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Assessing temporary traffic management measures on a motorway: lane closures vs narrow lanes for connected and autonomous vehicles in roadworks

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posted on 2025-01-17, 16:55 authored by Mohit Kumar Singh, Nicolette Formosa, Cheuk Ki Man, Craig MortonCraig Morton, Cansu Bahar Masera, Mohammed Quddus

Connected and automated vehicles (CAVs) are being developed and designed to operate on existing roads. Their safe and efficient operation during roadworks, where traffic management measures are often introduced, is crucial. Two alternative measures are commonly applied during roadworks on motorways: (i) closing one or multiple lanes (ii) narrowing one or all lanes. The former can cause delays and increased emissions, while the latter can pose safety risks. This study uses a VISSIM‐based traffic microsimulation to compare the effectiveness of these two strategies on traffic efficiency and safety, considering various market penetration rates (MPR) of CAVs. The model was calibrated and validated with the data collected from M1 motorway in the United Kingdom. Results show that average delays per vehicle‐kilometre‐travelled decreased from 102.7 to 2.5 s (with lane closure) and 23.6 to 0.6 s (with narrow lanes) with 0% and 100% CAV MPR, respectively. Moreover, safety in narrow lanes improved by 4.8 times compared to 1.5 times improvement in lane closure with a 100% CAV MPR; indicating that narrow lanes would result in better safety performance. These findings could assist transport authorities in designing temporary traffic management measure that results in better CAV performance when navigating through roadworks.

Funding

National Highways. Grant Number: 112278-649226

History

School

  • Architecture, Building and Civil Engineering

Published in

IET Intelligent Transport Systems

Volume

18

Issue

7

Pages

1210-1226

Publisher

John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Acceptance date

2024-02-22

Publication date

2024-03-08

Copyright date

2024

ISSN

1751-956X

eISSN

1751-9578

Language

  • en

Depositor

Dr Craig Morton. Deposit date: 11 March 2024

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