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