the scope of protection claimed, but are mainly used to describe the features of specific embodiments of specific inventions. Certain features described in multiple embodiments within this specification may also be implemented in combination in a single embodiment. On the other hand, the various features described in a single embodiment may also be implemented separately in multiple embodiments or in any suitable sub-combination. In addition, although features may work in certain combinations as described above and even initially claimed as such, one or more features from the claimed combination may be removed from the combination in some cases, and the claimed combination may point to a sub-combination or a variation of the sub-combination.

[0083] Similarly, although operations are depicted in a particular order in the accompanying drawings, this should not be understood as requiring that these operations be performed in the particular order shown or performed sequentially, or that all illustrated operations be performed to achieve the desired results. In some cases, multitasking and parallel processing may be advantageous. In addition, the separation of various system modules and components in the above-described embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product, or packaged into multiple software products.

[0084] Thus, specific embodiments of the subject matter have been described. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the particular order shown or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing may be advantageous.

[0085] The above description is only a preferred embodiment of this specification and is not intended to limit this specification. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this specification should be included in the scope of protection of this specification.

Claims

1. A method for dealing with vehicle collision risk, characterized in that: The method comprises: In a case where it is determined that a vehicle and a target object are about to collide, determining a target position on the vehicle based on vehicle motion state information of the vehicle and object motion state information of the target object, wherein a degree of vehicle damage corresponding to the target position is no greater than degrees of vehicle damage corresponding to other collision positions; adjusting a driving path of the vehicle so that the vehicle collides with the target object at the target location; While adjusting the driving path of the vehicle, periodically determining whether the vehicle is about to collide with a target object; If the judgment result is negative, adjusting the driving path of the vehicle to avoid a collision between the vehicle and the target object; The determining the target position on the vehicle according to the vehicle motion state information of the vehicle and the object motion state information of the target object includes: When the target object belongs to a preset vehicle model, the target position is determined based on a safety collision model, vehicle motion state information, object motion state information and vehicle model parameters of the target object. The safety collision model is used to characterize the correspondence between the degree of damage to each collision area and the collision parameters under different collision angles and different collision positions of the vehicle.

2. The method according to claim 1, characterized in that Determining that the vehicle is about to collide with the target object includes: acquiring first motion state information of the vehicle, second motion state information of candidate objects around the vehicle, and road environment information according to an onboard sensor of the vehicle; determining a collision probability between the vehicle and the candidate object based on the first motion state information, the second motion state information, and the road environment information; When the collision probability reaches a preset probability threshold, the candidate object is used as the target object, and it is determined that the vehicle and the target object are about to collide.

3. The method according to claim 2, characterized in that The determining the collision probability between the vehicle and the candidate object according to the first motion state information, the second motion state information, and the road environment information includes: generating at least one vehicle drivable path based on the road environment information; Predicting a motion trajectory of the candidate object within a preset duration based on the first motion state information and the second motion state information, so as to identify a spatial overlap point between the at least one drivable vehicle path and the object motion trajectory within the preset duration; The collision probability is calculated based on the number and time distribution characteristics of the spatial coincidence points.

4. The method according to claim 2, characterized in that The method further comprises: In the case that there are multiple candidate objects and a vulnerable road user group exists among the multiple candidate objects, the vulnerable road user group is removed from the candidate objects.

5. The method according to claim 1, wherein The determining the target position on the vehicle according to the vehicle motion state information of the vehicle and the object motion state information of the target object includes: generating occupant distribution information of occupants in the vehicle according to onboard sensors of the vehicle; determining a set of candidate target positions based on the occupant distribution information, wherein the occupant distribution information does not match any target position in the set of target positions; A target position on the vehicle is determined from the candidate target position set according to the vehicle motion state information of the vehicle and the object motion state information of the target object.

6. The method according to claim 1, wherein The adjusting the driving path of the vehicle includes: determining adjusted path parameters of the vehicle according to the target position; A path adjustment instruction based on braking, steering, and driving dimensions is generated according to the vehicle's adjusted path parameters, and the path adjustment instruction is executed to adjust the driving path.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

8. A computer program product, characterized in that The method comprises a computer program / instruction, which implements the steps of the method according to any one of claims 1 to 6 when the computer program / instruction is executed by a processor.

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