Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-27T11:30:14.482Z Has data issue: false hasContentIssue false

Automatic Ship Routing with High Reliability and Efficiency between Two Arbitrary Points at Sea

Published online by Cambridge University Press:  28 November 2018

Shuaidong Jia
Affiliation:
(Department of Military Oceanography and Hydrography & Cartography, Dalian Naval Academy, Dalian, China; Key Laboratory of Hydrographic Surveying and Mapping of PLA, Dalian Navy Academy, Dalian, China)
Zeyuan Dai*
Affiliation:
(Department of Military Oceanography and Hydrography & Cartography, Dalian Naval Academy, Dalian, China; Key Laboratory of Hydrographic Surveying and Mapping of PLA, Dalian Navy Academy, Dalian, China)
Lihua Zhang
Affiliation:
(Department of Military Oceanography and Hydrography & Cartography, Dalian Naval Academy, Dalian, China; Key Laboratory of Hydrographic Surveying and Mapping of PLA, Dalian Navy Academy, Dalian, China)

Abstract

Due to the limitations of the existing methods (for example, the route binary tree method) that can only automatically generate routes based on a single chart, a method for automatically generating the shortest distance route based on an obstacle spatial database is proposed. Using this proposed method, the route between two arbitrary points at sea can be automatically generated. First, the differences in accuracy and updating time of charts are quantitatively analysed. Next, the mechanism for updating obstacles is designed, an obstacle spatial database is constructed, and the obstacle data extracted from multiple charts are fused. Finally, considering the effect of efficiency on the amount of obstacle data, a route window and an improved R-tree index are designed for quickly extracting and querying the obstacle database. The experimental results demonstrate that compared with existing methods, the proposed method can generate the shortest distance between two arbitrary points at sea and eliminates the limitation of the area of the chart. In addition, with data from multiple charts, the route generated by the proposed method is more reliable than that of the existing methods, and it is more efficient.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Cao, H.B., Zhang, L.H., Jia, S.D. and Zhang, L. (2011). An Improved Method for Automatically Building Shortest Route Based on Electronic Chart, Geomatic and Information Science of Wuhan University, 36(9), 11071110.Google Scholar
Chang, K., Jan, G.E. and Parberry, I. (2004). A Method for Searching Optimal Routes with Collision Avoidance on Raster Charts. The Journal of Navigation, 56(3), 371384.Google Scholar
Dijkstra, E. (1959). A note on two problems in connection with graphs. Numerische Mathematic, 1, 269271.Google Scholar
Guilbert, E. (2016). Feature-Driven Generalization of Isobaths on Nautical Charts, A Multi-Agent System Approach. Transactions in GIS, 20(1), 126143.Google Scholar
Jones, M. and Rowe, R. (2016). Collision avoidance system. US Patent, US 9,505,404 B2.Google Scholar
Kim, H., Kim, D., Shin, J.U., Kim, H. and Myung, H. (2014). Angular rate-constrained path planning algorithm for unmanned surface vehicles. Ocean Engineering, 84(4), 3744.Google Scholar
Ladue, D. and Tetreault, B. (2017). Improving navigation safety with better charts, Prototyping AIS for Ship Reporting of ENC Discrepancies. Sea Technology, 58(3), 2024.Google Scholar
Lee, Y.H. and Kim, S.W. (2014). A Hybrid Search Method of A* and Dijkstra Algorithms to Find Minimal Path Lengths for Navigation Route Planning. Journal of the Institute of Electronics & Information Engineers, 51(10), 109117.Google Scholar
Li, Y.H., Pan, M.Y. and Wu, X. (2007). Automatic creating algorithm of route based on dynamic grid model. Journal of Traffic and Transportation Engineering, 7(3), 3439.Google Scholar
