## 4 Evacuation Model Design
As a final point, information on the distribution of the vehicles in the road network is required to inform operators about how various vehicles are dispersed and move along the routes [45]. The evacuation under the threat of wildfire modeling research is still in its early stages, and few are available. An agent-based simulation model (ABM) was developed by [PERSON] et al. [46] to study the behavior of evacuees in case of a fast-moving wildfire toward a community. A \"Post-disaster Survey\" and decision tree methods were used to model agent movements and decisions. The survey was conducted on the evacuees in Red Cross shelters just weeks after the evacuation from the 2018 Camp fire in northern California. Another study modeled awareness of the residents, departure, and preparation time in case of a no-notice wildfire evacuation [47]. The effects of age, race, income, and other characteristics of a resident at the time of being alerted to a wildfire were assessed. It was shown that smartphones and a community evacuation plan significantly and positively affect no-notice fire awareness time [47]. [PERSON] et al. [44] focused their study on the modeling of wildland-urban interface fire evacuations. Since the most important \"layers\" of a WUI wildfire, including wildfire, pedestrians, and traffic, were mainly modeled in isolation beforehand, this research presented a framework for evacuation simulation, including all the layers. This study obtained a more realistic framework to simulate wildfire evacuation. [PERSON] et al. [22] also developed a new method for delimiting wildfire evacuation trigger points using fire spread modeling and geographic information system (GIS). It was suggested that a trigger buffer could be computed using wind, topography, and fuel data in conjunction with estimated evacuation time. This trigger buffer is for a community whereby an evacuation is recommended if a fire crosses the edge of the buffer. Additionally, in an attempt to couple the fire simulation, pedestrian evacuation, and traffic, [PERSON] et al. [48] developed the WUI-NITY platform, which simultaneously models fire and evacuation to enhance situational awareness in evacuation scenarios. This model is currently the only evacuation model that considers the effects of wildfire on the evacuation process. [PERSON] et al. [49] provided a method for creating triggers by linking models for wildfires and evacuations. They used the fire spread model FARSITE to incorporate the earlier theory of [PERSON] et al. [22] and others on triggers into a tool known as PERIL for establishing trigger perimeters around a community. A safety factor was added to account for errors in the computations for an evacuation or a wildfire. [PERSON] [50] developed a data-driven evacuation simulation model for wildfire scenarios using different types of data, evacuation simulation models, and GIS to improve evacuation time in holiday homes and resorts. Car ownership and occupancy rates in second homes were considered two important factors in evacuation times, and results showed that they have high correspondence with evacuation time. [PERSON] et al. [51] made benchmarks for evacuation simulation models under the threat of wildfires. Using observations and questionnaires during evacuation drills in Roxburgh Park, Colorado they collected evacuation-related data such as the initial position of residents, time required before evacuation for preparation, route choice and use, and arrival time at specified locations as evacuation destinations. These data were used as inputs for two evacuation simulation models, WUI-NITY platform and Evacuation Management System, that use different modeling approaches over a variety of assumptions in different scenarios to create benchmarks. Based on the analyzed literature, to design an evacuation model, initially, four specific sub-models must be created.