A vehicle collision probability detection method, system, storage medium and vehicle

Abstract

The application provides a vehicle collision probability detection method, system, storage medium and vehicle. The vehicle collision probability detection method comprises the following steps: in response to a vehicle collision probability detection signal, first constructing a preset group of calibration speeds and calibration distances; then calculating the minimum safety distance corresponding to each group of calibration speeds respectively to form a minimum safety distance set, and comparing the minimum safety distance set with each group of calibration distances respectively; then obtaining a preset group of collision mark sets according to the comparison results, and calculating a collision probability set according to each group of collision mark sets to obtain the final collision probability of the current vehicle and the target vehicle according to the collision probability set. The application can effectively evaluate the collision probability between the current vehicle and the target vehicle, provide accurate and reliable vehicle collision probability evaluation, and flexibly adjust and adapt the related calibration parameters according to different roads and vehicle conditions, and provide more personalized collision probability detection.

Description

Technical Field

[0001] This application relates to the field of vehicle collision probability technology, and in particular to a vehicle collision probability detection method, system, storage medium, and vehicle. Background Technology

[0002] With the increasing popularity of automobiles, more and more safety hazards are emerging. Intelligent autonomous driving technology can help solve emergency risk situations encountered while driving and reduce the occurrence of dangers.

[0003] The safety collision avoidance system in intelligent autonomous driving technology is an important system to ensure the safe driving of vehicles. At present, the safety collision avoidance system often uses the safety distance model to judge the dangerous situation of the vehicle. The safety distance model mainly uses braking distance calculation to determine whether to take collision avoidance measures. It usually assumes that the vehicle is decelerating at a fixed speed at the current speed, and measures the difference between the distance the vehicle decelerates and the current relative distance to the target vehicle.

[0004] For intelligent vehicles, the future movement of traffic vehicles is uncertain and has a certain degree of randomness. Existing safe distance models usually ignore the uncertainty of traffic vehicle movement and environmental perception, and only use the current sensor measurements to calculate the degree of danger between the vehicle and the target vehicle. This will lead to inaccurate hazard assessment results, thereby affecting the driving safety of intelligent vehicles. Summary of the Invention

[0005] This application addresses the technical problem in the prior art where the uncertainty of vehicle motion and environmental perception is ignored, resulting in inaccurate hazard assessment and thus affecting the driving safety of intelligent vehicles. It provides a vehicle collision probability detection method, system, storage medium, and vehicle with more reliable and accurate collision probability detection results.

[0006] Specifically, this application provides a vehicle collision probability detection method, including the following steps:

[0007] S100: In response to the vehicle collision probability detection signal, acquire vehicle information of the current vehicle and the target vehicle, and construct a preset set of calibration speed and calibration distance based on the vehicle information.

[0008] S200: Calculate the minimum safe distance corresponding to each set of calibration speeds to form a set of minimum safe distances, and compare the set of minimum safe distances with each set of calibration distances.

[0009] S300: Obtain a preset set of collision markers based on the comparison results, and calculate a set of collision probabilities based on each set of collision markers, so as to obtain the final collision probability between the current vehicle and the target vehicle based on the set of collision probabilities.

[0010] In the above technical solution, by acquiring vehicle information and calculating the minimum safe distance set, the collision probability between the current vehicle and the target vehicle can be effectively assessed, providing accurate prediction results; by comparing the minimum safe distance set and the calibration distance, the collision marker set can be obtained based on the comparison results, and the collision probability set can be calculated, providing a reliable vehicle collision probability assessment; by constructing a preset set of calibration speeds and calibration distances, flexible adjustments and adaptations can be made according to different road and vehicle conditions, providing more personalized collision probability detection.

[0011] It should be noted that the construction process of calibration speed and calibration distance uses Gaussian function to transform a deterministic problem into a probabilistic one. Furthermore, the Monte Carlo method is used in the calculation of the collision probability set to quantify the uncertainty of trajectory points and more accurately measure the collision risk of the current vehicle.

