On the derivation of the velocity and fundamental traffic flow diagram from the modelling of the vehicle-driver behaviors

被引:6
|
作者
Bonzani, I. [2 ]
Mussone, L. [1 ]
机构
[1] Politecn Milan, Dept Bldg Environm Sci & Technol, Milan, Italy
[2] Politecn Torino, Dept Math, Turin, Italy
关键词
Traffic flow; Kinetic theory; Nonlinearity; Equilibrium flow; HYDRODYNAMIC MODELS; KINETIC-THEORY; MATHEMATICAL-THEORY; PARTICLES;
D O I
10.1016/j.mcm.2009.06.004
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper deals with derivation of the fundamental diagram by modelling the individual driver behavior that adjusts the velocity to the density of vehicles in order to respect the braking distance. A parameter is properly introduced to model the quality of the driver-vehicle subsystem referred to the environmental conditions. Subsequently, it is shown how to use this result in order to model traffic flows by the macroscopic representation and by the kinetic theory. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1107 / 1112
页数:6
相关论文
共 50 条
  • [41] Connecting Networkwide Travel Time Reliability and the Network Fundamental Diagram of Traffic Flow
    Mahmassani, Hani S.
    Hou, Tian
    Saberi, Meead
    TRANSPORTATION RESEARCH RECORD, 2013, (2391) : 80 - 91
  • [42] Fundamental diagram of mixed traffic flow of CAVs with different connectivity and automation levels
    Jiang, Yangsheng
    Chen, Hongyu
    Cong, Hongwei
    Wu, Yunxia
    Yao, Zhihong
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2024, 646
  • [43] Analysis of the impact of heterogeneous platoon for mixed traffic flow: A fundamental diagram method
    Li, Le
    Wu, Yunxia
    Zeng, Qiaoqiong
    Wang, Yi
    Jiang, Yangsheng
    Yao, Zhihong
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2025, 660
  • [44] Reproducible generation of experimental data sample for calibrating traffic flow fundamental diagram
    Zhang, Jin
    Qu, Xiaobo
    Wang, Shuaian
    TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2018, 111 : 41 - 52
  • [45] Position-Dependent Fundamental Diagram Parameterizations in Traffic Flow Modeling on Highways
    Benninger, Lukas
    Sawodny, Oliver
    IFAC PAPERSONLINE, 2022, 55 (27): : 503 - 508
  • [46] Macroscopic Fundamental Diagram Estimation Considering Traffic Flow Condition of Road Network
    Deng, Xiaoli
    Hu, Yao
    PROMET-TRAFFIC & TRANSPORTATION, 2023, 35 (05): : 681 - 697
  • [47] Discrete derivation of Ruijgrok and Wu's nonlinear two-velocity Boltzmann model with an application to traffic-flow modelling
    Filliger, R
    MULTISCALE MODELING & SIMULATION, 2004, 2 (03): : 440 - 451
  • [48] DETERMINING THE MACROSCOPIC FUNDAMENTAL DIAGRAM FROM MIXED AND PARTIAL TRAFFIC DATA
    Ji, Yangbeibei
    Xu, Mingwei
    Li, Jie
    van Zuylen, Henk J.
    PROMET-TRAFFIC & TRANSPORTATION, 2018, 30 (03): : 267 - 279
  • [49] Analysis of the macroscopic effect of a driver's desired velocity on traffic flow characteristics
    Cen, Bing-ling
    Xue, Yu
    Xia, Yu-xian
    Zhang, Kun
    Zhou, Ji
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2024, 637
  • [50] Traffic Velocity Estimation From Vehicle Count Sequences
    Katsuki, Takayuki
    Morimura, Tetsuro
    Inoue, Masato
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2017, 18 (07) : 1700 - 1712