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Global stability and bifurcation of macroscopic traffic flow models for upslope and downslope

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Abstract

A macro-continuum model of the traffic flow is derived from a micro-car-following model that considers both the upslope and downslope by using the transformation relationship between macro- and micro-variables. The perturbation propagation characteristics and stability conditions of the macroscopic continuum equation are discussed. For uniform flow in the initial equilibrium state, the stability conditions reveal that as the slope angle increased under the action of a small disturbance, the upslope stability increases and downslope stability decreases. Moreover, under a large disturbance, the global stability analysis is carried out by using the wavefront expansion technique for uniform flow in the initial equilibrium state. For the initial nonuniform flow, nonlinear bifurcation analysis such as Hopf bifurcation and saddle–node bifurcation is carried out at the equilibrium point. Subcritical Hopf bifurcation exists when the traffic flow state changes; thus, the limit cycle formed by the Hopf bifurcation is unstable. And the existence condition of saddle-node bifurcation is obtained. Simulation results verify the stability conditions of the model and determine the critical density range. The numerical simulation results show the existence of Hopf bifurcation in phase space, and the spiral saddle point of saddle-node bifurcation varies with the slope angle. Furthermore, the impact of the angle of both the upslope and downslope on the evolution of density waves is investigated.

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References

  1. Payne, H.J.: FREFLO: A macroscopic simulation model of freeway traffic. Transp. Res. Rec. 722, 68–77 (1979)

    Google Scholar 

  2. Nagatani, T.: The physics of traffic jams. Rep. Prog. Phys. 65, 1331–1386 (2002)

    Google Scholar 

  3. Zhang, H.M.: A theory of non-equilibrium traffic flow. Transp. Res. Part B 32, 485–498 (1998)

    Google Scholar 

  4. Nagel, K., Schreckenberg, M.: A cellular automaton model for freeway traffic. J. Phys. I(2), 2221–2229 (1992)

    Google Scholar 

  5. Mcdowell, M.: Kinetic theory of vehicular traffic. J. Oper. Res. Soc. 23(4), 599–600 (2017)

    Google Scholar 

  6. Pipes, L.A.: An operational analysis of traffic dynamics. J. Appl. Phys. 24, 274–281 (1953)

    Google Scholar 

  7. Newell, G.F.: Nonlinear effects in the dynamics of car following. Oper. Res. 9, 209–229 (1961)

    MATH  Google Scholar 

  8. Bando, M., Hasebe, K., Nakayama, A., et al.: Dynamical model of traffic congestion and numerical simulation. Phys. Rev. E 51, 1035 (1995)

    Google Scholar 

  9. Lighthill, M.J., Rs, F., Whitham, G.B.: On kinematic waves I. Flood movement in long rivers. Math. Phys. Sci. 229, 281–316 (1955)

    MATH  Google Scholar 

  10. Richards, P.I.: Shock waves on the highway. Oper. Res. 4, 42–51 (1956)

    MATH  Google Scholar 

  11. Payne, H.J.: Models of freeway traffic and control. Math. Models Public Syst. Simul. Council. 1, 51–61 (1971)

    Google Scholar 

  12. Papageorgiou, M.: A hierarchical control system for freeway traffic. Transp. Res. Part B Methodol. 17(3), 251–261 (1983)

    Google Scholar 

  13. Kühne, R.D.: Macroscopic freeway model for dense traffic: stop-start waves and incident detection. Int. Symp. Transp. Traffic Theory 9, 21–42 (1984)

    Google Scholar 

  14. Kerner, B.S., Konhäuser, P.: Structure and parameters of clusters in traffic flow. Phys. Rev. E 50(1), 54–83 (1994)

    Google Scholar 

  15. Lee, H.Y., Lee, H.W., Kim, D.: Dynamic states of a continuum traffic equation with on-ramp. Phys. Rev. E 59(5), 5101–5111 (1999)

