title: Identification of hazardous road locations of traffic accidents by means of kernel density estimation and cluster significance evaluation.
abstract: This paper proposes a procedure which evaluates clusters of traffic accident and organizes them according to their significance. The standard kernel density estimation was extended by statistical significance testing of the resulting clusters of the traffic accidents. This allowed us to identify the most important clusters within each section. They represent places where the kernel density function exceeds the significance level corresponding to the 95th percentile level, which is estimated using the Monte Carlo simulations. To show only the most important clusters within a set of sections, we introduced the cluster strength and cluster stability evaluation procedures. The method was applied in the Southern Moravia Region of the Czech Republic.
authors.affiliation: Transport Research Centre, Líšeňská 33a, Brno, 636 00, Czech Republic. m.bil@seznam.cz
authors.forename: Michal
authors.initials: M
authors.lastname: Bíl
authors.forename: Richard
authors.initials: R
authors.lastname: Andrášik
authors.forename: Zbyněk
authors.initials: Z
authors.lastname: Janoška
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D016000:Cluster Analysis; D018153:Czech Republic; D004777:Environment; D006801:Humans; D009010:Monte Carlo Method