In this paper, a multimodal optimization framework is proposed that combines vehicular traffic and mass transit for emergency evacuation. A multi-objective approach is used to optimize the multimodal evacuation procedure,namely three objectives are investigated: minimizing in-vehicle travel time, minimizing at-origin waiting time, and minimizing fleet cost in case of mass transit evacuation. For auto-evacuees, an Optimal Spatio-Temporal Evacuation (OSTE) formulation is presented for generating optimal demand scheduling, destination choice, and route choice simultaneously. The solution algorithm for the OSTE implements Dynamic Traffic Assignment (DTA) techniques coupled with Genetic Optimization. For transit-vehicles, a Multi-Depots, Time Constraints, Pickup-Delivery Vehicle Routing Problem (MDTCPD-VRP) is formulated to model the use of Mass Transit in evacuation situations.The proposed MDTCPD-VRP is solved using methods of Constraint Programming(CP). The OSTE and MDTCPD-VRP are integrated in one framework to replicate the impact of congestion caused by auto-evacuees on transit-vehicle travel times. The methodology is applied to a case study of a hypothetical evacuation event in the downtown area of the City of Toronto. The results show that including both the waiting time and the in-vehicle travel time in the objective function reduced the network clearance time for auto-evacueesby 40% compared to including only the in-vehicle travel time. For mass transit, when considering fleet cost, an increase of 13% in network clearness time for transit-evacuees was observed with a decrease of 12% in fleet size. Mass transit was shown to provide latent transportation capacity thatis surely needed in evacuation situations.
Abstract