IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i7p2087-d220849.html
   My bibliography  Save this article

Determining Appropriate Lane-Changing Spacing for Off-Ramp Areas of Urban Expressways

Author

Listed:
  • Zhufei Huang

    (Beijing Engineering Research Center of Urban Transportation Operation Support, 100 Pingleyuan, Chaoyang District, Beijing University of Technology, Beijing 100124, China)

  • Zihan Zhang

    (China Academy of Urban Planning & Design, Beijing 100044, China)

  • Haijian Li

    (Beijing Engineering Research Center of Urban Transportation Operation Support, 100 Pingleyuan, Chaoyang District, Beijing University of Technology, Beijing 100124, China)

  • Lingqiao Qin

    (TOPS Laboratory, Department of Civil and Environmental Engineering, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, WI 53706, USA)

  • Jian Rong

    (Beijing Engineering Research Center of Urban Transportation Operation Support, 100 Pingleyuan, Chaoyang District, Beijing University of Technology, Beijing 100124, China)

Abstract

Congestion has become a significant issue in recent years and has greatly affected the efficiency of urban traffic operation. Random and disorderly lane-changing behavior greatly reduces traffic capacity and safety. This paper is mainly concerned with the relationship of lane-changing spacing intervals provided by off-ramp facilities and traffic flow conditions. Through field investigations in Beijing, several typical lane-changing behaviors at off-ramp areas are analyzed. By using field traffic data and actual road geometry parameters, VISSIM-based micro-behavior simulations at off-ramp areas are implemented to obtain traffic flow conditions with different lane-changing spacing intervals and other model parameters, such as traffic volume and ratio of off-ramp vehicles. Then, the numerical relationships between traffic flow state and model parameters can be shown. The results show that with increasing traffic volume and the ratio of off-ramp vehicles, the lane-changing spacing interval required by vehicles should be increased. For the same ratio of off-ramp vehicles, if the traffic volume increases by 100 pcu/h/lane (pcu is a unit to stand for a standard passenger car), the corresponding lane-changing spacing interval should be increased by a spacing of 50–100 m to avoid increasing congestion. Based on the results of this paper, smart lane management can be implemented by optimizing lane-changing spacing intervals and lane-changing behaviors to improve traffic capacity.

Suggested Citation

  • Zhufei Huang & Zihan Zhang & Haijian Li & Lingqiao Qin & Jian Rong, 2019. "Determining Appropriate Lane-Changing Spacing for Off-Ramp Areas of Urban Expressways," Sustainability, MDPI, vol. 11(7), pages 1-15, April.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:7:p:2087-:d:220849
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/7/2087/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/7/2087/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiaoyuan Wang & Jianqiang Wang & Jinglei Zhang & Xuegang Jeff Ban, 2015. "Lane-changing model with dynamic consideration of driver's propensity," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 26(02), pages 1-19.
    2. Gong, Siyuan & Du, Lili, 2016. "Optimal location of advance warning for mandatory lane change near a two-lane highway off-ramp," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 1-30.
    3. Zheng, Zuduo, 2014. "Recent developments and research needs in modeling lane changing," Transportation Research Part B: Methodological, Elsevier, vol. 60(C), pages 16-32.
    4. Tie-Qiao Tang & Yun-Peng Wang & Xiao-Bao Yang & Hai-Jun Huang, 2014. "A Multilane Traffic Flow Model Accounting for Lane Width, Lane-Changing and the Number of Lanes," Networks and Spatial Economics, Springer, vol. 14(3), pages 465-483, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qiang Luo & Xiaodong Zang & Xu Cai & Huawei Gong & Jie Yuan & Junheng Yang, 2021. "Vehicle Lane-Changing Safety Pre-Warning Model under the Environment of the Vehicle Networking," Sustainability, MDPI, vol. 13(9), pages 1-16, May.

