CN201812368U - Test setup for lane departure warning system - Google Patents

本实用新型涉及一种车道偏离报警系统测试装置，其特征在于，它包括：图像传感器，固定在车辆上方两侧，且平面与路面平行，用于采集路面图像；图像采集单元，将所述图像传感器采集的路面图像信息转化为数字信息；车载CAN单元，提供原车信息中的车速信息和待测试车道偏离报警系统提供的报警时刻信息；数据处理单元，根据所述图像采集单元获取的含有车道线的路面信息，结合所述车载CAN单元提供的车速和报警时刻信息，计算出世界坐标系下报警时刻的车身上一点到车道线的距离和离线速度。本实用新型成本低，而且测试出的评价结果真实程度高，适用于各种车道偏离报警系统的测试。

The utility model relates to a test device for a lane departure warning system, which is characterized in that it comprises: an image sensor, which is fixed on both sides above the vehicle, and whose plane is parallel to the road surface, for collecting road surface images; The road surface image information collected by the sensor is converted into digital information; the vehicle-mounted CAN unit provides the vehicle speed information in the original vehicle information and the alarm time information provided by the lane departure alarm system to be tested; the data processing unit obtains according to the image acquisition unit. The road surface information of the line, combined with the vehicle speed and alarm time information provided by the vehicle CAN unit, calculates the distance and offline speed from a point on the vehicle body to the lane line at the alarm time in the world coordinate system. The utility model has low cost, and the evaluation result obtained by the test has a high degree of authenticity, and is suitable for testing various lane departure alarm systems.

车道偏离报警系统的测试装置 Test setup for lane departure warning system

技术领域technical field

本实用新型涉及一种报警系统的测试装置，特别是关于一种基于图像处理的车道偏离报警系统的测试装置。The utility model relates to a test device for an alarm system, in particular to a test device for a lane departure alarm system based on image processing.

背景技术Background technique

车道偏离报警系统(LDWS)以基本交通法规为基础，其主要目标是帮助驾驶员保持车辆在公路以及类似的其它道路的车道内进行安全行驶。当车辆因驾驶员疏忽等原因偏离车道时，系统会自动发出警告以提醒驾驶员注意车辆安全。所以，车道偏离报警产品在使用之前，往往需要进行报警测试和性能评估，以检验产品是否达到合格的报警标准。对车道偏离报警产品进行测试和性能评估后，合格产品必须达到：当车辆发生偏离时，及时向驾驶员发出警报，即合格产品必须具备低漏报率，或者是尽可能少错误警报。同时，由于车道偏离报警系统是面向驾驶员的，所以还需要考虑中国驾驶员的特性。此外，由于中国的道路情况较为复杂，须予以高度重视，因此国外的产品本地化也需要测试与调整。Lane Departure Warning Systems (LDWS) are based on basic traffic laws, and its main goal is to help drivers keep vehicles safely within lanes of highways and similar other roads. When the vehicle deviates from the lane due to driver negligence or other reasons, the system will automatically issue a warning to remind the driver to pay attention to vehicle safety. Therefore, before using a lane departure warning product, an warning test and performance evaluation are often required to check whether the product meets the qualified warning standard. After testing and performance evaluation of lane departure warning products, qualified products must achieve: when the vehicle deviates, the driver should be alerted in time, that is, qualified products must have a low false alarm rate, or as few false alarms as possible. At the same time, since the lane departure warning system is driver-oriented, the characteristics of Chinese drivers also need to be considered. In addition, since China's road conditions are more complicated and must be given great attention, the localization of foreign products also needs to be tested and adjusted.

目前，对车道偏离报警系统的报警性能评价方式尚未形成统一的认识，各大研究机构和厂商都有自己的评价方式。有的倾向于实车测试，优点在于能够最真实地反映车道偏离报警系统的工况，驾驶员也能严肃对待，测试结果真实程度高，但耗费人力财力较大。有的使用驾驶模拟器，优点在于能够模拟实车实验时必须承担风险的危险情况，更能测试出系统的潜在能力，各种参数的获取较为容易，但平台设计工作复杂、仿真环境较难建立、搭建成本较高。At present, there is no unified understanding of the evaluation methods of the alarm performance of the lane departure warning system, and major research institutions and manufacturers have their own evaluation methods. Some prefer real vehicle testing. The advantage is that it can most truly reflect the working conditions of the lane departure warning system, and the driver can also take it seriously. The test results are highly authentic, but they consume a lot of manpower and financial resources. Some use driving simulators, which have the advantage of being able to simulate the dangerous situations in which risks must be borne during real vehicle experiments, and can better test the potential capabilities of the system. It is easier to obtain various parameters, but the platform design is complicated and the simulation environment is difficult to establish , The construction cost is higher.

