A stochastic model for stop-and-go phenomenon in traffic oscillation: On the prospective of macro and micro traffic flow

Jianghui Wen, Lijiang Hong, Min Dai, Xinping Xiao and Chaozhong Wu

Applied Mathematics and Computation, 2023, vol. 440, issue C

Abstract: To investigate the stop-and-go phenomenon triggered by car-following, a hybrid model of micro and macro is proposed. Firstly, with the stochastic nature of driving behavior, a Brownian noise is added into the velocity difference to give a modification to the car-following model. Then, to combine the macroscopic traffic flow characteristics, the traffic stream model is introduced, and the two models are fused in the context of high traffic flow. Next, the theoretical validity of the fusion model is verified by the existence and uniqueness of the solution. The coefficients of the hybrid model are extracted as the stop coefficient and go coefficient which reflect the micro driving behavior. The Maximum Likelihood Estimations of the two coefficients are also given, as well as the boundedness of traffic oscillation in stop-and-go. Finally, numerical simulations show that the model has good fitting and prediction ability for traffic flow in high flow period. Moreover, the greater the stop coefficient, the stronger the traffic flow oscillation intensity, the larger the upper boundedness of the oscillation, the more severe the stop-and-go.

Keywords: Stop-and-go; Car-following; Stochastic driver's behavior; Sensitivity; Oscillation upper bound (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:440:y:2023:i:c:s0096300322007093

DOI: 10.1016/j.amc.2022.127637

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