Robustness of the off-line a priori stochastic dynamic traffic assignment solution for on-line operations

Robustness of the off-line a priori stochastic dynamic traffic assignment solution for on-line operations

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Article ID: iaor2001388
Country: United Kingdom
Volume: 7C
Issue: 5
Start Page Number: 281
End Page Number: 303
Publication Date: Oct 1999
Journal: Transportation Research. Part C, Emerging Technologies
Authors: ,
Keywords: traffic flow
Abstract:

This paper focuses on the off-line stochastic dynamic traffic assignment (DTA) problem as part of a hybrid framework that combines off-line and on-line strategies to solve the on-line DTA problem. The primary concept involves the explicit recognition of stochasticity in origin–destination (O–D) demand and/or network supply conditions to determine a robust off-line a priori solution that serves as the initial solution on-line. This strategy ensures that the computationally intensive components, which exploit historical data, are executed off-line while circumventing the need for very accurate on-line O–D demand forecast models. Thereby, efficient on-line reactive strategies could be used to address unfolding traffic conditions. The paper investigates the robustness of the off-line a priori DTA solution under plausible on-line situations. The results illustrate the superiority of the a priori solution over the currently used mean O–D demand-based solution for on-line route guidance applications.

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