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This paper presents a comprehensive evaluation of traffic impacts of a mass evacuation of the Halifax Peninsula under several flooding scenarios. Flood extent and associated damages to the transport network are identified through digital elevation modeling that intersects with the Halifax stream and transport networks. The resulting flood scenarios inform a traffic microsimulation model that uses a dynamic traffic assignment-based microsimulation approach and simulates the evacuation of 34,808 evacuees estimated from the Halifax Regional Transport Network Model. The simulation results suggest that flooding of the links by 7.9 m flood reduces alternative evacuation routes by 31.2%. It takes 15 hours to evacuate 83% of evacuees while the remaining 17% are not accommodated in the network due to reduced network capacity. The number of vehicles in the network has peaked at 13,000 in this flooding scenario. An evaluation of network performance reveals a sustained congestion prevailing from 4th to 7th hour of the evacuation. The novelty of this study is that it develops a comprehensive tool of flood risk and dynamic traffic microsimulation modeling to offer an in-depth evaluation of potential impacts during evacuation. The results will help emergency professionals in evacuation planning and making emergency decisions.

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This study presents a multimodal evacuation microsimulation modeling framework. The paper first determines optimum marshal point locations and transit routes, then examines network conditions through traffic microsimulation of a mass evacuation of the Halifax Peninsula, Canada. The proposed optimization modeling approach identifies marshal point locations based on transit demand obtained from a Halifax Regional Transport network model. A mixed integer linear programming (MILP) technique is used to formulate the marshal point location and transit route choice problem. The study proposes a novel approach to solving the MILP problem, using the “branch and cut” algorithm, which demonstrates superiority in computation time and production of quality solutions. The optimization model determines 135 marshal points and 12 transit routes to evacuate approximately 8,400 transit-dependent individuals. Transit demand and marshal point locations are found to be concentrated at the core of the peninsula. The microsimulation modeling takes a dynamic traffic assignment-based approach. The simulation model predicts that it takes 22 h to evacuate all auto users but just 7 h for the transit-dependent population. The study reveals that the transit system has excess capacity to assist evacuees who switch from auto and other modes. Local traffic congestion prolongs the evacuation of a few densely-populated zones in the downtown core of the peninsula. The findings of this research help policy-makers understand the impacts of marshal point locations and transit route choice decisions on multimodal evacuation performance, and provide insights into emergency planning of multimodal evacuations under "mode switch" and transit-based evacuation scenarios.