A time-series analysis of motorway collisions in England considering road infrastructure, socio-demographics, traffic and weather characteristics
journal contributionposted on 18.03.2016, 11:55 by Paraskevi Michalaki, Mohammed QuddusMohammed Quddus, D.E. Pitfield, Andrew Huetson
Traffic injuries on motorways are a public health problem worldwide. Collisions on motorways represent a high injury rate in comparison to the entire national network. Furthermore, collisions that occur on the hard–shoulder are even more severe than those that happen on the main carriageway. The purpose of this paper is to explore motorway safety through the identification of patterns in the sequence of monthly hard–shoulder and main carriageway collisions separately over a long period of time (1993– 2011) by using reported collision data from British motorways. In order to examine the trends of hard– shoulder and motorway collisions over the same period, a Vector Autoregressive (VAR) model is developed; this allows the inclusion of two time-series in the same model and the examination of the effect of one series on the other and vice-versa. Exogenous variables are also added in order to explore the long-term factors that might affect the occurrence of collisions. The factors considered are related to the infrastructure (e.g. length of motorways), socio-demographics (e.g. percentage of young drivers), traffic (e.g. percentage of vehicle-miles travelled by Heavy Goods Vehicles) and weather (e.g. precipitation). The results suggest different patterns in the sequences in terms of the lingering effects of preceding observations for the two time-series. In terms of the significance of exogenous variables, it is suggested that main carriageway collision frequency is affected by weather conditions and the presence of Heavy Goods Vehicles, while hard–shoulder collisions are decreased by the presence of Motorway Service Areas, which allow a safe exit off the motorway to stop and rest in case of fatigue.
This research was undertaken as part of an Engineering Doctorate project jointly funded by the Centre of Innovative and Collaborative Construction Engineering (CICE) at Loughborough University and Balfour Beatty. The support of the Engineering and Physical Sciences Research Council is gratefully acknowledged (EPSRC Grant EP/F037272/1).
- Architecture, Building and Civil Engineering