ITSC 2025 Paper Abstract

Paper TH-LM-T28.4

Wan, Jiahui (Tongji University), Wu, Guangqiang (Tongji University)

Fisheye Camera and LiDAR Fusion for Autonomous Following Vehicles

Scheduled for presentation during the Regular Session "S28a-Multi-Sensor Fusion and Perception for Robust Autonomous Driving" (TH-LM-T28), Thursday, November 20, 2025, 11:30−11:50, Stradbroke

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Keywords Advanced Sensor Fusion for Robust Autonomous Vehicle Perception, Sensor Integration and Calibration for Accurate Localization in Dynamic Road Conditions, Real-time Object Detection and Tracking for Dynamic Traffic Environments

Abstract

This paper presents a method that fuses LiDAR and fisheye camera data, aiming to address the current gap in research on the integration of these two sensors, with application to autonomous following vehicles. First, a joint calibration technique is employed to spatially align the LiDAR and fisheye camera, ensuring spatial consistency between the two sensors. Based on this, a target localization algorithm is developed through theoretical analysis. Experimental results show that the algorithm maintains a relative squared error within 10% across all tested distances and angles. Furthermore, even in complex scenarios involving foreground occlusions or background interference, the algorithm still achieves high localization accuracy, with results closely matching the ground truth. Additionally, compared to a pinhole camera, the fisheye camera provides a significantly wider field of view, further enhancing its applicability in dynamic and cluttered environments.