Stochastic Motion Planning and Applications to Traffic

This paper presents a stochastic motion planning algorithm and its application to traffic navigation. The algorithm copes with the uncertainty of road traffic conditions by stochastic modeling of travel delay on road networks. The algorithm deter min s paths between two points that optimize a cost function of the delay probability distribution. It c an be used to find paths that maximize the probability of reaching a destination within a partic ular travel deadline. For such problems, standard shortest-path algorithms don’t work because the optimal substructure property doesn’t hold. We evaluate our algorithm using bo th simulations and realworld drives, using delay data gathered from a set of taxis equipped with GPS sensors and a wireless network. Our algorithm can be integrated into on-board navigation systems as well as route-finding Web sites, providing drivers with good paths that meet th ir desired goals.

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