发明内容Contents of the invention

针对上述问题，本实用新型的目的是提供一种成本低，而且测试出的评价结果真实程度高的车道偏离报警系统的测试装置。In view of the above problems, the purpose of this utility model is to provide a test device for a lane departure warning system with low cost and a high degree of authenticity of the test evaluation results.

为实现上述目的，本实用新型采取以下技术方案：一种车道偏离报警系统测试装置，其特征在于，它包括：图像传感器，固定在车辆上方两侧，且平面与路面平行，用于采集路面图像；图像采集单元，将所述图像传感器采集的路面图像信息转化为数字信息；车载CAN单元，提供原车信息中的车速信息和待测试车道偏离报警系统提供的报警时刻信息；数据处理单元，根据所述图像采集单元获取的含有车道线的路面信息，结合所述车载CAN单元提供的车速和报警时刻信息，计算出世界坐标系下报警时刻的车身上一点到车道线的距离和离线速度。In order to achieve the above purpose, the utility model adopts the following technical solutions: a lane departure warning system test device, which is characterized in that it includes: image sensors, fixed on both sides above the vehicle, and the plane is parallel to the road surface, used to collect road surface images The image acquisition unit converts the road surface image information collected by the image sensor into digital information; the vehicle-mounted CAN unit provides the vehicle speed information in the original vehicle information and the alarm time information provided by the lane departure warning system to be tested; the data processing unit, according to The road surface information containing lane lines acquired by the image acquisition unit, combined with the vehicle speed and alarm time information provided by the vehicle CAN unit, calculates the distance and offline speed from a point on the vehicle body to the lane line at the alarm time in the world coordinate system.

所述图像传感器通过支架固定在车辆两侧的前大灯上方。The image sensor is fixed above the headlights on both sides of the vehicle through brackets.

所述图像传感器上显示图像的边框线与车道线平行。The border line of the image displayed on the image sensor is parallel to the lane line.

本实用新型由于采取以上技术方案，其具有以下优点：1、本实用新型测试装置不仅成本低，而且还将获取的路面信息、报警时刻以及该时刻对应的车身上一点到车道线的距离、车速和离线速度进行获取并记录，通过结合车辆工况，与现有的ISO17361：2007(E)《智能运输系统车道偏离报警系统性能要求与检测方法》进行比较，对待测试车道偏离报警系统的报警性能进行分析和生成报告，同时还通过离线分析数据处理单元记录的图像信息，对车辆轨迹进行重现，对待测试车道偏离报警系统的报警性能进行分析和生成报告，最后再综合在线和离线分析生成的报告，对待测试车道偏离报警系统的可靠性和报警的准确性进行评价，因此测试出的评价结果真实程度高。2、本实用新型由于在实车测试之前还对数据处理单元的参考误差进行了计算，因此进一步提高了测试出的评价结果真实程度。3、本实用新型装置设置简单，易于操作。本实用新型适用于各种车道偏离报警系统的测试。Because the utility model adopts the above technical scheme, it has the following advantages: 1. The test device of the utility model is not only low in cost, but also can obtain road surface information, alarm time, and the distance from a point on the vehicle body corresponding to the moment to the lane line, and the speed of the vehicle. Acquisition and recording of the off-line speed, combined with the vehicle operating conditions, compared with the existing ISO17361: 2007 (E) "Intelligent Transportation System Lane Departure Alarm System Performance Requirements and Detection Methods", the alarm performance of the lane departure alarm system to be tested Analyze and generate reports. At the same time, it also reproduces the vehicle trajectory through offline analysis of the image information recorded by the data processing unit, analyzes and generates reports on the alarm performance of the lane departure alarm system to be tested, and finally integrates the online and offline analysis. The report evaluates the reliability of the lane departure warning system to be tested and the accuracy of the warning, so the evaluation results of the test have a high degree of authenticity. 2. Since the utility model also calculates the reference error of the data processing unit before the actual vehicle test, it further improves the authenticity of the evaluation result obtained from the test. 3. The device of the utility model is simple to set up and easy to operate. The utility model is suitable for testing various lane departure alarm systems.

