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The theoretical analysis of the anticipation lattice models for traffic flow

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Abstract

Based on the anticipation lattice hydrodynamic models, which are described by the partial differential equations, the continuum version of the model is investigated through a reductive perturbation method. The linear stability theory is used to discuss the stability of the continuum model. The Korteweg–de Vries (for short, KdV) equation near the neutral stability line and the modified Korteweg–de Vries (for short, mKdV) equation near the critical point are obtained by using the nonlinear analysis method. And the corresponding solutions for the traffic density waves are derived, respectively. The results display that the anticipation factor has an important influence on traffic flow. From the simulation, it is shown that the traffic jam is suppressed efficiently with taking into account the anticipation effect, and the analytical result is consonant with the simulation one.

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References

  1. Treiber, M., Kesting, A.: Traffic Flow Dynamics. Springer, Berlin (2013)

    Book  Google Scholar 

  2. Treiber, M., Kesting, A.: Evidence of convective instability in congested traffic flow: a systematic empirical and theoretical investigation. Transp. Res., Part B, Methodol. 45, 1362–1377 (2011)

    Article  Google Scholar 

  3. Tang, T.Q., Li, C.Y., Huang, H.J., Shang, H.Y.: A new fundamental diagram theory with the individual difference of the driver’s perception ability. Nonlinear Dyn. 67, 2255–2265 (2012)

    Article  Google Scholar 

  4. Tang, T.Q., Huang, H.J., Xu, G.: A new macro model with consideration of the traffic interruption probability. Physica A 387, 6845–6856 (2008)

    Article  Google Scholar 

  5. Tang, T.Q., Li, C.Y., Wu, Y., Huang, H.J.: Impact of the honk effect on the stability of traffic flow. Physica A 390, 3362–3368 (2011)

    Article  Google Scholar 

  6. Tian, H.H., Xue, Y.: A lattice hydrodynamical model considering turning capability. Chin. Phys. B 21, 070505 (2012)

    Article  Google Scholar 

  7. Tang, T.Q., Huang, H.J., Shang, H.Y.: A new macro model for traffic flow with the consideration of the driver’s forecast effect. Phys. Lett. A 374, 1668–1672 (2010)

    Article  MATH  Google Scholar 

  8. Peng, G.H., Cai, X.H., Cao, B.F., Liu, C.Q.: A new lattice model of traffic flow with the consideration of the traffic interruption probability. Physica A 391, 656–663 (2012)

    Article  Google Scholar 

  9. Peng, G.H.: A driver’s memory lattice model of traffic flow and its numerical simulation. Nonlinear Dyn. 67, 1811–1815 (2012)

    Article  MATH  Google Scholar 

  10. Ngoduy, D.: Instabilities of cooperative adaptive cruise control traffic flow: a macroscopic approach. Commun. Nonlinear Sci. Numer. Simul. 18, 2838–2851 (2013)

    Article  MathSciNet  Google Scholar 

  11. 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, Math. Phys. Sci. 229, 281 (1955)

    Article  MATH  MathSciNet  Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

  13. Richards, P.I.: Shock waves on the high way. Oper. Res. 4, 4251 (1956)

    Article  MathSciNet  Google Scholar 

  14. Payne, H.J.: Models of freeway traffic and control. In: Bekey, G.A. (ed.) Mathematical Models of Public Systems. Proc. 1971 SCI Conference. Simulation Councils Proceedings Series, vol. 1, La Jolla, CA, pp. 51–56 (1971)

    Google Scholar 

  15. Treiber, M., Kesting, A., Helbing, D.: Delays, inaccuracies and anticipation in microscopic traffic model. Physica A 360, 71–88 (2006)

    Article  Google Scholar 

  16. Ngoduy, D., Wilson, R.E.: Multi-anticipative nonlocal second order traffic model. Comput.-Aided Civil Infrastruct. Eng. 7 (2013)

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

    Article  MathSciNet  Google Scholar 

  18. Ge, H.X., Dai, S.Q., Xue, Y., Dong, L.Y.: Phase transition and modified KdV equation in a cooperation system. Phys. Rev. E 71, 066119 (2005)

    Article  MathSciNet  Google Scholar 

  19. Ge, H.X.: Traffic anticipation effect in the lattice hydrodynamic model. In: Appert-Rolland, C., Chevoir, F., Gondret, P., lassarre, S., Lebacque, J.-P., Schreckenberg, M. (eds.) Traffic and Granular Flow’07, Orsay, France, pp. 293–299 (2007)

    Google Scholar 

  20. Nagatani, T.: Jamming transition in a two-dimensional. Phys. Rev. E 59, 4857–4864 (1999)

    Article  Google Scholar 

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

    Article  Google Scholar 

  22. Ge, H.X., Cheng, R.J., Dai, S.Q.: KdV and kink–antikink solitons in car-following models. Physica A 357(3–4), 466 (2005)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgement

Project supported by the National Natural Science Foundation of China (Grant Nos. 11072117, 11372166 and 61074142), the Scientific Research Fund of Zhejiang Provincial, China (Grant No. LY13A010005), Disciplinary Project of Ningbo, China (Grant No. SZXL1067) and the K.C. Wong Magna Fund in Ningbo University, China.

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Correspondence to Hong-Xia Ge.

Appendix

Appendix

Substituting Eqs. (12)–(13) into Eq. (10), then we get the linearized equation,

$$\begin{aligned} &{\partial^{2}_{t} y+a\partial_{t} y+a \rho_{0}^{2}V'(\rho _{0})y(x+1)} \\ &{\quad+sa \rho_{0}^{2}V'(\rho_{0}) \bigl(y(x+1)-y(x)\bigr)=0,} \end{aligned}$$
(38)

where V′(ρ 0)=dV(ρ)/, at ρ=ρ 0. Expanding y(x,t)=exp(ikx+zt), we have

$$\begin{aligned} &{z^{2}+az+a\rho_{0}^{2}V' \exp(ik)} \\ &{\quad+iksa\rho_{0}^{2}V'\bigl(\operatorname{exp}(ik)-1 \bigr)=0.} \end{aligned}$$
(39)

Prescribing z=z 1(ik)+z 2(ik)2+⋯ and \(\exp(ik)=1+ik+\frac{1}{2}(ik)^{2}+\cdots\), inserting them into Eq. (38), and keeping the first- and second-order terms of ik, then we get the coefficients of z, respectively,

$$\begin{aligned} &{z_{1}=-\rho_{0}^{2}V',\qquad z_{2}=-\tau\bigl(\rho_{0}^{2}V' \bigr)^{2}-(s+1)\rho_{0}^{2}V'.} \end{aligned}$$
(40)

If z 2 is a positive value, the uniform flow is stable. If z 2 is a negative value, the uniform flow is unstable for long wavelength modes. So we get the unstable condition

$$\begin{aligned} a<\frac{-\rho_{0}^{2}V'}{1+s}. \end{aligned}$$
(41)

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Cheng, RJ., Li, ZP., Zheng, PJ. et al. The theoretical analysis of the anticipation lattice models for traffic flow. Nonlinear Dyn 76, 725–731 (2014). https://doi.org/10.1007/s11071-013-1164-5

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