Chin. Phys. Lett.  2014, Vol. 31 Issue (08): 080505    DOI: 10.1088/0256-307X/31/8/080505
GENERAL |
The Stability Analysis for an Extended Car Following Model Based on Control Theory
GE Hong-Xia1,2,3, MENG Xiang-Pei4, ZHU Ke-Qiang1,2,3, CHENG Rong-Jun5**
1Faculty of Maritime and Transportation, Ningbo University, Ningbo 315200
2Jiangsu Province Collaborative Innovation Center for Modern Urban Traffic Technologies, Nanjing 210096
3National Traffic Management Engineering and Technology Research Centre, Ningbo University, Ningbo 315211
4Foundation College, Ningbo Dahongying University, Ningbo 315175
5Department of Fundamental Course, Ningbo Institute of Technology, Zhejiang University, Ningbo 315100
Cite this article:   
GE Hong-Xia, MENG Xiang-Pei, ZHU Ke-Qiang et al  2014 Chin. Phys. Lett. 31 080505
Download: PDF(590KB)  
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract A new method is proposed to study the stability of the car-following model considering traffic interruption probability. The stability condition for the extended car-following model is obtained by using the Lyapunov function and the condition for no traffic jam is also given based on the control theory. Numerical simulations are conducted to demonstrate and verify the analytical results. Moreover, numerical simulations show that the traffic interruption probability has an influence on driving behavior and confirm the effectiveness of the method on the stability of traffic flow.
Published: 28 July 2014
PACS:  05.70.Fh (Phase transitions: general studies)  
  05.70.Jk (Critical point phenomena)  
  89.40.-a (Transportation)  
TRENDMD:   
URL:  
https://cpl.iphy.ac.cn/10.1088/0256-307X/31/8/080505       OR      https://cpl.iphy.ac.cn/Y2014/V31/I08/080505
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
GE Hong-Xia
MENG Xiang-Pei
ZHU Ke-Qiang
CHENG Rong-Jun
[1] Nagatani T 1999 Phys. Rev. E 60 6395
[2] Komatsu T S and Sasa S 1995 Phys. Rev. E 52 5574
[3] Helbing D, Treiber M, Kesting A and Schonhof M 2009 Eur. Phys. J. B 69 583
[4] Machado J A T and Figueiredo L 2007 Nonlinear Dyn. 49 443
[5] Xue Y, Dong L Y, Yuan Y W and Dai S Q 2002 Acta Phys. Sin. 51 492 (in Chinese)
[6] Xue Y 2004 Commun. Theor. Phys. 41 477
[7] Jin S, Wang D H, Tao P F and Li P F 2010 Physica A 389 4654
[8] Bando M, Hasebe K, Shibata A and Sugiyama Y 1995 Phys. Rev. E 51 1035
[9] Wang T, Gao Z Y and Zhao X M 2006 Acta Phys. Sin. 55 634 (in Chinese)
[10] Ge H X, Dai S Q, Xue Y and Dong L Y 2005 Phys. Rev. E 71 066119
[11] Yu L, Shi Z K and Zhou B C 2008 Commun. Nonlinear Sci. Numer. Simul.on 13 2167
[12] Peng G H and Sun D H 2010 Phys. Lett. A 374 1694
[13] Li Y F, Sun D H, Liu W N, Zhang M, Zhao M, Liao X Y and Tang L 2011 Nonlinear Dyn. 66 15
[14] Nagatani T 2002 Rep. Prog. Phys. 65 1331
[15] Komatasu T and Sasa S 1995 Phys. Rev. E 52 5574
[16] Muramatsu M and Nagatani T 1999 Phys. Rev. E 60 180
[17] Nagatani T 2000 Phys. Rev. E 61 3564
[18] Ou Z H, Dai S Q and Dong L Y 2006 J. Phys. A 39 1251
