# Visualization of Emergency Evacuation Physical Behavior under Multi-Agent Decision-Making
## 1 Introduction  
In the event of an accident in a highly populated place, internal evacuation is very difficult, and mass casualties due to evacuation problems are very likely to occur [1]. The physical behavior of pedestrians during emergency evacuation falls under the category of evacuation dynamics, which is particularly prone to panic due to the limited and crowded environment in such crowded building environments, thus affecting evacuation efficiency and causing unnecessary casualties due to stampedes [2]. Therefore, an engineer is required to analyze the fire safety design of the building, and in such analysis usually, the engineer compares the output of the fire modeling with the estimated evacuation time of the building to assess whether there is enough time for the occupants to evacuate the structure [3, 4]. However, evacuation time is susceptible to the physical behavior of evacuees, and the importance of behavioral factors in emergency evacuation was discussed by [PERSON] as early as 1964, and these behaviors include partnering behavior, obstacle avoidance behavior, and exit competition behavior [5], which has received extensive attention from scholars in the fields of physics, psychology, computer science, and sociologists [6, 7]. [PERSON] et al., discussed the need to incorporate evacuation behavior into evacuation planning and modeling to support the incorporation of physical behavior (individual or collective) into evacuation models [8, 9], but due to the complexity of physical behavior, there is a plethora of research on physical behavior during evacuations. With the rapid development of computer simulations, researchers have introduced these physical behaviors into simulation models for the evaluation of fire safety design of buildings and solutions for behavioral factors [10]. For such problems, evaluation modelsat this stage are divided into two main categories: macroscopic and microscopic [11; 12; 13; 14; 15]. Macro is mainly studied for theoretical purposes, analyzing pedestrian movement characteristics, bottleneck effects, and crowding phenomena using more advanced model effects. However, macro models usually consider the crowd as a whole and ignore the interactions between pedestrians and pedestrians and pedestrians and the environment. Microscopic models, on the other hand, address detailed studies, such as human-person interaction forces. There have been many studies on microscopic models, including the cellular automata model [13; 16; 17; 18; 19; 20], social force models [21; 22; 23; 24; 25; 26; 27; 28], and lattice gas models [29; 30]. However, the difficulties of evacuation research are reflected in the large arbitrariness of pedestrian movement, the many factors that influence their behavior, and the complex walking behavior. The evacuation process and the realism of existing models can be greatly limited from the perspective of pedestrian factors, such as pedestrian psychological state and command execution. Crowd behavioral understanding is critical in a wide range of applications because crowd action essentially consists of a continuous decision-making process based on a vast array of factors, such as the pedestrian's destination, interactions with nearby pedestrians, and interactions with upcoming events. In addition to the number of factors that influence pedestrian decision-making, how humans consider these factors before making a decision is also underutilized. Humans do not simply act on them. They also anticipate future states and drive current actions backward. A typical example is when two people traveling in orthogonal directions are constantly positioning themselves about each other to predict whether they will collide. Therefore, it is significant to focus on methods and techniques for safe evacuation assessment [1]. However, most of the current emergency evacuation models have problems such as insufficient detail situation (realism), low reusability, poor operability, and lack of subsequent scalability hardly support the above work effectively.