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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Identifying Differences in Wet and Dry Road Crashes Using Data Mining
verfasst von : D. Emerson, R. Nayak, J. Weligamage, N. Piyatrapoomi
Erschienen in: Engineering Asset Management and Infrastructure Sustainability
Verlag: Springer London
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Abstract
It is commonly accepted that wet roads have higher risk of crash than dry roads; however, providing evidence to support this assumption presents some difficulty. This paper presents a data mining case study in which predictive data mining is applied to model the skid resistance and crash relationship to search for discernable differences in the probability of wet and dry road segments having crashes based on skid resistance. The models identify an increased probability of wet road segments having crashes for mid-range skid resistance values.