[19] Jiang R, Wu Q S and Zhu Z J 2001 Phys. Rev. E 64 017101
[20] Ge H X, Meng X P, Cheng R J and Lo S M 2011 Physica A 390 3348
[21] Tang T Q, Huang H J, Wong S C and Jiang R 2009 Chin. Phys. B 18 975
[22] Helbing D and Tilch B 1998 Phys. Rev. E 58 133
[23] Konishi K, Kokame H and Hirata K 2000 Eur. Phys. J. B 15 715
Related articles from Frontiers Journals
[1] Xiao-Qi Han, Sheng-Song Xu, Zhen Feng, Rong-Qiang He, and Zhong-Yi Lu. Framework for Contrastive Learning Phases of Matter Based on Visual Representations[J]. Chin. Phys. Lett., 2023, 40(2): 080505
[2] Lingxiao Wang, Yin Jiang, Lianyi He, and Kai Zhou. Continuous-Mixture Autoregressive Networks Learning the Kosterlitz–Thouless Transition[J]. Chin. Phys. Lett., 2022, 39(12): 080505
[3] Zhuo Cheng and Zhenhua Yu. Supervised Machine Learning Topological States of One-Dimensional Non-Hermitian Systems[J]. Chin. Phys. Lett., 2021, 38(7): 080505
[4] Hong-Mei Yin, Heng-Wei Zhou, Yi-Neng Huang. A New Model of Ferroelectric Phase Transition with Neglectable Tunneling Effect[J]. Chin. Phys. Lett., 2019, 36(7): 080505
[5] Yasuomi D. Sato. Frequency Switches at Transition Temperature in Voltage-Gated Ion Channel Dynamics of Neural Oscillators[J]. Chin. Phys. Lett., 2018, 35(5): 080505
[6] Wen Xiao, Chao Yang, Ya-Ping Yang, Yu-Guang Chen. Phase Transition in Recovery Process of Complex Networks[J]. Chin. Phys. Lett., 2017, 34(5): 080505
[7] Liang Zhao, Yu-Song Tu, Chun-Lei Wang, Hai-Ping Fang. Comparisons of Criteria for Analyzing the Dynamical Association of Solutes in Aqueous Solutions[J]. Chin. Phys. Lett., 2016, 33(03): 080505
[8] DENG Yi-Bo, GU Qiang. Berezinskii–Kosterlitz–Thouless Transition in a Two-Dimensional Random-Bond XY Model on a Square Lattice[J]. Chin. Phys. Lett., 2014, 31(2): 080505
[9] RAO Zhong-Hao, LIU Xin-Jian, ZHANG Rui-Kai, LI Xiang, WEI Chang-Xing, WANG Hao-Dong, LI Yi-Min. A Comparative Study on the Self Diffusion of N-Octadecane with Crystal and Amorphous Structure by Molecular Dynamics Simulation[J]. Chin. Phys. Lett., 2014, 31(1): 080505
[10] WANG Si-Ying, DUAN Wen-Gang, YIN Xie-Zhen. Transition Mode of Two Parallel Flags in Uniform Flow[J]. Chin. Phys. Lett., 2013, 30(11): 080505
[11] MENG Qing-Kuan, FENG Dong-Tai, GAO Xu-Tuan, MEI Yu-Xue. Generalized Zero-Temperature Glauber Dynamics in a Two-Dimensional Square Lattice[J]. Chin. Phys. Lett., 2012, 29(12): 080505
[12] HU Mao-Bin, Henry Y.K. Lau, LING Xiang, JIANG Rui. Pheromone Static Routing Strategy for Complex Networks[J]. Chin. Phys. Lett., 2012, 29(12): 080505
[13] LIU You-Jun, ZHANG Hai-Lin, HE Li. Cooperative Car-Following Model of Traffic Flow and Numerical Simulation[J]. Chin. Phys. Lett., 2012, 29(10): 080505
[14] LI Xiang, DONG Li-Yun. Modeling and Simulation of Pedestrian Counter Flow on a Crosswalk[J]. Chin. Phys. Lett., 2012, 29(9): 080505
[15] YU Wing-Chi, WANG Li-Gang, GU Shi-Jian, and LIN Hai-Qing. Scaling of the Leading Response in Linear Quench Dynamics in the Quantum Ising Model[J]. Chin. Phys. Lett., 2012, 29(8): 080505
Viewed
Full text


Abstract