Abstract
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.
Highlights
With recent developments in shipbuilding, many passenger ships are able to accommodate several thousands of people
To investigate the influence of obstacles 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 Maritime Safety Committee (MSC) of the International Maritime Organization (IMO) requires that evacuation simulations be conducted during the design process
Summary
With recent developments in shipbuilding, many passenger ships are able to accommodate several thousands of people. Aik and Choon [38] introduced a modified dynamic cellular automata model that was able to take account of the effects of human emotional responses and crowd density at the exits and applied it to both classroom and restaurant simulations These investigations have not considered the effect that the presence of stools may have on evacuation. We developed an agent-based social force model that contains submodels to account for crowd movement, path planning, and goal-driven decision-making. To reflect the ability to bypass stools, we increased the costs of edges near stools to a larger value such that an agent will avoid these edges in searching for the shortest path to the exit To modify these costs, we assigned different virtual heights to the nodes near each stool according to the total distance from the center of each stool, and costs were calculated using a trigonometric function based on the horizontal distance and the virtual height. The agent will pursue the enter assembly station goal if this goal is satisfied and the agent can reach the assembly station; otherwise, it will execute another move to node goal with the node in the path
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