Automatic ground points filtering of roadside LiDAR data using a channel-based filtering algorithm

Ground points information is valuable for various transportation applications. To date, limited studies have been applied for ground points identification with the roadside LiDAR sensor. This paper presents an innovative approach to extract the ground points for the roadside LiDAR effectively. The proposed method can be divided into four major parts: region of intersection (ROI) Selection, background filtering, channel-based clustering, and slope-based filtering. The channel information is used for the ground points extraction. Data collected at different scenarios were used to evaluate the performance of the proposed method. It was shown that the algorithm can successfully extract ground points regardless of slope on the road and package loss issue. The developed method can also accommodate the different types of the LiDAR. Compared to the state-of-the-art methods, the overall performance of the proposed method is superior.