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Research paper | Open Access

Active lane management for intelligent connected vehicles in weaving areas of urban expressway

Haijian Li1( )Junjie Zhang1Zihan Zhang2Zhufei Huang1
Beijing University of Technology, Beijing, China
China Academy of Urban Planning and Design, Beijing, China
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Abstract

Purpose

This paper aims to use active fine lane management methods to solve the problem of congestion in a weaving area and provide theoretical and technical support for traffic control under the environment of intelligent connected vehicles (ICVs) in the future.

Design/methodology/approach

By analyzing the traffic capacities and traffic behaviors of domestic and foreign weaving areas and combining them with field investigation, the paper proposes the active and fine lane management methods for ICVs to optimal driving behavior in a weaving area. The VISSIM simulation of traffic flow vehicle driving behavior in weaving areas of urban expressways was performed using research data. The influence of lane-changing in advance on the weaving area was evaluated and a conflict avoidance area was established in the weaving area. The active fine lane management methods applied to a weaving area were verified for different scenarios.

Findings

The results of the study indicate that ICVs complete their lane changes before they reach a weaving area, their time in the weaving area does not exceed the specified time and the delay of vehicles that pass through the weaving area decreases.

Originality/value

Based on the vehicle group behavior, this paper conducts a simulation study on the active traffic management control-oriented to ICVs. The research results can optimize the management of lanes, improve the traffic capacity of a weaving area and mitigate traffic congestion on expressways.

References

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Journal of Intelligent and Connected Vehicles
Pages 52-67

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Cite this article:
Li H, Zhang J, Zhang Z, et al. Active lane management for intelligent connected vehicles in weaving areas of urban expressway. Journal of Intelligent and Connected Vehicles, 2021, 4(2): 52-67. https://doi.org/10.1108/JICV-08-2020-0009

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Received: 30 August 2020
Revised: 17 January 2021
Accepted: 18 May 2021
Published: 08 September 2021
© 2021 Haijian Li, Junjie Zhang, Zihan Zhang and Zhufei Huang. Published in Journal of Intelligent and Connected Vehicles. Published by Emerald Publishing Limited.

This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at http://creativecommons.org/licences/by/4.0/legalcode