Collaborative perception for collision avoidance
Benjamin Mourllion, Andrew R. Lambert, Dominique Gruyer, D. Aubert · 2004
The aim of this paper is to propose a collaborative perception system in order to avoid potential vehicle collisions. We present a basic system where vehicles ensure their own localization using a global positioning system with a Kalman filtering process. This information and the velocity data are broadcasted via a wireless network to its neighbours. Moreover, some of the vehicles are equipped with telemetric sensors, thus they can supply a direct perception of their surrounding environment and update the knowledge given by the network. If a potential collision is detected, the vehicles are brought under speed control. We analyse the results and the limits of this system. All results are validated via an extended perception simulator.