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An extended car-following model under stochastic theory and its feedback control
  • Z. H. Liu,
  • Qinghu Kong
Z. H. Liu
Xiamen University

Corresponding Author:[email protected]

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Qinghu Kong
Xiamen University School of Architecture and Civil Engineering
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In the actual traffic flow, vehicle driving is affected by many random factors. Gaussian white noise is introduced into the optimization velocity model to describe the random behavior, and a stochastic optimization velocity model is proposed. In order to improve the stability of traffic flow, the velocity difference of two successive vehicles ahead is considered, and a velocity difference feedback control model is established by taking the velocity difference between the vehicle and the target two vehicle as the control signal. Then, the stability conditions of stochastic optimization velocity model and feedback control model are obtained by using the moment stability theory. Last, Monte Carlo simulation is used to simulate the traffic. The results show that considering the random factor will reduce the stability of traffic flow, and the feedback control can effectively improve the stability.
01 Jul 2022Submitted to Mathematical Methods in the Applied Sciences
04 Jul 2022Submission Checks Completed
04 Jul 2022Assigned to Editor
08 Jul 2022Reviewer(s) Assigned
16 Sep 2023Review(s) Completed, Editorial Evaluation Pending
17 Sep 2023Editorial Decision: Revise Major
31 Jan 2024Review(s) Completed, Editorial Evaluation Pending
01 Feb 2024Editorial Decision: Revise Minor
15 Mar 20242nd Revision Received
18 Mar 2024Submission Checks Completed
18 Mar 2024Assigned to Editor
18 Mar 2024Reviewer(s) Assigned