# Analysis of the Impact of Small Group Behavior on Cruise Ship Emergency Evacuation
## 1 Introduction:
Previous studies [13; 14; 15] improved the classical social force model by optimizing the effects of crowd density and visual perception on personnel evacuation. [PERSON] et al. [16] applied the microscopic model to simulate passenger evacuation in ship environments, specifically simulating the evacuation process during emergency situations. [PERSON] et al. [17] used computer simulations to analyze the spatiotemporal patterns of pedestrian movement, considering factors such as panic and herd behavior, and proposed an improved social force pedestrian flow model. This model effectively captures the evacuation patterns of onlookers and assesses the safety of personnel evacuation. The aforementioned studies primarily focus on the influence of individual characteristics on crowd evacuation dynamics, with relatively limited consideration of the constraints and effects of small group tendencies within the crowd on overall evacuation. During the evacuation process in various scenarios, pedestrian congestion occurs when individuals gather in a specific area, leading to increased crowd density and resulting in congestion and decreased pedestrian speed. As a result, many scholars conducted studies on localized congestion during evacuations. [PERSON] et al. [18] established a multi-objective and multi-level evacuation model for passenger ships using the fundamental theories of cellular automata. This model can simulate the evacuation process, accurately monitor changes in crowd density, and observe congestion. [PERSON] et al. [19] quantitatively analyzed the possibility of congestion propagation between grids and real-time variations in congestion locations using dynamic Bayesian networks. They applied measures to block congestion propagation paths and guided evacuees from the source to suppress congestion spread. [PERSON] et al. [20] analyzed congestion areas in the evacuation process of a specific passenger ship using International Maritime Organization (IMO) standards. These studies focused on monitoring localized congestion areas and mitigating congestion. However, the influence of group factors on congestion areas and the duration of congestion was not sufficiently researched. Studying the role of small groups in cruise ship evacuation is crucial as emergency evacuations involve both individuals evacuating independently and small groups of people. Several scholars conducted detailed research on the problem of congestion caused by group-behaved factors. For instance, [PERSON] et al. [21] established a behavior simulation model based on social force modeling to investigate the behavior of individuals in small groups in multi-exit venues, finding that the presence of small group factors hampers the evacuation process and reduces efficiency. [PERSON] et al. [22] studied the influence of group size and horizontal pressure on group behavior through experiments, revealing that group size has a significant impact on pre-evacuation time and decision-making time. [PERSON] et al. [23] incorporated rules for conformity behavior and small group behavior into a cellular automaton model, discovering that small-scale small groups can facilitate orderly evacuation and improve efficiency, although excessive crowd density within groups leads to congestion and reduces efficiency. [PERSON] et al. [24] used the velos platform to simulate and analyze how crews assist passengers in evacuating and how passengers are divided into different groups, and investigated the effect of orderly command and small groups on improving evacuation efficiency. [PERSON], [PERSON] [25] used the enhanced crowd modeling approach employed in VELOS to model the social conventions of panic aspects and social conventions of inter-relations for evacuated people to simulate the reality of crowd behavior in emergency situations so that ships can be evaluated and analyzed for evacuation. [PERSON] et al.