IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v636y2024ics0378437124000347.html
   My bibliography  Save this article

Modeling the road network capacity in a mixed HV and CAV environment

Author

Listed:
  • Zhou, Wenhan
  • Weng, Jiancheng
  • Li, Tongfei
  • Fan, Bo
  • Bian, Yang

Abstract

With the integration of the advanced Internet of Vehicles and autonomous driving technology, connected and autonomous vehicles (CAVs) possess a stronger information perception ability, real-time communication and cooperation ability, and a shorter reaction time. CAVs reveal great potential in increasing traffic efficiency and promoting sustainable development of urban traffic systems. Accordingly, the introduction of CAVs in the existing traffic system not only changes the driving behavior of vehicles but also reshapes the spatial distribution of traffic flow. To measure the impact of CAVs on urban traffic systems at a macro level, we first propose the concept of the road network capacity in a mixed human-driven vehicle (HV) and CAV environment and define it as the maximum total travel demand that can be accommodated by the road network. Two nonlinear programming models (NLP) are established to formulate and calculate the road network capacity (RNC) with mixed HV and CAV flows based on the assumption that CAVs’ route choice behavior follows the UE principle and the system optimal (SO) principle, respectively. Since the existence of the equilibrium conditions makes the established model challenging to solve, we reformulated the proposed model as a mixed-integer linear programming (MILP) after employing a piecewise linear approximation approach and solved it with the commercial solver. Finally, several numerical experiments based on Nguyen–Dupuis’s network demonstrate the validity of the proposed models and solution method. The change in the RNC with the variation of the CAV penetration rate and the reaction time of CAVs are also analyzed by conducting a set of sensitivity experiments.

