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Multiobjective Environmentally Sustainable Optimal Design of Dedicated Connected Autonomous Vehicle Lanes

Author

Listed:
  • Yu Lin

    (Transportation College, Jilin University, Changchun 130022, China)

  • Hongfei Jia

    (Transportation College, Jilin University, Changchun 130022, China)

  • Bo Zou

    (Department of Civil, Materials, and Environmental Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA)

  • Hongzhi Miao

    (College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China)

  • Ruiyi Wu

    (Transportation College, Jilin University, Changchun 130022, China)

  • Jingjing Tian

    (Transportation College, Jilin University, Changchun 130022, China)

  • Guanfeng Wang

    (Transportation College, Jilin University, Changchun 130022, China)

Abstract

The emergence of connected autonomous vehicles (CAVs) is not only improving the efficiency of transportation, but also providing new opportunities for the sustainable development of transportation. Taking advantage of the energy consumption of CAVs to promote the sustainable development of transportation has attracted extensive public attention in recent years. This paper develops a mathematical approach to investigating the problem of the optimal implementation of dedicated CAV lanes while simultaneously considering economic and environmental sustainability. Specifically, the problem is described as a multi-objective bi-level programming model, in which the upper level is to minimize the system-level costs including travel time costs, CAV lane construction cost, and emission cost, whereas the lower level characterizes the multi-class network equilibrium with a heterogeneous traffic stream consisting of both human-driven vehicle (HVs) and CAVs. To address the multi-objective dedicated CAV lane implement problem, we propose an integrated solution framework that integrates a non-dominated sorting genetic algorithm II (NSGA-II) algorithm, diagonalized algorithm, and Frank–Wolfe algorithm. The NSGA-II was adopted to solve the upper-level model, i.e., hunting for the optimal CAV lanes implementation schemes. The diagonalized Frank–Wolfe (DFW) algorithm is used to cope with multi-class network equilibrium. Finally, numerical experiments were conducted to demonstrate the effectiveness of the proposed model and solution method. The experimental results show that the total travel time cost, total emission cost, and total energy consumption were decreased by about 12.03%, 10.42%, and 9.4%, respectively, in the Nguyen–Dupuis network as a result of implementing the dedicated CAV lanes.

Suggested Citation

  • Yu Lin & Hongfei Jia & Bo Zou & Hongzhi Miao & Ruiyi Wu & Jingjing Tian & Guanfeng Wang, 2021. "Multiobjective Environmentally Sustainable Optimal Design of Dedicated Connected Autonomous Vehicle Lanes," Sustainability, MDPI, vol. 13(6), pages 1-21, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3454-:d:521007
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    References listed on IDEAS

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    Cited by:

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    2. Qingyu Luo & Rui Du & Hongfei Jia & Lili Yang, 2022. "Research on the Deployment of Joint Dedicated Lanes for CAVs and Buses," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
    3. Mohammed Al-Turki & Nedal T. Ratrout & Syed Masiur Rahman & Imran Reza, 2021. "Impacts of Autonomous Vehicles on Traffic Flow Characteristics under Mixed Traffic Environment: Future Perspectives," Sustainability, MDPI, vol. 13(19), pages 1-22, October.
    4. Wang, Guanfeng & Jia, Hongfei & Feng, Tao & Tian, Jingjing & Wu, Ruiyi & Gao, Heyao & Liu, Chao, 2024. "Modelling the dual dynamic traffic flow evolution with information perception differences between human-driven vehicles and connected autonomous vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 640(C).
    5. Chen, Shuiwang & Hu, Lu & Yao, Zhihong & Zhu, Juanxiu & Zhao, Bin & Jiang, Yangsheng, 2022. "Efficient and environmentally friendly operation of intermittent dedicated lanes for connected autonomous vehicles in mixed traffic environments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P2).

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