The dynamics of a two-wheeled vehicle represent a higher level of complexity, with a high variety of rider practices, peculiarly during the bend-taking maneuver. This complexity is one reason why research on motorcyclists' practiced trajectories is limited compared to cars. Another reason is the low representation of motorcycles in the land motor vehicle fleet.
View Article and Find Full Text PDFThe understanding of rider/vehicle interaction modalities remains an issue, specifically in the case of bend-taking. This difficulty results both from the lack of adequate instrumentation to conduct this type of study and from the variety of practices of this population of road users. Riders have numerous explanations of strategies for controlling their motorcycles when taking bends.
View Article and Find Full Text PDFIn this data article, we will present the data coming from 3D Inertial Measurement Unit (3-accelerometers and 3-gyroscopes sensors) mounted on the motorcycle collected during a motorcycle's falls experiments. Developing a motorcycle's fall events detection algorithms is a very challenging task because the motorcycle falling is multi-factorial and is strongly influenced by many unknown factors. To solve this issue, one solution can be to use a data-set collected during controlled experiments, knowing that the real motorcycle falls cannot be replicated, a stuntman can be chosen to be as close to reality as possible.
View Article and Find Full Text PDFInstrumented vehicles are key tools for in-depth understanding of drivers' behaviours, thus for the design of scientifically based countermeasures to reduce fatalities and injuries. The instrumentation of Powered Two-Wheelers (PTW) has been less widely implemented that for vehicles, in part due to the technical challenges involved. The last decade has seen the development in Europe of several tools and methodologies to study motorcycle riders' behaviours and motorcycle dynamics for a range of situations, including crash events involving falls.
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