[0012] Furthermore, before performing step S100, the following steps are included:

[0013] Pre-set collision calibration parameters, as well as preset group speed calibration values ​​and distance calibration values.

[0014] In the above technical solution, the collision calibration parameters, speed calibration parameters, and distance calibration parameters can all be customized according to actual needs and specific road and vehicle conditions to improve the accuracy and reliability of collision probability detection. Furthermore, reasonable parameter adjustments and optimizations can be made to enhance the performance and accuracy of vehicle collision probability detection.

[0015] The degree of collision risk assessment can be adjusted by changing the magnitude of the collision calibration parameters. Decreasing the collision calibration parameters expands the dangerous driving area around the current vehicle and narrows the safety boundary between the current vehicle and the target vehicle. Increasing the collision calibration parameters relaxes the safety boundary between the current vehicle and the target vehicle.

[0016] Both the speed and distance calibrators follow the principle of normal distribution. By adding the speed and distance calibrators to the subsequently obtained relative speed and relative distance, the uncertainty of speed and distance is represented, making vehicle collision detection more consistent with the polymorphism of vehicle operation.

[0017] Furthermore, the construction of the preset calibration speed and calibration distance in step S100 specifically includes:

[0018] The relative speed and relative distance of the target vehicle relative to the current vehicle are obtained based on the vehicle information.

[0019] Each set of speed calibration values ​​and distance calibration values ​​are added to the relative speed and relative distance, respectively, to form a preset set of calibration speed and calibration distance.

[0020] In the above technical solution, by calculating relative speed and relative distance based on vehicle information, adjustments can be made flexibly according to the actual vehicle dynamics to adapt to different driving scenarios and traffic conditions. By obtaining the relative speed and relative distance of the target vehicle relative to the current vehicle, the motion relationship between the two vehicles can be assessed more accurately, providing more reliable calibrated speed and calibrated distance. Adding each set of speed calibration values ​​and distance calibration values ​​to the relative speed and relative distance can comprehensively consider the collision risk under different speed and distance conditions, providing more comprehensive and accurate collision probability detection.

[0021] Furthermore, the formation of the minimum safe distance set in step S200 specifically includes:

[0022] S201: Obtain the current speed, braking delay, and maximum deceleration calibrated value of the current vehicle, as well as the safe distance between the current vehicle and the target vehicle after they come to a stop.

[0023] S202: Calculate the minimum safe distance between the current vehicle and the target vehicle corresponding to each set of calibration speeds based on the calibration speed and the results obtained in step S201, so as to form a minimum safe distance set based on each set of minimum safe distances.

[0024] In the above technical solution, by acquiring information such as the current vehicle's current speed, braking delay, and maximum deceleration calibration value, and combining this with the safe distance between the current vehicle and the target vehicle after stopping, a more accurate minimum safe distance can be provided by comprehensively considering factors such as the vehicle's own performance and the safe distance requirements when parking. Since step S200 is calculated at the current moment and incorporates real-time information such as the current vehicle's speed, the resulting minimum safe distance set can quickly respond to changes in dynamic traffic conditions and provide timely safety warnings. By calculating the corresponding minimum safe distance for different calibration speeds and forming a minimum safe distance set, a more accurate vehicle collision probability assessment can be provided, enhancing the reliability of collision detection.

[0025] Furthermore, after performing step S300, the process also includes:

[0026] The final collision probability is compared with the collision calibration parameters.

[0027] When the final collision probability is greater than the collision calibration parameter, it is determined that there is a collision risk between the current vehicle and the target vehicle, and each collision probability in the collision probability set is compared with the collision calibration parameter in turn.

[0028] If the consecutive preset collision probabilities are all greater than the collision calibration parameter, a collision risk command is issued, and an alarm message and a deceleration requirement value are issued according to the collision risk command.

