Research on an improved ship trajectory clustering method

Fan Jiang; Huaran Yan

doi:10.1117/12.3024768

14 February 2024 Research on an improved ship trajectory clustering method

Fan Jiang, Huaran Yan

Proceedings Volume 13018, International Conference on Smart Transportation and City Engineering (STCE 2023); 130181P (2024) https://doi.org/10.1117/12.3024768
Event: International Conference on Smart Transportation and City Engineering (STCE 2023), 2023, Chongqing, China

Abstract

Aiming at the problem that the trajectory direction cannot be distinguished from the historical data of ship Automatic Identification System (AIS) in the traditional clustering process, a DBSCAN clustering method based on the combination of improved Euclidean distance and cosine similarity is proposed. To measure the differences between arbitrary trajectory clusters in different directions, the improved DP algorithm is used to quickly and accurately extract the ship trajectory feature points, and maintain a high similarity with the original trajectory. The historical AIS data of the waterway near Port area of Zhoushan was selected to analyze and verify the algorithm. The results show that the proposed method can achieve the expected clustering effect, and the results are consistent with the actual situation, which has certain reference value in channel planning, navigation forecast, ship dynamic monitoring and other aspects.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Fan Jiang and Huaran Yan "Research on an improved ship trajectory clustering method", Proc. SPIE 13018, International Conference on Smart Transportation and City Engineering (STCE 2023), 130181P (14 February 2024); https://doi.org/10.1117/12.3024768

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