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Managing rush hour travel choices with tradable credit scheme

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  • Nie, Yu (Marco)
  • Yin, Yafeng

Abstract

This paper Analyzes a new tradable credit scheme (TCS) for managing commuters’ travel choices, which seeks to persuade commuters to spread evenly within the rush hour and between primary and alternative routes so that excessive traffic congestion can be alleviated. The scheme defines a peak time window and charges those who use the primary route within that window in the form of mobility credits. Those who avoid the peak-time window, by either traveling outside the peak time window or switching to the alternative route, may be rewarded credits. A market is created such that those who need to pay credits can purchase them from those who acquire them from their rewarding travel choices. A general analytical framework is proposed for a system of two parallel routes. The framework (1) considers a variety of assumptions about commuters’ behavior in response to the discontinuous credit charge introduced at the boundary of the peak-time window, (2) allows modeling congestion effects (or demand elasticity) on the alternative route, and (3) enables both the design of system optimal TCS and the analysis of the efficiency of any given TCS. Our analyses indicate that the proposed TCS not only achieves up to 33% efficiency gains in the base scenario, but also distributes the benefits among all the commuters directly through the credit trading. The results also suggest that very simple TCS schemes could provide substantial efficiency gains for a wide range of scenarios. Such simplicity and robustness are important to practicability of the proposed scheme. Numerical experiments are conducted to examine the sensitivity of TCS designs to various system parameters.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:transb:v:50:y:2013:i:c:p:1-19
    DOI: 10.1016/j.trb.2013.01.004
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    6. Zhu, Shanjiang & Du, Longyuan & Zhang, Lei, 2013. "Rationing and pricing strategies for congestion mitigation: Behavioral theory, econometric model, and application in Beijing," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 210-224.
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    12. Yu Nie, 2015. "A New Tradable Credit Scheme for the Morning Commute Problem," Networks and Spatial Economics, Springer, vol. 15(3), pages 719-741, September.
    13. Ren-Yong Guo & Hai Yang & Hai-Jun Huang & Zhijia Tan, 2016. "Day-to-Day Flow Dynamics and Congestion Control," Transportation Science, INFORMS, vol. 50(3), pages 982-997, August.
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    18. Xu, Meng & Grant-Muller, Susan, 2016. "Trip mode and travel pattern impacts of a Tradable Credits Scheme: A case study of Beijing," Transport Policy, Elsevier, vol. 47(C), pages 72-83.
    19. Wang, Guangmin & Gao, Ziyou & Xu, Meng & Sun, Huijun, 2014. "Joint link-based credit charging and road capacity improvement in continuous network design problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 1-14.
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