    Google Scholar 

  16. Daganzo, C.F.: Requiem for second-order fluid approximations of traffic flow. Transp. Res. Part B: Methodol. 29(4), 277–286 (1995)

    Google Scholar 

  17. Kaur, R., Sharma, S.: Analysis of driver’s characteristics on a curved road in a lattice model. Phys. A 471, 59–67 (2017)

    Google Scholar 

  18. Redhu, P., Gupta, A.K.: Effect of forward looking sites on a multi-phase lattice hydrodynamic model. Phys. A 445, 150–160 (2016)

    MATH  Google Scholar 

  19. Sharma, S.: Lattice hydrodynamic modeling of two-lane traffic flow with timid and aggressive driving behavior. Phys. A 421, 401–411 (2015)

    Google Scholar 

  20. Redhu, P., Gupta, A.K.: Delayed-feedback control in a lattice hydrodynamic model. Commun. Nonlinear Sci. Numer. Simulat. 27, 263–270 (2015)

    MATH  Google Scholar 

  21. Redhu, P., Gupta, A.K.: Jamming transitions and the effect of interruption probability in a lattice traffic flow model with passing. Phys. A 421, 249–260 (2015)

    MATH  Google Scholar 

  22. Gupta, A.K., Sharma, S., Redhu, P.: Effect of multi-phase optimal velocity function on jamming transition in a lattice hydrodynamic model with passing. Nonlinear Dyn. 80, 1091–1108 (2015)

    Google Scholar 

  23. Gupta, A.K., Redhu, P.: Analyses of the driver’s anticipation effect in a new lattice hydrodynamic traffic flow model with passing. Nonlinear Dyn. 76(2), 1001–1011 (2014)

    MATH  Google Scholar 

  24. Gupta, A.K., Redhu, P.: Analyses of driver’s anticipation effect in sensing relative flux in a new lattice model for two-lane traffic system. Phys. A 392, 5622–5632 (2013)

    Google Scholar 

  25. Kuang, H., et al.: An extended car-following model accounting for the honk effect and numerical tests. Nonlinear Dyn. 87, 149–157 (2017)

    Google Scholar 

  26. Qiang, X.H., Huang, L.: Traffic flow modeling in fog with cellular automata model. Modern Phys. Lett. B. 35(11), 2150180(1)-2150180(14) (2021)

    Google Scholar 

  27. Xue, Y., Zhang, Y.C., et al.: An extended macroscopic model for traffic flow on curved road and its numerical simulation. Nonlinear Dyn. 95(4), 3295–3307 (2019)

    MATH  Google Scholar 

  28. Kerner, B.S., Rehborn, H.: Experimental properties of phase transitions in traffic flow. Phys. Rev. Lett. 79, 4030–4033 (1997)

    Google Scholar 

  29. Helbing, D., Treiber, M.: Gas-kinetic-based traffic model explaining observed hysteretic phase transition. Phys. Rev. Lett. 81, 3042–3045 (1998)

    Google Scholar 

  30. Lee, H.Y., Lee, H.W., Kim, D.: Traffic states of a model highway with on-ramp. Phys. A 281, 78–86 (2008)

    Google Scholar 

  31. Komada, K., Masukura, S., Nagatani, T.: Effect of gravitational force upon traffic flow with gradients. Phys. A 388, 2880–2894 (2009)

    Google Scholar 

  32. Zhu, W.X., Yu, R.L.: Nonlinear analysis of traffic flow on a gradient highway. Phys. A 391, 954–965 (2012)

    Google Scholar 

  33. Wu, C.X., Zhang, P., Wong, S.C., Choi, K.: Steady-state traffic flow on a ring road with up- and down-slopes. Phys. A 403, 85–93 (2014)

    MATH  Google Scholar 

  34. Gupta, A.K., Sharma, S., Redhu, P.: Analyses of lattice traffic flow model on a gradient highway. Commun. Theor. Phys. 62(3), 393–404 (2014)

    MATH  Google Scholar 

  35. Kaur, R., Sharma, S.: Modeling and simulation of driver’s anticipation effect in a two lane system on curved road with slope. Phys. A 499, 110–120 (2018)

    MATH  Google Scholar 

  36. Li, X.L., Song, T., Kuang, H., Dai, S.Q., et al.: Phase transition on speed limit traffic with slope. Chin. Phys. B 17(8), 3014–3020 (2008)

    Google Scholar 

  37. Yu, R.L., Zhang, C.H.: Slope effect in traffic flow with a speed difference. Appl. Mech. Mater. 361–363, 2297–2303 (2013)

    Google Scholar 

  38. Chen, J.Z., Peng, Z.Y., et al.: An extended lattice model for two-lane traffic flow with consideration of the slope effect. Mod. Phys. Lett. B 29(05), 1550017–1550022 (2015)

    Google Scholar 

  39. Tan, J.H., Gong, L., Qin, X.Q.: An extended car-following model considering the low visibility in fog on a highway with slopes. Int. J. Mod. Phys. C 30(11), 1950090–1950096 (2019)

    Google Scholar 

  40. Zhou, J., Shi, Z.K., Cao, J.L.: An extended traffic flow model on a gradient highway with the consideration of the relative velocity. Nonlinear Dyn. 78(3), 1765–1779 (2014)

    Google Scholar 

  41. Zhang, X.D., Xu, J.L., Liang, Q.Q., et al.: Modeling impacts of speed reduction on traffic efficiency on expressway up slope sections. Sustainability 12(2), 587 (2020)

    Google Scholar 

  42. Choi, S., Suh, J., Yeo, H.: Microscopic analysis of climbing lane performance at freeway up slope section. Transp. Res. Proc. 21, 98–109 (2017)

    Google Scholar 

  43. He, H.D., Lu, W.Z., Xue, Y.: Dynamic characteristics and simulation of traffic flow with slope. Chin. Phys. B 18(7), 2703–2708 (2009)

    Google Scholar 

  44. Wang, Q.Y., Cheng, R.J., Ge, H.X.: A new lattice hydrodynamic model accounting for the traffic interruption probability on a gradient highway. Phys. Lett. A 16, 1879–1887 (2019)

    MATH  Google Scholar 

  45. Kuang, H., et al.: An extended car-following model incorporating the effects of driver’s memory and mean expected velocity field in ITS environment. Int. J. Mod. Phys. C 32, 2150095 (2021)

    Google Scholar 

  46. Kuang, H., et al.: An extended car-following model considering multi-anticipative average velocity effect under V2V environment. Phys. A 527, 121268 (2019)

    MATH  Google Scholar 

  47. Kuang, H., et al.: An extended car-following model accounting for the average headway effect in intelligent transportation system. Phys. A 471, 778–787 (2017)

    MATH  Google Scholar 

  48. Berg, P., Mason, A., Woods, A.: Continuum approach to car-following models. Phys. Rev. E 61, 1056–1066 (2000)

    Google Scholar 

  49. Helbing, D.: Derivation of non-local macroscopic traffic equations and consistent traffic pressures from microscopic car-following models. Eur. Phys. J. B 69(4), 539–548 (2009)

    Google Scholar 

  50. Gupta, A.K., Katiyar, V.K.: A new anisotropic continuum model for traffic flow. Phys. A 368(2), 551–559 (2006)

    Google Scholar 

  51. Gupta, A.K., Katiyar, V.K.: Analyses of shock waves and jams in traffic flow. J. Phys. A: Math. Gen. 38, 4069–4083 (2005)

    MATH  Google Scholar 

  52. Yi, J.G., Lin, H., Alvarez, L., Horowitz, R.: Stability of macroscopic traffic flow modeling through wavefront expansion. Transp. Res. Part B 37, 661–679 (2003)

