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Synergies of combining demand- and supply-side measures to manage congested streets

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  • Itani, Ibrahim
  • Cassidy, Michael J.
  • Daganzo, Carlos

Abstract

An agent-based, multichannel simulation of a downtown area reveals the impacts of both time-shifting traffic demand with congestion pricing, and supplying extra capacity by banning left turns. The downtown street network was idealized, and loosely resembles central Los Angeles. On the demand-side, prices were set based on time-of-day and distance traveled. On the supply side, left-turn maneuvers were prohibited at all intersections on the network.

Suggested Citation

  • Itani, Ibrahim & Cassidy, Michael J. & Daganzo, Carlos, 2021. "Synergies of combining demand- and supply-side measures to manage congested streets," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 172-179.
    • Handle: RePEc:eee:transa:v:151:y:2021:i:c:p:172-179
    DOI: 10.1016/j.tra.2021.07.002
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    1. Björn Hårsman & John M. Quigley, 2010. "Political and public acceptability of congestion pricing: Ideology and self-interest," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 29(4), pages 854-874.
    2. Witold J. Henisz, 2002. "The institutional environment for infrastructure investment," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 11(2), pages 355-389.
    3. Nie, Yu (Marco) & Yin, Yafeng, 2013. "Managing rush hour travel choices with tradable credit scheme," Transportation Research Part B: Methodological, Elsevier, vol. 50(C), pages 1-19.
    4. Eliasson, Jonas & Hultkrantz, Lars & Nerhagen, Lena & Rosqvist, Lena Smidfelt, 2009. "The Stockholm congestion - charging trial 2006: Overview of effects," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(3), pages 240-250, March.
    5. Jordi Casas & Jaime L. Ferrer & David Garcia & Josep Perarnau & Alex Torday, 2010. "Traffic Simulation with Aimsun," International Series in Operations Research & Management Science, in: Jaume Barceló (ed.), Fundamentals of Traffic Simulation, chapter 0, pages 173-232, Springer.
    6. Meng, Qiang & Liu, Zhiyuan & Wang, Shuaian, 2012. "Optimal distance tolls under congestion pricing and continuously distributed value of time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(5), pages 937-957.
    7. Vickrey, William S, 1969. "Congestion Theory and Transport Investment," American Economic Review, American Economic Association, vol. 59(2), pages 251-260, May.
    8. Zhang, Xiaoning & Yang, Hai, 2004. "The optimal cordon-based network congestion pricing problem," Transportation Research Part B: Methodological, Elsevier, vol. 38(6), pages 517-537, July.
    9. Lovell, David J. & Daganzo, Carlos F., 2000. "Access control on networks with unique origin-destination paths," Transportation Research Part B: Methodological, Elsevier, vol. 34(3), pages 185-202, April.
    10. Nicholas E. Burger & Daniel T. Kaffine, 2009. "Gas Prices, Traffic, and Freeway Speeds in Los Angeles," The Review of Economics and Statistics, MIT Press, vol. 91(3), pages 652-657, August.
    11. Cassidy, Michael J. & Rudjanakanoknad, Jittichai, 2005. "Increasing the capacity of an isolated merge by metering its on-ramp," Transportation Research Part B: Methodological, Elsevier, vol. 39(10), pages 896-913, December.
    12. Harrington, Winston & Krupnick, Alan J. & Alberini, Anna, 2001. "Overcoming public aversion to congestion pricing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(2), pages 87-105, February.
    13. Daganzo, Carlos F., 2007. "Urban gridlock: Macroscopic modeling and mitigation approaches," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 49-62, January.
    14. Bhat, Chandra R., 1997. "Work travel mode choice and number of non-work commute stops," Transportation Research Part B: Methodological, Elsevier, vol. 31(1), pages 41-54, February.
    15. Shin, Eun Jin, 2020. "Commuter benefits programs: Impacts on mode choice, VMT, and spillover effects," Transport Policy, Elsevier, vol. 94(C), pages 11-22.
    16. Yang, Hai & Bell, Michael G. H., 1997. "Traffic restraint, road pricing and network equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 31(4), pages 303-314, August.
    17. Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-479, June.
    18. Han, Deren & Yang, Hai & Wang, Xiaolei, 2010. "Efficiency of the plate-number-based traffic rationing in general networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(6), pages 1095-1110, November.
    19. Daganzo, Carlos F. & Lehe, Lewis J., 2015. "Distance-dependent congestion pricing for downtown zones," Transportation Research Part B: Methodological, Elsevier, vol. 75(C), pages 89-99.
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