Cell-Based Dynamic Equilibrium Models

Part of the Complex Networks and Dynamic Systems book series (CNDS, volume 2)


Cell-based dynamic equilibrium models are one class of dynamic traffic assignment (DTA) models that can capture equilibrium conditions and realistic traffic dynamics, such as queue spillback, queue formulation, and queue dissipation. However, compared with point-queue DTA models or DTA models using whole-link delay models for flow propagation, cell-based equilibrium models are often more computational demanding. This may raise issues for actual applications, in particular, for the implementation for real-time traffic control and route guidance applications, because the solution must be obtained quickly. Moreover, recent cell-based dynamic equilibrium models tend to capture more realistic travel behavior and traffic dynamics but this made the resulting models even more complicated and more difficult to solve for optimal solutions. Hence, this article aims at reviewing the recent development of cell-based dynamic equilibrium models, the formulation approaches, solution methods used, and the components of these models so as to point out the implementation issues of the latest cell-based dynamic equilibrium model with the consideration supply stochasticity for traffic control and route guidance applications as well as some gaps for future research directions.


Route Choice Dynamic Traffic Assignment Cell Transmission Model Dynamic User Equilibrium Departure Time Choice 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The work described in this paper was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (HKU 716312E). The author is grateful for the two reviewers for their constructive comments.


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© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of Civil EngineeringUniversity of Hong KongHong KongHong Kong

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