Skip to main content

Advertisement

Log in

KdV-Burgers equation in the modified continuum model considering the “backward looking” effect

  • Original Paper
  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

Considering the backward looking effect, a modified continuum model is put forward. The stability criterion of this continuum model is deduced by performing linear stability analysis. The theoretical result demonstrates that the traffic flow is stabilized considering backward looking effect. The KdV-Burgers equation is obtained through perturbed nonlinear analysis, which could show the propagating process of density wave. Numerical simulation is carried out to explores how backward looking affected each car’s velocity, density and energy consumption. Numerical results demonstrate that backward looking effect has significant impact on traffic dynamic characteristic. In addition, the energy consumptions of this modified continuum model are also studied. Numerical simulation results indicate that the effect of backward looking will suppress the traffic jam and decrease cars’ energy consumptions during the whole evolution of small perturbation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Tang, T.Q., Zhang, J., Liu, K.: A speed guidance model accounting for the driver’s bounded rationality at a signalized intersection. Phys. A 473, 45–52 (2017)

    Article  Google Scholar 

  2. Tang, T.Q., Huang, H.J., Shang, H.Y.: An extended macro traffic flow model accounting for the driver’ s bounded rationality and numerical tests. Phys. A 468, 322–333 (2017)

    Article  Google Scholar 

  3. Tang, T.Q., Luo, X.F., Liu, K.: Impacts of the driver’s bounded rationality on the traffic running cost under the car-following model. Phys. A 457, 316–321 (2016)

    Article  Google Scholar 

  4. Tang, T.Q., Yu, Q.: Influences of vehicles’ fuel consumption and exhaust emissions on the trip cost without late arrival under car-following model. Int. J. Mod. Phys. C 27, 1650011 (2016)

    Article  MathSciNet  Google Scholar 

  5. Li, Y.F., Sun, D.H., Liu, W.N., Zhang, M., Zhao, M., Liao, X.Y., Tang, L.: Modeling and simulation for microscopic traffic flow based on multiple headway, velocity and acceleration difference. Nonlinear Dyn. 66, 15–28 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  6. Bando, M., Hasebe, K., Shibata, A., Sugiyama, Y.: Dynamical model of traffic congestion and numerical simulation. Phys. Rev. E 51, 1035–1042 (1995)

    Article  Google Scholar 

  7. Lighthill, M.J., Whitham, G.B.: On kinematic waves. I. Flood movement in long rivers. Proc. R. Soc Lond. Ser. A 229, 281–316 (1955)

    Article  MathSciNet  MATH  Google Scholar 

  8. Lighthill, M.J., Whitham, G.B.: On kinematic waves. II. A theory of traffic flow on long crowded roads. Proc. R. Soc. Lond. Ser. A 229, 317–345 (1955)

    Article  MathSciNet  MATH  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  10. Payne, H.J.: Mathematical models of public systems. Simul. Counc. Proc. Ser. 1, 51–61 (1971)

    MathSciNet  Google Scholar 

  11. Jiang, R., Wu, Q.S., Zhu, Z.J.: Full velocity difference model for a car-following theory. Phys. Rev. E 64, 017101 (2001)

    Article  Google Scholar 

  12. Jiang, R., Hu, M.B., Zhang, H.M., Gao, Z.Y., Jia, B., Wu, Q.S., Wang, B., Yang, M.: Traffic experiment reveals the nature of car-following. PLOs ONE 9, 4 (2014)

    Google Scholar 

  13. Jiang, R., Hu, M.B., Zhang, H.M., Gao, Z.Y., Jia, B., Wu, Q.S.: On some experimental features of car-following behavior and how to model them. Transp. Res. B 80, 338–354 (2015)

    Article  Google Scholar 

  14. Tang, T.Q., Wu, Y.H., Caccetta, L., Huang, H.J.: A new car-following model with consideration of roadside memorial. Phys. Lett. A 375, 3845–3850 (2011)

    Article  MATH  Google Scholar 

  15. Tang, T.Q., Wang, Y.P., Yang, X.B., Wu, Y.G.: A new car-following model accounting for varying road condition. Nonlinear Dyn. 70, 1397–1405 (2012)

    Article  MathSciNet  Google Scholar 

  16. Tang, T.Q., Shi, W.F., Shang, H.Y., Wang, Y.P.: A new car-following model with consideration of inter-vehicle communication. Nonlinear Dyn. 76, 2013–2017 (2014)