附图说明Description of drawings

图1是本实用新型车道偏离报警系统测试装置的结构示意图Fig. 1 is the structural schematic diagram of the test device of the lane departure warning system of the present invention

图2是本实用新型车道偏离报警系统测试装置中图像传感器的安装位置示意图Fig. 2 is a schematic diagram of the installation position of the image sensor in the test device of the lane departure warning system of the present invention

图3是图像处理的流程图Figure 3 is a flow chart of image processing

图4是图像处理过程中获取数据处理单元的计算参考误差的流程图Fig. 4 is a flow chart of obtaining the calculation reference error of the data processing unit in the image processing process

图5是图像处理过程中实车测试的流程图Figure 5 is a flowchart of the real vehicle test in the image processing process

具体实施方式Detailed ways

下面结合附图和实施例对本实用新型进行详细的描述。Below in conjunction with accompanying drawing and embodiment the utility model is described in detail.

如图1所示，本实用新型测试装置包括两图像传感器1、2，一图像采集单元3，一数据处理单元4和一车载CAN单元5。其中，两图像传感器1、2采集路面图像，路面图像经图像采集单元3输入数据处理单元4，数据处理单元4根据含有车道线6的路面信息，结合车载CAN单元5采集到的原车信息中的车速信息V和待测试车道偏离报警系统提供的报警时刻信息T，经过计算处理得到世界坐标系下报警时刻车身上一点与车道线的距离和离线速度等信息。As shown in FIG. 1 , the test device of the present invention includes two image sensors 1 and 2 , an image acquisition unit 3 , a data processing unit 4 and a vehicle-mounted CAN unit 5 . Wherein, the two image sensors 1 and 2 collect road surface images, and the road surface images are input into the data processing unit 4 through the image collection unit 3, and the data processing unit 4 combines the original vehicle information collected by the vehicle-mounted CAN unit 5 according to the road surface information containing the lane line 6 The vehicle speed information V and the alarm time information T provided by the lane departure alarm system to be tested are calculated and processed to obtain information such as the distance between a point on the vehicle body and the lane line and the offline speed at the alarm time in the world coordinate system.

如图2所示，本实用新型测试装置中的图像传感器1、2通过支架7固定在车辆两侧的前大灯上方，且图像传感器1、2的平面与路面平行，用于采集含有车道线6的图像，支架7通过吸盘(图中未示出)固连在车身上。本实施例采用的是两图像传感器1、2，也可以根据实际需要设置更多的图像传感器。图像采集单元3将输入的图像转化成数字信息，其采用的是一图像采集卡。数据处理单元4对获取的含有车道线6的路面信息进行处理，得到报警时刻车身上一点与车道线的距离和离线速度等信息。As shown in Figure 2, the image sensors 1 and 2 in the test device of the present invention are fixed above the headlights on both sides of the vehicle through brackets 7, and the planes of the image sensors 1 and 2 are parallel to the road surface, and are used to collect images containing lane lines. 6, the bracket 7 is fixedly connected to the vehicle body through a suction cup (not shown). In this embodiment, two image sensors 1 and 2 are used, and more image sensors can also be provided according to actual needs. The image acquisition unit 3 converts the input image into digital information, which adopts an image acquisition card. The data processing unit 4 processes the acquired road surface information including the lane line 6 to obtain information such as the distance between a point on the vehicle body and the lane line and the off-line speed at the time of the alarm.

如图3所示，利用上述装置本实用新型测试方法包括以下步骤：As shown in Figure 3, utilize above-mentioned device the utility model test method to comprise the following steps:

1)如图1、图2所示，设置测试装置：在车身上牢靠地固定一支架7，通过支架7在车辆两侧的前大灯上方分别固定一图像传感器1、2，并将每一图像传感器1、2的平面设置为与路面平行，以便于获取路面图像。再将图像传感器1、2通过一图像采集单元3连接到一数据处理单元4，并将车载CAN单元5也与数据处理单元4连接。1) As shown in Figure 1 and Figure 2, set up the test device: securely fix a support 7 on the vehicle body, fix an image sensor 1 and 2 respectively above the headlights on both sides of the vehicle through the support 7, and place each The planes of the image sensors 1 and 2 are set parallel to the road surface, so as to obtain road surface images. Then the image sensors 1 and 2 are connected to a data processing unit 4 through an image acquisition unit 3 , and the vehicle-mounted CAN unit 5 is also connected to the data processing unit 4 .

