Freeway traffic flow cellular automata model based on mean velocity feedback

被引:35
|
作者
Zeng, Junwei [1 ]
Qian, Yongsheng [1 ]
Mi, Pengfei [1 ]
Zhang, Chaoyang [1 ]
Yin, Fan [1 ]
Zhu, Leipeng [1 ]
Xu, Dejie [1 ]
机构
[1] Lanzhou Jiaotong Univ, Sch Traff & Transportat, Lanzhou 730070, Peoples R China
基金
中国国家自然科学基金;
关键词
Traffic flow; MCD model; Mean velocity feedback; Deceleration wave; INFORMATION FEEDBACK; DYNAMICS; STRATEGY;
D O I
10.1016/j.physa.2020.125387
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Making full use of real-time feedback traffic information to guide road traffic is one of the hot spots in the field of intelligent transportation system, which has practical significance for improving travel efficiency and reducing congestion. This paper proposes a new average speed feedback strategy based on real-time information, and uses it to improve the MCD model. The fundamental diagram, space-time diagram and flow interruption effect diagram obtained by simulation show that the results are consistent with the three-phase flow theory. It is found that in the free flow phase, the mean velocity feedback enables vehicles to adjust the velocity, accelerate the dissipation of the deceleration wave and maintain the stability of the traffic flow. In contrast, in the synchronized flow phase, the mean velocity feedback strategy keeps the traffic flow constant, reduces the velocity disturbance caused by the drivers' own factors and improves the road operation efficiency. (C) 2020 Published by Elsevier B.V.
引用
收藏
页数:11
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