[0029] In the above technical solution, by comparing the final collision probability with the collision calibration parameters, it is possible to promptly determine whether there is a collision risk between the current vehicle and the target vehicle and make corresponding decisions. By continuously comparing the preset collision probabilities with the collision calibration parameters, the false alarm rate can be reduced and the accuracy of judging the real collision risk can be improved. Once the preset collision probabilities are all greater than the collision calibration parameters, the system can issue a collision risk command, promptly send an alarm message and a deceleration requirement value to the driver, and remind the driver to take appropriate actions.

[0030] Based on the same concept, this application also provides a vehicle collision probability detection system, the system comprising:

[0031] Construction module: In response to the vehicle collision probability detection signal, it acquires vehicle information of the current vehicle and the target vehicle, and constructs a preset set of calibration speed and calibration distance based on the vehicle information.

[0032] Formation module: Used to calculate the minimum safe distance corresponding to each set of calibration speeds, so as to form a set of minimum safe distances.

[0033] Comparison module: used to compare the minimum safe distance set with each set of calibration distances.

[0034] Acquisition module: used to acquire a preset set of collision markers based on the comparison result of the comparison module, and calculate a collision probability set based on each set of collision markers, so as to acquire the final collision probability between the current vehicle and the target vehicle based on the collision probability set.

[0035] In the above technical solution, triggered by a vehicle collision probability detection signal, the system can quickly acquire and process vehicle information of the current vehicle and the target vehicle, providing real-time collision probability estimation. By constructing preset sets of calibration speeds and distances, and calculating the minimum safe distance corresponding to each set of calibration speeds, the system can more accurately assess the collision risk between the current vehicle and the target vehicle. Through the comparison results of the comparison module and the processing of the acquisition module, the system can comprehensively consider multiple sets of calibration distances and collision markers, calculate multiple sets of collision probabilities, and obtain the final collision probability, providing a more comprehensive and reliable judgment. Since the preset sets of calibration speeds and distances in the system can be flexibly configured, the system can adaptively perform collision probability detection according to different vehicle and road conditions.

[0036] Furthermore, the system also includes:

[0037] The settings module is used to pre-set collision calibration parameters, as well as preset group speed calibration values ​​and distance calibration values.

[0038] Alarm module: When there is a risk of collision between the current vehicle and the target vehicle, it compares each collision probability in the collision probability set with the collision calibration parameters in turn, issues a collision risk command based on the comparison results, and issues an alarm message and a deceleration requirement value based on the collision risk command.

[0039] In the above technical solution, by setting the collision calibration parameters and preset speed and distance calibration values ​​in the module, the system can judge the collision probability set based on these parameters and issue relevant warning information to improve safety performance. The preset parameters of the setting module can be personalized according to different driving scenarios and vehicle characteristics, increasing the system's adaptability and flexibility. In addition, the alarm module can issue alarm information and deceleration requirements in real time based on the real-time calculated collision probability and comparison results, improving reaction speed and warning accuracy, and increasing the driver's alertness.

[0040] Furthermore, the forming module includes:

[0041] Acquisition Unit: Used to acquire the current speed, braking delay, and maximum deceleration calibrated value of the current vehicle, as well as the safe distance between the current vehicle and the target vehicle after they come to a stop.

[0042] Forming unit: used to calculate the minimum safe distance between the current vehicle and the target vehicle corresponding to each set of calibration speeds based on the calibration speed and the acquisition result of the acquisition unit, so as to form a minimum safe distance set based on each set of minimum safe distances.

[0043] In the above technical solution, the parameters acquired by the acquisition unit include the current speed of the vehicle, braking delay, and maximum deceleration calibration value. These parameters can provide accurate vehicle braking performance information, ensuring that the calculation results of the minimum safe distance are more accurate. By forming the unit to calculate the minimum safe distance corresponding to multiple sets of calibration speeds, the forming module can provide a set of multiple minimum safe distance values, comprehensively considering the collision risk at different speeds, and providing a more comprehensive and reliable judgment basis. In addition, the calibration speed can be set according to specific needs, realizing the configurability of the system and adapting to the needs of different driving scenarios and vehicle characteristics.

[0044] Based on the same concept, this application also provides a storage medium storing a computer program, wherein the computer program is configured to execute the vehicle collision probability detection method at runtime.

