Evacuation Network Optimization Based on Contraflow and Conflict Elimination for Pedestrian-Vehicle Mixed Flows

People under emergencies will choose different traffic modes (walking, driving, etc.) for evacuation. In this circumstance, the conflicts of the mixed flows (pedestrians and vehicles) at various locations in the network can be critical to the operational efficiency of the evacuation activities. This paper proposes an evacuation network optimization approach based on conflict elimination and contraflow strategy by separating pedestrian and vehicle flows with physical barriers at road intersections and reverse pedestrians and vehicles on main evacuation routes, respectively. A multi-objective optimization model is formulated to determine the appropriate locations of barriers or blocks in the evacuation network. A genetic based algorithm is developed to solve the optimization problem. The proposed model is tested for an evacuation zone with the area of 2 km² in Wuhan city. Besides, the sensitivity analysis is implemented for different mixing ratios of pedestrians and vehicles. The results show that the proposed approach can effectively separate pedestrian and vehicle flows at intersections to improve the evacuation efficiency, and the improvements are greater when pedestrians take a higher percentage in the evacuation system.