Method for reducing wear and tear of autonomous vehicle crash test equipment

Abstract

The present invention discloses a method for reducing the loss of autonomous vehicle collision test equipment, comprising the following steps: obtaining pre-set test vehicle parameters, the test vehicle parameters including the maximum deceleration of the automatic emergency braking system; a max , test vehicle speed v 试验 and communication system delay time t 延迟 ; When the emergency braking system of the test vehicle is triggered, the formula t 触发 = v 试验 / a max + t 延迟 Calculate the emergency avoidance trigger time t 触发 ; After collecting the position data of the test vehicle and the background target in real time, calculate the real-time relative distance D , and by the formula t 碰撞 = D / v 试验 Calculating collision time t 碰撞 ;when t 碰撞 ≤ t 触发 When the target object is moved away from the collision direction by the mechanical actuator, the present invention actively drives the target object away from the collision direction before the collision occurs, thereby avoiding structural damage caused by direct collision.

Description

Technical Field

[0001] The present invention relates to the field of autonomous driving. More specifically, the present invention relates to a method for reducing wear and tear of autonomous vehicle collision test equipment. Background Art

[0002] With the rapid development of autonomous driving technology, the frequency and complexity of autonomous vehicle crash tests have increased significantly. In traditional crash tests, the collision between the test vehicle and background targets (such as static or dynamic objects simulating pedestrians or other vehicles) typically relies on the target's own structural design (such as flying or dispersing after the collision) to dissipate the collision kinetic energy and protect the test vehicle. However, this passive protection method has significant drawbacks:

[0003] Severe equipment wear and tear: Background targets are prone to structural damage or even failure after repeated collisions. High-precision test targets (such as dynamic targets that can simulate complex motion) are expensive, and frequent replacement leads to a significant increase in testing costs.

[0004] Limited test efficiency: Repair or replacement of the target requires interruption of the test, affecting the continuity of the test process;

[0005] Insufficient safety: Passive protection cannot actively avoid collisions, which may cause target fragments to fly or lose control, posing potential risks to personnel and equipment at the test site.

[0006] Existing technologies lack an active protection mechanism for background targets, and it is difficult to reduce losses by dynamically adjusting the target position before a collision occurs. Therefore, there is an urgent need for a method that can accurately predict collision risks and trigger target avoidance to improve test safety and economy. Summary of the Invention

[0007] The purpose of the present invention is to provide a method for reducing wear and tear on autonomous vehicle collision test equipment. By real-time monitoring of the relative distance, speed, and deceleration between the test vehicle and background targets, the risk of collision can be accurately determined. Before a collision occurs, the target object can be actively driven away from the collision direction, thereby avoiding or reducing structural damage caused by direct collisions and extending the service life of the target object.

[0008] To achieve these and other advantages of the present invention, a method for reducing wear and tear of an autonomous vehicle crash test device is provided, comprising the following steps:

[0009] Obtain pre-set test vehicle parameters, including the maximum deceleration of the automatic emergency braking system a max , test vehicle speed v 试验 and communication system delay time t 延迟 ;

[0010] When the emergency braking system of the test vehicle is triggered, the t 触发 = v 试验 / a max + t 延迟 Calculate the emergency avoidance trigger time t 触发 ;

[0011] After collecting the position data of the test vehicle and the background target in real time, calculate the real-time relative distance D , and by the formula t 碰撞 = D / v 试验 Calculating collision time t 碰撞 ;

[0012] when t 碰撞 ≤ t 触发 When the collision occurs, the stationary background target is driven to move away from the collision direction by the mechanical actuator.

[0013] Preferably, the method for reducing wear and tear of autonomous driving vehicle collision test equipment further comprises the following steps:

[0014] Use GPS positioning equipment to obtain GPS information and acceleration data of the test vehicle and background target objects; set up communication system delay monitoring equipment on the test vehicle and background target object carrying platform respectively, t 延迟 The sum of the delay time measured by the vehicle-side communication system delay monitoring device and the delay time measured by the target-side communication system delay monitoring device;

[0015] When obtaining the pre-set test vehicle parameters, obtain the maximum deceleration of the test vehicle a 测试 ;

[0016] At consecutive time points t 1 and t 2. Record the GPS coordinates of the test vehicle and background objects. t 1. t 2 The coordinates at the moment calculate the relative displacement △ s 定位 ;

[0017] By formula v 相对= △ s 定位 / ( t 1- t 2 ) Calculate relative speed based on GPS information v 相对 ;

[0018] Based on real-time relative distance D and v 相对 , combined with a 测试 , through the uniformly accelerated linear motion displacement formula D = v 相对 t - 1 / 2 a 测试 t 2 , recalculate the collision time and get the new collision time t 新 .

[0019] Preferably, in the method for reducing the loss of autonomous vehicle collision test equipment, the actual deceleration is obtained by the acceleration sensor built into the GPS positioning device. a 实际 , and compare it with a 测试 For comparison:

[0020] like a 实际 = a 测试 , the collision time is t 新 ;

[0021] like a 实际 < a 测试 , combined with real-time relative distance D and v 相对 ,Will a 实际 Resubstitute the displacement formula of uniformly accelerated linear motion into D = v 相对 t - 1 / 2 a 实际 t 2 , recalculate the collision time and get the adjusted collision time t 调整 ;

[0022] likea 实际 > a 测试 , perform calibration check on the sensor data. If a 实际 > a 测试 , analyze whether there is a system abnormality. If there is an abnormality, issue an alarm and stop the test. If there is no abnormality, combine the real-time relative distance D and relative speed v 相对 ,Will a 实际 Resubstitute the displacement formula of uniformly accelerated linear motion into D = v 相对 t - 1 / 2 a 实际 t 2 , recalculate the collision time and get the adjusted collision time t 调整 .

[0023] Preferably, the method for reducing wear and tear of autonomous driving vehicle collision test equipment further comprises the following steps:

[0024] A laser radar and multiple visual sensors are installed on the test vehicle, and a laser radar is installed on the background target. A slope sensor and a laser roughness meter are set up on the test site. The laser radars on the test vehicle and the background target measure the distance to each other, and the visual sensor collects images of the surrounding environment. The slope sensor obtains real-time slope information of the test site, and the laser roughness meter measures the flatness of the ground to obtain high-precision map data.

