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Joint link-based credit charging and road capacity improvement in continuous network design problem

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  • Wang, Guangmin
  • Gao, Ziyou
  • Xu, Meng
  • Sun, Huijun

Abstract

In this paper, we will discuss the urban road network improvement problem from both supply and demand sides, and propose a bilevel programming model considering joint optimal link-based tradable credit charging scheme and road capacity improvement. The upper level decision-maker tries to minimize the total system travel time under a budget constraint by optimizing both link-based credit charging and road capacity improvement, whilst at the lower level considering the users’ route choice behavior through the generalized travel time including the travel time and the converted time from the value of credit charging for using the link. Therefore, this proposed model integrates the improvement of the urban road network according to improving the road capacity with the given budget constraint and decreasing the travel demand with the tradable credit scheme. After presenting a relaxation algorithm, the numerical experiments on the nine node network are illustrated. Analysis shows that the proposed model is efficient in mitigating traffic congestion according to the less total system travel time than the other ways compared in this paper. The tradable credit scheme offers the better combination of cost-effectiveness, administrative flexibility and distributional fairness comparing with congestion pricing. Moreover, this tradable credit scheme is revenue neutral.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:transa:v:67:y:2014:i:c:p:1-14
    DOI: 10.1016/j.tra.2014.05.012
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    Cited by:

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    3. Wang, Guangmin & Gao, Ziyou & Xu, Meng, 2019. "Integrating link-based discrete credit charging scheme into discrete network design problem," European Journal of Operational Research, Elsevier, vol. 272(1), pages 176-187.
    4. Wang, Guangmin & Xu, Meng & Grant-Muller, Susan & Gao, Zaihan, 2020. "Combination of tradable credit scheme and link capacity improvement to balance economic growth and environmental management in sustainable-oriented transport development: A bi-objective bi-level progr," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 459-471.
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    6. Zhang, Fang & Lu, Jian & Hu, Xiaojian & Fan, Ruochuan & Chen, Junlan, 2022. "Managing bottleneck congestion with tradable credit scheme under demand uncertainty," Research in Transportation Economics, Elsevier, vol. 95(C).
    7. Xu, Meng & Grant-Muller, Susan & Gao, Ziyou, 2015. "Evolution and assessment of economic regulatory policies for expressway infrastructure in China," Transport Policy, Elsevier, vol. 41(C), pages 42-49.
    8. Ge Gao & Xinmin Liu & Huijun Sun & Jianjun Wu & Haiqing Liu & Wei (Walker) Wang & Zhen Wang & Tao Wang & Haoming Du, 2019. "Marginal Cost Pricing Analysis on Tradable Credits in Traffic Engineering," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-10, January.
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