Understanding the traffic flow in different types of freeway tunnels based on car-following behaviors analysis

被引:4
|
作者
Shang, Ting [1 ]
Lu, Jiaxin [1 ]
Luo, Ying [2 ]
Wang, Song [1 ]
He, Zhengyu [3 ]
Wang, Aobo [4 ]
机构
[1] Chongqing Jiaotong Univ, Coll Traff & Transportat, Chongqing 400074, Peoples R China
[2] Beijing Univ Technol, Beijing Key Lab Traff Engn, Beijing 100124, Peoples R China
[3] Columbia Univ, Fu Fdn Sch Engn & Appl Sci, New York, NY 10027 USA
[4] Univ Nevada, Coll Engn, Reno, NV 89557 USA
基金
中国国家自然科学基金;
关键词
Continuous car -following behavior; Different tunnel types; Full velocity difference model; Traffic flow stability; Traffic flow safety; MODEL; CONGESTION; AGE;
D O I
10.1016/j.tust.2023.105494
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Tunnels are an engineering solution that has gained prominence for constructing freeways in mountainous regions. The length of the tunnels can vary, depending on the geological conditions, engineering requirements, and budget constraints. Car-following is the predominant driving behavior observed in tunnels, and understanding how drivers follow each other in different types of tunnels is crucial for ensuring smooth traffic flow and safety. Each type of tunnel environment can uniquely impact car-following behavior, which allows for targeted studies to optimize traffic management. In this research, natural driving data in freeway tunnels were collected through a driving experiment conducted on the Baomao Freeway in Chongqing, China. Then, the correlations and differences in car-following data between various tunnels and sections were analyzed. Finally, car-following models were developed considering various tunnel scenarios, and the influence of tunnel types on traffic flow was analyzed by simulation. The study revealed notable variations in car-following behavior across different types of tunnels, as well as within consecutive sections of the same tunnel. As tunnel length increased, the driving stability of following vehicles decreased, but the level of driving safety risk was not positively correlated with tunnel length. Significant vehicle trajectory oscillation was observed within the inner sections of long and extra-long tunnels, and a significant relationship between the acceleration of following vehicles and the location within the tunnel section was found. Additionally, the longer the tunnel, the greater the fluctuations in traffic flow, and the negative impact of the tunnel environment on traffic flow stability increased periodically downstream. These findings offer valuable insights for understanding and modeling car-following behavior in freeway tunnels, which ultimately facilitate traffic safety and mobility.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Investigating heterogeneous car-following behaviors of different vehicle types, traffic densities and road types
    Wang, Jinghua
    Zhang, Zhao
    Liu, Feng
    Lu, Guangquan
    TRANSPORTATION RESEARCH INTERDISCIPLINARY PERSPECTIVES, 2021, 9
  • [2] Study on car-following behaviors of combined traffic flow
    He, Min
    Rong, Jian
    Liu, Xiao-Ming
    Gongku Jiaotong Keji/Journal of Highway and Transportation Research and Development, 2002, 19 (03):
  • [3] Understanding traffic bottlenecks of long freeway tunnels based on a novel location-dependent lighting-related car-following model
    Yu, Shanchuan
    Zhao, Cong
    Song, Lang
    Li, Yishun
    Du, Yuchuan
    TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, 2023, 136
  • [4] Modeling a Car-Following Model with Comprehensive Safety Field in Freeway Tunnels
    Chen, Zheng
    Wen, Huiying
    JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS, 2022, 148 (07)
  • [5] Stabilisation analysis of multiple car-following model in traffic flow
    彭光含
    Chinese Physics B, 2010, 19 (05) : 438 - 445
  • [6] Stabilisation analysis of multiple car-following model in traffic flow
    Peng Guang-Han
    CHINESE PHYSICS B, 2010, 19 (05) : 0564011 - 0564018
  • [7] Analysis of traffic flow based on car-following theory: a cyber-physical perspective
    Liu, Hui
    Sun, Dihua
    Zhao, Min
    NONLINEAR DYNAMICS, 2016, 84 (02) : 881 - 893
  • [8] Analysis of traffic flow based on car-following theory: a cyber-physical perspective
    Hui Liu
    Dihua Sun
    Min Zhao
    Nonlinear Dynamics, 2016, 84 : 881 - 893
  • [9] Curved road traffic flow car-following model and stability analysis
    Zhang Li-Dong
    Jia Lei
    Zhu Wen-Xing
    ACTA PHYSICA SINICA, 2012, 61 (07)
  • [10] Numerical analysis on car-following traffic flow models with delay time
    李莉
    施鹏飞
    Journal of Zhejiang University Science A(Science in Engineering), 2006, (02) : 204 - 209