Author(s)

Jiayin Hu ¹, Duowen Yan ¹, Jian Zheng ¹

Affiliation(s)

¹ Transport and Communications College, Shanghai Maritime University, Shanghai 201306, China

Corresponding Author

Jiayin Hu

ABSTRACT

In order to solve the problems of ship path planning and slow convergence speed of traditional ant colony algorithm under different encounter situations in the dynamic complex water surface, a ship turns decision model was proposed based on Q-learning algorithm, and the transfer probability formula of ant colony algorithm was improved. The improved ant colony algorithm can quickly calculate the safe and realistic collision avoidance path. This algorithm uses Q-learning to plan the optimal collision avoidance path by ship improved ant colony algorithm. Simulation results show that the algorithm can converge quickly and calculate the optimal collision avoidance path. This method can be effectively applied to ship collision avoidance path planning in complex waters.

KEYWORDS

Dynamic collision avoidance, Path optimization, Improved ant colony algorithm

CITE THIS PAPER

Jiayin Hu, Duowen Yan, Jian Zheng, Embed Behavior Decision Making into Ship Collision Avoidance Path Planning Based on Ant Colony and Q-Learning Algorithm. Industrial Engineering and Innovation Management (2022) Vol. 5: 20-28. DOI: http://dx.doi.org/10.23977/ieim.2022.050105.

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