Research on using cellular automata and Bayesian algorithm to simulate optimal obstacle avoidance for ships

Abstract

This paper proposes a method combining Cellular Automata (CA) and Bayesian algorithm to optimize obstacle avoidance routes for ships in dynamic maritime environments. The system simulates real-world obstacle distributions through CA iterations and integrates a Bayesian risk assessment mechanism based on environmental data. The proposed approach reduces collision risks and achieves a higher success rate in obstacle avoidance compared to traditional heuristic methods. Experimental results demonstrate its effectiveness in dynamic scenarios, offering enhanced safety and adaptability for autonomous maritime navigation..

Keywords: Cellular automata; Bayesian algorithm; ship collision avoidance.