How to collect the real-time information of unconnected vehicles has been a challenge for connected vehicle technologies. The LiDAR sensors deployed along the roadside and at intersections provide a solution to fill the data gap during the transition from the traditional traffic to the full connected traffic. The roadside LiDAR sensors can record the movement of all road users with a relative long detection range. The lane detection serves as a fundamental but important step for LiDAR data processing. The location (which lane is occupied) of vehicles can be used for lane changing detection, vehicle departure warning and wrong-way alerts. But currently, there is not an effective method to identify the boundary of lanes using roadside LiDAR sensors. This paper presents a systematic procedure for lane detection based on the trajectories of vehicles collected on the road with the roadside LiDAR sensor. The whole procedure includes two major parts: background filtering and road boundary identification. This robust procedure can release engineers from the manual lane identification task and can avoid any error caused by manual work. Two case studies confirmed the effectiveness of the proposed method. Compared to previous lane detection methods, this procedure is not affected by the existence of pedestrians. This method can also detect the boundaries of lanes from the roads having curves with the limited time cost.

中文翻译：

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使用路边 LiDAR 传感器的自动车道识别

如何收集未联网车辆的实时信息一直是联网汽车技术面临的挑战。沿路和交叉路口部署的 LiDAR 传感器提供了一种解决方案，以填补从传统交通到全连接交通过渡期间的数据空白。路边激光雷达传感器可以在相对较长的检测范围内记录所有道路使用者的运动。车道检测是 LiDAR 数据处理的一个基本但重要的步骤。车辆的位置（哪个车道被占用）可用于车道变换检测、车辆偏离警告和错误方向警报。但目前还没有一种有效的方法来使用路边激光雷达传感器识别车道边界。本文提出了一种基于道路上使用路边 LiDAR 传感器收集的车辆轨迹进行车道检测的系统程序。整个过程包括两个主要部分：背景过滤和道路边界识别。这个强大的程序可以将工程师从手动车道识别任务中解放出来，并可以避免手动工作造成的任何错误。两个案例研究证实了所提出方法的有效性。与之前的车道检测方法相比，该过程不受行人存在的影响。该方法还可以在有限的时间成本下从有弯道的道路上检测车道的边界。这个强大的程序可以将工程师从手动车道识别任务中解放出来，并可以避免手动工作造成的任何错误。两个案例研究证实了所提出方法的有效性。与之前的车道检测方法相比，该过程不受行人存在的影响。该方法还可以在有限的时间成本下从有弯道的道路上检测车道的边界。这个强大的程序可以将工程师从手动车道识别任务中解放出来，并可以避免手动工作造成的任何错误。两个案例研究证实了所提出方法的有效性。与之前的车道检测方法相比，该过程不受行人存在的影响。该方法还可以在有限的时间成本下从有弯道的道路上检测车道的边界。