Cooperative Camera-LiDAR Extrinsic Calibration for Vehicle-Infrastructure Systems in Urban Intersections

Cameras and LiDARs are fundamental sensors for autonomous driving, with wide applicability. This paper comprehensively studies and analyzes the calibration of the multi-terminal camera-LiDAR devices from the perspectives of vehicle, roadside, and road cooperation, and outlines its related applications and far-reaching significance. Different from previous studies that focused on sensor calibration of a single platform, ignoring the differences between vehicle-end and roadside, this paper particularly emphasizes the difference between vehicle-end and roadside, as well as heterogeneous calibration challenges emerging in vehicle-road cooperation scenarios. These challenges include cross-sensor temporal synchronization and spatial alignment in dynamic environments. It reveals the advantages and differences of different methods in dealing with constraints such as the fixed installation postures of vehicle-mounted and roadside devices and the large-scale observation domain. This paper further points out key research gaps, such as the adaptability of online calibration and the maintenance of calibration consistency among multiagents, providing important references for the technological evolution from isolated calibration to a sensor-collaborative calibration framework in traffic scenarios.