The whole process route planning algorithm based on AIS spatio-temporal big data analysis

This paper proposes a route planning algorithm that can comprehensively integrate ship safety, economic benefits and algorithm universality. Firstly, the Polynomial Approximation with the Exponential Kernel method was used to smooth the repaired trajectory and the similarity of the smoothed trajectory was evaluated using Hausdorff distance. The results showed that the similarity of ship trajectories was effectively improved by 36.53%. Using the Douglas Pucker algorithm to compress the smoothed trajectory, the compression rate exceeded 92%. Then, the HDBSCAN self-adjusting clustering analysis method was used to cluster the ship trajectory and the silhouette coefficient index was used to quantitatively evaluate the clustering effect, the calculation result was 0.9032. Finally, using the average centre method to extract the centres of each cluster, 299 key turning points were obtained and connected to construct an undirected route network. Based on this, the Dijkstra algorithm was used to achieve optimal route planning.

Authors

Institutions

Publication Details

Journal
Ships and Offshore Structures
Published
2024-08-19
DOI
https://doi.org/10.1080/17445302.2024.2386883
Citations
4
Primary Topic
Maritime Navigation and Safety
Type
article
Field-Weighted Citation Impact
1.34
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The whole process route planning algorithm based on AIS spatio-temporal big data analysis

Zhu Li’an, Han Zhen, Sha Hongjie
4 citations
Ships and Offshore Structures
Maritime Navigation and Safety
1.34
article

The whole process route planning algorithm based on AIS spatio-temporal big data analysis

Zhu Li’an, Han Zhen, Sha Hongjie
article en
4 citations

Abstract

This paper proposes a route planning algorithm that can comprehensively integrate ship safety, economic benefits and algorithm universality. Firstly, the Polynomial Approximation with the Exponential Kernel method was used to smooth the repaired trajectory and the similarity of the smoothed trajectory was evaluated using Hausdorff distance. The results showed that the similarity of ship trajectories was effectively improved by 36.53%. Using the Douglas Pucker algorithm to compress the smoothed trajectory, the compression rate exceeded 92%. Then, the HDBSCAN self-adjusting clustering analysis method was used to cluster the ship trajectory and the silhouette coefficient index was used to quantitatively evaluate the clustering effect, the calculation result was 0.9032. Finally, using the average centre method to extract the centres of each cluster, 299 key turning points were obtained and connected to construct an undirected route network. Based on this, the Dijkstra algorithm was used to achieve optimal route planning.

Ships and Offshore StructuresVol. 20(7)
Shanghai Estuarine & Coastal Science Research Center (CN), Institute of Navigation (US), Shanghai Ocean University (CN)
Sustainable cities and communities
Openalex Percentile: Top 21%
Maritime Navigation and Safety
1.34
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.