[0025] Use GPS positioning device information to calculate the relative distance between the test vehicle and background targets D 定位 ;

[0026] Process and analyze the laser radar measurement data to obtain the relative distance based on the laser radar D 雷达 ;

[0027] Process the image collected by the visual sensor to obtain the relative distance based on the visual sensor D 视觉 ;

[0028] Match the position information of the test vehicle and background targets with the high-precision map to obtain the relative distance based on the high-precision map D 地图 ;

[0029] Using data fusion algorithm, D 定位 、 D 雷达 、 D 视觉 and D 地图 Fusion, get the relative distance after fusion D 融合 , based on the slope angle obtained by the slope sensor i , 0° ≤ i < 15°, if the vehicle and the target are on the same slope and the slope is a straight line, the formula D 修正 = D 融合 / cosθ right D 融合 Make corrections to get the slope-corrected distance D 修正 If the vehicle and the target are not on the same straight slope, skip the correction and directly use D 融合 As D 修正 ;

[0030] The laser roughness meter divides the ground into several small areas and measures the height of each small area. h i and length l i , i = 1, 2, …, n , i Indicates the number of regions and calculates the actual distance increase of each small region , accumulate the actual distance increase of all small areas , and finally obtain a more accurate real-time relative distance D = D 修正 + △ L .

[0031] Preferably, the method for reducing wear and tear of autonomous driving vehicle collision test equipment further comprises:

[0032] When the test vehicle's emergency braking system is triggered and the maximum deceleration of the automatic emergency braking system is reached a max After that, based on the maximum deceleration of the automatic emergency braking system a max and real-time relative speed v 相对 , through the kinematic formula s最短 = v 2 相对 / (2 a max ) Calculate the theoretical shortest braking distance s 最短 ; If the remaining real-time relative distance in the braking phase D ≤ s 最短 , it is determined that the collision cannot be avoided by braking alone;

[0033] If and only if the following conditions are simultaneously met, the computing module sends a trigger signal to the background target carrying system via the communication link. After receiving the trigger signal, the background target carrying system activates the mechanical actuator to drive the background target away from the collision direction:

[0034] 1) From the start of the test t 0 = Current time starting from 0s t satisfy t 制动 ≤ t ≤ t 制动 + Collision time, where t 制动 The moment when the emergency braking system is triggered;

[0035] 2) The test vehicle's emergency braking system has been triggered and the deceleration has reached the maximum deceleration of the automatic emergency braking system a max ;

[0036] 3) The collision time is less than or equal to the trigger time;

[0037] like a 实际 = a 测试 , the collision time is t 新 ;like a 实际 ≠ a 测试 , the collision time is t 调整 .

[0038] Preferably, in the method for reducing the loss of autonomous vehicle collision test equipment, after the background target carrying system receives the trigger signal, it calculates the collision risk coefficient R = D / D 参考 × v 相对 Determine the movement method of the background target, whereR The dimension is m / s, D 参考 The reference distance is pre-set based on the performance of the test vehicle and the background target object; the method for determining the movement of the background target object based on the collision risk coefficient is:

[0039] like R < R 低 , the mechanical actuator drives the background target with 30% of its maximum power, moving the distance L 1= k 1×( DD 安全 ), t 移动 < t 碰撞 , t 移动 = L 1 / v 驱动 ;in k 1The value range is 1.1-1.3, t 移动 is the moving time, v 驱动 is the actuator driving speed, D 安全 is the safety distance threshold; and k 1 According to the relative speed v 相对 and relative distance D Dynamic Selection:

[0040] when v 相对 ≤ 5m / s, and D > 10m, k 1= 1.1;

[0041] when v 相对 ≤ 5m / s, and 5m < D ≤ 10m, k 1= 1.2;

[0042] when v 相对 ≤ 5m / s, and D ≤ 5m, k 1= 1.3;

[0043] like R 低 ≤ R < R 高 , the mechanical actuator drives the background target with 60% of its maximum power, moving the distanceL 2= k 2× ( D-D 安全 ), t 移动 < t 碰撞 , t 移动 = L 2 / v 驱动 ;in k 2The value range is 1.3-1.5; and k 2 According to the relative speed v 相对 and relative distance D Dynamic Selection:

[0044] When 5m / s < v 相对 ≤ 15m / s, and D > 8m, k 2= ​​1.3;

[0045] When 5m / s < v 相对 ≤ 15m / s, and 5m < D When ≤8m, k 2= ​​1.4;

[0046] When 5m / s < v 相对 ≤ 15m / s, and D ≤ 5m, k 2= ​​1.5;

[0047] If the collision risk factor R ≥ R 高 ,regardless v 相对 If the speed is greater than 15m / s, the mechanical actuator will immediately drive the background target with maximum power and move it to the safe area closest to the current position along the shortest straight path. L 3= L 初始 + L 缓冲 , t 移动 < t 碰撞 , t 移动 = L 3 / v 驱动 , v 驱动 is the actuator driving speed; where,L 初始 is the straight-line distance from the current position to the center of the safe area, L 缓冲 The buffer distance is 5-10m.

[0048] Preferably, in the method for reducing the loss of autonomous driving vehicle collision test equipment, R 低 The value range is 1.2-2.5; R 高 The value range is 2.5-4.0; D 参考 = k × s 最短 ; k、D 参考 Dynamic matching according to the following rules based on the test scenario:

[0049] Urban road test: k = 1.5-2.0, D 参考 = 15-25m;

[0050] Highway test: k = 2.0-3.0, D 参考 ≥ 100m;

[0051] Extreme working condition testing: k = 2.5-3.5, D 参考 = 5-10m;

[0052] D 安全 The value range is 5.56-50m and meets the D ≤ D 安全 ≤ D 参考 ,and D 安全 = max(2 × L 车辆 , 1.2 × s 最短 , v 相对 × t 响应 ), L 车辆 To test the full length of the vehicle, t 响应 The total time from when the system detects a collision risk to when the mechanical actuator starts to drive the background target to move, including: sensor data processing time t数据处理 , calculation module decision time t 计算 、 t 延迟 , Mechanical actuator start time t 执行 ;

[0053] Urban road test: t 响应 = 0.3-0.5s;

[0054] Highway test: t 响应 = 0.2-0.3s;

[0055] Extreme working condition testing: t 响应 = 0.1-0.2s;

[0056] v 相对 The unit is m / s; t 响应 The unit is s; L 车辆 、 s 最短 、 D 安全 All units are in m.

