Naturalistic cycling data are increasingly available worldwide and promise ground-breaking insights into road-user behavior and crash-causation mechanisms. Because few, low-severity crashes are available, safety analyses of naturalistic data often rely on near crashes. Nevertheless, the relation between near crashes and crashes is still unknown, and the debate on whether it is legitimate to use near crashes as a proxy for crashes is still open. This paper exemplifies a methodology that combines crashes from a crash database and near crashes from naturalistic studies to explore their potential relation. Using exposure to attribute a risk level to individual crashes and near crashes depending on their temporal and spatial distribution, this methodology proposes an alternative to blackspots for crash analysis and compares crash risk with near-crash risk. The novelty of this methodology is to use exposure with high time and space resolution to estimate the risk for specific crashes and near crashes. (Author/publisher)
Samenvatting