An extended macro model accounting for acceleration changes with memory and numerical tests

被引:14
作者
Cheng Rongjun [1 ,2 ,3 ]
Ge Hongxia [1 ,2 ,3 ]
Sun Fengxin [4 ]
Wang Jufeng [5 ]
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] Ningbo Univ Technol, Fac Sci, Ningbo 315016, Zhejiang, Peoples R China
[5] Ningbo Dahongying Univ, Coll Informat Technol, Ningbo 315175, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Traffic flow; Continuum model; Acceleration changes with memory; Fuel consumption; Emissions; CAR-FOLLOWING MODEL; DRIVERS BOUNDED RATIONALITY; LATTICE HYDRODYNAMIC MODEL; VELOCITY DIFFERENCE MODEL; VEHICULAR TRAFFIC FLOW; CONTINUUM MODEL; JAMMING TRANSITION; FUEL CONSUMPTION; MKDV EQUATIONS; FULL VELOCITY;
D O I
10.1016/j.physa.2018.04.060
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Considering effect of acceleration changes with memory, an improved continuum model of traffic flow is proposed in this paper. By applying the linear stability theory, we derived the new model's linear stability condition. Through nonlinear analysis, the KdV-Burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line. Numerical simulation is carried out to study the extended traffic flow model, which explores how acceleration changes with memory affected each car's velocity, density and fuel consumption and exhaust emissions. Numerical results demonstrate that acceleration changes with memory have significant negative effect on dynamic characteristic of traffic flow. Furthermore, research results verify that the effect of acceleration changes with memory will deteriorate the stability of traffic flow and increase cars' total fuel consumptions and emissions during the whole evolution of small perturbation. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:270 / 283
页数:14
相关论文
共 50 条
[21]   A macro traffic flow model accounting for real-time traffic state [J].
Tang, Tie-Qiao ;
Chen, Liang ;
Wu, Yong-Hong ;
Caccetta, Lou .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2015, 437 :55-67
[22]   An extended car-following model considering the acceleration derivative in some typical traffic environments [J].
Zhou, Tony ;
Chen, Dong ;
Liu, Weining .
MODERN PHYSICS LETTERS B, 2018, 32 (08)
[23]   An improved macro model for traffic flow and numerical tests [J].
Ai, W. H. ;
Chen, Q. ;
Liu, D. W. .
2017 INTERNATIONAL CONFERENCE ON SMART CITY AND SYSTEMS ENGINEERING (ICSCSE 2017), 2017, :152-155
[24]   An extended car-following model considering driver's memory and average speed of preceding vehicles with control strategy [J].
Sun, Yuqing ;
Ge, Hongxia ;
Cheng, Rongjun .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2019, 521 :752-761
[25]   Bifurcation analysis of an extended macro model considering time delay and anticipation effect [J].
Lyu, Hao ;
Cheng, Rongjun ;
Ge, Hongxia .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2022, 585
[26]   Modeling and analyses for an extended car-following model accounting for drivers' situation awareness from cyber physical perspective [J].
Chen, Dong ;
Sun, Dihua ;
Zhao, Min ;
Zhou, Tong ;
Cheng, Senlin .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2018, 501 :52-68
[27]   An extended lattice hydrodynamic model considering the average optimal velocity effect field and driver's sensory memory [J].
Zheng, Yaxing ;
Ge, Hongxia ;
Cheng, Rongjun .
MODERN PHYSICS LETTERS B, 2021, 35 (20)
[28]   An extended macro model for traffic flow with consideration of multi static bottlenecks [J].
Tang, T. Q. ;
Li, P. ;
Yang, X. B. .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2013, 392 (17) :3537-3545
[29]   Nonlinear analysis of the car-following model considering headway changes with memory and backward looking effect [J].
Ma, Guangyi ;
Ma, Minghui ;
Liang, Shidong ;
Wang, Yansong ;
Guo, Hui .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2021, 562
[30]   Nonlinear analysis of a new car-following model accounting for the optimal velocity changes with memory [J].
Peng, Guanghan ;
Lu, Weizhen ;
He, Hong-di ;
Gu, Zhenghua .
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2016, 40 :197-205