## 2 Related Work
### Wayfinding in Virtual Reality Training Simulations  
Wayfinding is defined as \"the ways in which people orient themselves in physical space and navigate from origin to destination [24]\". When people try to find their way to a destination in a foreign environment, they look for external information that will complement their orientation and navigation processes in this unfamiliar environment. When VR training simulations are designed for flood evacuation, it is difficult for VR users to navigate inside the unfamiliar immersive environment. Researches have shown that when people evacuate flooded areas, their wayfinding capabilities are crucial in determining the efficiency of their evacuation and hence their chances of survival. Therefore, VR environments should be designed to ensure the transfer of flood evacuation knowledge and skills gained in the VRE to the real world by incorporating wayfinding cues [24]. [PERSON] [25] used the term signifier to describe wayfinding cues by stating that \"any perceivable indicator (a signal) that communicates appropriate purpose, structure, operation, and behavior of an object to a user\". Wayfinding has been used extensively in evacuation and navigation experiments, since it creates affordances by prompting human actions [26; 27]. Various studies have investigated design, and implementation of navigation processes such as wayfinding cues inside the VRE for training and evacuation applications [28]. Researchers have suggested that VR game designers need to incorporate wayfinding processes in the VR to aid users in navigating the environment. A recent study proposed several wayfinding affordances that need to be incorporated in the VR design to assist users in constructing mental models in virtual environments [29]. Further studies have shown the use of contextual cues such as wayfinding installations, signage systems to improve users' ability to navigate through the complex VR environments [30]. Various risk mitigation institutes across the globe are adapting VR applications to train users in hazardous situations that cannot be portrayed through traditional methods. A recent study proposed two methods to encourage early evacuations during flash floods by implementing environmental or social cues in VR [31]. Results revealed the effectiveness of using VR to promote evacuation during natural disasters. [PERSON] et al. [32] used VR wayfinding installations to investigate the effect of wayfinding lights on behavioral, physiological, and psychological outcomes in indoor fire evacuation scenarios. Results showed that wayfinding affordances could be used to reduce cognitive demands, and wayfinding installations along with visual stimulus can also contribute to improved brain wiring connectivity during the game. In the past, wayfinding studies have been conducted in indoor environments [31; 33] and mostly for fire [27; 34; 35], underground rock-related hazards safety training [33] and earthquake evacuations [10; 14]. These researches have [32] suggested that further studies should be conducted to improve the evaluation process for VR evacuation trainings. Measuring the impact of wayfinding installations on user behavior and improving their effectiveness is a very important task [36]. Although VR training simulations are becoming well accepted because of the cost-effective way of providing training, few studies have used VR experiments to test flood-related behaviors. Similarly, the validity of user behaviors in VR SGs is not widely researched [31] and is critical as VR applications are increasingly being used for training. Furthermore, the methodologies to measure these VR applications' emotional impact and influence need to be developed and tested. We used a mixed-method approach to fully capture the impact of wayfinding cues in VRE to gain comprehensive understanding of user behaviors inside the VRE. The research question addressed was: What is the impact of wayfinding cues on users physiological signals and perceived quality of experience in a VR SG for flood evacuation training?