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Journal of Intelligent and Connected Vehicles 2018, 1(1): 1-14 https://doi.org/10.1108/JICV-11-2017-0001
Research paper | Open Access | Issue | Published: 07 August 2018

On the impact of connected automated vehicles in freeway work zones: a cooperative cellular automata model based approach

Show Author's Information Yun Zou1,  Xiaobo Qu2( )
School of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia
Department of Architecture and Civil Engineering, Chalmers University of Technology, Gothenburg, Sweden
Keywords:
Connected and automated vehicles, Work zone, Cooperative cellular automata model, Microscopic traffic flow models
Cite this article:
Zou Y, Qu X. On the impact of connected automated vehicles in freeway work zones: a cooperative cellular automata model based approach. Journal of Intelligent and Connected Vehicles, 2018, 1(1): 1-14. https://doi.org/10.1108/JICV-11-2017-0001
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Abstract Full text About this article
Purpose

Freeway work zones have been traffic bottlenecks that lead to a series of problems, including long travel time, high-speed variation, driver’s dissatisfaction and traffic congestion. This research aims to develop a collaborative component of connected and automated vehicles (CAVs) to alleviate negative effects caused by work zones.

Design/methodology/approach

The proposed cooperative component is incorporated in a cellular automata model to examine how and to what scale CAVs can help in improving traffic operations.

Findings

Simulation results show that, with the proposed component and penetration of CAVs, the average performances (travel time, safety and emission) can all be improved and the stochasticity of performances will be minimized too.

Originality/value

To the best of the authors’ knowledge, this is the first research that develops a cooperative mechanism of CAVs to improve work zone performance.


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About this article

On the impact of connected automated vehicles in freeway work zones: a cooperative cellular automata model based approach

Show Author's information Yun Zou1, Xiaobo Qu2( )
School of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia
Department of Architecture and Civil Engineering, Chalmers University of Technology, Gothenburg, Sweden

Abstract

Purpose

Freeway work zones have been traffic bottlenecks that lead to a series of problems, including long travel time, high-speed variation, driver’s dissatisfaction and traffic congestion. This research aims to develop a collaborative component of connected and automated vehicles (CAVs) to alleviate negative effects caused by work zones.

Design/methodology/approach

The proposed cooperative component is incorporated in a cellular automata model to examine how and to what scale CAVs can help in improving traffic operations.

Findings

Simulation results show that, with the proposed component and penetration of CAVs, the average performances (travel time, safety and emission) can all be improved and the stochasticity of performances will be minimized too.

Originality/value

To the best of the authors’ knowledge, this is the first research that develops a cooperative mechanism of CAVs to improve work zone performance.

Keywords: Connected and automated vehicles, Work zone, Cooperative cellular automata model, Microscopic traffic flow models

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Publication history
Copyright
Acknowledgements
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Publication history

Received: 20 November 2017
Revised: 18 February 2018
Accepted: 03 April 2018
Published: 07 August 2018
Issue date: October 2018

Copyright

© 2018 Yun Zou and Xiaobo Qu. Published in Journal of Intelligent and Connected Vehicles. Published by Emerald Publishing Limited.

Acknowledgements

The authors would like to thank University of Technology Sydney (UTS) for providing the scholarship.

Rights and permissions

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 may be seen at http://creativecommons.org/licences/by/4.0/legalcode

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