A Study on A Novel Collision Risk Prediction Map for Maritime Traffic Surveillance Based on Ship Domain


  • Van Quang Nguyen Vietnam Maritime University, Department of Personel & Administration Lach Tray Street, Haiphong, Vietnam
  • Tu Nam Luong Vietnam Maritime University, Faculty of Navigation Lach Tray Street, Haiphong, Vietnam
  • Van Luong Tran Vietnam Maritime University, International School of Education Lach Tray Street, Haiphong, Vietnam




ship collision, collision risk, ship domain, maritime traffic, heatmap


Recently, a regional model for assessing the risk of multi-ship collision has been developed to reduce the risk of ship collision in territorial sea areas such as trade ports and entry waterways and improve the safety and efficiency of ship traffic. The focus is on marine traffic in the visualized waters with the risk of ship collision. However, due to the lack of information from experts with sufficient knowledge and experience in a given area, they also have some limitations in adequately and comprehensively representing the risk of collision, especially in busy waterways where encounters of more than two ships often appear. In addition, they could not visualize the location of the proximity collision and the exact risk value in real time. Therefore, to overcome the limitations of previous studies, this paper proposes a new regional collision risk visualization system, which combines density-based spatial clustering of applications with noise (DBSCAN) and analysis and knowledge-based ship domains and uses AIS data to intuitively and accurately map the dynamic collision risk of water areas at successive moments, predict areas where collisions can happen by dynamic risk index and warn the ships. Identifying high-risk collision areas between multi-ships can be enhanced using the developed system, which allows for reliable and accurate analysis to help implement safety measures.




How to Cite

V. Q. Nguyen, T. N. Luong, and V. L. Tran, “A Study on A Novel Collision Risk Prediction Map for Maritime Traffic Surveillance Based on Ship Domain”, IJECES, vol. 15, no. 6, pp. 499-513, May 2024.



Original Scientific Papers