Abstract
A one‐dimensional cellular automaton traffic flow model, which considers the deceleration in advance, is addressed in this paper. The model reflects the situation in the real traffic that drivers usually adjust the current velocity by forecasting its velocities in a short time of future, in order to avoid the sharp deceleration. The fundamental diagram obtained by simulation shows the ability of this model to capture the essential features of traffic flow, for example, synchronized flow, meta‐stable state, and phase separation at the high density. Contrasting with the simulation results of the VE model, this model shows a higher maximum flux closer to the measured data, more stability, more efficient dissolving blockage, lower vehicle deceleration, and more reasonable distribution of vehicles. The results indicate that advanced deceleration has an important impact on traffic flow, and this model has some practical significance as the result matching to the actual situation.
Highlights
With the drastic growth in the vehicle amount, traffic congestion has become more and more serious
Our model shows the metastable state, phase separation, and hysteresis phenomenon by computer simulating, which exists in actual traffic
From the views of time and space, this paper proposes the cellular automaton model based on the deceleration in advance
Summary
With the drastic growth in the vehicle amount, traffic congestion has become more and more serious. The model deals with single-lane traffic flow of cars moving in a onedimensional cellular chain under periodic boundary conditions, which only considers vehicle acceleration, deceleration, random delays, and update of vehicle location. Literature 4 took into account the velocity effect of a car on the successive and proposed the VE velocity effect model. Literature 5 presented a cellular automaton model for single-lane traffic flow, and the model considers the effect of headway distance between two successive cars on the randomization of the latter car. Literature 6 took into account the diversity of traffic behaviors under real traffic situations induced by various driving characters and habits to modify the weighted probabilistic cellular automaton model. Literature 8 proposed an improved cellular automaton model to describe the urban traffic flow with the consideration of traffic light and driving behavior effects. Our model shows the metastable state, phase separation, and hysteresis phenomenon by computer simulating, which exists in actual traffic
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