Urban gridlock: Macroscopic modeling and mitigation approaches
AbstractThis paper describes an adaptive control approach to improve urban mobility and relieve congestion. The basic idea consists in monitoring and controlling aggregate vehicular accumulations at the neighborhood level. To do this, physical models of the gridlock phenomenon are presented both for single neighborhoods and for systems of inter-connected neighborhoods. The models are dynamic, aggregate and only require observable inputs. The latter can be obtained in real-time if the neighborhoods are properly instrumented. Therefore, the models can be used for adaptive control. Experiments should determine accuracy. Pareto-efficient strategies are shown to exist for the single-neighborhood case, and optimality principles are introduced for multi-neighborhood systems. The principles can be used without knowing the origin-destination table or the precise system dynamics.
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Bibliographic InfoArticle provided by Elsevier in its journal Transportation Research Part B: Methodological.
Volume (Year): 41 (2007)
Issue (Month): 1 (January)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description
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- Daganzo, Carlos F., 2005. "Improving City Mobility through Gridlock Control: an Approach and Some Ideas," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt7w6232wq, Institute of Transportation Studies, UC Berkeley.
- Todd Litman, 2005. "London Congestion Pricing – Implications for Other Cities," CESifo DICE Report, Ifo Institute for Economic Research at the University of Munich, vol. 3(3), pages 17-21, November.
- Munoz, Juan Carlos & Daganzo, Carlos, 2000. "Experimental Characterization of Multi-Lane Freeway Traffic Upstream of an Off-Ramp Bottleneck," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8635j1df, Institute of Transportation Studies, UC Berkeley.
- Cassidy, Michael J., 1998. "Bivariate relations in nearly stationary highway traffic," Transportation Research Part B: Methodological, Elsevier, vol. 32(1), pages 49-59, January.
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