## 1 Introduction
### Literature Review
Parameters also make it difficult to reflect differences between individuals. These two models have been widely used in studying the exit choice behavior of evacuees in rooms. During the evacuation process, the selection of exits is also crucial, and many researchers have conducted extensive research based on the above models. First, based on the social force model, an exit model was modified to evaluate several important factors influencing multiple exit scenarios [18; 19; 20; 21; 22; 23; 24]. [PERSON] and [PERSON] found that the number of luggage-laden pedestrians was the main factor for the increase in evacuation time, and the relationship between time and population density is not monotonic [18]. [PERSON] et al. pointed out that evacuation efficiency sensitively depends on the arrangement of obstacles for multi-exits configurations [20]. [PERSON] et al. simulated the number and positions of evacuation leaders on the evacuation dynamics in rooms with limited visibility range, and they found that each leader should head to a different exit, otherwise the evacuation efficiency was slower [21]. Second, using the cellular automata model, [PERSON] et al. not only revealed that the spatial distance to exits and the occupant density were two important factors influencing evacuated the decision-making of the personals [25], but they studied the evacuation time with different exit widths and suggested that the symmetrical layout of the exits should be applied. Additionally, [PERSON] et al. [26] studied the exit-choosing behavior conserving the reserve capacity in rooms with multiple exits; similar issues were also discussed from the influencing factors, such as destination, utilization of the exit area [27], and seat pitch in aircraft [28]. A series of these studies have characterized the decision-making behavior of the pedestrians, such as the evacuation flow rate [29; 30], time, and route and exit selection under the influence of the occupant density [30; 31; 32], obstacle, evacuation distance, exit size, and visibility in the process of evacuation [33]. However, it is notable that most published computer simulations using the pedestrian dynamics model did not consider the connection between the real space of the control experiment and the simulated space of the computer simulation, bringing a great influence on the study of micro behavior among pedestrians. For example, in previous work by [PERSON] et al., they pointed to that because people perform more stochastic behaviors in reality than in the model, only the overall tendency of the distribution of evacuation could be well reproduced [5]. Additionally, there were few studies on exit behavior-related to personnel trajectory characteristics. In recent years, some researchers have applied mixed reality to pedestrian research and evacuation, which helped solve this problem. Mixed Reality is an emerging technology that integrates graphics processing, human-computer interaction, computer vision, and other technologies; Mixed Reality can realize the superposition of the virtual world and the real physical world, allowing users to see the objects in each world [34]. It combines virtual elements with the real world, allowing users to perceive the natural world while interacting with virtual objects. With head-mounted devices like Microsoft's HoloLens, MR technology can superimpose virtual objects into the user's field of view to interact with these virtual elements in the natural environment. In 2018, [PERSON] et al. proposed a new eye tracking method in mixed reality applications, and conducted experiments to demonstrate the feasibility of this method [35]. In 2019, [PERSON] et al. built a fire scene visualization and interaction system based on mixed reality technology [34]. In 2022, We developed a mixed reality evacuation simulation system, providing a new method for studying crowd behavior. In this work, the mixed reality evacuation LVC simulation system was introduced into the experiments to build the connection between human behavior and the real environment.