Short-Term Trajectory Prediction of Maritime Vessel Using k-Nearest Neighbor Points
The prediction of ship location has become an increasingly popular research hotspot in the field of maritime transportation engineering, which benefits maritime safety supervision and security. Existing methods of ship location prediction based on motion characteristics have a large uncertainty and...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-12-01
|
| Series: | Journal of Marine Science and Engineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-1312/10/12/1939 |
| _version_ | 1797456939815272448 |
|---|---|
| author | Minglong Zhang Liang Huang Yuanqiao Wen Jinfen Zhang Yamin Huang Man Zhu |
| author_facet | Minglong Zhang Liang Huang Yuanqiao Wen Jinfen Zhang Yamin Huang Man Zhu |
| author_sort | Minglong Zhang |
| collection | DOAJ |
| description | The prediction of ship location has become an increasingly popular research hotspot in the field of maritime transportation engineering, which benefits maritime safety supervision and security. Existing methods of ship location prediction based on motion characteristics have a large uncertainty and cannot guarantee trajectory prediction accuracy of the target ship. An improved method of location prediction using <i>k-nearest neighbor</i> (<i>KNN</i>) is proposed in this paper. An expanded circle area of the latest point of the target ship is first generated to find the reference points with similar movement characteristics in the constraints of distance and time intervals. Then, the top k-nearest neighbors are determined based on the degree of similarity. Relationships between the reference point of each neighbor and the latest points of the target ship are calculated. The predicted location of the target ship can then be determined by a weighted calculation of the locations of all neighbors at the predicted time and their relationships with the target ship. Experiments of ship location prediction in 10 min, 20 min, and 30 min were conducted. The correlation coefficient of the location prediction error for the three experiments was 0.992, 0.99, and 0.9875, respectively. The results show that ship location prediction with reference to multiple nearest neighbors with similar movements can provide better accuracy. |
| first_indexed | 2024-03-09T16:14:03Z |
| format | Article |
| id | doaj.art-937efe113ee7497a8016e2ada1d69608 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-09T16:14:03Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-937efe113ee7497a8016e2ada1d696082023-11-24T15:56:54ZengMDPI AGJournal of Marine Science and Engineering2077-13122022-12-011012193910.3390/jmse10121939Short-Term Trajectory Prediction of Maritime Vessel Using k-Nearest Neighbor PointsMinglong Zhang0Liang Huang1Yuanqiao Wen2Jinfen Zhang3Yamin Huang4Man Zhu5Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, ChinaIntelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, ChinaIntelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, ChinaIntelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, ChinaIntelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, ChinaIntelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, ChinaThe prediction of ship location has become an increasingly popular research hotspot in the field of maritime transportation engineering, which benefits maritime safety supervision and security. Existing methods of ship location prediction based on motion characteristics have a large uncertainty and cannot guarantee trajectory prediction accuracy of the target ship. An improved method of location prediction using <i>k-nearest neighbor</i> (<i>KNN</i>) is proposed in this paper. An expanded circle area of the latest point of the target ship is first generated to find the reference points with similar movement characteristics in the constraints of distance and time intervals. Then, the top k-nearest neighbors are determined based on the degree of similarity. Relationships between the reference point of each neighbor and the latest points of the target ship are calculated. The predicted location of the target ship can then be determined by a weighted calculation of the locations of all neighbors at the predicted time and their relationships with the target ship. Experiments of ship location prediction in 10 min, 20 min, and 30 min were conducted. The correlation coefficient of the location prediction error for the three experiments was 0.992, 0.99, and 0.9875, respectively. The results show that ship location prediction with reference to multiple nearest neighbors with similar movements can provide better accuracy.https://www.mdpi.com/2077-1312/10/12/1939short-term location predictionk-nearest neighbor pointssimilarity measurement |
| spellingShingle | Minglong Zhang Liang Huang Yuanqiao Wen Jinfen Zhang Yamin Huang Man Zhu Short-Term Trajectory Prediction of Maritime Vessel Using k-Nearest Neighbor Points Journal of Marine Science and Engineering short-term location prediction k-nearest neighbor points similarity measurement |
| title | Short-Term Trajectory Prediction of Maritime Vessel Using k-Nearest Neighbor Points |
| title_full | Short-Term Trajectory Prediction of Maritime Vessel Using k-Nearest Neighbor Points |
| title_fullStr | Short-Term Trajectory Prediction of Maritime Vessel Using k-Nearest Neighbor Points |
| title_full_unstemmed | Short-Term Trajectory Prediction of Maritime Vessel Using k-Nearest Neighbor Points |
| title_short | Short-Term Trajectory Prediction of Maritime Vessel Using k-Nearest Neighbor Points |
| title_sort | short term trajectory prediction of maritime vessel using k nearest neighbor points |
| topic | short-term location prediction k-nearest neighbor points similarity measurement |
| url | https://www.mdpi.com/2077-1312/10/12/1939 |
| work_keys_str_mv | AT minglongzhang shorttermtrajectorypredictionofmaritimevesselusingknearestneighborpoints AT lianghuang shorttermtrajectorypredictionofmaritimevesselusingknearestneighborpoints AT yuanqiaowen shorttermtrajectorypredictionofmaritimevesselusingknearestneighborpoints AT jinfenzhang shorttermtrajectorypredictionofmaritimevesselusingknearestneighborpoints AT yaminhuang shorttermtrajectorypredictionofmaritimevesselusingknearestneighborpoints AT manzhu shorttermtrajectorypredictionofmaritimevesselusingknearestneighborpoints |