Lin, Y.H., Fang, M.C. and Yeung, R.W. (2013). The optimization of ship weather-routing algorithm based on the composite influence of multi-dynamic elements. Applied Ocean Research, 43(43), 184194.Google Scholar
Montes, A.A. (2005). Network Shortest Path Application for Optimum Track Ship Routing. California, Naval Postgraduate School.Google Scholar
Nash, A., Daniel, K., Koenig, S. and Felner, A. (2014). Theta*, Any-Angle Path Planning on Grids. Journal of Artificial Intelligence Research, 39(1), 533579.Google Scholar
Panigrahi, J.K., Padhy, C.P., Sen, D., Swain, J. and Larsen, O. (2012). Optimal ship tracking on a navigation route between two ports, a hydrodynamics approach. Journal of Marine Science & Technology, 17(1), 5967.Google Scholar
Peters, R., Ledoux, H., Meijers, M. (2014). A Voronoi-Based Approach to Generating Depth-Contours for Hydrographic Charts. Marine Geodesy, 37(2), 145166.Google Scholar
Pietrzykowski, Z. and Uriasz, J. (2009). The Ship Domain - A Criterion of Navigational Safety Assessment in an Open Sea Area. The Journal of Navigation, 62(1), 93108.Google Scholar
Reed, S. and Schmidt, V.E. (2016). Providing Nautical Chart awareness to autonomous surface vessel operations. OCEANS 2016 MTS/IEEE Monterey. Monterey, CA. 1–8.Google Scholar
Szlapczynski, R. (2006). A New Method of Ship Routing on Raster Grids, with Turn Penalties and Collision Avoidance. The Journal of Navigation, 59(1), 27.Google Scholar
Wang, D.C., Chen, L.M. and Zhang, X.F. (2005). Selecting Ship's Optimum Route Using A* Algorithm. Journal of Qingdao University (Natural Science Edition), 18(4), 1013.Google Scholar
Wang, T., Zhang, L.H., Peng, R.C., Cao, H.B. and Jiang, L.J. (2016a). A Method for Automatically Generating the Shortest Distance Route Based on Electronic Navigational Chart Considering Channel Width. Hydrographic Surveying and Charting, 36(3), 2931, 36.Google Scholar
Wang, T., Zhang, L.H., Peng, R.C., Cao, H.B. and Jiang, L.J. (2016b). Automatic generation of the shortest route of an electronic navigational chart considering turning restrictions. Journal of Harbin Engineering University, 37(7), 923929.Google Scholar
Wang, Z., Li, S.J., Zhang, L.H. and Li, N. (2010). A method for Automatic Routing Based on Route Binary Tree. Geomatic and Information Science of Wuhan University, 35(4), 407410.Google Scholar
Wijayaningrum, V.N. and Mahmudy, W.F. (2016). Optimization of Ship's Route Scheduling Using Genetic Algorithm. Indonesian Journal of Electrical Engineering and Computer Science, 2(1), 180186.Google Scholar
Yan, J., Guilbert, E. and Saux, E. (2016). An ontology-driven multi-agent system for nautical chart generalization.American Cartographer, 44(3), 201215.Google Scholar
Ye, Q. and Yu, Z.W. (2003). The Improved Shortcut Algorithm and It's Application in Selecting Ship's Optimum Route. Navigation of China, 2, 1517.Google Scholar
Ying, S., Shi, C. and Yang, S. (2007). Ship Route Designing for Collision Avoidance Based on Bayesian Genetic Algorithm. IEEE International Conference on Control and Automation. Guangzhou, CHINA. 18071811.Google Scholar
Yu, Y., Zhu, H., Yang, L. and Wang, C.X. (2017). Spatial Indexing for Effective Visualization of Vector-Based Electronic Nautical Chart. International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration. Wuhan, CHINA. 323326.Google Scholar
Zhang, L.H. (2011). The Methods for Generating The Optimal Route Based on Electronic Navigation Chart. Science Press.Google Scholar
Zhang, L.H., Zhang, L., Peng, R.C., Li, G.X. and Zou, W. (2011). Determination of the Shortest Time Route Based on the Composite Influence of Multidynamic Elements. Marine Geodesy, 34(2), 108118.Google Scholar
Zhang, L.H., Zhu, Q., Zhang, A.M., Liu, Y.C. and Han, Y.L. (2008). An intelligent method for the shortest routing. Acta Geodaetica et Cartographica Sinica, 1, 114120.Google Scholar