Identification of motorcycle accidents hotspots in the Czech Republic and their conditional factors: The use of KDE+ and two‐step cluster analysis

Abstract

In recent decades, there has been a significant increase in the number of newly registered motorcycles worldwide. However, there is not only an increase in the number of motorcycles in traffic but also an increase in the number of conflicts between motorcyclists and the surrounding environment. A relatively significant research gap can be identified in the relationship between spatial factors and motorcycle accident rates. This paper analyses the spatiotemporal patterns of motorcycle accidents and studies their underlying factors. The KDE+ method (an extension of the kernel density estimation method) is used to identify concentrations of motorcycle accident key hotspots. To study the underlying traffic accident determinants, a two‐step cluster analysis is used. The analysis is based on the database of motorcycle accidents in the Czech Republic from 1 January 2016 to 31 December 2020. The paper achieves a few main findings. By applying the KDE+ method, the most dangerous sections of the road network in the Czech Republic were identified, where a significant accumulation of motorcycle accidents occur. Motorcycle accidents are highly seasonal. Motorcycle accidents tend to accumulate in the afternoon, especially during the summer months. Concerning the frequency of accidents and the collective risk index, urban traffic, that is the traffic density, is an important cause of motorcycle accidents, along with the winter period with rather unfavourable weather conditions, and especially the directional conditions—curves and intersections—are among the hazardous sections.