[0057] Preferably, in the method for reducing the loss of autonomous driving vehicle collision test equipment, the data fusion algorithm adopts a dynamic weight adjustment mechanism, specifically comprising the following steps:

[0058] Real-time evaluation of confidence indicators of each sensor data, including:

[0059] Calculating confidence based on lidar measurement noise level C 雷达 ,in, C 雷达 = 1 / ( s 雷达 2 + e ), s 雷达 is the standard deviation of the current frame data of the lidar, e To prevent the denominator from being zero, a very small constant;

[0060] Confidence calculation based on image clarity and feature matching of visual sensors C 视觉 ,in, C 视觉 = S 视觉 ×M 匹配 , S 视觉 Rate the image sharpness, M 匹配 The accuracy of target feature point matching;

[0061] Calculate confidence based on the number of satellites and signal strength of GPS positioning devices C 定位 ,in, C 定位 = N 卫星 × I 信号 , N 卫星 is the number of visible satellites, I 信号 is the normalized value of signal intensity;

[0062] Confidence calculation based on update timeliness and matching error of high-precision maps C 地图 ,in, C 地图 = 1 / (△ t 更新 + E 匹配 ),△ t 更新 Update time difference for map data, E 匹配 is the position matching error;

[0063] right D 定位 、 D 雷达 、 D 视觉 and D 地图 Assign dynamic weights respectively W 定位 、 W 雷达 、 W 视觉 and W 地图 , the weight calculation formula is:

[0064] W j = C j / (Σ C j )

[0065] in, j ∈{positioning, radar, vision, map};C j is the confidence index of each sensor, C j include C 雷达 、 C 视觉 、 C 定位 、 C 地图 ;

[0066] The relative distance after fusion is calculated using the weighted fusion formula:

[0067] D 融合 = W 定位 × D 定位 + W 雷达 × D 雷达 + W 视觉 × D 视觉 + W 地图 × D 地图 .

[0068] The present invention has at least the following beneficial effects:

[0069] The present invention calculates the collision time in real time t 碰撞 Emergency avoidance trigger time t 触发 , driving background targets away from the collision direction before a collision occurs, avoiding structural damage caused by direct collision, and extending the service life of high-value targets (such as dynamic simulation dummies and high-precision vehicle models). It is especially suitable for scenarios that require repeated tests.

[0070] The present invention is based on the collision risk coefficient R Dynamically adjust the power of mechanical actuators (30%, 60%, maximum power), reduce energy consumption in low-risk scenarios, and respond quickly to high-risk scenarios. This ensures safety while reducing unnecessary actuator losses and balancing protection effectiveness with equipment life.

[0071] The present invention integrates GPS, laser radar, visual sensor and terrain data (slope, ground flatness), and corrects the data through data fusion algorithm and formula (such as D 修正 = D 融合 / cosθ), eliminate single sensor errors and terrain influences, improve the accuracy of relative distance and collision time calculation, and prevent misjudgment or missed judgment.

[0072] The present invention monitors the actual deceleration in real time a 实际 And with the design value a 测试 Compare and automatically adjust collision time t 新 or t 调整 , adapt to the actual performance of the braking system, ensure that the trigger time matches the vehicle's dynamic performance, and avoid avoidance failure due to braking deviation.

[0073] The present invention can avoid the need for repair or replacement of the target object due to collision damage, achieve the continuity of the test process, and is particularly suitable for high-frequency and long-cycle test scenarios, significantly improving test efficiency.

[0074] The present invention dynamically adjusts the reference distance according to the test scenario (urban roads, highways, extreme working conditions) D 参考 , safe distance D 安全 and response time t 响应 , compatible with different vehicle models and complex environments (such as slopes and slippery roads), ensuring reliable operation under non-ideal conditions.

[0075] The present invention targets extreme scenarios involving short distances and high speeds (such as pedestrians crossing the road and high-speed rear-end collisions). By planning the shortest path and using maximum power, the vehicle can avoid the problem in a very short time, thus meeting the safety requirements of high-risk scenarios.

[0076] The complete closed loop of "real-time data acquisition-collision risk calculation-active control execution" in this invention realizes automation from risk identification to action execution through algorithm optimization and hardware collaboration, providing an intelligent protection solution for autonomous driving collision tests.

[0077] The present invention supports integration with vehicle ECUs, high-precision maps, and multiple types of sensors, and can be flexibly adapted to different test platforms, providing a universal framework for the sustainable development of future autonomous driving test technologies.

[0078] Through core advantages such as active protection, precise calculation, cost optimization and scenario adaptation, this invention effectively solves the pain point of equipment loss in traditional collision tests. It combines technological innovation, engineering practicality and economic rationality, and provides an efficient, safe and sustainable solution for the field of autonomous driving testing.

[0079] Other advantages, objectives and features of the present invention will be reflected in part from the following description and will be understood by those skilled in the art through study and practice of the present invention. DETAILED DESCRIPTION

[0080] The present invention is further described in detail below with reference to the embodiments so that those skilled in the art can implement the invention with reference to the description.

[0081] The present invention provides a method for reducing wear and tear of autonomous vehicle collision test equipment, comprising the following steps:

[0082] Obtaining pre-set test vehicle parameters, including the maximum deceleration of the automatic emergency braking system a max , test vehicle speed v 试验 and communication system delay time t 延迟 ;

[0083] When the emergency braking system of the test vehicle is triggered, the t 触发 = v 试验 / a max + t 延迟 Calculate the emergency avoidance trigger time t 触发 ;

[0084] After collecting the position data of the test vehicle and the background target in real time, calculate the real-time relative distance D , and by the formula t 碰撞 = D / v 试验 Calculating collision time t 碰撞 ;

[0085] when t 碰撞 ≤ t 触发 When the collision occurs, the stationary background target is driven by a mechanical actuator to move along the track in the direction away from the collision.

[0086] When obtaining pre-set test vehicle parameters, the test vehicle speed can be set between 8.33 and 16.67 m / s, the maximum deceleration of the automatic emergency braking system can be set between 3 and 5 m / s², and the communication system delay can be set between 0.1 and 0.5 seconds. These parameters can be determined from the vehicle design manual or historical test data. The communication system delay monitoring device used can be a commercially available wireless signal delay tester, installed on the test vehicle and the background target platform.

[0087] When the emergency braking system of the test vehicle is triggered, the calculation module built into the vehicle's central processing unit uses the formula t 触发 = v 试验 / a max + t 延迟 Calculate the emergency avoidance trigger time. v 试验 The maximum deceleration of the automatic emergency braking system is obtained in real time from the vehicle dashboard a max The default value for the vehicle is the communication system delay time. t 延迟 Real-time feedback from real-time monitoring equipment.

[0088] When collecting the position data of the test vehicle and the background target in real time, a centimeter-level precision GPS positioning device can be used, installed on the top of the vehicle and the center of the target respectively. The real-time relative distance is calculated by analyzing the GPS coordinates. D , and using the formula t 碰撞 = D / v 试验 Calculate the collision time. t 碰撞 ≤ t 触发 When the collision occurs, the computing module sends a trigger signal to the background target, starts its mechanical actuator, and drives the target along the preset track away from the collision direction.

[0089] The background target is stationary during the test.

[0090] Before testing, dynamic parameter adjustments are performed based on relevant parameters such as the vehicle's designed maximum deceleration, test vehicle speed, and communication system delay time.

