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

被引:5
|
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 38 条
  • [21] Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect
    Li, Tenglong
    Hui, Fei
    Liu, Ce
    Zhao, Xiangmo
    Khattak, Asad J.
    JOURNAL OF ADVANCED TRANSPORTATION, 2020, 2020
  • [22] Feedback control strategy of a new car-following model based on reducing traffic accident rates
    Zhai, Cong
    Liu, Weiming
    Tan, Feigang
    Huang, Ling
    Song, Minglei
    TRANSPORTATION PLANNING AND TECHNOLOGY, 2016, 39 (08) : 801 - 812
  • [23] Stabilizing mixed cooperative adaptive cruise control traffic flow to balance capacity using car-following model
    Qin, Yanyan
    Wang, Hao
    JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 27 (01) : 57 - 79
  • [24] Car-Following Behavior of Human-Driven Vehicles in Mixed-Flow Traffic: A Driving Simulator Study
    Zhou, Anye
    Liu, Yongyang
    Tenenboim, Einat
    Agrawal, Shubham
    Peeta, Srinivas
    IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 8 (04): : 2661 - 2673
  • [25] Analysis of the trip costs of a traffic corridor with two entrances and one exit under car-following model
    Tang, Tie-Qiao
    Wang, Tao
    Chen, Liang
    Shang, Hua-Yan
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2017, 486 : 720 - 729
  • [26] Optimal fuzzy control system design for car-following behaviour based on the driver-vehicle unit online delays in a real traffic flow
    Ghaffari, Ali
    Khodayari, Alireza
    Faraji, Maysam
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2014, 228 (12) : 1440 - 1451
  • [27] Psychological Field Effect Analysis and Car-Following Behavior Modeling Based on Driving Style
    Song, Hui
    Qu, Dayi
    Hu, Chunyan
    Wang, Tao
    Ji, Liyuan
    INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, 2024, 25 (05) : 1065 - 1076
  • [28] Analysis of the equilibrium trip cost without late arrival and the corresponding traffic properties using a car-following model
    Tang, Tie-Qiao
    Chen, Liang
    Huang, Hai-Jun
    Song, Ziqi
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2016, 460 : 348 - 360
  • [29] Car-Following Strategy Involving Stabilizing Traffic Flow with Connected Automated Vehicles to Reduce Particulate Matter (PM) Emissions in Rainy Weather
    Li, Renjie
    Qin, Yanyan
    SUSTAINABILITY, 2024, 16 (05)
  • [30] Analysis of trip cost allowing late arrival in a traffic corridor with one entry and one exit under car-following model
    Wang, Tao
    Tang, Tie-Qiao
    Chen, Liang
    Huang, Hai-Jun
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2019, 521 : 387 - 398