Efficient L-shape Fitting Based on Critical Edge for Vehicle Orientation Estimation Using LiDAR

Vehicle orientation detection is essential for autonomous driving. L-Shape fitting is a crucial step for model-based vehicle detection and tracking. This paper proposes a novel method to determine the critical edge from the point cloud of a vehicle. The critical edge is used to estimate the vehicle orientation. An edge merging pre-process is proposed to generate a simplified convex hull of the point cloud, which can improve the performance of the proposed method. Simulations conducted on the KITTI dataset demonstrate the accuracy and efficiency of the proposed method. Comparisons with previous methods indicate that the proposed method produces lower mean absolute errors while meeting real-time requirements.