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Nonlinear Dynamics

, Volume 85, Issue 3, pp 1423–1443 | Cite as

Lattice hydrodynamic model for two-lane traffic flow on curved road

  • Jie Zhou
  • Zhong-Ke Shi
  • Chao-Ping Wang
Original Paper

Abstract

Traffic flow on curved road is irregular, and it is more complicated than the one on straight road. In order to investigate the effect of lane-change behavior upon traffic dynamics on curved road, an extended lattice hydrodynamic model for two-lane traffic flow on curved road is proposed and studied analytically and numerically in this paper. The stability condition is obtained by the use of linear stability analysis. It is shown that the stability of traffic flow varies with lane-changing coefficient. The time- dependent Ginzburg–Landau equation is derived near the critical point to describe the nonlinear traffic behavior. Meanwhile, the Burgers, Korteweg–de Vries (KdV) and modified KdV equations are derived to describe the nonlinear density waves in the stable, metastable and unstable regions, respectively. The simulations are given to verify the analytical results. The results show that there are two distinct types of jamming transition. One is conventional jamming transition to the kink jam, and the other is jamming transition to the chaotic jam through kink jam. The numerical results also indicate that lane-changing behavior has a stabilizing effect on traffic flow on curved road, and it also can suppress the occurrence of chaotic phenomena.

Keywords

Traffic flow Lane-changing effect Curved road  TDGL equation 

Notes

Acknowledgments

The authors wish to thank the anonymous referees for their useful comments. This work was partially supported by the National Natural Science Foundation of China (Grant No. 61134004), Zhejiang Province National Science Foundation (Grant No. LY12A010 09) and Scientific Research Fund of Zhejiang Provincial Education Department (Grant No.Y201328023).

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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.School of Mathematics, Physics and Information ScienceZhejiang Ocean UniversityZhoushanChina
  2. 2.College of AutomationNorthwestern Polytechnical UniversityXi’anChina
  3. 3.Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province, Zhejiang Ocean UniversityZhoushanChina

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