An efficient heterogeneous platoon dispersion model for real-time traffic signal control

被引:16
|
作者
Yao, Zhihong [1 ,2 ,3 ,4 ]
Zhao, Bin [1 ,2 ]
Qin, Lingqiao [3 ]
Jiang, Yangsheng [1 ,2 ]
Ran, Bin [3 ]
Peng, Bo [4 ]
机构
[1] Southwest Jiaotong Univ, Sch Transportat & Logist, Chengdu 610031, Sichuan, Peoples R China
[2] Southwest Jiaotong Univ, Natl Engn Lab Integrated Transportat Big Data App, Chengdu 610031, Sichuan, Peoples R China
[3] Univ Wisconsin, TOPS Lab, Dept Civil & Environm Engn, 1415 Engn Dr, Madison, WI 53706 USA
[4] Chongqing Jiaotong Univ, Chongqing Key Laborat Traff & Transportat, Chongqing 400074, Peoples R China
关键词
Traffic engineering; Platoon dispersion model; Heterogeneous traffic flow; Travel time; Signal coordination; TRAVEL-TIME; CALIBRATION;
D O I
10.1016/j.physa.2019.122982
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
In China, urban arterial traffic presents a heterogeneous flow feature because of a high proportion of buses. Existing research on heterogeneous platoon dispersion models is very complex, which are not suitable for real-time signal timing optimization. Considering the classic Robertson's model has a simple form and high computation efficiency, an efficient heterogeneous platoon dispersion model is proposed based on Robertson's model. Firstly, the classic Robertson's model is used to capture different homogeneous platoon dispersion features. Then, these classic Robertson's models for homogeneous traffic flow are superposed to capture the characteristic of heterogeneous traffic flow. Finally, based on field observations, the performance of the proposed model, the classic Robertson's model, and the mixed Gaussian model are compared. The results show that the proposed model has a better prediction accuracy and higher computational efficiency, compared with the classic Robertson's model and the mixed Gaussian model. It is noteworthy that the proposed model not only better describes the dispersion feature of heterogeneous traffic flow but also meets the requirement of real-time signal control. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页数:12
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