Citation

Boubezoul A, Dufour F, Bouaziz S, Larnaudie B, Espié S. Data Brief 2019; 23: e103828.

Affiliation

TROPHY R&D, 1 Avenue Eiffel, 78420 Carrières-sur-Seine, France.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.dib.2019.103828

PMID

31372464

PMCID

PMC6660605

Abstract

In 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. The experiments have been conducted based on predefined scenarios such as: fall in a curve, fall on a slippery straight road section, fall with leaning of the motorcycle ''intentional manoeuvre'' and fall in a roundabout. These scenarios have been designed based on realistic falls. Other experiments have been conducted under different extreme driving situations. These extreme manoeuvres were carried out on track by professional riders. The purpose of performing these manoeuvres was to obtain a dataset describing the limit handling behaviour.

Language: en