Pose Tracking of Leading Vehicle Using Mass-Produced Sensors

Vehicle-following presents significant advantages in flexible scenarios such as platooning and valet parking, where a human-driven leader navigates complex environments, and an autonomous follower replicates the leader's trajectory. The key objective is accurate, robust, long-term pose tracking of the leader. This paper proposes a framework using mass-produced sensors, including a front fisheye camera, front millimeter-wave radar, and wireless communication. The framework consists of three modules: 1) a Visual Feature Tracking module using a DiMP tracker for robust taillight feature tracking; 2) a Visual-radar Fusion module to estimate the rear center of the leader vehicle for reference point tracking; 3) a Leader Pose Tracking module combining sensor data and vehicle-to-vehicle communication in a particle filter framework for precise pose tracking in three degrees of freedom. Real-world experiments show lateral and longitudinal errors of 0.056 meters and 0.165 meters, respectively.