Citation

Harris D, Durdin P, Brodie C, Tate F, Gardener R. J. Australas. Coll. Road Saf. 2016; 27(1): 26-33.

Copyright

(Copyright © 2016, Australasian College of Road Safety)

DOI

unavailable

PMID

unavailable

Abstract

The roads of New Zealand's Eastern Bay of Plenty region have relatively low vehicle volumes and experience a number of rural road safety issues, including inappropriate speed, the use of drugs and alcohol, low levels of restraint use and young/inexperienced drivers. Over half of all rural crashes are loss-of-control crashes on curves. Due to low network traffic volumes, crashes tend to be sporadic and difficult to predict using risk assessment techniques that rely on crash histories. This paper introduces a new risk prediction methodology that identifies high-risk curves independent of crash history. Using geospatial data and innovative analysis techniques, existing methodologies for identifying curves and calculating vehicle operating speeds were modelled and automated to undertake a network-wide assessment of high risk curves. The new methodology extracted and classified almost 7000 curves across 1500km of road network. When compared to the location of loss-of-control crashes, it was found that 66.6% of crashes occurred on 20.3% of curves classified as 'high risk' in at least one direction. These results have been shared with road controlling authorities and will support prioritised road safety improvements targeting high risk curves. This methodology is the first network screening tool that has been specifically developed to address road safety risk in low volume rural areas in New Zealand or Australia. The methodology demonstrates how existing research into vehicle operating speed behaviour can be applied to identify high risk road elements and support targeted improvements that have the potential to significantly reduce road safety risk.

Language: en