## 1 Introduction
### Literature Review
#### 1.2.2 Pedestrian Dynamics and Passenger Decision Making  
The ultimate goal of analyzing the exit width, exit location, and bottleneck area is to identify the behaviors of passengers and simulate their decision-making process, which dominantly determine the path selection, passenger flow on paths or links, and total travel time in platform navigation. Pedestrian dynamics is the main paradigm used to investigate the aforementioned issues, and it can be roughly divided into a macroscopic model and microscopic model [21]. The macroscopic model views pedestrians as a whole, moving in a manner similar to liquid. Thus, concepts such as density, speed, and flow are introduced into the simulation and prediction of the status of pedestrians' movements [21; 22; 23; 24]. The relationship between speed, density, and flow determines the optimal dimensions of facilities [25]. Scholars empirically measure and estimate this relationship through experiments under different circumstances. Unfortunately, the significant differences between various research results [26] imply that there are no fixed and precise functional relations among them, requiring the fitted model to be correct based on observed data. Additionally, the macroscopic model ignores individual choice behaviors and has poor performance in application scenarios for small-scale pedestrians. Conversely, microscopic models focus on each pedestrian's choice behavior to describe their movements on links, paths, and key locations. This type of model mainly includes Cellular Automata, the social force model, the game-theoretic model, and the mathematical optimization model. The Cellular Automata (CA) model was used to divide the layout of a place into cells and to represent each cell as a pedestrian [27]. Thus, a pedestrian makes decisions relying on the adjacent cells in a predefined set of rules. The authors of [28] further developed a new model that allows several pedestrians in one cell or a single pedestrian to occupy multiple cells for more detailed information. The social force (SF) model has received the most attention and was adopted in the description of pedestrian reactions to the surroundings in recent years. The authors of [29]introduced the SF model to stimulate pedestrian movement on stairs. To conduct a more in-depth study on exit selection, the authors of [30] categorized pedestrians into different groups with the SF model, which can be summarized as the modified social force (MSF) model. The authors of [31] introduced the utility function to the SF model and formulated the results of exit choices by calculating the utility value. Game theory originates from economics and has also been applied to pedestrian dynamics. When considering game theory, it often means treating pedestrians as smart individuals with rational expectations so that their choices can be more accurately predicted. An early study [32] adopted game theory to predict the walking behavior of pedestrians. Subsequently, several works continued to extend game theory to investigate pedestrian behaviors based on equilibrium principles [33]. Mathematical programming methods are also widely used for modeling individual behaviors. In order to evacuate people through exits with the goal of the shortest time, the authors of [34] developed a fast dynamic programming evacuation approach to assign the optimal number of evacuees to each possible path. The authors of [35] focused on the problem of facilitating the final exit assignment and proposed an integer programming model to minimize the average evacuation time in a complex building when an emergency event occurs. The authors of [36] established a simulation-optimization model, which combines the Genetic Algorithm (GA) with the microscopic traveler assignment model, aiming to help evacuees find the optimal exit gates and start times in a large-scale evacuation problem with multiple exits. Pedestrian dynamics provides an important perspective for modeling passenger decision making.