LAUSR

In this article, a new approach for ship-ship collision probability estimation based on the Cross-Entropy (CE) method is introduced, which can be treated as an adaptive importance sampler. It has the advantage of attaining low variance estimates of small collision probabilities, which will most often be the case in realistic scenarios. Furthermore, a risk-based Collision Avoidance (COLAV) system being able to take obstacle kinematic uncertainty and intention uncertainty into account is presented, namely the Probabilistic Scenario-Based Model Predictive Control (PSB-MPC). The collision probability estimator (CPE) is used in the risk assessment of the PSB-MPC, and tested in a simulation study, where the total system is validated. Simulation results show that the MPC is able to utilize the CPE for better risk assessment than the original version, in order to make safer decisions in close quarter situations and cases where nearby obstacles make unexpected maneuvers. It is also shown that when all vessels involved use the PSB-MPC, situations are resolved according to the traffic rules in a safe manner.