Next Article in Journal
Multi-Innovation-Based Parameter Identification for Vertical Dynamic Modeling of AUV Under High Maneuverability and Large Attitude Variations
Previous Article in Journal
Comparative Study of Local Stress Approaches for Fatigue Strength Assessment of Longitudinal Web Connections
Previous Article in Special Issue
Hybrid Obstacle Avoidance Algorithm Based on IAPF and MPC for Underactuated Multi-USV Formation
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

A CDC–ANFIS-Based Model for Assessing Ship Collision Risk in Autonomous Navigation

1
Division of Education and Planning, Korea Institute of Maritime and Fisheries Technology, Busan 49111, Republic of Korea
2
Department of Maritime Industry Convergence, Mokpo National Maritime University, Mokpo 58628, Republic of Korea
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2025, 13(8), 1492; https://doi.org/10.3390/jmse13081492 (registering DOI)
Submission received: 7 July 2025 / Revised: 31 July 2025 / Accepted: 1 August 2025 / Published: 1 August 2025

Abstract

To improve collision risk prediction in high-traffic coastal waters and support real-time decision-making in maritime navigation, this study proposes a regional collision risk prediction system integrating the Computed Distance at Collision (CDC) method with an Adaptive Neuro-Fuzzy Inference System (ANFIS). Unlike Distance at Closest Point of Approach (DCPA), which depends on the position of Global Positioning System (GPS) antennas, Computed Distance at Collision (CDC) directly reflects the actual hull shape and potential collision point. This enables a more realistic assessment of collision risk by accounting for the hull geometry and boundary conditions specific to different ship types. The system was designed and validated using ship motion simulations involving bulk and container ships across varying speeds and crossing angles. The CDC method was used to define collision, almost-collision, and near-collision situations based on geometric and hydrodynamic criteria. Subsequently, the FIS–CDC model was constructed using the ANFIS by learning patterns in collision time and distance under each condition. A total of four input variables—ship speed, crossing angle, remaining time, and remaining distance—were used to infer the collision risk index (CRI), allowing for a more nuanced and vessel-specific assessment than traditional CPA-based indicators. Simulation results show that the time to collision decreases with higher speeds and increases with wider crossing angles. The bulk carrier exhibited a wider collision-prone angle range and a greater sensitivity to speed changes than the container ship, highlighting differences in maneuverability and risk response. The proposed system demonstrated real-time applicability and accurate risk differentiation across scenarios. This research contributes to enhancing situational awareness and proactive risk mitigation in Maritime Autonomous Surface Ship (MASS) and Vessel Traffic System (VTS) environments. Future work will focus on real-time CDC optimization and extending the model to accommodate diverse ship types and encounter geometries.
Keywords: ship collision; fuzzy inference system; CDC; MASS; CRI ship collision; fuzzy inference system; CDC; MASS; CRI

Share and Cite

MDPI and ACS Style

Lee, H.-J.; Namgung, H. A CDC–ANFIS-Based Model for Assessing Ship Collision Risk in Autonomous Navigation. J. Mar. Sci. Eng. 2025, 13, 1492. https://doi.org/10.3390/jmse13081492

AMA Style

Lee H-J, Namgung H. A CDC–ANFIS-Based Model for Assessing Ship Collision Risk in Autonomous Navigation. Journal of Marine Science and Engineering. 2025; 13(8):1492. https://doi.org/10.3390/jmse13081492

Chicago/Turabian Style

Lee, Hee-Jin, and Ho Namgung. 2025. "A CDC–ANFIS-Based Model for Assessing Ship Collision Risk in Autonomous Navigation" Journal of Marine Science and Engineering 13, no. 8: 1492. https://doi.org/10.3390/jmse13081492

APA Style

Lee, H.-J., & Namgung, H. (2025). A CDC–ANFIS-Based Model for Assessing Ship Collision Risk in Autonomous Navigation. Journal of Marine Science and Engineering, 13(8), 1492. https://doi.org/10.3390/jmse13081492

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop