An Integrated Risk Assessment and Collision Avoidance Methodology for an Autonomous Catamaran with Fuzzy Weighting Functions
Collision avoidance and risk assessment are open problems to be practically addressed in maritime transportation. In high-speed vessels this problem becomes more challenging due to manoeuvring and reaction time constraints. Here, a reactive collision avoidance and risk assessment technique with fuzzy weighting functions are proposed for a relatively high-speed autonomous catamaran. To follow paths between predefined waypoints, a Line of Sight (LOS) technique with Cross Tracking Error (CTE) is utilised. Besides, a new collision risk index is introduced based on fuzzy weighting functions. To perform formal maritime decision making, the standard marine COLlision REGulations (COLREGs) are incorporated into the algorithm. Furthermore, a simplified Closest Point of Approach (CPA) formulation is presented. The proposed framework is simulated on a realistic model of a vessel including input and non-holonomic constraints and disturbances. Simulation results for various encounter scenarios demonstrate the merits of the proposed method.
Item Type | Book Section |
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Keywords | machine learning algorithms, simulation, transportation, machine learning, regulation, risk management, indexes |
Date Deposited | 15 May 2025 16:47 |
Last Modified | 04 Jun 2025 17:16 |
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