IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i23p16160-d1284637.html
   My bibliography  Save this article

Network-Level Hierarchical Bottleneck Congestion Control Method for a Mixed Traffic Network

Author

Listed:
  • Yuncheng Zeng

    (College of Transportation Engineering, Tongji University, 4800 Cao’an Highway, Shanghai 201804, China
    Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China)

  • Minhua Shao

    (College of Transportation Engineering, Tongji University, 4800 Cao’an Highway, Shanghai 201804, China
    Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China)

  • Lijun Sun

    (College of Transportation Engineering, Tongji University, 4800 Cao’an Highway, Shanghai 201804, China
    Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China)

Abstract

Due to the escalating transportation demand and the significant ramifications of traffic congestion, there is an imperative to investigate the sources of congestion, known as “congestion bottlenecks”. The implementation of control methods ahead of the occurrence of congestion is crucial. Connected and autonomous vehicles (CAVs) have a high potential within the field of traffic control. CAVs are exceptionally controllable and facilitate management feasibility. This study utilizes the high compliance of CAVs to provide an effective solution for the congestion management problem at the network level when mixed traffic flows are saturated. A linear programming model to reduce average travel time over the road network is developed. By utilizing a genetic algorithm, the optimal traffic demand regulation scheme can be obtained and the departure time of CAVs optimized. The effectiveness of the proposed method is validated through simulation across various road network scales, CAVs penetration rates, and controlled CAV proportions. The proposed method can only control a specific amount of CAVs, which, according to an analysis of the simulation results, significantly improves the performance of the transportation system. The importance of employing advanced control methods to improve the sustainability of urban transportation development and the travel experience is underscored in the conclusion.