[0045] Based on the same concept, this application also provides a vehicle equipped with a vehicle collision probability detection system, wherein the system uses the vehicle collision probability detection method described above to detect the final collision probability between the current vehicle and the target vehicle.

[0046] Compared with the prior art, the beneficial effects of this application are as follows:

[0047] After responding to the vehicle collision probability detection signal, this application first constructs a preset set of calibration speeds and calibration distances based on the acquired vehicle information of the current vehicle and the target vehicle; then, it calculates the minimum safe distance corresponding to each set of calibration speeds to form a set of minimum safe distances, and compares the set of minimum safe distances with each set of calibration distances; then, it obtains a preset set of collision markers based on the comparison results, and calculates a collision probability set based on each set of collision markers, so as to obtain the final collision probability between the current vehicle and the target vehicle based on the collision probability set.

[0048] This application can effectively assess the collision probability between the current vehicle and the target vehicle, providing accurate and reliable vehicle collision probability assessment. Furthermore, it can flexibly adjust and adapt the relevant calibration parameters according to different road and vehicle conditions, providing more personalized collision probability detection. Attached Figure Description

[0049] Figure 1 This is a flowchart of the vehicle collision probability detection method described in this application.

[0050] Figure 2 for Figure 1 The flowchart describes the method for constructing a preset calibration group for speed and distance.

[0051] Figure 3 for Figure 1 The flowchart of the method for forming the minimum safe distance set.

[0052] Figure 4 This is a flowchart of the method for issuing early warning information based on the final collision probability as described in this application.

[0053] Figure 5 for Figure 1 The system framework diagram of the vehicle collision probability detection method is shown below. Detailed Implementation

[0054] This application provides a vehicle collision probability detection method, system, storage medium, and vehicle to solve the technical problem in the prior art that the inaccurate hazard assessment caused by ignoring the uncertainty of traffic vehicle motion and the uncertainty of environmental perception affects the driving safety of intelligent vehicles.

[0055] The following detailed description, in conjunction with specific embodiments and accompanying drawings, describes a vehicle collision probability detection method, system, storage medium, and vehicle according to this application.

[0056] Example 1:

[0057] Please see Figure 1 This application provides a vehicle collision probability detection method, including the following steps:

[0058] S100: In response to the vehicle collision probability detection signal, acquire vehicle information of the current vehicle and the target vehicle, and construct a preset set of calibration speed and calibration distance based on the vehicle information.

[0059] In one feasible implementation, after the vehicle is started, it will send out a vehicle collision probability detection signal to detect in real time whether there is a collision risk for the current vehicle.

[0060] It should be noted that the vehicle information is obtained through sensors.

[0061] Before performing step S100, the following are included:

[0062] Pre-set the collision calibration parameter ε, as well as the preset group speed calibration value Uv and distance calibration value Ux.

[0063] The degree of collision risk assessment can be adjusted by changing the value of the collision calibration parameter ε. Decreasing the collision calibration parameter ε expands the dangerous driving area around the current vehicle and narrows the safety boundary between the current vehicle and the target vehicle. Increasing the collision calibration parameter ε relaxes the safety boundary between the current vehicle and the target vehicle.

[0064] It should be noted that the collision calibration parameter ε is obtained in advance through simulation experiments. These simulation experiments include, for example: first, designing a simulation scenario that conforms to actual road conditions based on real-world needs; this scenario includes vehicle information, road conditions, traffic flow, and the target vehicle's behavior pattern; then, setting initial parameters for the current vehicle based on the simulation scenario, such as the vehicle's current speed, braking delay, and maximum deceleration calibration value; running the designed simulation scenario multiple times using appropriate simulation software and recording data during the simulation process, including collision probability and alarm triggering data; further analyzing the recorded collision probability and alarm triggering data; and, based on the experimental objectives, statistically analyzing the simulation results to determine the appropriate collision calibration parameter ε.

