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High-occupancy vehicle lane management with tradable credit scheme: An equilibrium analysis

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  • Zang, Guangzhi
  • Xu, Meng
  • Gao, Ziyou

Abstract

The tradable credit scheme (TCS), as a revenue-neutral management measure, has received much attention in the field of traffic management in recent years. This paper investigates the management performance of the TCS on high-occupancy vehicle (HOV) lanes with the approach of equilibrium analysis. The analysis is based on a commuting scenario in which commuters use a multi-lane highway with HOV lanes. We developed a basic system in which commuters have two alternative travel modes: driving alone in general-purpose (GP) lanes or carpooling in HOV lanes. Under this assumption, the HOV lane management with TCSs is formulated as a mathematical programming problem. We analyze the effects with respect to feasible TCSs, effective TCSs, and optimal TCSs, respectively. We extend the basic system by considering regular carpoolers with the scenario of HOVs choosing GP lanes. Under this situation, the HOV lane management with TCSs is formulated as a variational inequality problem. We further analyze the management effects of different TCSs. Numerical examples demonstrate system indicators with several typical states, the impact of key parameters on TCS management performance, and the feature of the extended system in typical scenarios. Results show that the optimal TCS is achievable in the basic system by limiting the traffic flow of GP lanes. However, the optimal TCS may not exist in the extended system considering regular carpoolers, and a sufficient condition is proposed to guarantee its existence.

Suggested Citation

  • Zang, Guangzhi & Xu, Meng & Gao, Ziyou, 2020. "High-occupancy vehicle lane management with tradable credit scheme: An equilibrium analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
  • Handle: RePEc:eee:transe:v:144:y:2020:i:c:s1366554520307687
    DOI: 10.1016/j.tre.2020.102120
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    References listed on IDEAS

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