Nonlinear analysis of a new car-following model accounting for the optimal velocity changes with memory

Guanghan Peng, Weizhen Lu*, Hongdi He, Zhenghua Gu

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

100 Citations (Scopus)

Abstract

We, in this study, construct a new car-following model by accounting for the effect of the optimal velocity changes with memory in terms of the full velocity difference (FVD) model. The stability condition and mKdV equation concerning the optimal velocity changes with memory are derived through both linear stability and nonlinear analyses, respectively. Then, the space concerned can be divided into three regions classified as the stable, the metastable and the unstable ones. Moreover, it is shown that the effect of the optimal velocity changes with memory could enhance the stability of traffic flow. Furthermore, the numerical results verify that not only the sensitivity parameter of the optimal velocity changes with memory of driver but also the memory step could effectively stabilize the traffic flow. In addition, the stability of traffic flow is strengthened by increasing the memory step-size of optimal velocity changes and the intensity of drivers' memory with such changes. Most importantly, the effect of the optimal velocity changes with memory may avoid the disadvantage of historical information, which decreases the stability of traffic flow on road.
Original languageEnglish
Pages (from-to)197-205
JournalCommunications in Nonlinear Science and Numerical Simulation
Volume40
Online published21 Apr 2016
DOIs
Publication statusPublished - Nov 2016

Research Keywords

  • 45.70.Vn
  • 89.40.-a
  • Car-following model
  • Nonlinear analysis
  • Stability
  • Traffic flow

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