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Fig 1.

AIS trajectories of a ship, showing complexity, repetition, and some redundancy.

This figure was generated using public domain map data from Natural Earth (http://www.naturalearthdata.com/).

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Fig 1 Expand

Fig 2.

Current state of trajectories based on AIS data.

(a) Trajectories are cyclic and lack clear start or end points; (b) Trajectories contain complex and repetitive sections; (c) Trajectories may include multiple routes encompassing both (a) and (b) scenarios.

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Fig 2 Expand

Fig 3.

Workflow of the proposed typical route extraction framework.

The process comprises two sequential stages. Stage 1 applies a distance threshold to raw AIS data, generating simplified candidate routes. These routes feed directly into Stage 2, which refines them by: (a) correcting deviated starting points using route direction continuity, and (b) merging segments based on endpoint directional similarity and proximity.

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Fig 3 Expand

Fig 4.

Diagram Showing the Distance Between the Starting and Ending Points and the Route.

This diagram illustrates the search radii and , which control the connection of route segments. corrects deviated starting points by linking them to nearby routes, while the larger reconnects incorrectly split segments by spanning the potential divergence region between them.

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Fig 4 Expand

Fig 5.

Diagram Illustrating the Adjustment of Starting Points Using Route Direction.

The algorithm projects the initial direction of the route backwards. This projection intersects an existing route at . The point on that route is then identified and becomes the new, corrected starting point, ensuring topological continuity.

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Fig 5 Expand

Fig 6.

Diagram illustrating the determination of route association based on the similarity of starting and ending point directions.

Two segments are merged if the angle between their respective direction vectors ( and ) falls below a threshold , ensuring directional continuity in the resulting typical route.

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Fig 6 Expand

Fig 7.

Trajectory Diagram Formed by AIS Data of Ships Over the Past Five Years.

This figure was generated using public domain map data from Natural Earth (http://www.naturalearthdata.com/).

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Fig 7 Expand

Fig 8.

Comparison Between Raw Data and Data Processed by the Complex Trajectory Simplification Algorithm Based on Data Continuity.

This figure was generated using public domain map data from Natural Earth (http://www.naturalearthdata.com/).

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Fig 8 Expand

Fig 9.

Detailed Diagram of Data Processed by the Complex Trajectory Simplification Algorithm Based on Data Continuity.

This figure was generated using public domain map data from Natural Earth (http://www.naturalearthdata.com/).

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Fig 9 Expand

Fig 10.

Comparison Between Thinned Routes and Data Processed by the Trajectory Optimization Algorithm Based on Ship Navigation Patterns.

This figure was generated using public domain map data from Natural Earth (http://www.naturalearthdata.com/).

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Fig 11.

Detailed Diagram of Trajectories Processed by the Trajectory Optimization Algorithm Based on Ship Navigation Patterns.

This figure was generated using public domain map data from Natural Earth (http://www.naturalearthdata.com/).

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Fig 11 Expand

Table 1.

The compression ratio use DP algorithm, SW algorithm and our algorithm.

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Table 1 Expand

Table 2.

Comparison of model performance on raw and simplified AIS data.

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Table 3.

Performance comparison of anomaly detection methods on original and simplified datasets.

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