Real-time integrated re-scheduling for public transit

Abstract

© Civil-Comp Press, 2016. The research described in this paper is motivated by the operations of a public transit company in Hong Kong. We investigate how real-time information can be utilized in combination with historical data to improve the controllers' routing and scheduling decisions practically. A dynamic and integrated vehicle and crew scheduling problem is introduced with the following characteristics: 1) The travel times are stochastic and time-dependent, and its realizations are only revealed during the execution of the plan. 2) The schedule can be revised when updated information is provided or when unexpected events occur. The objective is to maximize the route frequencies and mileage in order to provide good service to passengers, and simultaneously minimize overtime and mealbreak delays for motormen. To mitigate unexpected delays due to uncertainties in operations, various mathematical models are proposed for revising the schedules in real-time under a rolling-horizon framework. The efficiency and the effectiveness of the formulations are evaluated via simulation using real-world data.