[0091] Emergency avoidance module triggering time = test vehicle speed / automatic emergency braking system maximum deceleration + communication system delay time;

[0092] In the test collision experiment, when the emergency braking system of the test vehicle is triggered, the calculation module calculates the GPS information of the test vehicle and the background target (calculate the relative distance between the test vehicle and the background target, and calculate the relative distance in real time). t 碰撞 The relative relationship with the triggering time of the emergency avoidance module is calculated in real time when the relative distance t 碰撞 The calculation module triggers the emergency avoidance module of the background target object when the pre-set triggering time of the emergency avoidance module is reached, so as to move the background target object away from the collision direction, thereby reducing possible damage to the background target object.

[0093] In another embodiment, the method for reducing wear and tear of autonomous vehicle collision test equipment includes the following steps:

[0094] Use a GPS positioning device with centimeter-level positioning capability and built-in acceleration sensor and gyroscope to obtain GPS information and acceleration data of the test vehicle and background target. The GPS positioning device can be installed at the center of gravity of the vehicle and target; set up communication system delay monitoring equipment on the test vehicle and background target platform respectively. t 延迟 The real-time delay is the sum of the delay time measured by the vehicle-side communication system delay monitoring device and the delay time measured by the target-side communication system delay monitoring device. The real-time delay time is usually obtained by the system through a real-time measurement mechanism, for example: 1. Round-trip time measurement: By sending a specific test signal and recording the time difference between the signal being sent and received, the current delay is directly calculated. 2. System built-in monitoring module: Deploy dedicated monitoring nodes or algorithms in the communication link to collect and feedback current delay data in real time. 3. Protocol layer feedback: Some communication protocols (such as TCP and Real-time Transport Protocol RTP) have built-in delay statistics functions, which report delay information in real time through protocol interaction.

[0095] These real-time measurement results can be directly used for system control (e.g., adjusting control strategies, compensating for delay effects), ensuring that real-time requirements are met even when delays vary.

[0096] When obtaining the pre-set test vehicle parameters, the maximum deceleration of the test vehicle is also obtained. a 测试 ; a 测试 It is the maximum deceleration value that the vehicle can withstand during braking, determined during the vehicle design phase by comprehensively considering factors such as body structure, braking system reliability, tire grip, etc. It can be obtained through the vehicle braking system technical documentation and used as a preset parameter in the design phase.

[0097] At consecutive time points t 1 and t 2 ( t 1 and t 2 From the start of the test t 0 = 0s, the time interval can be set to 0.1s) Record the GPS coordinates of the test vehicle and background targets, and t 1. t Calculate the relative displacement △ at the coordinates of moment 2 s 定位 ;

[0098] By formula v 相对 = △ s 定位 / ( t 1- t 2) Calculate relative speed based on GPS information v 相对 ;

[0099] The calculation of relative velocity can help determine the relative motion state between the vehicle and the target object, providing an important basis for subsequent trigger time calculation and collision risk assessment.

[0100] Based on real-time relative distance D and v 相对 , combined with a 测试 , through the uniformly accelerated linear motion displacement formula D = v 相对 t - 1 / 2 a 测试 t 2 , recalculate the collision time and get the new collision time t 新 .

[0101] In another embodiment, in the method for reducing the loss of autonomous vehicle collision test equipment, the actual deceleration is obtained by the acceleration sensor built into the GPS positioning device. a 实际 , and compare it with a 测试 For comparison:

[0102] like a 实际 = a 测试 , the collision time is t 新 ;

[0103] like a 实际 < a 测试 , combined with real-time relative distance D and v 相对 ,Will a 实际 Resubstitute the displacement formula of uniformly accelerated linear motion into D = v 相对 t - 1 / 2 a 实际 t 2 , recalculate the collision time and get the adjusted collision time t 调整 ;

[0104] When the actual deceleration is less than the designed maximum deceleration, it means that the vehicle's braking capacity still has a certain margin. The collision time can be recalculated based on the actual deceleration to further optimize the avoidance strategy.

[0105] like a 实际 > a 测试 , the system automatically triggers the sensor calibration program and performs a calibration check on the sensor data. If a 实际 > a 测试 , analyze whether there is a system abnormality. If there is an abnormality, issue an alarm and stop the test. If there is no abnormality, combine the real-time relative distance D and relative speed v 相对 ,Will a 实际 Resubstitute the displacement formula of uniformly accelerated linear motion into D = v 相对 t - 1 / 2 a 实际 t 2 , recalculate the collision time and get the adjusted collision time t 调整 When the actual deceleration is greater than the designed maximum deceleration, there may be a sensor failure or system abnormality, and calibration and inspection are required to ensure the safety and reliability of the test.

[0106] In another embodiment, the method for reducing wear and tear of autonomous vehicle collision test equipment further includes the following steps:

[0107] The test vehicle is equipped with a lidar and multiple vision sensors, while a lidar is installed on the background target. A slope sensor and a laser roughness meter are installed on the test site. The lidars on the test vehicle and background target measure the distance to each other, while the vision sensor captures images of the surrounding environment. The slope sensor obtains real-time slope information of the test site, while the laser roughness meter measures the ground flatness, generating high-precision map data. The lidars can be commercial 16- or 32-pixel models and installed on the vehicle's front bumper and the sides of the target. The vision sensors can be 1080p resolution industrial cameras and mounted on both sides of the vehicle's windshield. The purpose of this multi-sensor layout is to obtain test-related data from multiple angles, improving data accuracy and reliability. Different sensor types provide complementary information. For example, a GPS device provides vehicle and target location information, the lidar accurately measures distance, the vision sensor captures images of the surrounding environment, and the slope sensor and laser roughness meter provide terrain information. This data is used to subsequently calculate relative distance and velocity and optimize trigger timing.

[0108] Use GPS positioning device information to calculate the relative distance between the test vehicle and background targets D 定位 ;GPS positioning equipment can provide accurate location information of vehicles and targets, and the relative distance can be obtained by calculating the position difference between the two.

[0109] Process and analyze the laser radar measurement data to obtain the relative distance based on the laser radar D 雷达 ; LiDAR calculates distance by emitting laser beams and measuring the time it takes for the reflected light, and is characterized by high precision.

[0110] Use computer vision technology to process the images collected by the visual sensor and obtain the relative distance based on the visual sensor D 视觉 ; Computer vision technology can estimate distance by analyzing the features and proportional relationships of objects in images.

[0111] Match the position information of the test vehicle and background targets with the high-precision map to obtain the relative distance based on the high-precision map D 地图 High-precision maps can provide detailed geographic information. By matching the positions of vehicles and objects with the information on the map, more accurate relative distances can be obtained.

