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Feedback control strategy of a new car-following model based on reducing traffic accident rates

Author

Listed:
  • Cong Zhai
  • Weiming Liu
  • Feigang Tan
  • Ling Huang
  • Minglei Song

Abstract

To reduce the traffic accident death rate effectively and alleviate the traffic congestion phenomenon, this study proposes a new type of car-following model under the influence of drivers’ time-varying delay response time. Based on Lyapunov function theory, this paper reduces the traffic accident rate problem to the stability issues of the new model. By constructing suitable Lyapunov functions and using the linear matrix inequality method, the stability problem of the new car-following model is studied. The model, under the action of the controller, can effectively restrain traffic congestion. Using the traffic accident rate model proposed by Solomon, compared with the car-following model without the controller, the model under the controller shows a stronger convergence. This also means that the traffic congestion phenomenon has been effectively suppressed while greatly reducing the mortality rate of traffic accidents.

Suggested Citation

  • Cong Zhai & Weiming Liu & Feigang Tan & Ling Huang & Minglei Song, 2016. "Feedback control strategy of a new car-following model based on reducing traffic accident rates," Transportation Planning and Technology, Taylor & Francis Journals, vol. 39(8), pages 801-812, November.
    • Handle: RePEc:taf:transp:v:39:y:2016:i:8:p:801-812
    DOI: 10.1080/03081060.2016.1231900
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    References listed on IDEAS

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    1. Sun, Di-Hua & Liao, Xiao-Yong & Peng, Guang-Han, 2011. "Effect of looking backward on traffic flow in an extended multiple car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 631-635.
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    Cited by:

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