Deriving a joint risk estimate from dynamic data collected at motorcycle rides.

Making motorcycle rides safer by advanced technology is an ongoing challenge in the context of developing driving assistant systems and safety infrastructure. Determining which section of a road and which driving behaviour is "safe" or "unsafe" is rarely possible due to the individual differences in driving experience, driving style, fitness and potentially available assistant systems. This study investigates the feasibility of a new approach to quantify motorcycle riding risk for an experimental sample of bikers by collecting motorcycle-specific dynamic data of several riders on selected road sections.