Young Researcher Award

This paper presents the development of a novel framework that optimizes the evacuation of large cities using multiple modes including vehicular traffic, rapid transit, and mass transit shuttle buses. A large-scale evacuation model is developed for the evacuation of the City of Toronto in cases of emergency. A demand estimation model is first designed to accurately quantify the evacuation demand by mode (drivers vs. transit users), over time of the day when the crisis begins and over space (location). The output of the demand estimation model is then fed into two optimization platforms: (1) an Optimal Spatio-Temporal Evacuation (OSTE) model that synergizes evacuation scheduling, route choice, and destination choice for vehicular traffic and (2) a model based on a new variant of the Vehicle Routing Problem (VRP) to optimize the routing and scheduling of mass transit vehicles. The study concluded that OSTE can clear the City of Toronto four times faster than the do-nothing strategy. The OSTE average automobile evacuation time for the 1.21 million people using their cars is close to 2 hours. The optimization of the routing and scheduling of the readily available Toronto Transit Commission (TTC) fleet (4 Rapid Transit lines and 1320 transit buses used as shuttles) can efficiently evacuate the transit-dependent population (1.34 million) within 2 hours.