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作者:

Li, Haijian (Li, Haijian.) | Huang, Zhufei (Huang, Zhufei.) | Zou, Xiaofang (Zou, Xiaofang.) | Zheng, Shuo (Zheng, Shuo.) | Yang, Yanfang (Yang, Yanfang.)

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摘要:

The traffic congestion in ramp areas is becoming increasingly prominent. In the upstream segments of ramp areas, effective management and control of lane-changing behaviors can improve the road capacity and make full use of the existing road resource. With the continuous development and application of connected vehicle technologies, lane-changing behaviors can be performed by vehicle groups. Under a connected vehicle environment, the lane-changing behaviors by vehicle groups are controlled in the upstream segment in a ramp area, and the lane-changing behaviors can be completed prior to entering the ramp area. Finally, lane-changing strategies are optimized and identified. VISSIM simulates these proposed strategies. This paper considers the delay as the output index for analyzing and comparing various strategies. The results demonstrate that the delays of different lane-changing strategies are also different. If the delays of ramp areas are to be substantially reduced, it is necessary to continuously optimize the lane-changing strategies by vehicle groups in the upstream segments. This optimization of lane-changing strategies will effectively regulate drivers' lane-changing behaviors, improve road safety, and increase traffic capacity.

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作者机构:

  • [ 1 ] [Li, Haijian]Beijing Univ Technol, Beijing Engn Res Ctr Urban Transportat Operat Sup, Beijing 100124, Peoples R China
  • [ 2 ] [Huang, Zhufei]Beijing Univ Technol, Beijing Engn Res Ctr Urban Transportat Operat Sup, Beijing 100124, Peoples R China
  • [ 3 ] [Zou, Xiaofang]China Merchants New Intelligence Technol Co Ltd, Beijing 100073, Peoples R China
  • [ 4 ] [Zheng, Shuo]Beijing Jiaotong Univ, Natl Virtual Expt Teaching Ctr Rail Traff Commun, Beijing 100044, Peoples R China
  • [ 5 ] [Yang, Yanfang]China Acad Transportat Sci, Lab Transport Ind Big Data Applicat Technol Compr, Beijing 100029, Peoples R China

通讯作者信息:

  • [Yang, Yanfang]China Acad Transportat Sci, Lab Transport Ind Big Data Applicat Technol Compr, Beijing 100029, Peoples R China

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来源 :

JOURNAL OF ADVANCED TRANSPORTATION

ISSN: 0197-6729

年份: 2020

卷: 2020

2 . 3 0 0

JCR@2022

ESI学科: ENGINEERING;

ESI高被引阀值:115

被引次数:

WoS核心集被引频次: 9

SCOPUS被引频次: 10

ESI高被引论文在榜: 0 展开所有

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