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Predicting Flow Breakdown Probability and Duration in Stochastic Network Models: Impact on Travel Time Reliability...

by Jing Dong, Hani Mahmassani
Publication Type
Conference Paper
Publication Date
Conference Name
90th Annual Meeting of the Transportation Research Board
Conference Location
Washington DC, District of Columbia, United States of America
Conference Date
-

This paper proposes a methodology to produce random flow breakdown endogenously in a mesoscopic operational model, by capturing breakdown probability and duration. Based on previous research findings that probability of flow breakdown can be represented as a function of flow rate and the duration can be characterized by a hazard model. By generating random flow breakdown at various levels and capturing the traffic characteristics at the onset of the breakdown, the stochastic network simulation model provides a tool for evaluating travel time variability. The proposed model can be used for (1) providing reliability related traveler information; (2) designing ITS (intelligent transportation systems) strategies to improve reliability; and (3) evaluating reliability-related performance measures of the system.