Automatic Vehicle Tracking with LiDAR-Enhanced Roadside Infrastructure

Abstract

Abstract Vehicle tracking technology is a prerequisite for the connected-vehicle (CV) system. However, a mixture of CV and unconnected vehicles will be under normal conditions on roads in the near future. How to obtain the real-time traffic status of unconnected vehicles remains a challenge for traffic engineers. The roadside Light Detection and Ranging (LiDAR) sensor provides a solution for collecting real-time high-resolution micro traffic data of all road users (CV and unconnected vehicles). This article developed a systematic procedure for vehicle tracking using the roadside LiDAR sensors. The procedure can be divided into five major parts: point registration, background filtering, point clustering, object classification, and vehicle tracking. For each step, the corresponding data processing algorithms were provided. A field test was conducted to evaluate the performance of the proposed method. Compared to the state-of-the-art method, the proposed methods can track vehicles with higher accuracy and lower computation loads.