Suggested Citation

  • Zhou, Wenhan & Weng, Jiancheng & Li, Tongfei & Fan, Bo & Bian, Yang, 2024. "Modeling the road network capacity in a mixed HV and CAV environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
  • Handle: RePEc:eee:phsmap:v:636:y:2024:i:c:s0378437124000347
    DOI: 10.1016/j.physa.2024.129526
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124000347
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2024.129526?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wong, S. C. & Yang, Hai, 1997. "Reserve capacity of a signal-controlled road network," Transportation Research Part B: Methodological, Elsevier, vol. 31(5), pages 397-402, October.
    2. Xu, Xiangdong & Chen, Anthony & Jansuwan, Sarawut & Yang, Chao & Ryu, Seungkyu, 2018. "Transportation network redundancy: Complementary measures and computational methods," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 68-85.
    3. Li, Tongfei & Sun, Huijun & Wu, Jianjun & Ge, Ying-en, 2017. "Optimal toll of new highway in the equilibrium framework of heterogeneous households' residential location choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 123-137.
    4. Wang, Jie & Cai, Zhiyu & Chen, Yaohui & Yang, Peng & Chen, Bokui, 2023. "An advanced control strategy for connected autonomous vehicles based on Micro simulation models at multiple intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    5. Ye, Lanhang & Yamamoto, Toshiyuki, 2018. "Impact of dedicated lanes for connected and autonomous vehicle on traffic flow throughput," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 588-597.
    6. Wang, Jian & Peeta, Srinivas & He, Xiaozheng, 2019. "Multiclass traffic assignment model for mixed traffic flow of human-driven vehicles and connected and autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 139-168.
    7. Chen, Anthony & Kasikitwiwat, Panatda, 2011. "Modeling capacity flexibility of transportation networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 105-117, February.
    8. Sang Nguyen & Clermont Dupuis, 1984. "An Efficient Method for Computing Traffic Equilibria in Networks with Asymmetric Transportation Costs," Transportation Science, INFORMS, vol. 18(2), pages 185-202, May.
    9. Li, Tongfei & Cao, Yaning & Xu, Min & Sun, Huijun, 2023. "Optimal intersection design and signal setting in a transportation network with mixed HVs and CAVs," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    10. Chen, Zhibin & He, Fang & Yin, Yafeng & Du, Yuchuan, 2017. "Optimal design of autonomous vehicle zones in transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 44-61.
    11. Chen, Shukai & Wang, Hua & Xiao, Ling & Meng, Qiang, 2022. "Random capacity for a single lane with mixed autonomous and human-driven vehicles: Bounds, mean gaps and probability distributions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    12. Zheng, Yu & Zhang, Xiaoning & Liang, Zhe, 2020. "Multimodal subsidy design for network capacity flexibility optimization," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 16-35.
    13. Yang, Hai & Bell, Michael G. H. & Meng, Qiang, 2000. "Modeling the capacity and level of service of urban transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(4), pages 255-275, May.
    14. Liu, Zhiyuan & Wang, Zewen & Cheng, Qixiu & Yin, Ruyang & Wang, Meng, 2021. "Estimation of urban network capacity with second-best constraints for multimodal transport systems," Transportation Research Part B: Methodological, Elsevier, vol. 152(C), pages 276-294.
    15. Li, Tongfei & Xu, Min & Sun, Huijun & Xiong, Jie & Dou, Xueping, 2023. "Stochastic ridesharing equilibrium problem with compensation optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    16. Jia, Yanfeng & Qu, Dayi & Song, Hui & Wang, Tao & Zhao, Zixu, 2022. "Car-following characteristics and model of connected autonomous vehicles based on safe potential field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    17. Ye, Lanhang & Yamamoto, Toshiyuki, 2019. "Evaluating the impact of connected and autonomous vehicles on traffic safety," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    18. Jian Wang & Muqing Du & Lili Lu & Xiaozheng He, 2018. "Maximizing Network Throughput under Stochastic User Equilibrium with Elastic Demand," Networks and Spatial Economics, Springer, vol. 18(1), pages 115-143, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Du, Muqing & Zhou, Jiankun & Chen, Anthony & Tan, Heqing, 2022. "Modeling the capacity of multimodal and intermodal urban transportation networks that incorporate emerging travel modes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    2. Li, Tongfei & Cao, Yaning & Xu, Min & Sun, Huijun, 2023. "Optimal intersection design and signal setting in a transportation network with mixed HVs and CAVs," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    3. 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).
    4. Liu, Zhiyuan & Wang, Zewen & Cheng, Qixiu & Yin, Ruyang & Wang, Meng, 2021. "Estimation of urban network capacity with second-best constraints for multimodal transport systems," Transportation Research Part B: Methodological, Elsevier, vol. 152(C), pages 276-294.
    5. Zhang, Fang & Lu, Jian & Hu, Xiaojian & Meng, Qiang, 2023. "Integrated deployment of dedicated lane and roadside unit considering uncertain road capacity under the mixed-autonomy traffic environment," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    6. Sun, Mingmei, 2023. "A day-to-day dynamic model for mixed traffic flow of autonomous vehicles and inertial human-driven vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    7. Zheng, Yu & Zhang, Xiaoning & Liang, Zhe, 2020. "Multimodal subsidy design for network capacity flexibility optimization," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 16-35.
    8. Ye, Jiao & Cao, Ruide & He, Biao & Kuai, Xi & Guo, Renzhong, 2024. "Disaggregated spatiotemporal traffic assignment for road reservation service and supply-demand statistical analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 645(C).
    9. Jansuwan, Sarawut & Chen, Anthony & Xu, Xiangdong, 2021. "Analysis of freight transportation network redundancy: An application to Utah’s bi-modal network for transporting coal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 154-171.
    10. Ye, Jiao & Jiang, Yu & Chen, Jun & Liu, Zhiyuan & Guo, Renzhong, 2021. "Joint optimisation of transfer location and capacity for a capacitated multimodal transport network with elastic demand: a bi-level programming model and paradoxes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    11. Gu, Yu & Fu, Xiao & Liu, Zhiyuan & Xu, Xiangdong & Chen, Anthony, 2020. "Performance of transportation network under perturbations: Reliability, vulnerability, and resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    12. Zhaoqi Zang & Xiangdong Xu & Anthony Chen & Chao Yang, 2022. "Modeling the α-max capacity of transportation networks: a single-level mathematical programming formulation," Transportation, Springer, vol. 49(4), pages 1211-1243, August.
    13. Wang, Jian & He, Xiaozheng & Peeta, Srinivas & Wang, Wei, 2022. "Globally convergent line search algorithm with Euler-based step size-determination method for continuous network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 119-144.
    14. Sugiura, Satoshi & Chen, Anthony, 2021. "Vulnerability analysis of cut-capacity structure and OD demand using Gomory-Hu tree method," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 111-127.
    15. Zhaoming Zhou & Jianbo Yuan & Shengmin Zhou & Qiong Long & Jianrong Cai & Lei Zhang, 2023. "Modeling and Analysis of Driving Behaviour for Heterogeneous Traffic Flow Considering Market Penetration under Capacity Constraints," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    16. Wang, Ting & Li, Yao & Jia, Bin & Long, Jiancheng, 2024. "An autonomous vehicle exclusive lane design problem under the mixed autonomy traffic environment: Model formulation and large-scale algorithm design," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 188(C).
    17. Wei, Qinshuang & Gao, Zhenyu & Clarke, John-Paul & Topcu, Ufuk, 2024. "Risk-aware urban air mobility network design with overflow redundancy," Transportation Research Part B: Methodological, Elsevier, vol. 185(C).
    18. Zhang, Fang & Lu, Jian & Hu, Xiaojian, 2022. "Integrated path controlling and subsidy scheme for mobility and environmental management in automated transportation networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    19. Xu, Xiangdong & Chen, Anthony & Jansuwan, Sarawut & Yang, Chao & Ryu, Seungkyu, 2018. "Transportation network redundancy: Complementary measures and computational methods," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 68-85.
    20. Du, Jinxiao & Ma, Wei, 2024. "Maximin headway control of automated vehicles for system optimal dynamic traffic assignment in general networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 188(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:636:y:2024:i:c:s0378437124000347. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.