[0065] The maximum deceleration calibration value is obtained in advance based on relevant simulation experiments. The process is as follows: the vehicle travels at a certain speed and brakes suddenly according to set conditions, the deceleration of the vehicle is recorded, and the average value can be obtained as the maximum deceleration calibration value through repeated experiments. The set conditions can be set according to actual application needs and are not limited here.

[0066] Both the speed calibration value Uv and the distance calibration value Ux follow the principle of normal distribution. By adding the speed calibration value Uv and the distance calibration value Ux to the subsequently obtained relative speed and relative distance, the uncertainty of speed and distance is represented, making vehicle collision detection more consistent with the polymorphism of vehicle operation.

[0067] It should be noted that Ux~N(0,σ1), Uv~N(0,σ2), where σ1 and σ2 represent the errors of distance and velocity uncertainty, respectively.

[0068] Furthermore, the preset group is set to N groups here.

[0069] For further details, please see Figure 2 The construction of N sets of calibration speeds and calibration distances in step S100 specifically includes:

[0070] Based on the vehicle information, obtain the relative speed V1 and relative distance X1 of the target vehicle relative to the current vehicle.

[0071] The vehicle information obtained by the sensor includes the position coordinates of the current vehicle and the target vehicle in space, as well as the speeds of the current vehicle and the target vehicle. The relative distance X1 between the current vehicle and the target vehicle can be calculated based on the position coordinates, and the relative speed V1 can be obtained based on the difference in speed between the current vehicle and the target vehicle.

[0072] Then, the velocity calibration value Uv and distance calibration value Ux are added to the relative velocity V1 and relative distance X1 respectively to form N sets of calibration velocities V1+Uv and calibration distances X1. i , where X i =X1+Ux, 0 <i≤N。

[0073] After the calibration speed and calibration distance are constructed, step S200 can be executed.

[0074] S200: Calculate the minimum safe distance d corresponding to each set of calibration speeds V1+Uv. i To form the minimum safe distance set {d1,d2,d3,…,d N}, and set the minimum safe distance set {d1,d2,d3,…,d N} respectively with each group of calibration distances X i Comparison, where 0 <i≤N。

[0075] For further details, please see Figure 3 The step S200 of forming the minimum safe distance set specifically includes:

[0076] S201: Obtain the current vehicle's current speed V0 and braking delay T. DAnd the maximum deceleration calibration quantity A max1 , and the safe distance d0 between the current vehicle and the target vehicle after they stop.

[0077] Among them, the braking delay T D includes braking response delay, driver reaction delay, deceleration delay and judgment delay; the braking delay T D and the safe distance d0 are both preset before detecting the collision probability, and those skilled in the art can set them according to actual application requirements. Here, the braking delay T D and the safe distance d0 are not limited.

[0078] S202: Calculate the minimum safe distance d between the current vehicle and the target vehicle corresponding to each calibrated speed V1 + Uv according to the calibrated speed V1 + Uv and the obtained result of step S201 i , so as to form a set of minimum safe distances {d1, d2, d3,..., d i} according to each group of minimum safe distances d. N}

[0079] Among them,

[0080] After comparing the set of minimum safe distances with each group of calibrated distances, step S300 can be executed.

[0081] S300: Obtain a preset set of collision markers according to the comparison result, and calculate a set of collision probabilities {P1, P2, P3,..., P N} according to each group of collision marker sets, so as to obtain the final collision probability P of the current vehicle and the target vehicle according to the set of collision probabilities {P1, P2, P3,..., P N} aver .

[0082] Among them, taking the current calibrated distance as X1 as an example, <s

[0083] Compare d in {d1, d2, d3,..., d N} with X1 in turn. If d i ≥X1, it is marked as 1. If d i <X1, it is marked as 0, so as to obtain a set of collision markers such as {00011111...000}. i <X1 is marked as 0, so as to obtain a set of collision markers such as {00011111...000}.

[0084] After the comparison of the calibrated distance X1 is completed, compare d in {d1, d2, d3,..., d N} with X2 in turn, and so on, until d in {d1, d2, d3,..., d i} is compared with X2 in turn, and so on, until d in {d1, d2, d3,..., d N}i sequentially with X N After comparison, N sets of collision mark sets are obtained.

