@article{He_Zhang_Zhang_Zhang_Li_2019, author = {He , Yan Kang and Zhang, Di and Zhang, Jinfen and Zhang, M.Y. and Li, T.W.}, title = {Ship Route Planning Using Historical Trajectories Derived from AIS Data}, journal = {TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation}, volume = {13}, number = {1}, pages = {69-76}, year = {2019}, url = {./Article_Ship_Route_Planning_Using_Historical_He ,49,876.html}, abstract = {Ship route planning is one of the key issues in enhancing traffic safety and efficiency. Many route planning methods have been developed, but most of them are based on the information from charts. This paper proposes a method to generate shipping routes based on historical ship tracks. The ship's historical route information was obtained by processing the AIS data. From which the ship turning point was extracted and clustered as nodes. The ant colony algorithm was used to generate the optimize route. The ship AIS data of the Three Gorges dam area was selected as a case study. The ships’ optimized route was generated, and further compared with the actual ship's navigation trajectory. The results indicate that there is space of improvement for some of the trajectories, especially near the turning areas.}, doi = {10.12716/1001.13.01.06}, issn = {2083-6473}, publisher = {Gdynia Maritime University, Faculty of Navigation}, keywords = {AIS Data, Automatic Identification System (AIS), Route Planning, Historical Trajectories, AIS Messages, Marine Traffic, Dijkstra’s Algorithm, Ant Colony Algorithm} }