[0112] Use data fusion algorithms, such as weighted average or Kalman filter, to D 定位 、 D 雷达、 D 视觉 and D 地图 Fusion, get the relative distance after fusion D 融合 ,Data fusion can integrate data from different sensors to improve the accuracy and reliability of relative distance calculation. ,According to the slope angle obtained by the slope sensor i , 0°≤ i < 15°, if the vehicle and the target are on the same slope and the slope is a straight line, the formula D 修正 = D 融合 / cosθ right D 融合 Make corrections to get the slope-corrected distance D 修正 If the vehicle and the target are not on the same straight slope, skip the correction and directly use D 融合 As D 修正 Taking the influence of slope into account can more accurately calculate the actual distance between the vehicle and the target object, avoiding distance calculation errors caused by slope.

[0113] The laser roughness meter divides the ground into multiple small areas, such as 1m×1m, and measures the height of each small area. h i and length l i , i = 1, 2, …, n , i Indicates the number of regions and calculates the actual distance increase of each small region , accumulate the actual distance increase of all small areas , and finally obtain a more accurate real-time relative distance D = D 修正 + △ L .

[0114] Considering the influence of ground flatness can further improve the accuracy of relative distance calculation and ensure the reliability of subsequent calculations.

[0115] In another embodiment, the method for reducing wear and tear of autonomous vehicle collision test equipment further includes:

[0116] With the help of the high-precision clock module inside the device that is synchronized with the vehicle's electronic control unit (ECU), the device can continuously obtain real-time data from the start of the test at a set frequency. t0 = Current time, calculated from 0s, is compared with the time the emergency avoidance module is triggered. Real-time time monitoring ensures that the emergency avoidance module is triggered at the appropriate time, avoiding collisions caused by timing errors.

[0117] The built-in acceleration sensor of the GPS positioning device provides real-time feedback on the changes in vehicle deceleration during braking. When the emergency braking system is activated, the vehicle's central processing unit (CPU) tracks the deceleration changes and determines whether it has reached the preset maximum deceleration of the automatic emergency braking system. a max The GPS positioning device uses built-in multi-sensor fusion technology to perform redundant verification of acceleration data, eliminating outliers and averaging the data. Accurately monitoring the braking system ensures that the vehicle brakes at the expected deceleration rate during braking, improving the accuracy and safety of the test.

[0118] When the test vehicle's emergency braking system is triggered and the maximum deceleration of the automatic emergency braking system is reached a max After that, based on the maximum deceleration of the automatic emergency braking system a max and real-time relative speed v 相对 , through the kinematic formula s 最短 = v 2 相对 / (2 a max ) Calculate the theoretical shortest braking distance s 最短 ; s 最短 The vehicle is braking at its maximum capacity (i.e. a max The shortest stopping distance achievable during deceleration is used to determine whether a collision would occur even with optimal braking.

[0119] If the remaining real-time relative distance in the braking phase D ≤ s 最短 , it is determined that the collision cannot be avoided by braking alone;

[0120] If and only if the following conditions are simultaneously met, the computing module sends a trigger signal to the background target carrying system via the communication link. After receiving the trigger signal, the background target carrying system activates the mechanical actuator to drive the background target away from the collision direction:

[0121] 1) From the start of the test t 0 = Current time starting from 0s t satisfyt 制动 ≤ t ≤ t 制动 + Collision time, where t 制动 The moment when the emergency braking system is triggered;

[0122] 2) The test vehicle's emergency braking system has been triggered and the deceleration has reached the maximum deceleration of the automatic emergency braking system a max ;

[0123] 3) The collision time is less than or equal to the trigger time;

[0124] like a 实际 = a 测试 , the collision time is t 新 ;like a 实际 ≠ a 测试 , the collision time is t 调整 The efficient triggering of emergency avoidance can promptly activate the avoidance mechanism of background targets when a collision is about to occur, reducing the possibility of collision and equipment loss.

[0125] In another embodiment, in the method for reducing the loss of autonomous vehicle collision test equipment, after the background target carrying system receives the trigger signal, it calculates the collision risk coefficient. R = D / D 参考 × v 相对 Determine the movement method of the background target, where R The dimension is m / s, the collision risk coefficient R The ratio of the relative distance to the reference distance, combined with the relative speed, comprehensively quantifies the target's required avoidance speed. A larger value indicates a higher force is required to move the target to avoid collision. D 参考 The reference distance is pre-set based on the performance of the test vehicle and the background target object; the method for determining the movement of the background target object based on the collision risk coefficient is:

[0126] like R < R 低 ( R 低Determined through statistical analysis of historical collision data), the mechanical actuator drives the background target at 30% of its maximum power. In low-risk situations, using a smaller power to drive the background target can reduce energy consumption and equipment wear. L 1= k 1× ( D-D 安全 ), t 移动 < t 碰撞 , t 移动 = L 1 / v 驱动 ;in k 1The value range is 1.1-1.3, t 移动 is the moving time, v 驱动 is the actuator driving speed, D 安全 is the safety distance threshold, D ≤ D 安全 ;and k 1 According to the relative speed v 相对 and relative distance D Dynamic Selection:

[0127] when v 相对 ≤ 5m / s, and D > 10m, k 1= 1.1;

[0128] when v 相对 ≤ 5m / s, and 5m < D ≤ 10m, k 1= 1.2;

[0129] when v 相对 ≤ 5m / s, and D ≤ 5m, k 1= 1.3;

[0130] like R 低 ≤ R < R 高 ( R 高The mechanical actuator drives the background target at 60% of its maximum power (determined by statistical analysis of historical collision data). In medium-risk situations, appropriately increasing the power and moving distance can improve the avoidance effect. Moving distance L 2= k 2× ( D-D 安全 ), t 移动 < t 碰撞 , t 移动 = L 2 / v 驱动 ;in k 2The value range is 1.3-1.5; and k 2 According to the relative speed v 相对 and relative distance D Dynamic Selection:

[0131] When 5m / s < v 相对 ≤ 15m / s, and D > 8m, k 2= ​​1.3;

[0132] When 5m / s < v 相对 ≤ 15m / s, and 5m < D ≤ 8m, k 2= ​​1.4;

[0133] When 5m / s < v 相对 ≤ 15m / s, and D ≤ 5m, k 2= ​​1.5;

[0134] If the collision risk factor R ≥ R 高 ,regardless v 相对 If the speed is greater than 15m / s, the mechanical actuator will immediately drive the background target with maximum power and move it to the safe area closest to the current position along the shortest straight line path. The safe area is pre-marked in the test site, for example, a circular area with a radius of 5m is marked with reflective road signs. The moving distance L 3= L 初始 + L 缓冲 , t 移动 < t 碰撞, t 移动 = L 3 / v 驱动 , v 驱动 is the actuator driving speed; where, L 初始 is the straight-line distance from the current position to the center of the safe area, L 缓冲 A buffer distance of 5-10m is provided. In high-risk situations, moving background objects with maximum power and the shortest path can minimize the possibility of collision.

