Abstract

ABSTRACTIn urban public transportation system, operators tend to set a series of time points and scheduled travel time (STT) to monitor bus operation. Meanwhile, bus drivers are generally supposed to adjust speed to keep on schedule, among which STT is of rather importance. This paper aims to develop a multistate-based model to design travel time schedule for fixed transit route. First, multistate model is used to identify service states and model travel time distribution. Then, an optimization model was proposed, followed by a Monte Carlo simulation-based genetic algorithm procedure to obtain the optimal slack time. A numerical example from a fixed transit route in the city of Shenzhen, China was used to demonstrate the model applicability. The results indicate that the multistate model fits real-world travel time better than lognormal distribution model. For the optimal solutions, sensitivity analysis with respect to random samples and deployed buses was also conducted. Findings of this study may be used for transit travel time modeling and timetable design.

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