Multi Sensorial Data Fusion for Efficient Detection and Tracking of Road Obstacles for Inter-Distance and Anti-Colision Safety Management

In this paper we present an automatic obstacle detection and tracking system for efficient inter-distance and anti-collision management that fuses both 3D LiDAR and 2D image data. The obstacles are first detected both in LiDAR scans and camera images and the data are then fused together. Even though LiDAR based detections are very accurate they are slower than image based detections. Hence, the proposed method helps in obtaining the state estimates more quickly with good accuracy. The unique fusion technique presented uses the detected object's geometrical information to extract the depth information at each image scan which is then corrected at each LiDAR scan. The results evaluated on real data demonstrate the prowess as well as the applicability of the proposed method which can be used for different vehicle safety applications