基于红外技术与激光雷达的新能源汽车无人驾驶障碍检测  

New Energy Vehicle Driverless Obstacle Detectionbased on Infrared Technology and Lidar

作　　者：刘树伟[1] 梁聪聪 Liu Shuwei;Liang Congcong(School of Automobile and Traffic Engineering,Liaoning Unmiversity of Technology,Jinzhou Liaoning 121001,China)

机构地区：[1]辽宁工业大学汽车与交通工程学院,辽宁锦州121001

出　　处：《应用激光》2022年第9期97-104,共8页Applied Laser

基　　金：辽宁省教育厅项目;辽宁省高等学校国(境)外培养项目;无人驾驶电动汽车关键技术研究(2018LNGXGJWPY-YB014)。

摘　　要：障碍物检测是无人车研究的重点之一,需要多角度获取障碍物数据。提出基于红外技术与激光雷达的新能源汽车无人车驾驶障碍检测方法。引用Trimble MX2三维激光雷达设备,结合红外线传感器,获取驾驶过程中障碍物数据,通过预处理降低数据获取误差。采用处理后的障碍数据点连接成障碍轮廓,并根据障碍分类信息完成障碍物检测。构建检测性能测试环境,试验结果表明,红外技术与激光雷达相结合后,可以实现对全部障碍物的准确检测,能够精准划分障碍物类型,行驶障碍物种类划分的误分率始终保持在0%~10%之间,检测用时始终保持在2 s以内,用时较短,检测识别效果较好,能够提高无人车夜间驾驶安全系数。Obstacle detection is one of the key points of unmanned vehicle research, which needs to obtain obstacle data from multiple angles. A method on driving obstacle detection of new energy vehicle unmanned vehicle based on infrared technology and lidar is proposed. Using Trimble MX2 3 D lidar equipment and infrared sensor, the obstacle data during driving is obtained, and the data acquisition error is reduced through preprocessing. The processed obstacle data points are connected into an obstacle contour, and the obstacle detection is completed according to the obstacle classification information. Based on the building of a detection performance test environment,, experimental results show that the combination of infrared technology and lidar can accurately detect all obstacles, accurately divide the types of obstacles, keep the misclassification rate of driving obstacle classification between 0%~10%, and keep the detection time within 2 s. The detection and recognition effect is good, which can improve the safety factor of unmanned vehicle driving at night.

关 键 词：红外技术 激光雷达 夜间驾驶 无人车 控制系统 

分 类 号：TN219[电子电信—物理电子学]