2)调试测试装置：检查图像传感器1、2，图像采集单元3与数据处理单元4的连接是否正常，以及车载CAN单元5的通讯是否正常，当确认测试装置连接和通讯正常后，进入下一步。2) Debugging and testing device: Check whether the image sensors 1 and 2, the connection between the image acquisition unit 3 and the data processing unit 4 are normal, and whether the communication of the vehicle-mounted CAN unit 5 is normal. After confirming that the connection and communication of the test device are normal, proceed to the next step .

3)建立二维图像坐标系：将车辆平行于车道线停靠，将图像传感器1、2上显示图像的边框线调整至与车道线平行，由此建立一个二维的图像坐标系，也就是说，该图像坐标系是以图像传感器上显示图像的边框线作为两坐标轴方向。3) Establish a two-dimensional image coordinate system: park the vehicle parallel to the lane line, adjust the frame lines of the images displayed on the image sensors 1 and 2 to be parallel to the lane line, thereby establishing a two-dimensional image coordinate system, that is to say , the image coordinate system uses the border line of the image displayed on the image sensor as the direction of the two coordinate axes.

4)标定图像传感器的实际高度：打开数据处理单元4上的标定程序，在标定程序上标定图像传感器1、2在世界坐标系下的高度，即图像传感器1、2离地面的实际高度。4) Calibrate the actual height of the image sensor: open the calibration program on the data processing unit 4, and calibrate the height of the image sensors 1 and 2 in the world coordinate system on the calibration program, that is, the actual height of the image sensors 1 and 2 from the ground.

5)如图4所示，获取数据处理单元4的计算参考误差，获取方法如下：5) As shown in Figure 4, the calculation reference error of the data processing unit 4 is acquired, and the acquisition method is as follows:

①获取并记录图像：在车道线6附近放置一标尺，通过图像采集单元3，数据处理单元4获取含有标尺和车道线的路面信息。① Acquire and record the image: place a ruler near the lane line 6, and through the image acquisition unit 3, the data processing unit 4 acquires the road surface information including the scale and the lane line.

②图像预处理：通过数据处理单元4，对步骤①中获取的含有标尺和车道线6的路面信息进行边缘提取和二值化。在本实施例中，采用FIR(Finit Impulse Response Filter，有限冲击响应)对含有标尺和车道线6的路面信息进行滤波，并选择[-1，0，1]作为滤波系数，将标尺和车道线6的双边缘转化为单边缘，在此基础上再进行二值化。② Image preprocessing: through the data processing unit 4, edge extraction and binarization are performed on the road surface information including scales and lane lines 6 obtained in step ①. In this embodiment, FIR (Finit Impulse Response Filter, finite impact response) is used to filter the road surface information containing scale and lane line 6, and [-1, 0, 1] is selected as the filter coefficient, and the scale and lane line The double edge of 6 is converted into a single edge, and binarization is performed on this basis.

③车道线提取和参数拟合：通过数据处理单元4，利用Hough变换对步骤②中二值化后的边缘图像信息中的直线进行提取和参数拟合，得到在图像坐标系下标尺的直线方程和车道线6的直线方程。③ Lane line extraction and parameter fitting: through the data processing unit 4, use the Hough transform to extract and parameter fit the straight line in the edge image information after binarization in step ②, and obtain the straight line equation of the scale in the image coordinate system and the straight line equation of lane line 6.

④计算图像坐标系下标尺与车道线的距离：通过数据处理单元4，根据步骤③得出的标尺和车道线的直线方程，计算图像坐标系下标尺与车道线6之间的距离。④ Calculate the distance between the scale and the lane line in the image coordinate system: through the data processing unit 4, calculate the distance between the scale and the lane line 6 in the image coordinate system according to the linear equation of the scale and the lane line obtained in step ③.

⑤计算世界坐标系下标尺与车道线的距离：通过数据处理单元4，根据步骤④计算出的图像坐标系下标尺与车道线6之间的距离，并结合步骤4)中标定的图像传感器1、2的实际高度，计算出世界坐标系下标尺与车道线6之间的距离。5. Calculate the distance between the ruler and the lane line in the world coordinate system: through the data processing unit 4, the distance between the scale and the lane line 6 in the image coordinate system calculated according to step ④, combined with the image sensor 1 calibrated in step 4) , the actual height of 2, and calculate the distance between the ruler and the lane line 6 in the world coordinate system.

