Abstract
In this study, assuming that traffic accident occurrence is determined by some road and environment related factors, and future traffic accidents will occur under the same conditions as past traffic accidents, use of Relative Frequency Method (RFM) (also called frequency ratio method) in the determination of accident-prone road sections is investigated. Method was tested on a highway in Trabzon province of Turkey. At the end of the study, sensitivity and specificity values were calculated as 1.00 and 0.83 respectively, which reflects that the method identified all of the 'accident-prone' sections (there is no false negative) and the method has very strong ability to distinguish 'relatively safe' sections. The most useful property of the method is that, if accident data does not exist due to any reason for some part of the road, method can be still used to identify accident-prone sections by using the road properties.
Highlights
The first step in road safety improvement process is the identification of black-spots [1]
Assuming that traffic accident occurrence is determined by some road and environment-related factors, and that future traffic accidents will occur under the same conditions as past traffic accidents this study investigates the use of Relative Frequency Method (RFM) in the determination of accident-prone road sections
The number of accidents or accident rate is not used directly; instead, a relationship between accident number and environmental properties of road sections is established and this relationship is used for accident-prone road section identification
Summary
The first step in road safety improvement process is the identification of black-spots [1]. If accident experience of a point or a segment is higher than the other segments of the network, most probably, the reason are the road and/or environmental conditions in that point or segment. Places like these are called accident-prone locations ( called hot spots, black spots, hazardous locations, sites with promise, risky sections, etc.). False positives (observation of elevated crash frequencies at a relatively safe site) lead to investment of public funds with little to no safety benefits. False negatives (an unsafe site that does not reveal elevated crash frequencies) lead to missed opportunities for effective safety investments [8]
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