Passenger behavior and ship environment are the key factors affecting evacuation efficiency. However, current studies ignore the interior layout of passenger ship cabins and treat the cabins as empty rooms. To investigate the influence of obstacles (e.g., tables and stools) on cabin evacuation, we propose an agent-based social force model for advanced evacuation analysis of passenger ships; this model uses a goal-driven submodel to determine a plan and an extended social force submodel to govern the movement of passengers. The extended social force submodel considers the interaction forces between the passengers, crew, and obstacles and minimises the range of these forces to improve computational efficiency. We drew the following conclusions based on a series of evacuation simulations conducted in this study: (1) the proposed model endows the passenger with the behaviors of bypassing and crossing obstacles, (2) funnel-shaped exits from cabins can improve evacuation efficiency, and (3) as the exit angle increases, the evacuation time also increases. These findings offer ship designers some insight towards increasing the safety of large passenger ships.

A new agent-based model is proposed to support designers in assessing the evacuation capabilities of passenger ships and in improving ship safety. It comprises models for goal-driven decision-making, path planning, and movement. The goal-driven decision-making model determines an agent's target by decomposing abstract goals into subgoals. The path-planning model plans the shortest path from the agent's current position to its target. The movement model is a combination of social-force and steering models to control the agent in moving along its path. The utility of the proposed model is verified using 11 tests for passenger ships proposed by the Maritime Safety Committee of the International Maritime Organization.

In actual evacuations, passengers should collect their life jackets before moving toward assembly stations. Passengers who do not wear life jackets must return to their cabins to collect their life jackets, as this equipment is usually stocked in individual cabins. However, current studies ignore the behavior of collection and donning of life jackets exhibited by passengers initially walking to the assembly station without life jackets. In order to investigate the influence of the collection of life jackets on the evacuation, an agent-based social force model is proposed. This model incorporates the collection and donning of life jacket, following behavior, and counterflow avoidance behavior. The model was validated by the International Maritime Organization (IMO)'s counterflow test, and satisfied its requirements. The fundamental diagram of the bidirectional flow of our model was validated against the results of a previous study. The results show that this model can reproduce collective phenomena in pedestrian trac, such as dynamic multilane flow and stable separate-lane flow. Finally, the model was applied to deck 5 of a passenger ship. It was found

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