China Safety Science Journal ›› 2020, Vol. 30 ›› Issue (1): 128-135.doi: 10.16265/j.cnki.issn1003-3033.2020.01.020

• Public safety • Previous Articles     Next Articles

Antensive form game theory based multi-ship collision avoidance scheme

OUYANG Xudong1,2, ZHI Yunxiang 1,2, WANG Tengfei3, WU Bing 1,2, WANG Yang1,2   

  1. 1. Intelligent Transportation System Research Center, Wuhan University of Technology, Wuhan Hubei 430063, China;
    2. National Engineering Research Center for Water Transport Safety, Wuhan Hubei 430063, China;
    3. School of Logistics Engineering, Wuhan University of Technology, Wuhan Hubei 430063, China
  • Received:2019-10-20 Revised:2019-12-20 Online:2020-01-28 Published:2021-01-22

Abstract: This paper is aimed at revealing the motives and preferences of ship operators in collision avoidance decision-making for ship collision avoidance (SCA) research, and more accurately reflecting the changing trend of each ship's motion in MSCA scenarios. The game model was introduced into the existing MSCA analysis, and a method was proposed to transform the MSCA problem into a non-zero-sum dynamic game problem with complete information between related ships. Firstly, the collision risk of the encounter situations was estimated by using parameters such as DCPA and TCPA, and the SCA priority matrix of all involved ships was established. Secondly, by considering the principles of the Conventional International Regulations for Preventing Collisions at Sea (COLREGS) and choosing ship maneuverability and economy preference as SCA decision making features, the extensive form game tree was established for each ship. Finally, the backward induction was used to obtain the subgame Nash equilibrium. The simulation results show that the presented game theory-based MSCA model provides more beneficial strategy than the conventional MSCA models in terms of solving the collision-prone situation.

Key words: multi-ship collision avoidance(MSCA), extensive form game theory, distance to closest point of approach (DCPA), time to closest point of approach (TCPA), pay-off matrix

CLC Number: