Roadside LiDAR for C-ITS: placement, calibration, and fusion of perception

The ongoing transition from Intelligent Transport Systems (ITS) to Cooperative Intelligent Transportation System (C-ITS) facilitates the coexistence of connected vehicles (CV) and conventional vehicles. Roadside Light Detection and Ranging (LiDAR), leveraging its precise target detection capabilities, compensates for the sensing limitations of CV. But its performance is limited by the placement and calibration of roadside LiDAR systems in engineering projects. To address these challenges, this paper introduces a solution that combines roadside LiDAR with Cellular Vehicle-to-Everything (C-V2X) technology. To enable rapid deployment and calibration of roadside LiDAR at real-world environments, the study simulates a road segment environment using a real intersection and analyzes the distribution of LiDAR point clouds within the Roadside LiDAR Occupation Board (RSLOB). By calculating two indicators-Roadside Density (<i>D</i>_RS) and Roadside Normalized Uniformity Coefficient (<i>C</i>_RSNU)-the optimal installation angle for roadside LiDAR in real-world scenarios is determined. To overcome the limitations of existing roadside LiDAR calibration methods, this study proposes a C-V2X-based calibration method that converts LiDAR coordinates to the World Geodetic System-84 (WGS-84) coordinates. The calibration experiment results show that 97.08% of the validation points meet the accuracy requirements. Furthermore, recognizing the redundancy between the target data provided by roadside LiDAR and the broadcast data from CV, we propose a data fusion method. The experimental results show that this fusion method effectively resolves the redundancy between the information broadcast by roadside LiDAR detecting CV and the data broadcast by the CV themselves. This study lays the foundation and performs crucial groundwork for the application of LiDAR on the roadside, aiming to facilitate widespread adoption in the future.