[0085] Furthermore, taking the first set of collision mark sets {00011111…000} as an example, the number of marks with Flag = 1 is counted as N1 = ∑Flag. From Monte Carlo, the collision probability between the current vehicle and the target vehicle is P1(d i <X1) = N1 / N; and so on, P2(d i <X2) = N2 / N,..., P2(d i <X N ) = N N / N; Therefore, the collision probability set {P1, P2, P3, …, P N} is obtained.

[0086] Furthermore, the final collision probability 1 ≤ i ≤ N.

[0087] Please refer to Figure 4 , after step S300 is executed, it further includes:

[0088] Compare the final collision probability P aver with the collision calibration parameter ε.

[0089] When the final collision probability P aver is greater than the collision calibration parameter ε, it is determined that there is a collision risk between the current vehicle and the target vehicle, and each collision probability in the collision probability set {P1, P2, P3, …, P2} is sequentially compared with the collision calibration parameter ε; when the final collision probability P aver is less than or equal to the collision calibration parameter ε, it is determined that there is no collision risk between the current vehicle and the target vehicle.

[0090] If a preset number of consecutive collision probabilities are greater than the collision calibration parameter ε, a collision risk instruction is issued to send an alarm message and a deceleration demand value according to the collision risk instruction; otherwise, it is determined that there is no collision risk between the current vehicle and the target vehicle.

[0091] Among them, the preset number is set to 5 in this embodiment. The 5 are obtained from the alarm trigger data in the above simulation process. Using the condition that 5 consecutive collision probabilities are greater than the collision calibration parameter as the trigger condition for the collision risk instruction can reduce the probability of false alarms, reduce the possibility of false alerts, and improve the accuracy and credibility of the alarm message.

[0092] The alarm message, for example, appears as a pop-up window on the vehicle's infotainment screen displaying "Current collision risk" and is accompanied by a voice announcement. At the same time, a deceleration requirement value is sent to the relevant actuator, which then controls the vehicle to decelerate to the required deceleration value to ensure the vehicle's driving safety.

[0093] Example 2:

[0094] Please see Figure 5 This application also provides a vehicle collision probability detection system, the system comprising:

[0095] Construction module: In response to the vehicle collision probability detection signal, it acquires vehicle information of the current vehicle and the target vehicle, and constructs a preset set of calibration speed and calibration distance based on the vehicle information.

[0096] Formation module: Used to calculate the minimum safe distance corresponding to each set of calibration speeds, so as to form a set of minimum safe distances.

[0097] Comparison module: used to compare the minimum safe distance set with each set of calibration distances.

[0098] Acquisition module: used to acquire a preset set of collision markers based on the comparison result of the comparison module, and calculate a collision probability set based on each set of collision markers, so as to acquire the final collision probability between the current vehicle and the target vehicle based on the collision probability set.

[0099] In the above technical solution, triggered by a vehicle collision probability detection signal, the system can quickly acquire and process vehicle information of the current vehicle and the target vehicle, providing real-time collision probability estimation. By constructing preset sets of calibration speeds and distances, and calculating the minimum safe distance corresponding to each set of calibration speeds, the system can more accurately assess the collision risk between the current vehicle and the target vehicle. Through the comparison results of the comparison module and the processing of the acquisition module, the system can comprehensively consider multiple sets of calibration distances and collision markers, calculate multiple sets of collision probabilities, and obtain the final collision probability, providing a more comprehensive and reliable judgment. Since the preset sets of calibration speeds and distances in the system can be flexibly configured, the system can adaptively perform collision probability detection according to different vehicle and road conditions.

[0100] The system also includes:

[0101] The settings module is used to pre-set collision calibration parameters, as well as preset group speed calibration values ​​and distance calibration values.

[0102] Alarm module: When there is a risk of collision between the current vehicle and the target vehicle, it compares each collision probability in the collision probability set with the collision calibration parameters in turn, issues a collision risk command based on the comparison results, and issues an alarm message and a deceleration requirement value based on the collision risk command.