    Google Scholar 

  17. Zhu, W.X., Zhang, L.D.: Analysis of car-following model with cascade compensation strategy. Phys. A 449, 265–274 (2016)

    Article  MathSciNet  Google Scholar 

  18. Peng, G.H., Cheng, G.H.: A new car-following model with the consideration of anticipation optimal velocity. Phys. A 392, 3563–3569 (2013)

    Article  MathSciNet  Google Scholar 

  19. Peng, G.H., Lu, W.Z., He, H.D., Gu, Z.H.: Nonlinear analysis of a new car-following model accounting for the optimal velocity changes with memory. Commun. Nonlinear Sci. Numer. Simul. 40, 197–205 (2016)

    Article  MathSciNet  Google Scholar 

  20. Song, H., Ge, H.X., Chen, F.Z., Cheng, R.J.: TDGL and mKdV equations for car-following model considering traffic jerk and velocity difference. Nonlinear Dyn. 87, 1809–1817 (2017)

    Article  Google Scholar 

  21. Nagatani, T.: Thermodynamic theory for the jamming transition in traffic flow. Phys. Rev. E 58, 4271–4276 (1998)

    Article  Google Scholar 

  22. Nagatani, T.: TDGL and MKDV equation for jamming transition in the lattice models of traffic. Phys. A 264, 581–592 (1999)

    Article  Google Scholar 

  23. Nagatani, T.: Jamming transition in the lattice models of traffic. Phys. Rev. E 59, 4857–4864 (1999)

    Article  Google Scholar 

  24. Li, Z.P., Liu, F.Q., Sun, J.: A lattice traffic model with consideration of preceding mixture traffic information. Chin. Phys. B 20, 088901 (2011)

    Article  Google Scholar 

  25. Ge, H.X., Cheng, R.J., Lo, S.M.: Time-dependent Ginzburg Landau equation for lattice hydrodynamic model describing pedestrian flow. Chin. Phys. B 22, 070507 (2013)

    Article  Google Scholar 

  26. Sun, D.H., Zhang, M., Chuan, T.: Multiple optimal current difference effect in the lattice traffic flow model. Mod. Phys. Lett. B 28, 1450091 (2014)

    Article  MathSciNet  Google Scholar 

  27. Sun, D.H., Zhang, G., Liu, W.N.: Effect of explicit lane changing in traffic lattice hydrodynamic model with interruption. Nonlinear Dyn. 86, 269–282 (2016)

    Article  MathSciNet  Google Scholar 

  28. Li, Z.P., Zhong, C.J., Chen, L.Z., Xu, S.Z., Qian, Y.Q.: Analytical studies on a new lattice hydrodynamic traffic flow model with consideration of traffic current cooperation among three consecutive sites. Int. J. Mod. Phys. C 27, 1650034 (2016)

    Article  MathSciNet  Google Scholar 

  29. Peng, G.H., Qing, L.: The effects of drivers aggressive characteristics on traffic stability from a new car-following model. Mod. Phys. Lett. B 30, 1650243 (2016)

    Article  MathSciNet  Google Scholar 

  30. Li, X.Q., Fang, K.L., Peng, G.H.: A new lattice model of traffic flow with the consideration of the drivers’ aggressive characteristics. Phys. A 468, 315–321 (2017)

    Article  MathSciNet  Google Scholar 

  31. Nagatani, T.: Modified KdV equation for jamming transition in the continuum models of traffic. Phys. A 261, 599–607 (1998)

    Article  MathSciNet  Google Scholar 

  32. Ge, H.X., Lai, L.L., Zheng, P.J., Cheng, R.J.: The KdV-Burgers equation in a new continuum model with consideration of driver’s forecast effect and numerical tests. Phys. A 377, 3193–3198 (2013)

    MathSciNet  MATH  Google Scholar 

  33. Lai, L.L., Cheng, R.J., Li, Z.P., Ge, H.X.: Theoretical analysis of the density wave in a new continuum model and numerical simulation. Phys. A 402, 0378–4371 (2014)

    Article  MathSciNet  Google Scholar 

  34. Liu, F.X., Cheng, R.J., Zheng, P.J., Ge, H.X.: TDGL and mKdV equations for car-following model considering traffic jerk. Nonlinear Dyn. 261, 793–800 (2015)

    Google Scholar 

  35. Liu, H.Q., Zheng, P.J., Zhu, K.Q., Ge, H.X.: KdV-Burgers equation in the modified continuum model considering anticipation effect. Phys. A 438, 26–31 (2015)

    Article  MathSciNet  Google Scholar 

  36. Liu, H.Q., Cheng, R.J., Zhu, K.Q., Ge, H.X.: The study for continuum model considering traffic jerk effect. Nonlinear Dyn. 83, 57–64 (2016)

    Article  Google Scholar 

  37. Cheng, R.J., Ge, H.X., Wang, J.F.: An extended continuum model accounting for the driver’s timid and aggressive attributions. Phys. A 381, 1302–1312 (2017)

    MathSciNet  MATH  Google Scholar 

  38. Nakayama, A., Sugiyama, Y., Hasebe, K.: Effect of looking at the car that follows in an optimal velocity model of traffic flow. Phys. Rev. E 65, 016112 (2001)

    Article  Google Scholar 

  39. Ge, H.X., Zhu, H.B., Dai, S.Q.: Effect of looking backward on traffic flow in a cooperative driving car following model. Eur. Phys. J. B 54, 503–507 (2006)

    Article  Google Scholar 

  40. Ge, H.X., Cheng, R.J.: The “backward looking” effect in the lattice hydrodynamic model. Phys. A 387, 6952–6958 (2008)

    Article  Google Scholar 

  41. Sun, D.H., Liao, X.Y., Peng, G.H.: Effect of looking backward on traffic flow in an extended multiple car-following model. Phys. A 390, 631–635 (2011)

    Article  Google Scholar 

  42. Yang, D., Jin, P., Pu, Y., Ran, B.: Safe distance car-following model including backward-looking and its stability analysis. Phys. B 86, 92 (2013)

    MathSciNet  Google Scholar 

  43. Jiang, R., Wu, Q.S., Zhu, Z.J.: A new continuum model for traffic flow and numerical tests. Transp. Res. B 36, 405–419 (2002)

    Article  Google Scholar 

  44. Berg, B., Woods, A.: Traveling waves in an optimal velocity model of freeway traffic. Phys. Rev. E 64, 035602 (2001)

    Article  Google Scholar 

  45. Arqub, O.A.: Numerical solutions for the Robin time-fractional partial differential equations of heat and fluid flows based on the reproducing kernel algorithm. J. Numer. Methods Heat Fluid Flow Int. (2017). https://doi.org/10.1108/HFF-07-2016-0278

  46. Arqub, O.A.: Fitted reproducing kernel Hilbert space method for the solutions of some certain classes of time-fractional partial differential equations subject to initial and Neumann boundary conditions. Comput. Math. Appl. 73, 1243–1261 (2017)

    Article  MathSciNet  Google Scholar 

  47. Arqub, O.A., El-Ajou, A., Momani, S.: Constructing and predicting solitary pattern solutions for nonlinear time-fractional dispersive partial differential equations. J. Comput. Phys. 293, 385–399 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  48. El-Ajou, A., Arqub, O.A., Momani, S.: Approximate analytical solution of the nonlinear fractional KdV-Burgers equation: a new iterative algorithm. J. Comput. Phys. 293, 81–95 (2015)

    Article  MathSciNet  MATH  Google Scholar 

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

    Article  Google Scholar 

  50. Kerner, B.S., Konhauser, P.: Cluster effect in initially homogeneous traffic flow. Phys. Rev. E 48, 2335–2338 (1993)

    Article  Google Scholar 

Download references

Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant Nos. 11702153, 71571107, 61773290), the Natural Science Foundation of Zhejiang Province, China (Grant No. LY18A010003) and the K.C. Wong Magna Fund in Ningbo University, China. Funding was provided by National Natural Science Foundation of China (Grant No. 11372166), the Scientific Research Fund of Zhejiang Provincial, China (Grant Nos. LY15A020007, LY15E080013).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rongjun Cheng.

Ethics declarations

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this article.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, Z., Wang, J., Ge, H. et al. KdV-Burgers equation in the modified continuum model considering the “backward looking” effect. Nonlinear Dyn 91, 2007–2017 (2018). https://doi.org/10.1007/s11071-017-3999-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11071-017-3999-7

Keywords

Navigation