⑥计算数据处理单元的参考误差：通过数据处理单元6，将步骤⑤计算出的世界坐标系下标尺与车道线6之间的距离与实际距离进行比对，计算得到一参考误差。⑥ Calculate the reference error of the data processing unit: through the data processing unit 6, compare the distance between the lower scale in the world coordinate system and the lane line 6 calculated in step ⑤ with the actual distance, and calculate a reference error.

6)如图5所示，进行实车测试：对图像传感器1、2获取的路面信息、报警时刻以及该时刻对应的车身上一点到车道线6的距离、车速和离线速度进行获取并记录，其包括以下步骤：6) As shown in Figure 5, the actual vehicle test is carried out: the road surface information obtained by the image sensors 1 and 2, the alarm time, and the distance from a point on the vehicle body to the lane line 6 corresponding to the time, vehicle speed and offline speed are obtained and recorded, It includes the following steps:

①获取并记录图像：通过图像采集单元3，数据处理单元4获取路面信息。① Obtaining and recording images: through the image acquisition unit 3, the data processing unit 4 acquires road surface information.

②图像预处理：通过数据处理单元4，对含有车道线6的路面信息进行边缘提取和二值化，为检测车道线做准备。采用上述步骤5)中的FIR对含有车道线6的路面信息进行滤波，并选择[-1，0，1]作为滤波系数，将车道线6的双边缘转化为单边缘，在此基础上再进行二值化。② Image preprocessing: through the data processing unit 4, edge extraction and binarization are performed on the road surface information containing the lane line 6 to prepare for the detection of the lane line. Use the FIR in the above step 5) to filter the road surface information containing the lane line 6, and select [-1, 0, 1] as the filter coefficient to convert the double edge of the lane line 6 into a single edge, and then further Do binarization.

③车道线提取和参数拟合：通过数据处理单元4，利用Hough变换对步骤②中二值化后的边缘图像信息中的直线进行提取和参数拟合，得到在图像坐标系下车道线6的直线方程。③ Lane line extraction and parameter fitting: through the data processing unit 4, use the Hough transform to extract and parameter fit the straight line in the edge image information after binarization in step ②, and obtain the lane line 6 in the image coordinate system. straight line equation.

④计算车辆的偏航角：通过数据处理单元4，根据步骤③获取的图像坐标系下车道线6的直线方程，计算车道线6与该车辆中轴线之间的夹角，即为车辆的偏航角。④ Calculating the yaw angle of the vehicle: through the data processing unit 4, according to the straight line equation of the lane line 6 in the image coordinate system obtained in step ③, calculate the angle between the lane line 6 and the central axis of the vehicle, which is the yaw angle of the vehicle. flight angle.

⑤计算图像坐标系下车身上一点与车道线的距离：通过数据处理单元4，根据步骤③得出的车道线6的直线方程，计算图像坐标系下车身上一点与车道线6之间的距离。⑤ Calculate the distance between a point on the vehicle body and the lane line in the image coordinate system: through the data processing unit 4, calculate the distance between the point on the vehicle body and the lane line 6 in the image coordinate system according to the straight line equation of the lane line 6 obtained in step ③ .

⑥计算世界坐标系下车身上该点与车道线的距离：通过数据处理单元4，根据步骤③得出的图像坐标系下车身上该点与车道线6之间的距离，结合步骤4)中标定的图像传感器1、2的实际高度，计算世界坐标系下车身上该点与车道线6之间的距离。6. Calculate the distance between the point on the vehicle body and the lane line under the world coordinate system: through the data processing unit 4, the distance between the point on the vehicle body and the lane line 6 under the image coordinate system obtained according to step 3, combined with step 4) Calculate the actual height of the calibrated image sensors 1 and 2, and calculate the distance between the point on the vehicle body and the lane line 6 in the world coordinate system.

⑦读取原车信息和待测试车道偏离报警系统信息：通过车载CAN单元5，数据处理单元6读取原车信息中的车速V和测试车道偏离报警系统提供的报警时刻T。⑦Read the original vehicle information and the information of the lane departure warning system to be tested: through the vehicle CAN unit 5, the data processing unit 6 reads the vehicle speed V in the original vehicle information and the alarm time T provided by the test lane departure warning system.

⑧计算离线速度：通过数据处理单元4，根据步骤⑦获取的原车车速V和测试车道偏离报警系统提供的报警时刻信息T，结合步骤④计算得到的偏航角，将车速V乘以步骤④中的偏航角的正弦值，计算得到报警时刻T对应的离线速度，输出后返回步骤①。⑧Calculation of offline speed: Through the data processing unit 4, according to the original vehicle speed V obtained in step ⑦ and the alarm time information T provided by the test lane departure warning system, combined with the yaw angle calculated in step ④, multiply the vehicle speed V by step ④ The sine value of the yaw angle in is calculated to obtain the offline speed corresponding to the alarm time T, and returns to step ① after outputting.

