Congestion in cities: can road capacity expansions provide a solution?
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Published version
Author(s)
Anupriya
Bansal, P
Graham, DJ
Type
Journal Article
Abstract
Road network congestion; a traffic state characterised by slower speeds, longer trip times, and increased vehicular queuing; is a major issue in most urban areas around the globe. Building more roads is a commonly employed policy intervention to reduce congestion. This strategy, however, is controversial because under certain conditions road capacity expansions may induce growth in traffic volumes. A crucial precursor to understanding whether road capacity expansions provide a solution to congestion is to quantify the technology driving congestion in urban road networks. This congestion technology describes the variation in performance of the network, often represented by traffic flow through the road network, over its intensity of use given by the number of vehicles in the network. However, obtaining empirical estimates of congestion technology from data on traffic variables is challenging due to statistical biases that emerge via the complex interactions between traffic flow, traffic controls, and capacity. To adjust for such biases, this paper presents an approach based on causal statistical modelling to quantify the nature and form of congestion technology in road networks in twenty-four cities worldwide. Our results suggest that increasing network capacity is in general not an efficient solution to manage congestion, in the sense that the average travel speed in the network does not increase substantially with an increase in capacity. This result and our congestion technology estimates have important implications for optimal urban transportation strategies.
Date Issued
2023-08
Online Publication Date
2023-06-22T13:27:01Z
Date Acceptance
2023-05-19
ISSN
0965-8564
Publisher
Elsevier
Start Page
1
End Page
29
Journal / Book Title
Transportation Research Part A: Policy and Practice
Volume
174
Copyright Statement
© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license
(http://creativecommons.org/licenses/by/4.0/).
(http://creativecommons.org/licenses/by/4.0/).
License URI
Identifier
https://www.sciencedirect.com/science/article/pii/S0965856423001465
Publication Status
Published
Article Number
103726
Date Publish Online
2023-06-20