A Cellular Automaton Traffic Flow Model with Advanced Decelerations

被引:1
|
作者
Liu, Yingdong [1 ]
机构
[1] Lanzhou Jiaotong Univ, Coll Traff & Transportat, Lanzhou 730070, Peoples R China
基金
高等学校博士学科点专项科研基金; 中国国家自然科学基金;
关键词
D O I
10.1155/2012/717085
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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, metastable 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.
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页数:14
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