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Bifurcation analysis of visual angle model with anticipated time and stabilizing driving behavior |
| Xueyi Guan(管学义), Rongjun Cheng(程荣军)†, and Hongxia Ge(葛红霞) |
| Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China |
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Abstract In the light of the visual angle model (VAM), an improved car-following model considering driver's visual angle, anticipated time and stabilizing driving behavior is proposed so as to investigate how the driver's behavior factors affect the stability of the traffic flow. Based on the model, linear stability analysis is performed together with bifurcation analysis, whose corresponding stability condition is highly fit to the results of the linear analysis. Furthermore, the time-dependent Ginzburg-Landau (TDGL) equation and the modified Korteweg-de Vries (mKdV) equation are derived by nonlinear analysis, and we obtain the relationship of the two equations through the comparison. Finally, parameter calibration and numerical simulation are conducted to verify the validity of the theoretical analysis, whose results are highly consistent with the theoretical analysis.
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Received: 06 December 2021
Revised: 22 January 2022
Accepted manuscript online: 17 February 2022
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PACS:
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05.60.-k
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(Transport processes)
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45.70.Vn
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(Granular models of complex systems; traffic flow)
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| Fund: Project supported by the Natural Science Foundation of Zhejiang Province, China (Grant Nos. LY22G010001, LY20G010004), the Program of Humanities and Social Science of Education Ministry of China (Grant No. 20YJA630008), the National Key Research and Development Program of China-Traffic Modeling, Surveillance and Control with Connected & Automated Vehicles (Grant No. 2017YFE9134700), and the K.C. Wong Magna Fund in Ningbo University, China. |
Corresponding Authors:
Rongjun Cheng
E-mail: chengrongjun@nbu.edu.cn
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Cite this article:
Xueyi Guan(管学义), Rongjun Cheng(程荣军), and Hongxia Ge(葛红霞) Bifurcation analysis of visual angle model with anticipated time and stabilizing driving behavior 2022 Chin. Phys. B 31 070507
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[1] Sun Y Q, Ge H X and Cheng R J 2019 Phys. A 521 752
[2] Ge H X, Dai S Q, Dong L Y and Xue Y 2004 Phys. Rev. E 70 066134
[3] Jiang C T, Ge H X and Cheng R J 2019 Phys. A 513 465
[4] Tian H H, Xue Y, Kan S J and Jiang Y J 2009 Acta Phys. Sin. 58 4506 (in Chinese)
[5] Nagatani T 1996 J. Phys. Soc. Jpn. 65 3150
[6] Redhu P and Gupta A K 2015 Commun. Nonlinear Sci. Numer. Simul. 27 263
[7] Chang Y Y and Cheng R J 2019 Physica A 531 12175
[8] Cheng R J, Ge H X and Wang J F 2018 Appl. Math. Comput. 332 493
[9] Zhai Q T, Ge H X and Cheng R J 2018 Phys. A 490 774
[10] Chandler R E, Herman R and Montroll W E 1958 Operations Res. 6 165
[11] Gazis D C and Rothery H R W 1961 Operations Res. 9 545
[12] Herman R, Montroll E W, Potts R B and Rothery R W 1959 Operations Res. 7 86
[13] Yang Q I and Koutsopoulos H N 1996 Transport. Res. C 4 113
[14] Edie L C 1961 Operations Res. 9 66
[15] Greenshields B D, Bibbins J, Channing W and Miller H 1935 Proceedings of the Highway Research, December 6-7, 1935, Washington, U.S. p. 448
[16] Lee G 1966 Operations Res. 14 595
[17] Jin Z Z, Cheng R J and Ge H X 2018 Mod. Phys. Lett. B 32 1750366
[18] Newell G F 1961 Operations Res. 9 209
[19] Helly W 1961 Proceedings of the Symposium on the Theory of Traffic Flow p. 207
[20] Koshi M, Kuwarara M and Akahane H 1992 Ite J. 62 17
[21] Xing J 1995 Proceedings of the Steps Forward Intelligent Transport Systems World Congress, November 9-11, 1995, Yokohama, Japan, p. 1739
[22] Bando M, Hasebe K, Nakayama A, Shibata A and Sugiyama Y 1995 Phys. Rev. E 51 1035
[23] Helbing D and Tilch B 1998 Phys. Rev E 58 133
[24] Jiang R, Wu Q and Zhu Z 2001 Phys. Rev. E 64 017101
[25] Yan C Y, Ge H X and Cheng R J 2019 Phys. A 535 122216
[26] Michaels R M 1963 Proceedings of the Second International Symposium on the Theory of Traffic Flow 1963, Paris, OECD, p. 44
[27] Winsum W V 1999 Transportation Research Part F-Traffic Psychology and Behaviour 2 207
[28] Andersen G J and Sauer C W 2007 The Journal of the Human Factors and Ergonomics Society 49 878
[29] Jin S, Wang D H, Huang Z Y and Tao P F 2011 Phys. A 390 1931
[30] Huilgol R R 1978 Quart. Appl. Math. 36 85
[31] Igarashi Y, Itoh K, Nakanishi K, Ogura K and Yokokawa K 1999 Phys. Rev. Lett. 83 718
[32] Orosz G, Wilson R E and Krauskopf B 2004 Phys. Rev. E 70 026207
[33] Yamamoto M, Nomura Y and Sugiyama Y 2009 Phys. Rev. E 80 026203
[34] Gasser I, Sirito G and Werner B 2004 Physica D 197 222
[35] Jin Y F and Xu M 2010 Chin. Phys. Lett. 27 040501
[36] Zhang Y C, Xue Y, Zhang P, Fan D L and He H D 2019 Phys. A 514 133
[37] Ossen S, Hoogendoorn S P and Gorte B G H 2006 Transportation Research Record Journal of the Transportation Research Board 1965 121 |
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