[0135] In another embodiment, in the method for reducing the loss of autonomous driving vehicle collision test equipment, R 低 The value range is 1.2-2.5; R 高 The value range is 2.5-4.0; D 参考 = k × s 最短 ; k、D 参考 Dynamic matching according to the following rules based on the test scenario:

[0136] Urban road test: k = 1.5-2.0, D 参考 = 15-25m;

[0137] Highway test: k = 2.0-3.0, D 参考 ≥ 100m;

[0138] Extreme working condition testing: k = 2.5-3.5, D 参考 = 5-10m

[0139] D 安全 The value range is 5.56-50m and meets the D ≤ D 安全 ≤ D 参考 ,and D 安全 = max(2 × L 车辆 , 1.2 × s 最短 , v相对 × t 响应 ). L 车辆 To test the full length of the vehicle, t 响应 The total time from when the system detects a collision risk to when the mechanical actuator starts to drive the background target to move, including: sensor data processing time t 数据处理 , calculation module decision time t 计算 、 t 延迟 , Mechanical actuator start time t 执行 ;

[0140] Urban road test: t 响应 = 0.3-0.5s;

[0141] Highway test: t 响应 = 0.2-0.3s;

[0142] Extreme working condition testing: t 响应 = 0.1-0.2s.

[0143] v 相对 The unit is m / s; t 响应 The unit is s; L 车辆 、 s 最短 、 D 安全 All are in meters. In this application, the speed unit is m / s, the time unit is s, and the length unit is meter.

[0144] Extreme operating conditions typically refer to highly dynamic, short-distance, high-collision-risk test scenarios, where a target object suddenly cuts into the lane (such as a pedestrian crossing or a vehicle braking suddenly), the test vehicle approaches a stationary target object at high speed (such as a broken-down vehicle on a highway), and emergency avoidance is required in complex terrain (such as ramps or slippery roads).

[0145] Core requirement: Collision prediction and avoidance actions must be completed in a very short time, otherwise the probability of avoidance failure increases sharply.

[0146] Response time t 响应 It refers to the total time required from the system detecting the collision risk to the mechanical actuator starting to drive the background target to move. It includes the following stages:

[0147] 1. Sensor data processing time t 数据处理 :

[0148] The time it takes for GPS, lidar, visual sensors, etc. to collect and fuse data (typical value: 50-100ms).

[0149] 2. Calculation module decision time t 计算 :

[0150] Calculating collision time t 碰撞 , risk factor R time (typical value: 20-50ms).

[0151] 3. Communication system delay time t 延迟 :

[0152] The time from when the computing module sends the trigger signal to when the background target carrying system receives the signal.

[0153] 4. Mechanical actuator start-up time t 执行 :

[0154] The time it takes for the actuator to start moving after receiving a signal (typical value: 100-200ms).

[0155] D 安全 = max(2 × L 车辆 , 1.2 × s 最短 , v 相对 × t 响应 ), take the maximum value among the three results.

[0156] Urban road test:

[0157] typical v 相对 ≤ 5m / s, t 响应 ≤ 0.5s, the safety distance is mainly composed of 2 × L 车辆 or 1.2 × s 最短 Decide.

[0158] Highway test:

[0159] high v 相对 (such as 30m / s) and shortt 响应 (such as 0.2s), v 相对 × t 响应 = 6m, possibly less than 2 × L 车辆 .

[0160] Extreme working condition testing

[0161] like v 相对 =40m / s, t 响应 = 0.1s, then v 相对 × t 响应 = 4m, the static parameters are still dominant.

[0162] In another embodiment, in the method for reducing wear and tear of autonomous vehicle collision test equipment, the data fusion algorithm adopts a dynamic weight adjustment mechanism, specifically comprising the following steps:

[0163] Real-time evaluation of confidence indicators of each sensor data, including:

[0164] Calculating confidence based on lidar measurement noise level C 雷达 ,in, C 雷达 = 1 / ( s 雷达 2 + e ), s 雷达 is the standard deviation of the current frame data of the lidar, e To prevent the denominator from being zero, a very small constant;

[0165] Confidence calculation based on image clarity and feature matching of visual sensors C 视觉 ,in, C 视觉 = S 视觉 × M 匹配 , S 视觉 Rate the image sharpness, M 匹配 The accuracy of target feature point matching;

[0166] Calculate confidence based on the number of satellites and signal strength of GPS positioning devices C 定位 ,in,C 定位 = N 卫星 × I 信号 , N 卫星 is the number of visible satellites, I 信号 is the normalized value of signal intensity;

[0167] Confidence calculation based on update timeliness and matching error of high-precision maps C 地图 ,in, C 地图 = 1 / (△ t 更新 + E 匹配 ),△ t 更新 Update time difference for map data, E 匹配 is the position matching error;

[0168] right D 定位 、 D 雷达 、 D 视觉 and D 地图 Assign dynamic weights respectively W 定位 、 W 雷达 、 W 视觉 and W 地图 , the weight calculation formula is:

[0169] W j = C j / (Σ C j )

[0170] in, j ∈{positioning, radar, vision, map}; j is the index variable of sensor type, C j is the confidence index of each sensor, C j include C 雷达 、 C 视觉 、 C 定位 、 C地图 ;Σ C j is the sum of all sensor confidences;

[0171] The relative distance after fusion is calculated using the weighted fusion formula:

[0172] D 融合 = W 定位 × D 定位 + W 雷达 × D 雷达 + W 视觉 × D 视觉 + W 地图 × D 地图 .

[0173] Confidence can be calculated based on the lidar measurement noise level C 雷达 , where the standard deviation s 雷达 The range is 0.01m to 0.1m, with a minimum constant e Set to 1×10 -6 Image sharpness rating of vision sensors S 视觉 The value range is 0.8-1.0, the feature point matching accuracy M 匹配 The number of visible satellites for GPS positioning equipment is 0.7-0.95. N 卫星 Requires ≥ 4, signal strength normalized value I 信 ≥ 0.7. High-precision map update time difference △ t 更新 ≤ 5s, position matching error E 匹配 ≤ 0.5m. The LiDAR can be installed in the center of the test vehicle's front bumper, the visual sensors can be placed on both sides of the windshield, the GPS module can be fixed in the center of the roof, and high-precision map data can be stored in the onboard computing unit. During operation, the LiDAR collects point cloud data in real time and calculates the standard deviation, while the visual sensors use image processing algorithms to evaluate sharpness and matching.

[0174] The dynamic weight calculation formula is: W j = C j / (ΣC j ),in C j is the confidence level of each sensor. For example, if C 雷达 =0.4, C 视觉 = 0.3, C 定位 = 0.2, C 地图 = 0.1, then the weights are 0.4, 0.3, 0.2, and 0.1 respectively. If the confidence of a sensor is lower than the threshold for three consecutive frames C 阈值 = 0.2, it can be determined to be invalid and the compensation mechanism can be triggered. The weight calculation module can be integrated into the vehicle computing unit, and the real-time update frequency is 100ms. During operation, the system dynamically adjusts the weight according to the sensor status, for example, reducing the weight when the GPS signal is lost. W 定位 ,promote W 雷达 and W 视觉 .

