Ego-centered Path Planning in Evacuation Simulation

Path planning is one of the critical issues of evacuation simulations. We present a real-time path planning approach under the microscopic simulation framework. Based on his/her cognitive ability, a cognitive field around each pedestrian is constructed during simulation. The environment information perceived by each individual is recorded in different accuracy in different sub-regions of his/her cognitive field. During path planning, the pedestrian will account factors including time-cost, safety of the path and the crowd flow etc., which we model as mental cost, based on the information provided by the cognitive field to evaluate the priority of each candidate path. An algorithm is developed to estimate the mental cost to select the best evacuation path. During simulation, the cognitive field of each pedestrian will keep updated and the pedestrian can adjust his/her original evacuation path if necessary. We adopt Mental A* algorithm to search the path from the navigation graph. Experiments regarding different scenarios demonstrate the effectiveness of our approach.