Multivariate analysis of pedestrian-related crashes on Vienna’s roads

Abstract

Pedestrians are the least protected traffic group when compared to other participants. When compared to moto riders (independent of engine power) they have head protection provided by helmet or vehicle metal shield along with airbag that is providing highest level of body protection for personal vehicles drivers. This vulnerable group is characterized by the high presence of very young participants whose psychological characteristics place them in a vulnerable risky subgroup. According to the police original data on crashes involving pedestrians in the town of Vienna, since 2010 there was highest number of crashes in 2012 and after slow decrease is recorded but still high in total number of crashes involving only pedestrians is an extremely worrying problem.This research is essential to address leading characterizations in crashes with the aim to answer what is current trend in crash occurrence during 2010–2020 inside Vienna municipality, and what is predicted trend. Is there significant and distinctive difference based on gender and age with specific conditions under which crashes are occurring influencing different injury degree. Multiple regression undoubtedly points fields for action in statistically based findings providing the most important answer to this research: why crashes do occur so frequently and what is leading cause of injured pedestrians. Stepwise procedure in discriminant analysis at statistically significant level shows what differentiates injured and not injured pedestrians.