[0175] The weighted fusion formula is: D 融合 = W 定位 × D 定位 + W 雷达 × D 雷达 + W 视觉 × D 视觉 + W 地图 × D 地图 .For example, D 定位 =10.0m, D 雷达 = 9.8m, D 视觉 = 10.2m, D 地图 = 10.1m, and the weights are 0.2, 0.5, 0.2, and 0.1 respectively. D 融合 = 9.89m. The fused data can be further corrected using the slope correction formula D 修正 = D 融合 / cosθ (Slope angle iThe calculation module can use an embedded processor that supports parallel computing, with a data output frequency of 10Hz. During operation, the fusion results are transmitted in real time to the avoidance decision module to trigger the action of the mechanical actuator.

[0176] This solution, through dynamic weight allocation and multi-sensor data fusion, effectively suppresses measurement deviations caused by single-sensor noise or environmental interference (such as rain, fog, and strong light), improving the accuracy of relative distance calculations. Weight adjustments can maintain reliable output even when some sensors fail, reducing false or missed triggers caused by data errors and enhancing the stability and safety of the test process.

[0177] Based on the existing data fusion, this solution innovatively introduces a dynamic weight adjustment mechanism. By quantifying the confidence of each sensor data in real time (such as lidar noise, visual image quality, GPS signal strength, map timeliness), the fusion weight is dynamically allocated. Compared with traditional fixed weight or simple filtering methods, this technology can adaptively suppress noise interference and compensate for environmental mutations (such as GPS signal loss and visual occlusion), significantly improving fusion accuracy. Especially when there is a conflict in multi-sensor data (such as a sudden increase in lidar noise in rainy and foggy days), it can automatically reduce the confidence of low-confidence sensors (such as C 雷达 ) to avoid error accumulation, solve the fusion deviation problem caused by single sensor failure in complex scenarios, and further enhance the system robustness and adaptability.

[0178] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the description and implementation methods. They can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and embodiments shown and described herein.

Claims

1. A method for reducing wear and tear of autonomous vehicle collision test equipment, characterized in that: The following steps are involved: Obtain pre-set test vehicle parameters, including the maximum deceleration of the automatic emergency braking system a max , test vehicle speed v 试验 and communication system delay time t 延迟 ; When the emergency braking system of the test vehicle is triggered, the t 触发 = v 试验 / a max + t 延迟 Calculate the emergency avoidance trigger time t 触发 ; After collecting the position data of the test vehicle and the background target in real time, calculate the real-time relative distance D , and by the formula t 碰撞 = D / v 试验 Calculating collision time t 碰撞 ; when t 碰撞 ≤ t 触发 When the collision occurs, the stationary background target is driven to move away from the collision direction by the mechanical actuator.

2. The method for reducing wear and tear of autonomous vehicle collision test equipment according to claim 1, wherein: The following steps are also included: Use GPS positioning equipment to obtain GPS information and acceleration data of the test vehicle and background target objects; set up communication system delay monitoring equipment on the test vehicle and background target object carrying platform respectively, t 延迟 The sum of the delay time measured by the vehicle-side communication system delay monitoring device and the delay time measured by the target-side communication system delay monitoring device; When obtaining the pre-set test vehicle parameters, obtain the maximum deceleration of the test vehicle a 测试 ; At consecutive time points t 1 and t 2. Record the GPS coordinates of the test vehicle and background objects. t 1. t 2 The coordinates at the moment calculate the relative displacement △ s 定位 ; By formula v 相对 = △ s 定位 / ( t 1 - t 2 ) Calculate relative speed based on GPS information v 相对 ; Based on real-time relative distance D and v 相对 , combined with a 测试 , through the uniformly accelerated linear motion displacement formula D = v 相对 t - 1 / 2 a 测试 t 2 , recalculate the collision time and get the new collision time t 新 .

3. The method for reducing wear and tear of autonomous vehicle collision test equipment according to claim 2, wherein: The actual deceleration is obtained through the built-in acceleration sensor of the GPS positioning device a 实际 , and compare it with a 测试 For comparison: like a 实际 = a 测试 , the collision time is t 新 ; like a 实际 < a 测试 , combined with real-time relative distance D and v 相对 ,Will a 实际 Resubstitute the displacement formula of uniformly accelerated linear motion into D = v 相对 t - 1 / 2 a 实际 t 2 , recalculate the collision time and get the adjusted collision time t 调整 ; like a 实际 > a 测试 , perform calibration check on the sensor data. If a 实际 > a 测试 , analyze whether there is a system abnormality. If there is an abnormality, issue an alarm and stop the test. If there is no abnormality, combine the real-time relative distance D and relative speed v 相对 ,Will a 实际 Resubstitute the displacement formula of uniformly accelerated linear motion into D = v 相对 t - 1 / 2 a 实际 t 2 , recalculate the collision time and get the adjusted collision time t 调整 .

4. The method for reducing wear and tear of autonomous vehicle collision test equipment according to claim 2, wherein: The following steps are also included: A laser radar and multiple visual sensors are installed on the test vehicle, and a laser radar is installed on the background target. A slope sensor and a laser roughness meter are set up on the test site. The laser radars on the test vehicle and the background target measure the distance to each other, and the visual sensor collects images of the surrounding environment. The slope sensor obtains real-time slope information of the test site, and the laser roughness meter measures the flatness of the ground to obtain high-precision map data. Use GPS positioning device information to calculate the relative distance between the test vehicle and background targets D 定位 ; Process and analyze the lidar measurement data to obtain the relative distance based on the lidar D 雷达 ; Process the image collected by the visual sensor to obtain the relative distance based on the visual sensor D 视觉 ; Match the position information of the test vehicle and background targets with the high-precision map to obtain the relative distance based on the high-precision map D 地图 ; Using data fusion algorithm, D 定位 、 D 雷达 、 D 视觉 and D 地图 Fusion, get the relative distance after fusion D 融合 , based on the slope angle obtained by the slope sensor θ , 0° ≤ θ < 15°, if the vehicle and the target are on the same slope and the slope is a straight line, the formula D 修正 = D 融合 / cosθ right D 融合 Make corrections to get the slope-corrected distance D 修正 If the vehicle and the target are not on the same straight slope, skip the correction and directly use D 融合 As D 修正 ; The laser roughness meter divides the ground into several small areas and measures the height of each small area. h i and length l i , i =1, 2, ..., n , i Indicates the number of regions and calculates the actual distance increase of each small region , accumulate the actual distance increase of all small areas , and finally obtain a more accurate real-time relative distance D = D 修正 + △ L .

