Object Detection and Tracking Based on Lidar for Autonomous Vehicles on Highway Conditions

Multiple object detection and tracking are central aspects of modeling the environment of autonomous vehicles. Lidar is a necessary component in the autonomous driving system. Without Lidar sensors, we will most probably not see fully self-driving cars become a reality. Lidar sensing gives us high-resolution data by sending out thousands of laser signals. In advanced driver assistance systems or automated driving systems, 3-D point clouds from lidar scans are typically used to measure physical surfaces. Lidar is a powerful sensor that you can use in challenging environments where other sensors might prove inadequate. Lidar can provide a complete 360-degree view of a scene. This paper designs Lidar based multi-target detection and tracking system based on the traditional point cloud processing method including down-sampling, denoising, segmentation, and clustering objects. Based on the detections from Lidar, a multi-target tracking system is involved in this paper which can be used on Highway conditions. Finally, the Lidar-based detection and tracking system is tested on the vehicle equipped with Lidar sensors and the result shows that miss-detection rate and the lateral and longitudinal position and velocity tracking accuracy can satisfy the need for Adaptive Cruise Control (ACC), Navigation on Pilot (NOP) Auto Emergency Braking (AEB) or other application.