Abstract
A tree search algorithm is proposed for planning cooperative motions of multiple vehicles. The method relies on planning techniques from artificial intelligence such as A* search and cost-to-go estimation. It avoids the restrictions of decoupling assumptions and exploits the full potential of cooperative actions. Precomputation of lower bounds is used to restrict the search to a small portion of the tree of possible cooperative actions. The proposed algorithm is applied to the problem of planning cooperative maneuvers for multiple cognitive vehicles with the aim of preventing accidents in dangerous traffic situations. Simulation results show the feasibility of the approach and the performance gain obtained by precomputing lower bounds.
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Frese, C., Beyerer, J. (2010). Planning Cooperative Motions of Cognitive Automobiles Using Tree Search Algorithms. In: Dillmann, R., Beyerer, J., Hanebeck, U.D., Schultz, T. (eds) KI 2010: Advances in Artificial Intelligence. KI 2010. Lecture Notes in Computer Science(), vol 6359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16111-7_10
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DOI: https://doi.org/10.1007/978-3-642-16111-7_10
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