Finding the fastest route in dynamic transportation networks aids navigation service considerably. Existing approaches are either too complex or incapable or handling complex circumstances wherein both the location or a mobile user and the traffic conditions change incessantly over time. In this paper, we propose an incremental search approach based on a variation of A*-Lifelong Planning A* (LPA*) to derive a dynamic fastest path, which continually adapts to the real-time traffic condition while making use of the previous search result. Our experimental results reveal that the proposed approach is a significant improvement over a conventional approach also using the A* algorithm. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Wu, Q., Huang, B., & Tay, R. (2006). Adaptive path finding for moving objects. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3833 LNCS, pp. 155–167). https://doi.org/10.1007/11599289_14
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