BibTex format

author = {Bhuyan, P and McCoy, EJ and Li, H and Graham, DJ},
doi = {10.1214/21-AOAS1450},
journal = {Annals of Applied Statistics},
pages = {1999--2022},
title = {Analysing the causal effect of London cycle superhighways on traffic congestion},
url = {},
volume = {15},
year = {2021}

RIS format (EndNote, RefMan)

AB - Transport operators have a range of intervention options available to improve or enhance their networks. Such interventions are often made in the absence of sound evidence on resulting outcomes. Cycling superhighways were promoted as a sustainable and healthy travel mode, one of the aims of which was to reduce traffic congestion. Estimating the impacts that cycle superhighways have on congestion is complicated due to the nonrandom assignment of such intervention over the transport network. In this paper we analyse the causal effect of cycle superhighways utilising preintervention and postintervention information on traffic and road characteristics along with socioeconomic factors. We propose a modeling framework based on the propensity score and outcome regression model. The method is also extended to the doubly robust set-up. Simulation results show the superiority of the performance of the proposed method over existing competitors. The method is applied to analyse a real dataset on the London transport network. The methodology proposed can assist in effective decision making to improve network performance.
AU - Bhuyan,P
AU - McCoy,EJ
AU - Li,H
AU - Graham,DJ
DO - 10.1214/21-AOAS1450
EP - 2022
PY - 2021///
SN - 1932-6157
SP - 1999
TI - Analysing the causal effect of London cycle superhighways on traffic congestion
T2 - Annals of Applied Statistics
UR -
UR -
UR -
UR -
VL - 15
ER -