An extended macro traffic flow model accounting for multiple optimal velocity functions with different probabilities

被引:93
|
作者
Cheng, Rongjun [1 ,2 ,3 ]
Ge, Hongxia [1 ,2 ,3 ]
Wang, Jufeng [4 ]
机构
[1] Ningbo Univ, Fac Maritime & Transportat, Ningbo 315211, Zhejiang, Peoples R China
[2] Jiangsu Prov Collaborat Innovat Ctr Modern Urban, Nanjing 210096, Jiangsu, Peoples R China
[3] Ningbo Univ Subctr, Natl Traff Management Engn & Technol Res Ctr, Ningbo 315211, Zhejiang, Peoples R China
[4] Zhejiang Univ, Ningbo Inst Technol, Ningbo 315100, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Traffic flow; Macro traffic flow model; Multiple optimal velocity with different probabilities; CAR-FOLLOWING MODEL; DRIVERS BOUNDED RATIONALITY; LATTICE HYDRODYNAMIC MODEL; BIDIRECTIONAL PEDESTRIAN FLOW; ANTICIPATION OPTIMAL VELOCITY; JAMMING TRANSITION; CONTINUUM MODEL; NUMERICAL TESTS; MKDV EQUATIONS; TDGL;
D O I
10.1016/j.physleta.2017.06.008
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Due to the maximum velocity and safe headway distance of the different vehicles are not exactly the same, an extended macro model of traffic flow with the consideration of multiple optimal velocity functions with probabilities is proposed in this paper. By means of linear stability theory, the new model's linear stability condition considering multiple probabilities optimal velocity is obtained. The KdV-Burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line through nonlinear analysis. The numerical simulations of influences of multiple maximum velocities and multiple safety distances on model's stability and traffic capacity are carried out. The cases of two different kinds of maximum speeds with same safe headway distance, two different types of safe headway distances with same maximum speed and two different max velocities and two different time-gaps are all explored by numerical simulations. First cases demonstrate that when the proportion of vehicles with a larger v(max) increase, the traffic tends to unstable, which also means that jerk and brakes is not conducive to traffic stability and easier to result in stop and go phenomenon. Second cases show that when the proportion of vehicles with greater safety spacing increases, the traffic tends to be unstable, which also means that too cautious assumptions or weak driving skill is not conducive to traffic stability. Last cases indicate that increase of maximum speed is not conducive to traffic stability, while reduction of the safe headway distance is conducive to traffic stability. Numerical simulation manifests that the mixed driving and traffic diversion does not have effect on the traffic capacity when traffic density is low or heavy. Numerical results also show that mixed driving should be chosen to increase the traffic capacity when the traffic density is lower, while the traffic diversion should be chosen to increase the traffic capacity when the traffic density is heavier. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:2608 / 2620
页数:13
相关论文
共 50 条
  • [41] Macro Traffic Flow Model Based on the Hydromechanics Theory
    Wang Fu
    Li Jie
    [J]. FLOW IN POROUS MEDIA - FROM PHENOMENA TO ENGINEERING AND BEYOND, 2009, : 112 - +
  • [42] A Macro Model for Traffic Flow with Consideration of Static Bottleneck
    唐铁桥
    李鹏
    吴永洪
    黄海军
    [J]. Communications in Theoretical Physics, 2012, 58 (08) : 300 - 306
  • [43] An improved macro model for traffic flow and numerical tests
    Ai, W. H.
    Chen, Q.
    Liu, D. W.
    [J]. 2017 INTERNATIONAL CONFERENCE ON SMART CITY AND SYSTEMS ENGINEERING (ICSCSE 2017), 2017, : 152 - 155
  • [44] Ultradiscrete optimal velocity model: A cellular-automaton model for traffic flow and linear instability of high-flux traffic
    Kanai, Masahiro
    Isojima, Shin
    Nishinari, Katsuhiro
    Tokihiro, Tetsuji
    [J]. PHYSICAL REVIEW E, 2009, 79 (05):
  • [45] Branch Analysis of Macro-Traffic Flow Model With Different Driving Characteristics in Its Environment
    Ai, Wenhuan
    Xing, Tao
    Su, Yuhang
    Liu, Dawei
    [J]. IEEE ACCESS, 2021, 9 : 164752 - 164768
  • [46] Effect of looking backward on traffic flow in an extended multiple car-following model
    Sun, Di-Hua
    Liao, Xiao-Yong
    Peng, Guang-Han
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2011, 390 (04) : 631 - 635
  • [47] Analysis of Multiple Velocity Difference Model in Two-lane Traffic Flow with an Accident
    Tao, Wang
    Jing, Zhang
    [J]. 2008 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6, 2008, : 2805 - +
  • [48] A MACROSCOPIC TRAFFIC FLOW MODEL ACCOUNTING FOR BOUNDED ACCELERATION
    Laurent-Brouty, Nicolas
    Costeseque, Guillaume
    Goatin, Paola
    [J]. SIAM JOURNAL ON APPLIED MATHEMATICS, 2021, 81 (01) : 173 - 189
  • [49] Macro autonomous traffic flow model with traffic jerk and downstream vehicle information
    Cong, Zhai
    Wu, Weitiao
    [J]. ENGINEERING COMPUTATIONS, 2021, 38 (10) : 4066 - 4090
  • [50] Traveling waves in an optimal velocity model of freeway traffic
    Berg, P
    Woods, A
    [J]. PHYSICAL REVIEW E, 2001, 63 (03):