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Reversible lane network design for maximizing the coupling measure between demand structure and network structure

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  • Di, Zhen
  • Yang, Lixing

Abstract

This paper investigates demand-originated reversible lane design plans for transportation networks, where the tidal and asymmetrical characteristics of the demand structure are taken into consideration. Compared to traditional network design methods, this reversible lane technique has some advantages. It not only can improve the performance of the considered network by taking full advantage of the potential resources and existing infrastructures but is also easy to operate, returns rapidly, is less costly and requires no additional land. Specifically, this study first defines a coupling measure to quantify the relationship between network structure and demand structure. Then, focusing on maximizing the coupling measure, a nonlinear bilevel mixed-integer programming model is presented to find the optimal lane combination strategy in the considered network from the viewpoint of systematology. For solving the proposed model, we design heuristic algorithms to obtain its approximate optimal solution. Finally, the effectiveness of the proposed approaches is examined on the Sioux Falls network and Beijing main road network.

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  • Di, Zhen & Yang, Lixing, 2020. "Reversible lane network design for maximizing the coupling measure between demand structure and network structure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    • Handle: RePEc:eee:transe:v:141:y:2020:i:c:s1366554520306724
    DOI: 10.1016/j.tre.2020.102021
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    Cited by:

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    2. Qiang Zhang & Shi Qiang Liu & Andrea D’Ariano, 2023. "Bi-objective bi-level optimization for integrating lane-level closure and reversal in redesigning transportation networks," Operational Research, Springer, vol. 23(2), pages 1-51, June.
    3. Zhang, Xiang & Liu, Wei & Levin, Michael & Travis Waller, S., 2023. "Equilibrium analysis of morning commuting and parking under spatial capacity allocation in the autonomous vehicle environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 172(C).
    4. Weiqi Hong & Zishu Yang & Xu Sun & Jianyu Wang & Pengpeng Jiao, 2022. "Temporary Reversible Lane Design Based on Bi-Level Programming Model during the Winter Olympic Games," Sustainability, MDPI, vol. 14(8), pages 1-17, April.
    5. Fu, Xiao & Wu, Youqi & Huang, Di & Wu, Jianjun, 2022. "An activity-based model for transit network design and activity location planning in a three-party game framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    6. Wang, Yu & Liu, Haoxiang & Fan, Yinchao & Ding, Jianxun & Long, Jiancheng, 2022. "Large-scale multimodal transportation network models and algorithms-Part II: Network capacity and network design problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    7. Chi Sun & Weiqi Hong & Hao Li & Chenjing Zhou, 2022. "Lane Optimization of Highway Reconstruction and Expansion Work Zone Considering Carbon Dioxide Emission Factors," Sustainability, MDPI, vol. 14(19), pages 1-17, September.

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