IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i20p13234-d942677.html
   My bibliography  Save this article

Research on Safety and Traffic Efficiency of Mixed Traffic Flows in the Converging Section of a Super-Freeway Ramp

Author

Listed:
  • Quan Yu

    (School of Electrical and Control Engineering, North China University of Technology, Beijing 100144, China)

  • Linlong Lei

    (School of Electrical and Control Engineering, North China University of Technology, Beijing 100144, China)

  • Yuqi Bao

    (School of Electrical and Control Engineering, North China University of Technology, Beijing 100144, China)

  • Li Wang

    (School of Electrical and Control Engineering, North China University of Technology, Beijing 100144, China)

Abstract

On-ramp merging areas are essential parts of freeways. The merging behavior of vehicles is the main factor affecting the continuity of freeway traffic flow, which determines the capacity of the main freeway line. With the development of innovative car technology, ACC technology has been widely used in actual vehicles. At the same time, the public’s demand for freeway-speed improvement is increasing. However, the evaluative research on freeway-speed-improvement schemes, safety, and efficiency, is incomplete. Therefore, this paper aims at the study of the mixed traffic flow of ACC and human-driven vehicles, simultaneously increasing the maximum speed limit to 140 km/h, and establishes a ramp-entry model through the SUMO simulation platform. The traffic-flow parameters upstream of the ramp entry and downstream of the weaving area are analyzed, including the flow, average speed, headway, and lane-change rate. The influence of the driving conditions for mixed ACC vehicles with different proportions in the ramp-merging scenario is analyzed from efficiency and safety perspectives. Studies have shown that mixing ACC vehicles can improve the safety and efficiency of the road, and the increase in the maximum speed limit has limited road capacity. When considering the inclusion of ACC vehicles, increasing the maximum speed limit can improve the operating efficiency of the road.

Suggested Citation

  • Quan Yu & Linlong Lei & Yuqi Bao & Li Wang, 2022. "Research on Safety and Traffic Efficiency of Mixed Traffic Flows in the Converging Section of a Super-Freeway Ramp," Sustainability, MDPI, vol. 14(20), pages 1-15, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:13234-:d:942677
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/20/13234/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/20/13234/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Davis, L.C., 2007. "Effect of adaptive cruise control systems on mixed traffic flow near an on-ramp," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 274-290.
    2. Davis, L.C., 2013. "Optimality and oscillations near the edge of stability in the dynamics of autonomous vehicle platoons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3755-3764.
    3. Davis, L.C., 2016. "Improving traffic flow at a 2-to-1 lane reduction with wirelessly connected, adaptive cruise control vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 320-332.
    4. Yuntao Shi & Ye Li & Qing Cai & Hao Zhang & Dan Wu, 2020. "How Does Heterogeneity Affect Freeway Safety? A Simulation-Based Exploration Considering Sustainable Intelligent Connected Vehicles," Sustainability, MDPI, vol. 12(21), pages 1-18, October.
    5. Yu, Shaowei & Shi, Zhongke, 2015. "The effects of vehicular gap changes with memory on traffic flow in cooperative adaptive cruise control strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 206-223.
    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. Davis, L.C., 2017. "Dynamic origin-to-destination routing of wirelessly connected, autonomous vehicles on a congested network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 478(C), pages 93-102.
    2. Zhang, Peng & Zhu, Huibing & Zhou, Yijiang, 2022. "Modeling cooperative driving strategies of automated vehicles considering trucks’ behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    3. Saeed Vasebi & Yeganeh M. Hayeri, 2021. "Collective Driving to Mitigate Climate Change: Collective-Adaptive Cruise Control," Sustainability, MDPI, vol. 13(16), pages 1-30, August.
    4. Guo, Lantian & Zhao, Xiangmo & Yu, Shaowei & Li, Xiuhai & Shi, Zhongke, 2017. "An improved car-following model with multiple preceding cars’ velocity fluctuation feedback," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 436-444.
    5. Rehborn, Hubert & Klenov, Sergey L. & Palmer, Jochen, 2011. "An empirical study of common traffic congestion features based on traffic data measured in the USA, the UK, and Germany," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4466-4485.
    6. Liu, Huaqing & Jiang, Rui, 2021. "Improving comfort level in traffic flow of CACC vehicles at lane drop on two-lane highways," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 575(C).
    7. Davis, L.C., 2018. "Dynamics of a long platoon of cooperative adaptive cruise control vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 818-834.
    8. Cen, Bing-ling & Xue, Yu & Zhang, Yi-cai & Wang, Xue & He, Hong-di, 2020. "A feedback control method with consideration of the next-nearest-neighbor interactions in a lattice hydrodynamic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    9. Mei, Yiru & Zhao, Xiaoqun & Qian, Yeqing & Xu, Shangzhi & Li, Zhipeng, 2021. "Effect of self-stabilizing control in lattice hydrodynamic model with on-ramp and off-ramp," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 575(C).
    10. Qingtao, Zhai & Hongxia, Ge & Rongjun, Cheng, 2018. "An extended continuum model considering optimal velocity change with memory and numerical tests," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 774-785.
    11. Davis, L.C., 2012. "Mitigation of congestion at a traffic bottleneck with diversion and lane restrictions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1679-1691.
    12. Pei, Xin & Pan, Yan & Wang, Haixin & Wong, S.C. & Choi, Keechoo, 2016. "Empirical evidence and stability analysis of the linear car-following model with gamma-distributed memory effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 311-323.
    13. Yang, Da & Jin, Peter (Jing) & Pu, Yun & Ran, Bin, 2014. "Stability analysis of the mixed traffic flow of cars and trucks using heterogeneous optimal velocity car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 371-383.
    14. Hosen, Md. Zakir & Hossain, Md. Anowar & Tanimoto, Jun, 2024. "Traffic model for the dynamical behavioral study of a traffic system imposing push and pull effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 645(C).
    15. Zhang, Yi-cai & Xue, Yu & Shi, Yin & Guo, Yan & Wei, Fang-ping, 2018. "Congested traffic patterns of two-lane lattice hydrodynamic model with partial reduced lane," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 135-147.
    16. Xu, Ting & Jiang, Ruisen & Wen, Changlei & Liu, Meijun & Zhou, Jiehan, 2019. "A hybrid model for lane change prediction with V2X-based driver assistance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    17. Diakaki, Christina & Papageorgiou, Markos & Papamichail, Ioannis & Nikolos, Ioannis, 2015. "Overview and analysis of Vehicle Automation and Communication Systems from a motorway traffic management perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 147-165.
    18. Jin, Zhizhan & Li, Zhipeng & Cheng, Rongjun & Ge, Hongxia, 2018. "Nonlinear analysis for an improved car-following model account for the optimal velocity changes with memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 278-288.
    19. Luo, Ying & Chen, Yanyan & Lu, Kaiming & Chen, Liang & Zhang, Jian, 2024. "Modeling and analysis of heterogeneous traffic flow considering dynamic information flow topology and driving behavioral characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    20. Jiang, Yangsheng & Cong, Hongwei & Chen, Hongyu & Wu, Yunxia & Yao, Zhihong, 2024. "Adaptive cruise control design for collision risk avoidance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 640(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:gam:jsusta:v:14:y:2022:i:20:p:13234-:d:942677. 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.