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Big Data Trajectory Analysis and Traffic Flow Framework Construction for Ship Manipulation Decision-Making Yingkou Port Pilot Station, Yingkou, China
- Format:
- Book
- Conference/Event
- Author/Creator:
- Kong, Xiangyu, author.
- Conference Name:
- 2025 International Conference on Big Data, Internet of Things and Intelligent Transportation (BDIT2025) (2025-07-19 : Zhengzhou, China)
- Language:
- English
- Physical Description:
- 1 online resource cm
- Place of Publication:
- Warrendale, PA SAE International 2025
- Summary:
- We present a novel processing approach to extract a ship traffic flow framework in order to cope with problems such as large volume, high noise levels and complexity spatio-temporal nature of AIS data. We preprocess AIS data using covariance matrix-based abnormal data filtering, develop improved Douglas-Peucker (DP) algorithm for multi-granularity trajectory compression, identify navigation hotspots and intersections using density-based spatial clustering and visualize chart overlays using Mercator projection. In experiments with AIS data from the Laotieshan waters in the Bohai Bay, we achieve compression rate up to 97% while maintaining a key trajectory feature retention error less than 0.15 nautical miles. We identify critical areas such as waterway intersections and generate traffic flow heatmap for maritime management, route planning, et cetera
- Notes:
- Vendor supplied data
- Publisher Number:
- 2025-99-0134
- Access Restriction:
- Restricted for use by site license
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