5. The method for reducing wear and tear of autonomous vehicle collision test equipment according to claim 3, wherein: Also includes: When the test vehicle's emergency braking system is triggered and the maximum deceleration of the automatic emergency braking system is reached a max After that, based on the maximum deceleration of the automatic emergency braking system a max and real-time relative speed v 相对 , through the kinematic formula s 最短 = v 2 相对 / (2 a max ) Calculate the theoretical shortest braking distance s 最短 ; If the remaining real-time relative distance in the braking phase D ≤ s 最短 , it is determined that the collision cannot be avoided by braking alone; If and only if the following conditions are simultaneously met, the computing module sends a trigger signal to the background target carrying system via the communication link. After receiving the trigger signal, the background target carrying system activates the mechanical actuator to drive the background target away from the collision direction: 1) From the start of the test t 0 = Current time starting from 0s t satisfy t 制动 ≤ t ≤ t 制动 + Collision time, where t 制动 The moment when the emergency braking system is triggered; 2) The test vehicle's emergency braking system has been triggered and the deceleration has reached the maximum deceleration of the automatic emergency braking system a max ; 3) The collision time is less than or equal to the trigger time; like a 实际 = a 测试 , the collision time is t 新 ;like a 实际 ≠ a 测试 , the collision time is t 调整 .

6. The method for reducing wear and tear of autonomous vehicle collision test equipment according to claim 5, wherein: After the background target carrying system receives the trigger signal, it calculates the collision risk coefficient R = D / D 参考 × v 相对 Determine the movement method of the background target, where R The dimension is m / s, D 参考 The reference distance is pre-set based on the performance of the test vehicle and the background target object; the method for determining the movement of the background target object based on the collision risk coefficient is: like R < R 低 , the mechanical actuator drives the background target with 30% of its maximum power, moving the distance L 1 = k 1 × ( DD 安全 ), t 移动 < t 碰撞 , t 移动 = L 1 / v 驱动 ;in k 1The value range is 1.1-1.3, t 移动 is the moving time, v 驱动 is the actuator driving speed, D 安全 is the safety distance threshold; and k 1 According to the relative speed v 相对 and relative distance D Dynamic Selection: when v 相对 ≤ 5m / s, and D > 10m, k 1 = 1.1; when v 相对 ≤ 5m / s, and 5m < D ≤ 10m, k 1 = 1.2; when v 相对 ≤ 5m / s, and D ≤ 5m, k 1 = 1.3; like R 低 ≤ R < R 高 , the mechanical actuator drives the background target with 60% of its maximum power, moving the distance L 2 = k 2 × ( D - D 安全 ), t 移动 < t 碰撞 , t 移动 = L 2 / v 驱动 ;in k 2The value range is 1.3-1.5; and k 2 According to the relative speed v 相对 and relative distance D Dynamic Selection: When 5m / s < v 相对 ≤ 15m / s, and D > 8m, k 2 = 1.3; When 5m / s < v 相对 ≤ 15m / s, and 5m < D When ≤8m, k 2 = 1.4; When 5m / s < v 相对 ≤ 15m / s, and D ≤ 5m, k 2 = 1.5; If the collision risk factor R ≥ R 高 ,regardless v 相对 If the speed is greater than 15m / s, the mechanical actuator will immediately drive the background target with maximum power and move it to the safe area closest to the current position along the shortest straight path. L 3 = L 初始 + L 缓冲 , t 移动 < t 碰撞 , t 移动 = L 3 / v 驱动 , v 驱动 is the actuator driving speed; where, L 初始 is the straight-line distance from the current position to the center of the safe area, L 缓冲 The buffer distance is 5-10m.

7. The method for reducing wear and tear of autonomous vehicle collision test equipment according to claim 6, wherein: R 低 The value range is 1.2-2.5; R 高 The value range is 2.5-4.0; D 参考 = k × s 最短 ; k、D 参考 Dynamic matching according to the following rules based on the test scenario: Urban road test: k = 1.5-2.0, D 参考 = 15-25m; Highway test: k = 2.0-3.0, D 参考 ≥ 100m; Extreme working condition testing: k = 2.5-3.5, D 参考 = 5-10m; D 安全 The value range is 5.56-50m and meets the D ≤ D 安全 ≤ D 参考 ,and D 安全 = max(2 × L 车辆 , 1.2 × s 最短 , v 相对 × t 响应 ), L 车辆 To test the full length of the vehicle, t 响应 The total time from when the system detects a collision risk to when the mechanical actuator starts to drive the background target to move, including: sensor data processing time t 数据处理 , calculation module decision time t 计算 、 t 延迟 , Mechanical actuator start time t 执行 ; Urban road test: t 响应 = 0.3-0.5s; Highway test: t 响应 = 0.2-0.3s; Extreme working condition testing: t 响应 = 0.1-0.2s; v 相对 The unit is m / s; t 响应 The unit is s; L 车辆 、 s 最短 、 D 安全 All units are in m.

8. The method for reducing wear and tear of autonomous vehicle collision test equipment according to claim 4, wherein: The data fusion algorithm adopts a dynamic weight adjustment mechanism, which specifically includes the following steps: Real-time evaluation of confidence indicators of each sensor data, including: Calculating confidence based on lidar measurement noise level C 雷达 ,in, C 雷达 = 1 / ( σ 雷达 2 + ε ), σ 雷达 is the standard deviation of the current frame data of the lidar, ε To prevent the denominator from being zero, a very small constant; Confidence calculation based on image clarity and feature matching of visual sensors C 视觉 ,in, C 视觉 = S 视觉 × M 匹配 , S 视觉 Rate the image sharpness, M 匹配 The accuracy of target feature point matching; Calculate confidence based on the number of satellites and signal strength of GPS positioning devices C 定位 ,in, C 定位 = N 卫星 × I 信号 , N 卫星 is the number of visible satellites, I 信号 is the normalized value of signal intensity; Confidence calculation based on update timeliness and matching error of high-precision maps C 地图 ,in, C 地图 = 1 / (△ t 更新 + E 匹配 ),△ t 更新 Update time difference for map data, E 匹配 is the position matching error; right D 定位 、 D 雷达 、 D 视觉 and D 地图 Assign dynamic weights respectively W 定位 、 W 雷达 、 W 视觉 and W 地图 , the weight calculation formula is: W j = C j / (S C j ) in, j ∈{positioning, radar, vision, map}; C j is the confidence index of each sensor, C j include C 雷达 、 C 视觉 、 C 定位 、 C 地图 ; The relative distance after fusion is calculated using the weighted fusion formula: D 融合 = W 定位 × D 定位 + W 雷达 × D 雷达 + W 视觉 × D 视觉 + W 地图 × D 地图 。