For the emergency evacuation of cruise ships in case of sudden fire, this research proposes a dynamic route optimization method based on the improved ${\mathit{A}}^{\ast }$ algorithm for real-time information, in order to obtain the real-time optimal evacuation route. Initially, a basic network topology diagram is established according to the internal structure of the cruise ship. Before the occurrence of the accident, the ${\mathit{A}}^{\ast }$ algorithm can be applied to obtain an a priori evacuation network consisting of all the optimal routes from each node to the exit. At the time of the accident, the dynamic diffusion of fire can be simulated using Fire Dynamics Simulator (FDS) based on the preliminary information of the fire, so as to estimate the impact of the fire domain on each node of the network. Then, according to the fire dynamic diffusion data, the evacuation route planning is carried out by the improved ${\mathit{A}}^{\ast }$ algorithm applying the breadth-first search strategy, so as to determine the optimal route from the current node to the safety exit and to reduce the possibility of casualties due to the uncertainty of the fire during the evacuation. This model allows for both people’s safety and evacuation time to dynamically avoid fire-affected nodes and helps people to reach the safe area as soon as possible. Finally, the evacuation model is established according to the open-source cruise ship structure, and the evacuation process of people under the dynamic spread of cruise ship fire is simulated. The results show that the route planning method proposed in this research works out well in evacuating mass people, which can effectively reduce the evacuation time and improve the safety of the evacuation process.

Cruise ships are large and complex, and it is difficult to manually make a plan to evacuate people to safe areas in a short time. Evacuation time and personnel safety are both important for emergency evacuation. This paper proposes an evacuation strategy that considers the path capacity and risk level to guide evacuees in fire; it not only ensures the safety of people on dangerous paths but also reduces road congestion to shorten evacuation time. High crowd density means slow moving speed, an exponential function including straight path and stairs speed characteristics is proposed to illustrate the relationship between crowd density and moving speed. Path capacity constraints are used to avoid the congestion caused by the evacuees in a panic. In order to evacuate the evacuees in the risk areas as soon as possible, this paper divides the path into three risk levels according to carbon monoxide concentration, visibility, and temperature along the paths. The people on the higher-risk paths are given higher priority to enter evacuation paths than those on lower risk. The priority strategy evacuates the people on risk paths to safe areas in less time. This paper models the evacuation network topology of a cruise ship and simulates the evacuation process of some situations that have different numbers of evacuees and path capacity constraints. The evacuation strategies and simulation results are guidelines for the crews to guide the people to evacuate to safe areas when there is a fire accident on the cruise ship.