TITLE:
Effects of Adaptive Random Deceleration on Traffic Flow
AUTHORS:
Qi Wang, Shu Zhu, Liuhua Zhu
KEYWORDS:
Traffic Flow, Cellular Automaton, Adaptive Random Deceleration, Synchronized Flow
JOURNAL NAME:
Journal of Applied Mathematics and Physics,
Vol.11 No.3,
March
9,
2023
ABSTRACT: Based on the Nagel-Schreckenberg model, an improved cellular automaton traffic flow model is proposed, in which the random deceleration probability of each vehicle is no longer fixed, but is adaptively adjusted according to the local traffic density in its vision and its current velocity. The numerical simulation results show that the maximum traffic capacity of the improved model under the same parameters is greater than that of the Nagel-Schreckenberg model, and is closer to the measured data. In addition, the traffic flow and vehicle velocity under different meteorological conditions are simulated by using the improved model, and the synchronized flow phenomenon consistent with the actual traffic is reproduced. Meanwhile, the results show that under the same parameters, when the traffic density is equal to 0.3, the traffic flow of the improved model increases by about 11% compared with the original model, and when the traffic density increases to 0.6, the traffic flow increases by about 27%.