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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/19642

Title: Predicting the safety impact of a speed limit increase using condition-based multivariate Poisson lognormal regression
Authors: Imprialou, Maria-Ioanna
Quddus, Mohammed A.
Pitfield, D.E.
Keywords: Speed limit increase
Speed and crashes
Single vehicle crashes
20 multiple vehicle crashes
Condition-based modelling
Issue Date: 2016
Publisher: © Taylor & Francis
Citation: IMPRIALOU, M-I., QUDDUS, M.A. and PITFIELD, D.E., 2016. Predicting the safety impact of a speed limit increase using condition-based multivariate Poisson lognormal regression. Transportation Planning and Technology, 39 (1), pp. 3-23.
Abstract: Speed limit changes are considered to lead to proportional changes in the number and severity of crashes. To predict the impact of a speed limit alteration, it is necessary to define a relationship between crashes and speed on a road network. This paper examines the relationship of crashes with speed, as well as with other traffic and geometric variables, on the UK motorways in order to estimate the impact of a potential speed limit increase from 70 mph to 80 mph on traffic safety. Full Bayesian multivariate Poisson lognormal regression models are applied to a dataset aggregated using the condition-based approach for crashes by vehicle (i.e. single-vehicle and multiple-vehicle) and severity (i.e. fatal or serious and slight). The results show that single-vehicle crashes of all severities and fatal or serious injury crashes involving multiple vehicles increase at higher speed conditions and particularly when these are combined with lower volumes. Slight injury multiple-vehicle crashes are found not to be related with high speeds, but instead with congested traffic. Using the speed elasticity values derived from the models the predicted annual increase in crashes after a speed limit increase on the UK motorway is found to be 6.2-12.1 % for fatal or serious injury crashes and 1.3-2.7% for slight injury, or else up to 167 more crashes.
Description: This paper is in closed access until 25th May 2017.
Version: Accepted for publication
DOI: 10.1080/03081060.2015.1108080
URI: https://dspace.lboro.ac.uk/2134/19642
Publisher Link: http://dx.doi.org/10.1080/03081060.2015.1108080
ISSN: 1029-0354
Appears in Collections:Closed Access (Civil and Building Engineering)

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