Road structure based scene understanding for intelligent vehicle systems

We address the topic of intelligent vehicle systems and especially systems aiming at high level scene understanding. Our goal is to build an on-line Behavior Map of surrounding environment. In this case, the road structure becomes important in order to understand entities behavior. From a general view-point, this paper demonstrates two important concepts: 1) the smooth integration of global, absolute but partial information (the Navi Map) in a local and relative map (the Behavior Map). This is demonstrated by the building of the Behavior Map composed of the roads structure and pedestrian/vehicle's position and trajectory. 2) the use of both global and local information to improve the understanding of the environment. This is demonstrated by the proposed “Pedestrian Warning System”. From a technical viewpoint, the main contributions are: 1) the dual ground plane/image plane approach which avoid introduction of errors in both the cost function evaluation and the constraints for minimization, 2) the smooth and efficient integration of prior data in a realistic road model computation when they are available.