Suggested Citation

  • Yuncheng Zeng & Minhua Shao & Lijun Sun, 2023. "Network-Level Hierarchical Bottleneck Congestion Control Method for a Mixed Traffic Network," Sustainability, MDPI, vol. 15(23), pages 1-27, November.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:23:p:16160-:d:1284637
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/23/16160/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/23/16160/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Friesz, Terry L. & Han, Ke, 2019. "The mathematical foundations of dynamic user equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 309-328.
    2. Andrew Hamilton & Ben Waterson & Tom Cherrett & Andrew Robinson & Ian Snell, 2013. "The evolution of urban traffic control: changing policy and technology," Transportation Planning and Technology, Taylor & Francis Journals, vol. 36(1), pages 24-43, February.
    3. Guo, Qiangqiang & Ban, Xuegang (Jeff), 2023. "A multi-scale control framework for urban traffic control with connected and automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 175(C).
    4. Ceylan, Halim & Bell, Michael G. H., 2004. "Traffic signal timing optimisation based on genetic algorithm approach, including drivers' routing," Transportation Research Part B: Methodological, Elsevier, vol. 38(4), pages 329-342, May.
    5. Martin Savelsbergh & Tom Van Woensel, 2016. "50th Anniversary Invited Article—City Logistics: Challenges and Opportunities," Transportation Science, INFORMS, vol. 50(2), pages 579-590, May.
    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. Peng, Xiaoshuai & Zhang, Lele & Thompson, Russell G. & Wang, Kangzhou, 2023. "A three-phase heuristic for last-mile delivery with spatial-temporal consolidation and delivery options," International Journal of Production Economics, Elsevier, vol. 266(C).
    2. Cai, Ya-Jun & Lo, Chris K.Y., 2020. "Omni-channel management in the new retailing era: A systematic review and future research agenda," International Journal of Production Economics, Elsevier, vol. 229(C).
    3. Xuedong Hua & YinHai Wang & Weijie Yu & Wenbo Zhu & Wei Wang, 2019. "Control Strategy Optimization for Two-Lane Highway Lane-Closure Work Zones," Sustainability, MDPI, vol. 11(17), pages 1-22, August.
    4. Liu, Yubin & Ye, Qiming & Escribano-Macias, Jose & Feng, Yuxiang & Candela, Eduardo & Angeloudis, Panagiotis, 2023. "Route planning for last-mile deliveries using mobile parcel lockers: A hybrid q-learning network approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    5. Mo, Pengli & Yao, Yu & D’Ariano, Andrea & Liu, Zhiyuan, 2023. "The vehicle routing problem with underground logistics: Formulation and algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    6. Joseph Y. J. Chow & Amelia C. Regan, 2011. "Real Option Pricing of Network Design Investments," Transportation Science, INFORMS, vol. 45(1), pages 50-63, February.
    7. He, Dongdong & Guan, Wei, 2023. "Promoting service quality with incentive contracts in rural bus integrated passenger-freight service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    8. Evers, Ruth & Proost, Stef, 2015. "The myth of traffic-responsive signal control: Why common sense does not always make sense," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 350-357.
    9. Ozan, Cenk & Haldenbilen, Soner & Ceylan, Halim, 2011. "Estimating emissions on vehicular traffic based on projected energy and transport demand on rural roads: Policies for reducing air pollutant emissions and energy consumption," Energy Policy, Elsevier, vol. 39(5), pages 2542-2549, May.
    10. Haider, Zulqarnain & Hu, Yujie & Charkhgard, Hadi & Himmelgreen, David & Kwon, Changhyun, 2022. "Creating grocery delivery hubs for food deserts at local convenience stores via spatial and temporal consolidation," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    11. Chen, Enming & Zhou, Zhongbao & Li, Ruiyang & Chang, Zhongxiang & Shi, Jianmai, 2024. "The multi-fleet delivery problem combined with trucks, tricycles, and drones for last-mile logistics efficiency requirements under multiple budget constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 187(C).
    12. Daniela Paddeu & Paulus Aditjandra, 2020. "Shaping Urban Freight Systems via a Participatory Approach to Inform Policy-Making," Sustainability, MDPI, vol. 12(1), pages 1-15, January.
    13. Abhishek, & Legros, Benjamin & Fransoo, Jan C., 2021. "Performance evaluation of stochastic systems with dedicated delivery bays and general on-street parking," Other publications TiSEM 09ed9572-d59c-4f28-a9c4-b, Tilburg University, School of Economics and Management.
    14. Haldenbilen, Soner, 2006. "Fuel price determination in transportation sector using predicted energy and transport demand," Energy Policy, Elsevier, vol. 34(17), pages 3078-3086, November.
    15. A. Assaf, 2011. "Accounting for technological differences in modelling the performance of airports: a Bayesian approach," Applied Economics, Taylor & Francis Journals, vol. 43(18), pages 2267-2275.
    16. Grote, Matt & Waterson, Ben & Rudolph, Felix, 2021. "The impact of strategic transport policies on future urban traffic management systems," Transport Policy, Elsevier, vol. 110(C), pages 402-414.
    17. Ninja Soeffker & Marlin W. Ulmer & Dirk C. Mattfeld, 2019. "Adaptive State Space Partitioning for Dynamic Decision Processes," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(3), pages 261-275, June.
    18. Kokkinou, Alinda & Quak, Hans & Mitas, Ondrej & Mandemakers, Albert, 2024. "Should I wait or should I go? Encouraging customers to make the more sustainable delivery choice," Research in Transportation Economics, Elsevier, vol. 103(C).
    19. Nocera, Silvio & Pungillo, Giuseppe & Bruzzone, Francesco, 2021. "How to evaluate and plan the freight-passengers first-last mile," Transport Policy, Elsevier, vol. 113(C), pages 56-66.
    20. Leibowicz, Benjamin D., 2020. "Urban land use and transportation planning for climate change mitigation: A theoretical framework," European Journal of Operational Research, Elsevier, vol. 284(2), pages 604-616.

    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:gam:jsusta:v:15:y:2023:i:23:p:16160-:d:1284637. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.