Methods and Tools to Strengthen Transit System Resilience

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Transit riders dislike nothing in their journeys more than long delays and overcrowding of transit vehicles, according to the results of most rider satisfaction surveys around the world. Many factors can cause transit delays, ranging from minor perturbations in the operating environment all the way to major incidents due to emergencies or system failure. In Toronto, the subway system alone is afflicted by more than 12000 incidents/year, approximately 1000 of which are considered "major". Transit delays often exacerbate overcrowding, and the opposite is also true. The cost to users and the operator can be enormous. One recent study estimated the economic cost of user delays due to subway incidents in New York to be upward of 389 million USD annually. This research program is aimed directly at tackling the problems of delays and overcrowding in large multi-modal transit systems. It adopts a broad, multi-faceted approach which will produce solutions for demand management, supply management and flow management, all aimed consistently and coherently at alleviating transit delays and overcrowding, particularly in subway systems. To manage demand, our research will develop innovative incentive-based programs which offer reward points to transit riders who switch away from overcrowded spots and times. Incentive-based and loyalty programs have been applied effectively to a variety of other services and industries, and while they are slowly being introduced to public transit they require supporting empirical tools to maximize their effectiveness. These tools will be developed in this research. To manage supply, specifically in the event of a major disruption to subway service, we will develop a system of models and tools to help transit agencies deploy effective shuttle bus services to fill the gap in subway service. In more specific terms, we will develop analytics to predict in real-time the expected duration of any given subway incident, and we will determine the optimal number of buses and which routes these buses should be pulled from for dispatching to the disrupted subway section such that total delays are minimized. The third major track of this research is concerned with managing the flows of passengers into all stations of a subway line to avoid capacity loss due to overcrowding. This will be achieved through creative scheduling of the bus and streetcar feeder lines connecting with the subway line, along with a real-time control strategy to avoid oversaturation at any given station. The proposed solutions will be developed using the rich and diverse data on transit operations and demand which are now available abundantly. Founded in sound theory, the proposed models will be built using rigorous and new modelling approaches. The proposed research is likely to have a transformative effect on transit resilience policy and technologies.