711 Multivariate analysis of road crashes involving moto riders at Vienna’s roads

<h3>Background</h3> Road safety is worldwide researched field where crashes are playing causal role and injuries are counted as outcomes. Approaches and techniques are diverse, but with same goal – contribute to safer road environment for everyone. Moto riders are the least protected traffic group due to head protection provided by helmet when compared to personal car driver that are protected by vehicle carrosserie. This group is characterized by the high presence of very young drivers whose psychological characteristics place them in a vulnerable risky subgroup. <h3>Objective</h3> According to the original data of the police on crashes of heavy moto riders in the town of Vienna, since 2010 they have had the highest number of crashes in 2019 and after slow decrease is recorded. Still high in total number of crashes involving only moto riders from a traffic safety point of view this still represent an extremely worrying problem that has not received proper social attention. <h3>Methods</h3> To address this main problem of research it is performed: inferential analysis with focus on determining statistically significant differences, if any, among rider based on gender, age and injury severity; cluster analysis to identify relevant homogenous groups based on individual characteristics; factorial analysis method of main components to get principal dimension of crashes on variables that significantly characterize the crash event; second order factorial analysis to uncover underlying structures in crash event involving two-wheelers, and regression analysis to explain causal interconnection of continuous high number of crashes. <h3>Results</h3> In response to knowledge gaps, this research is essential to address leading characterizations in crashes with aim to answer what is trend in crash occurrence, 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. Cluster analysis can be seen as more descriptive contribution, multiple regression undoubtedly points fields for action in statistically based findings providing the most important answer to this research: why there are so many crashes and what is leading cause of them. <h3>Conclusions</h3> Answering this question contributes toward higher safety environment for all participants.