7)在线分析：将步骤6)中获取的报警时刻以及该时刻对应的车身上一点到车道线的距离、车速和离线速度作为报警性能测试参量，并结合车辆工况，与现有的ISO17361：2007(E)《智能运输系统 车道偏离报警系统 性能要求与检测方法》进行比较，对待测试车道偏离报警系统的报警性能进行分析，并生成报告。7) On-line analysis: The alarm time obtained in step 6) and the distance from the corresponding point on the vehicle body to the lane line, vehicle speed and off-line speed are used as the alarm performance test parameters, combined with the vehicle operating conditions, and the existing ISO17361: 2007 (E) "Intelligent Transportation System Lane Departure Warning System Performance Requirements and Detection Methods" was compared, the warning performance of the lane departure warning system to be tested was analyzed, and a report was generated.

上述车辆工况包括车型、天气情况、线型和车道线质量，其中，车型分为乘用车和商用车，天气情况包括：阴天与雾天、黎明与黄昏、雨天。线型是依据中国《公路工程技术标准》，其包括：实线或者虚线、单线或者双线、白线或者黄线。车道线质量分为：车道线清晰可见、车道线较为模糊但肉眼可见、车道线很模糊肉眼基本不可见。本实施例中，对待测试车道偏离报警系统的报警性能进行评价的标准是：当待测试车道偏离报警系统误报率小于2％为优秀，大于2％而小于5％为良好，大于5％而小于10％为合格，大于10％为不合格；当待测试车道偏离报警系统错报率小于2％为优秀，大于2％而小于5％为良好，大于5％而小于10％为合格，大于10％为不合格。The above-mentioned vehicle operating conditions include vehicle types, weather conditions, line shapes and lane line quality. Among them, vehicle types are divided into passenger cars and commercial vehicles, and weather conditions include: cloudy and foggy days, dawn and dusk, and rainy days. The line type is based on China's "Technical Standards for Highway Engineering", which includes: solid or dashed lines, single or double lines, white or yellow lines. The quality of lane lines is divided into: lane lines are clearly visible, lane lines are relatively blurred but visible to the naked eye, and lane lines are very blurred and basically invisible to the naked eye. In this embodiment, the standard for evaluating the alarm performance of the lane departure warning system to be tested is: when the false alarm rate of the lane departure warning system to be tested is less than 2%, it is excellent; if it is greater than 2% but less than 5%, it is good; Less than 10% is qualified, greater than 10% is unqualified; when the false alarm rate of the lane departure warning system to be tested is less than 2%, it is excellent, greater than 2% but less than 5% is good, greater than 5% but less than 10% is qualified, greater than 10% is unqualified.

8)离线分析：根据步骤6)中①记录的图像信息，对车辆轨迹进行重现，对待测试车道偏离报警系统的报警性能进行分析，并生成报告。这种轨迹重现方法能够有效避免偏离事故，即报警后车辆不会大尺度，比如0.5米以上偏离车道线的待测试车道偏离报警系统是合格产品。8) Offline analysis: According to the image information recorded in step 6) ①, the vehicle track is reproduced, the alarm performance of the lane departure alarm system to be tested is analyzed, and a report is generated. This trajectory reproduction method can effectively avoid deviation accidents, that is, the vehicle will not be large-scale after the alarm, such as a lane departure alarm system to be tested that deviates from the lane line by more than 0.5 meters is a qualified product.

9)综合步骤7)和8)生成的报告，对待测试车道偏离报警系统的可靠性和报警的准确性进行评价。9) Combine the reports generated in steps 7) and 8) to evaluate the reliability of the lane departure warning system to be tested and the accuracy of the warning.

上述各实施例仅用于说明本实用新型，其中各部件的结构、连接方式等都是可以有所变化的，凡是在本实用新型技术方案的基础上进行的等同变换和改进，均不应排除在本实用新型的保护范围之外。The above-mentioned embodiments are only used to illustrate the utility model, wherein the structure and connection mode of each component can be changed, and any equivalent transformation and improvement carried out on the basis of the technical solution of the utility model should not be excluded. Outside the scope of protection of the present utility model.