Congestion in Cities: Can Road Capacity Expansions Provide a Solution?
67 Pages Posted: 27 Oct 2021 Last revised: 8 Feb 2022
Date Written: October 25, 2021
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 understand 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 thirty-four cities worldwide. Our results suggest that increasing network capacity is in general not an efficient solution to manage congestion, in the sense that average travel speed in the network does not increase substantially with increase in capacity. This result and our congestion technology estimates have important implications for optimal urban transportation strategies.
Keywords: urban congestion, congestion technology , causal statistical modelling, Bayesian machine learning, non-parametric statistics.
JEL Classification: R41, C11, C14, C26
Suggested Citation: Suggested Citation