Abstract
Regarding aiming at multiple mobile objects in a complex water traffic–navigation environment, the chapter puts forward a route-planning method based on the complexity map. First, a Complexity Map was established according to the theory of complexity measurement. Then, combined with the A* algorithm, the actual cost was modified by making use of the distribution of the complexity values. Meanwhile, to reduce the distance of the whole voyage and avoid the local minimum in the process of path-finding, the Euclidean distance from the current point to the target was set to estimate heuristic cost. In addition, by using the standardization method, the value of complexity and distance became dimensionless. Finally, considering the ship dimensions, a channel-boundary constraint was added. The experimental results show that in the case of satisfying the ship dimensions, the best path is close to the shortest route and avoids all the high complex areas.
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References
Zong G, Hu B, Han J (2012) Research on complexity spatial structure for chinese coastal port network. China Soft Sci 12:171–178
Hua Z (2011) Key technology research on route planning for UAV based on intelligent optimization algorithm. Nanjing University of Aeronautics and Astronautics, Nanjing
Hao Y, Liu Y (2015) Review of genetic operators applied in VRP. J Southeast Univ (Philosophy and Social Science) S2:85–87
Ji M, Chen Z, Wang Q (2011) Optimization algorithm for regional transportation route of container ship. J Transp Eng 04:68–75
Li X, Xiao J, Wang X (2011) Shipping route optimization based on tabu-search algorithm. Intelligent information technology application association. 2011 International Conference on Machine Intelligence (ICMI 2011 V4). Intelligent Information Technology Application Association, 2011:6
Zhang Y (2013) Path planning research on large ship material handling system. Huazhong University of Science and Technology
Chen J (2013) Study of path planning algorithm on unmanned rescue ship. Wuhan University of Technology
Phanthong T, Maki T, Ura T, Sakamaki T, Aiyarak P (2014) Application of A* algorithm for real-time path re-planning of an unmanned surface vehicle avoiding underwater obstacles. J Mar Sci Appl 01:105–116
Xie S, Wu P, Liu H, Yan P, Li X, Luo J, Li Q (2016) A novel method of unmanned surfacevehicle autonomous cruise. Ind Robot Int J 43(1):121–130
Zhang J, Minghua Hu, Zhang C (2009) Research on complexity on air traffic management. Acta Aeronautica et Astronautica Sinica 30(11):2132–2142
Hong Y, Kim Y, Lee K (2013) Application of complexity assessment for conflict resolution in Air Trac Management system. AIAA Guidance, Navigation, and Control (GNC) Conference, Boston, US
Huang Y (2014) Research on water traffic complexity measure. Wuhan University of Technology
Wen Y, Huang Y, Yang J, Xiao C, Zhou C, Wu X (2014) Modeling for complexity of water traffic flow structure. Navig China 02:62–68
Hart PE, Nilsson NJ, Raphael B (1968) A formal basis for the heuristic determination of minimum cost paths. IEEE Trans Syst Sci Cybern SSC-4(2):100–107
Guo Y, Yi P (2008) Properties analysis for method of linear dimensionless. Stat Res 02:93–100
Acknowledgements
This work was supported by the National Science Foundation of China (Grant No. 51679180) and Double First-Rate Project of WUT; the National Science Foundation of China (Grant No. 51579204) and Double First-Rate Project of WUT; and the China Postdoctoral Science Foundation (Grant No. 2016M602382).
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Du, Z., Huang, L., Wen, Y., Xiao, C., Zhou, C. (2018). Route Planning for Vessels Based on the Dynamic Complexity Map. In: Popovich, V., Schrenk, M., Thill, JC., Claramunt, C., Wang, T. (eds) Information Fusion and Intelligent Geographic Information Systems (IF&IGIS'17). Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-59539-9_8
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DOI: https://doi.org/10.1007/978-3-319-59539-9_8
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