A New Multi-Lanes Detection Using Multi-Camera for Robust Vehicle Location

This paper deals with a new multi-lane markings detection and tracking system. The proposed system uses multiple cameras positioned differently in order to reduce different kind of perturbations, such as light sensitivity. The algorithm combines Robust Kalman Filtering and association based on belief theory to achieve multi-object tracking. Thus, the system provides the ability to track lane markings without any assumption on their number. It also proposes a new lane change management. To study this new system, the algorithm has been implemented on an embedded computer equipped with multiple cameras. We present experimental results obtained on a track. These results allow us to show important advantages of this new system and its robustness by comparing it to a classical system