[0103] In the above technical solution, by setting the collision calibration parameters and preset speed and distance calibration values ​​in the module, the system can judge the collision probability set based on these parameters and issue relevant warning information, thereby improving safety performance. The preset parameters of the setting module can be personalized according to different driving scenarios and vehicle characteristics, increasing the system's adaptability and flexibility. In addition, the alarm module can issue alarm information and deceleration requirements in real time based on the real-time calculated collision probability and comparison results, improving reaction speed and warning accuracy, and increasing driver alertness.

[0104] The forming module includes:

[0105] Acquisition Unit: Used to acquire the current speed, braking delay, and maximum deceleration calibrated value of the current vehicle, as well as the safe distance between the current vehicle and the target vehicle after they come to a stop.

[0106] Forming unit: used to calculate the minimum safe distance between the current vehicle and the target vehicle corresponding to each set of calibration speeds based on the calibration speed and the acquisition result of the acquisition unit, so as to form a minimum safe distance set based on each set of minimum safe distances.

[0107] In the above technical solution, the parameters acquired by the acquisition unit include the current speed of the vehicle, braking delay, and maximum deceleration calibration value. These parameters can provide accurate vehicle braking performance information, ensuring that the calculation results of the minimum safe distance are more accurate. By forming the unit to calculate the minimum safe distance corresponding to multiple sets of calibration speeds, the forming module can provide a set of multiple minimum safe distance values, comprehensively considering the collision risk at different speeds, and providing a more comprehensive and reliable judgment basis. In addition, the calibration speed can be set according to specific needs, realizing the configurability of the system and adapting to the needs of different driving scenarios and vehicle characteristics.

[0108] Example 3:

[0109] This application also provides a storage medium storing a computer program, wherein the computer program is configured to execute the vehicle collision probability detection method at runtime.

[0110] In this embodiment, the storage medium stores several computer programs to cause a device to perform all or part of the steps of the methods described in the various embodiments of this application.

[0111] The medium may include various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks.

[0112] Example 4:

[0113] This application also provides a vehicle equipped with a vehicle collision probability detection system, wherein the system uses the aforementioned vehicle collision probability detection method to detect the final collision probability between the current vehicle and a target vehicle.

[0114] In summary, this application provides a vehicle collision probability detection method, system, storage medium, and vehicle. Upon responding to a vehicle collision probability detection signal, a preset set of calibration speeds and distances is first constructed based on the acquired vehicle information of the current vehicle and the target vehicle. Then, the minimum safe distance corresponding to each set of calibration speeds is calculated to form a minimum safe distance set, which is then compared with each set of calibration distances. A preset set of collision markers is obtained based on the comparison results, and a collision probability set is calculated based on each set of collision markers to obtain the final collision probability between the current vehicle and the target vehicle. This application can effectively assess the collision probability between the current vehicle and the target vehicle, providing accurate and reliable vehicle collision probability assessment. Furthermore, it allows for flexible adjustment and adaptation of relevant calibration parameters according to different road and vehicle conditions, providing more personalized collision probability detection.

[0115] Although exemplary embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above exemplary embodiments are merely illustrative and are not intended to limit the scope of this application. Various changes and modifications can be made therein by those skilled in the art without departing from the scope and spirit of this application. All such changes and modifications are intended to be included within the scope of this application as claimed in the appended claims.

[0116] 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 apparatus 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 apparatus. 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 apparatus that includes said element.

[0117] Although the description of this application has been made in conjunction with the specific embodiments described above, it will be apparent to those skilled in the art that many substitutions, modifications, and variations can be made based on the foregoing. Therefore, all such substitutions, modifications, and variations are included within the spirit and scope of the appended claims.