    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. Li, Zhengming & Smirnova, M.N. & Zhang, Yongliang & Smirnov, N.N. & Zhu, Zuojin, 2022. "Tunnel speed limit effects on traffic flow explored with a three lane model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 194(C), pages 185-197.
    2. Zhou, Hao & Toth, Christopher & Guensler, Randall & Laval, Jorge, 2022. "Hybrid modeling of lane changes near freeway diverges," Transportation Research Part B: Methodological, Elsevier, vol. 165(C), pages 1-14.
    3. Zhang, Hanyu & Du, Lili & Shen, Jinglai, 2022. "Hybrid MPC System for Platoon based Cooperative Lane change Control Using Machine Learning Aided Distributed Optimization," Transportation Research Part B: Methodological, Elsevier, vol. 159(C), pages 104-142.
    4. Blanch Micó, Mª Teresa & Lucas Alba, Antonio & Bellés Rivera, Teresa & Ferruz Gracia, Ana Mª & Melchor Galán, Óscar M. & Delgado Pastor, Luis C. & Ruíz Jiménez, Francisco & Chóliz Montañés, Mariano, 2018. "Car following: Comparing distance-oriented vs. inertia-oriented driving techniques," Transport Policy, Elsevier, vol. 67(C), pages 13-22.
    5. Tian, Junfang & Li, Guangyu & Treiber, Martin & Jiang, Rui & Jia, Ning & Ma, Shoufeng, 2016. "Cellular automaton model simulating spatiotemporal patterns, phase transitions and concave growth pattern of oscillations in traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 560-575.
    6. Saifuzzaman, Mohammad & Zheng, Zuduo & Haque, Md. Mazharul & Washington, Simon, 2017. "Understanding the mechanism of traffic hysteresis and traffic oscillations through the change in task difficulty level," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 523-538.
    7. Li Li & Dong Zhang, 2018. "Merging Vehicles and Lane Speed-Flow Relationship in a Work Zone," Sustainability, MDPI, vol. 10(7), pages 1-13, June.
    8. Sharma, Anshuman & Zheng, Zuduo & Bhaskar, Ashish, 2019. "Is more always better? The impact of vehicular trajectory completeness on car-following model calibration and validation," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 49-75.
    9. Oh, Simon & Yeo, Hwasoo, 2015. "Impact of stop-and-go waves and lane changes on discharge rate in recovery flow," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 88-102.
    10. Ma, Yanli & Lv, Zhiliang & Zhang, Peng & Chan, Ching-Yao, 2021. "Impact of lane changing on adjacent vehicles considering multi-vehicle interaction in mixed traffic flow: A velocity estimating model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    11. Ouyang, Pengying & Liu, Pan & Guo, Yanyong & Chen, Kequan, 2023. "Effects of configuration elements and traffic flow conditions on Lane-Changing rates at the weaving segments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 171(C).
    12. Yun, Lifen & Wang, Xifu & Fan, Hongqiang & Li, Xiaopeng, 2020. "Reliable facility location design with round-trip transportation under imperfect information Part I: A discrete model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    13. Li, Linheng & Gan, Jing & Zhou, Kun & Qu, Xu & Ran, Bin, 2020. "A novel lane-changing model of connected and automated vehicles: Using the safety potential field theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    14. Khelfa, Basma & Ba, Ibrahima & Tordeux, Antoine, 2023. "Predicting highway lane-changing maneuvers: A benchmark analysis of machine and ensemble learning algorithms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 612(C).
    15. Gong, Siyuan & Du, Lili, 2016. "Optimal location of advance warning for mandatory lane change near a two-lane highway off-ramp," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 1-30.
    16. Yibing Wang & Long Wang & Xianghua Yu & Jingqiu Guo, 2023. "Capacity Drop at Freeway Ramp Merges with Its Replication in Macroscopic and Microscopic Traffic Simulations: A Tutorial Report," Sustainability, MDPI, vol. 15(3), pages 1-27, January.
    17. Mohammadian, Saeed & Zheng, Zuduo & Haque, Mazharul & Bhaskar, Ashish, 2023. "NET-RAT: Non-equilibrium traffic model based on risk allostasis theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    18. Jia, Dongyao & Ngoduy, Dong, 2016. "Enhanced cooperative car-following traffic model with the combination of V2V and V2I communication," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 172-191.
    19. Mehr, Negar & Li, Ruolin & Horowitz, Roberto, 2021. "A game theoretic macroscopic model of lane choices at traffic diverges with applications to mixed–autonomy networks," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 45-59.
    20. Saifuzzaman, Mohammad & Zheng, Zuduo & Mazharul Haque, Md. & Washington, Simon, 2015. "Revisiting the Task–Capability Interface model for incorporating human factors into car-following models," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 1-19.

    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:11:y:2019:i:7:p:2087-:d:220849. 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.