Computational Modeling is a useful tool for ensuring safety conditions in Road Tunnels. Designers often have to face the problem of modeling the evacuation process through only one model and this could lead to mistakes caused by its weak points. A holistic approach is necessary in order to understand the evacuation process better, but in non-research applications it is not always applied and the influence of the factors related to Human Behavior could be wrongly modeled. The case of road tunnel fires includes specific problems related to Human Behavior such as the analysis of pre-movement times (e.g. reluctance to leave the vehicle)1,2,3, interactions between occupants initially located in different parts of the tunnel, interactions between occupants and smoke coming from the accident4, smoke influence on walking speed4,5,6, herding behaviors, way-finding, etc. Information about these factors can be obtained from real data, experiments or evacuation drills. The most reliable studies are based on real data, but unfortunately these data are hard to collect. On the other hand, there is not much experimental literature available (as the real conditions are not easy to reproduce). Designers require a deep knowledge not only about the model features, but also about the inputs that cannot be inserted into the model. They need to know the modeling method itself and the specific features of each model. The comparison between different models will make this work easier and the purpose of this paper is to give the practitioners information to properly model emergency scenarios during road tunnel evacuations. Fahy and Proulx7 identify the primary goal of this kind of comparison analysis. It can be summarized as a process of understanding the sources of uncertainty and variability in egress models, focusing on variables that “may have an impact on the results of the egress model that is significant enough to cause a change in an engineer's design”7.