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Traffic Congestion in Networks, and Alleviating it with Public Transportation and Pricing

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  • Daganzo, Carlos F.
  • Gonzales, Eric J.
  • Gayah, Vikash V.

Abstract

It has recently been demonstrated, both theoretically and experimentally, that the average flow and density of some urban traffic networks is related by a unique, reproducible curve known as the Macroscopic Fundamental Diagram (MFD). For networks in which vehicles cannot adaptively re-route to avoid congestion, this relationship is robust only when there are few vehicles on the network. As these types of networks become more crowded, trips are completed at a much lower rate than predicted by MFD theory. Thus, operating a network in congestion is extremely damaging on these networks. The damage is particularly harmful for networks in which multiple modes operate mixed together because the more efficient modes, such as public transportation, suffer from the congestion created by other vehicles. This tends to happen in cities when infrastructure development has not caught up with economic development; one example that we have observed is Nairobi, Kenya. One way to increase efficiency is to exclusively dedicate more of the limited road space to these efficient modes so they can operate free of congestion. The remaining road space should be rationed by some means so that it does not become overcrowded. We show that segregating modes in this way allows the network to serve the same number of person-trips with fewer vehicles and no delay. We show that this can be accomplished by pricing the modes to ensure that users behave in a way that maximizes the productivity of the network and benefits everyone.

Suggested Citation

  • Daganzo, Carlos F. & Gonzales, Eric J. & Gayah, Vikash V., 2011. "Traffic Congestion in Networks, and Alleviating it with Public Transportation and Pricing," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8qt041v8, Institute of Transportation Studies, UC Berkeley.
    • Handle: RePEc:cdl:itsrrp:qt8qt041v8
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    References listed on IDEAS

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    1. Gonzales, Eric Justin, 2011. "Allocation of Space and the Costs of Multimodal Transport in Cities," University of California Transportation Center, Working Papers qt07x7h9pg, University of California Transportation Center.
    2. Geroliminis, Nikolas & Daganzo, Carlos F., 2008. "Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 759-770, November.
    3. Daganzo, Carlos F. & Gayah, Vikash V. & Gonzales, Eric J., 2011. "Macroscopic relations of urban traffic variables: Bifurcations, multivaluedness and instability," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 278-288, January.
    4. Gonzales, Eric Justin, 2011. "Allocation of Space and the Costs of Multimodal Transport in Cities," University of California Transportation Center, Working Papers qt7s28n4nj, University of California Transportation Center.
    5. Daganzo, Carlos F., 2010. "Structure of competitive transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 434-446, May.
    6. Daganzo, Carlos F., 2007. "Urban gridlock: Macroscopic modeling and mitigation approaches," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 49-62, January.
    7. Daganzo, Carlos F. & Geroliminis, Nikolas, 2008. "An analytical approximation for the macroscopic fundamental diagram of urban traffic," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 771-781, November.
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