    Google Scholar 

  53. Ou, Z.H., Dai, S.Q., Zhang, P., Dong, L.Y.: Nonlinear analysis in the Aw-Rascle anticipation model of traffic flow. SIAM J. Appl. Math. 67(3), 605–618 (2007)

    MATH  Google Scholar 

  54. Gupta, A.K., Sharma, S.: Nonlinear analysis of traffic jams in an anisotropic continuum model. Chin. Phys. B 11, 160–168 (2010)

    Google Scholar 

  55. Carrillo, F.A., Delgado, J., et al.: Traveling waves, catastrophes and bifurcations in a generic second order traffic flow model. Int. J. Bifurcat. Chaos. 23, 1350191–1350207 (2013)

    MATH  Google Scholar 

  56. Delgado, J., Saavedra, P.: Global bifurcation diagram for the Kerner-Konhauser traffic flow model. Int. J. Bifurcat. Chaos. 25, 1550064–1550075 (2015)

    MATH  Google Scholar 

  57. Gasser, I., Sirito, G., Werner, B.: Bifurcation analysis of a class of ‘car following’ traffic models. Phys. D 197, 222–241 (2004)

    MATH  Google Scholar 

  58. Orosz, G.: Hopf bifurcation calculations in delayed systems. Period. Polytech. 48, 189–200 (2004)

    MATH  Google Scholar 

  59. Orosz, G., Stepan, G.: Hopf bifurcation calculations in delayed systems with translational symmetry. J. Nonlin. Sci. 14, 505–528 (2004)

    MATH  Google Scholar 

  60. Orosz, G., Stepan, G.: Subcritical Hopf bifurcations in a car-following model with reaction-time delay. Proc. R. Soc. A 462, 2643–2670 (2006)

    MATH  Google Scholar 

  61. Ngoduy, D., Li, T.: Hopf bifurcation structure of a generic car-following model with multiple time delays. Transp. A: Transp. Sci. 17, 878–896 (2020)

    Google Scholar 

  62. Ai, W.H., Shi, Z.K., Liu, D.W.: Bifurcation analysis of a speed gradient continuum traffic flow model. Phys. A 437, 418–429 (2015)

    MATH  Google Scholar 

  63. Miura, Y., Sugiyama, Y.: Coarse analysis of collective behaviors: Bifurcation analysis of the optimal velocity model for traffic jam formation. Phys. Lett. A 381, 3983–3988 (2017)

    MATH  Google Scholar 

  64. Ren, W.L., Cheng, R.J., Ge, H.X.: Bifurcation analysis of a heterogeneous continuum traffic flow model. Appl. Math. Model. 94, 369–387 (2021)

    MATH  Google Scholar 

  65. Kerner, B.S., Konhäuser, P.: Cluster effect in initially homogeneous traffic flow. Phys. Rev. E 48(4), R2335–R2338 (1993)

    Google Scholar 

  66. Cao, J.F., Han, C.Z., Fang, Y.W.: Nonlinear Systems Theory and Application. Xi’an Jiao Tong University Press, Xi’an (2006)

    Google Scholar 

  67. Herrmann, M., Kerner, B.S.: Local cluster effect in difference traffic flow models. Phys. A 255, 163–188 (1998)

    Google Scholar 

  68. Igarashi, Y., Itoh, K., Nakanishi, K., et al.: Bifurcation phenomena in optimal velocity model for traffic flows. Phys. Rev. E 64, 047102 (2001)

    Google Scholar 

Download references

Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant No. 11962002 & 11902083 & 12072195), the Natural Science Foundation of Guangxi, China (Grant No. 2018GXNSFAA138205) and Innovation Project of Guangxi Graduate Education (YCBZ2021021).

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Cen, BL., Xue, Y., Qiao, YF. et al. Global stability and bifurcation of macroscopic traffic flow models for upslope and downslope. Nonlinear Dyn 111, 3725–3742 (2023). https://doi.org/10.1007/s11071-022-08032-y

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