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• W2626203751 abstract "To be “fast enough” is a key issue for intelligent vehicle motion planning. The traditional simplicity high dimensional search approach for motion planning often suffers from huge statue-spaces, high time complexity and inefficiency. In this paper, we propose a method, increment-dimensional heuristic search to solve the problem. Our method employs a stepped-up heuristic search to reduce the searching status and improve the search algorithm execution efficiency, while the continues motion planning in this scheme still provides high quality trajectory for the vehicle. In experiment, the quantitative evaluation shows that the proposed algorithm reduces more than 90% of searching status and executes time is about 1/10 of that of the simplicity heuristic search method. It turns out to be a very good trade-off between execution efficiency and trajectory quality in real world scenarios. In practice, this algorithm is implemented in the decision-making module in TiEV (Tongji Intelligent Electronic Vehicle)." @default.
• W2626203751 created "2017-06-23" @default.
• W2626203751 creator A5007977858 @default.
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• W2626203751 date "2017-04-01" @default.
• W2626203751 modified "2023-09-25" @default.
• W2626203751 title "Increment-dimensional heuristic search for Intelligent Vehicle motion planning" @default.
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• W2626203751 doi "https://doi.org/10.1109/iccar.2017.7942774" @default.
• W2626203751 hasPublicationYear "2017" @default.
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