Cellular Automata-Based Model for Simulation of Collective Pedestrian Dynamics in Open-air Environments with Stochastic Transitions and Traffic Signs

The literature contains several studies that use cellular automata models applied to pedestrian evacuation simulations. Some of these models use the floor field concept to model scenarios and indicate the position of exits. However, most of these studies are focused on indoor environments. This study develops a new model based on the Varas model, restricting determinism by including stochastic transitions (confusion parameter) and by including road signs to reduce the impact of the new parameter. Applied to maps based on outdoor scenarios, experiments show that the new model presents a significant performance improvement in the metrics of average evacuation time and average waiting time. In addition, the inclusion of road signs also presents a considerable improvement in the average evacuation time when the scenario has a complex configuration, such as isolated regions partially closed by obstacles. This regions are unsafe spaces for pedestrians to find an exit in an emergency situation.