# Analysis of the Impact of Small Group Behavior on Cruise Ship Emergency Evacuation
## 1 Introduction:  
The cruise industry is experiencing growth due to the rapid development of the marine tourism industry. Large cruise ships are characterized by their high passenger capacity, intricate internal structure, limited passageways, and limited exits. In the event of an emergency such as fire or flooding on a large cruise ship, heavy casualties may be caused, and passengers have to abandon the ship and board the lifeboat. For example, in 2021, a fire broke out on the luxury cruise ship Omar Khayyam on the Nile River in Egypt, causing the entire ship to be engulfed in flames and passengers were forced to abandon the ship. Fortunately, due to timely evacuation, there were no casualties. In 2021, a passenger ship caught fire while in transit in Bangladesh, leading to several casualties. At least 38 people died and over 200 were injured as a result of delayed rescue efforts and evacuation. Thus, establishing a model for passenger evacuation is crucial in effectively assessing and enhancing the safety of such evacuations on cruise ships. Many scientists conducted research on ship evacuation routes, taking into account the effects of personnel loads and evacuation distances. [PERSON] et al. [1] used the shortest path and genetic algorithms to acquire optimal evacuation plans with the goal of reducing congestion. [PERSON] et al. [2] used the equivalent shortest path algorithm to determine the optimal evacuation path for passenger ship personnel, fully considering the ease of passage in each section. [PERSON] et al. [3] optimized the evacuation routes of pedestrians departing from different locations using a genetic algorithm and found that the shortest path is not necessarily the optimal path for ship personnel evacuation. [PERSON] et al. [4] proposed a method for determining the optimal evacuation path considering distance factors, channel congestion levels, and personnel behavior, which significantly improved passenger evacuation efficiency. [PERSON] [5] established an evacuation model for small groups of people,obtaining the optimal route for the point-to-point flow of small groups and improving evacuation efficiency. However, these studies mainly focus on the optimal paths for passenger evacuation, and insufficient research was conducted on the selection of quasi-safe areas for ship personnel evacuation. The macro model focuses on the overall pedestrian flow in crowd evacuation activities. It draws on the laws of fluid mechanics and mainly studies the relationship between the macroscopic statistical parameters (speed, flow, and density) of pedestrian flow. For the evacuation scenario, it mainly focuses on the configuration of the evacuation space and the distribution of people, without considering the details of the interaction between personnel and the influence of various elements in the facility on the movement of people, and focuses on analyzing the overall movement law of the pedestrian flow. [PERSON] first proposed a research model of microfluid dynamics [6], treating pedestrians as gas molecules and the movement of pedestrian flow as the movement of liquid. [PERSON] et al. [7] proposed a gas model. Microscopic models focus on the individual behavior of pedestrians in crowd evacuation activities, considering various elements in the evacuation scenario. They specifically observe, record, extract, and analyze the microscopic characteristics of pedestrian groups in the scene. These models describe individual behavior in evacuation activities using mathematical formulas, logical judgments, or evolutionary rules. The microscopic models for cruise ship evacuation include [PERSON]'s social force model [8], the cellular automaton model [9; 10], and the agent-based model [11; 12]. The social force model converts the environmental impact on individuals into the force exerted on pedestrians by the environment and quantifies the influence of environmental information on pedestrian movement speed as the magnitude of the force.