Multi-Sensor Fusion for Obstacle Detection and Recognition: A Belief-Based Approach

This paper presents an obstacle detection and classification method for intelligent vehicles. We use both a camera and radar in a multi-sensor perception framework. Our main goal is to improve the reliability of pedestrian and vehicle recognition of the system, avoiding false alarms and reducing miss detections in an uncertain environment with imprecise models. To deal with this issue, an evidential sensor fusion is developed and implemented. Simulation results and preliminary experimental test are presented and confirm the reliability improvement.