Claims

1. A method for detecting vehicle collision probability, characterized in that, Includes the following steps: S100: In response to the vehicle collision probability detection signal, acquire vehicle information of the current vehicle and the target vehicle, and construct a preset set of calibration speed and calibration distance based on the vehicle information; Specifically, the construction of the preset group of calibration speed and calibration distance in step S100 includes: obtaining the relative speed and relative distance of the target vehicle relative to the current vehicle based on the vehicle information; and adding the speed calibration amount and distance calibration amount of each group to the relative speed and relative distance respectively to form the preset group of calibration speed and calibration distance. S200: Calculate the minimum safe distance corresponding to each set of calibration speeds to form a set of minimum safe distances, and compare the set of minimum safe distances with each set of calibration distances; S300: Obtain a preset set of collision markers based on the comparison results, and calculate a set of collision probabilities based on each set of collision markers. Obtain the final collision probability between the current vehicle and the target vehicle based on the set of collision probabilities. Compare the final collision probability with the collision calibration parameters. When the final collision probability is greater than the collision calibration parameters, determine that there is a collision risk between the current vehicle and the target vehicle. Compare each collision probability in the set of collision probabilities with the collision calibration parameters in sequence, and issue a collision risk command based on the comparison results.

2. The vehicle collision probability detection method according to claim 1, characterized in that, Before performing step S100, the following steps are included: presetting collision calibration parameters, as well as presetting group speed calibration values ​​and distance calibration values.

3. The vehicle collision probability detection method according to claim 2, characterized in that, The process of forming the minimum safe distance set in step S200 specifically includes: S201: Obtain the current speed, braking delay, and maximum deceleration calibrated value of the current vehicle, as well as the safe distance between the current vehicle and the target vehicle after they come to a stop; S202: Calculate the minimum safe distance between the current vehicle and the target vehicle corresponding to each set of calibration speeds based on the calibration speed and the results obtained in step S201, so as to form a minimum safe distance set based on each set of minimum safe distances.

4. The vehicle collision probability detection method according to claim 3, characterized in that, Step S300 includes: If the consecutive preset collision probabilities are all greater than the collision calibration parameter, a collision risk command is issued, and an alarm message and a deceleration requirement value are issued according to the collision risk command.

5. A system employing the vehicle collision probability detection method as described in any one of claims 1-4, characterized in that, The system includes: Construction module: In response to the vehicle collision probability detection signal, it acquires vehicle information of the current vehicle and the target vehicle, and constructs a preset set of calibration speed and calibration distance based on the vehicle information; Formation module: used to calculate the minimum safe distance corresponding to each set of calibration speeds, so as to form a set of minimum safe distances; Comparison module: used to compare the set of minimum safe distances with each set of calibration distances; Acquisition module: used to acquire a preset set of collision markers based on the comparison result of the comparison module, and calculate a set of collision probabilities based on each set of collision markers, so as to acquire the final collision probability between the current vehicle and the target vehicle based on the set of collision probabilities.

6. The system according to claim 5, characterized in that, The system also includes: Settings module: used to preset collision calibration parameters, as well as preset group speed calibration values ​​and distance calibration values; Alarm module: When there is a risk of collision between the current vehicle and the target vehicle, it compares each collision probability in the collision probability set with the collision calibration parameters in turn, issues a collision risk command based on the comparison results, and issues an alarm message and a deceleration requirement value based on the collision risk command.

7. The system according to claim 6, characterized in that, The forming module includes: Acquisition unit: used to acquire the current speed, braking delay, and maximum deceleration calibrated value of the current vehicle, as well as the safe distance between the current vehicle and the target vehicle after they stop; Forming unit: used to calculate the minimum safe distance between the current vehicle and the target vehicle corresponding to each set of calibration speeds based on the calibration speed and the acquisition result of the acquisition unit, so as to form a minimum safe distance set based on each set of minimum safe distances.

8. A storage medium, characterized in that, The storage medium stores a computer program, wherein the computer program is configured to execute the vehicle collision probability detection method as described in any one of claims 1-4 when it is run.

9. A vehicle, characterized in that, A vehicle collision probability detection system is configured, wherein the system uses the vehicle collision probability detection method as described in any one of claims 1-4 to detect the final collision probability between the current vehicle and the target vehicle.

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