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- Both Lidars and Radars are sensors for obstacle detection. While Lidars arevery accurate on obstacles positions and less accurate on their velocities,Radars are more precise on obstacles velocities and less precise on theirpositions. Sensor fusion between Lidar and Radar aims at improving obstacledetection using advantages of the two sensors. The present paper proposes areal-time Lidar/Radar data fusion algorithm for obstacle detection and trackingbased on the global nearest neighbour standard filter (GNN). This algorithm isimplemented and embedded in an automative vehicle as a component generated by areal-time multisensor software. The benefits of data fusion comparing with theuse of a single sensor are illustrated through several tracking scenarios (on ahighway and on a bend) and using real-time kinematic sensors mounted on the egoand tracked vehicles as a ground truth.

Real Time Lidar and Radar High-Level Fusion for Obstacle Detection and Tracking with evaluation on a ground truth