Étude biomécanique des chutes à trottinette électrique

Abstract

In the last few years, E-scooters have shown an increase of popularity as a form of micromobility transport in urban areas. However, E-scooter democratization has significantly increased the number of injured people. Individual falls are common, and the head is one of the most injured body parts in accidents. Meanwhile, the use of helmets remains very low. As E-scooters are a relatively new modality of transport, there is a lack of knowledge on the fall kinematics and impact conditions during crashes. The objective of this work is to simulate Escooter crashes to evaluate the head impact conditions and the risk of head injuries. A multibody model of E-scooter fall induced by the collision with a curb was built using the MADYMO software and was validated against an experimental E-scooter crash test performed with a Hybrid III dummy. A helmet model was included based on contact properties obtained experimentally. A design of experiment was performed to evaluate the effect of fall conditions (initial speed, orientation of the obstacle, size of user, E-scooter inclination) and the wearing of the helmet on the head impact kinematics (impact speed and acceleration) and on the risk of injury. A total of 162 crashes scenarios were simulated. In 62% of those, the head first hit the ground in the frontal and temporal zone. The average tangential and normal impact speeds were 3.5 m/s and 4.8 m/s respectively. The average peak linear acceleration was 571 g and the average peak rotational acceleration was 25 580 rad/s2. Nearly 100% of the simulations identify a risk of concussion (linear acceleration peak>82 g and rotational acceleration peak>6 383 rad/s2) and 90% of simulations suggest severe head injuries (HIC>700). For specific impact configurations, wearing a helmet reduces peak linear acceleration by up to 76% and peak rotational acceleration by up to 73%. Finally, this work provides preliminary data useful for the assessment and design of protective gears.

Date	18 May 2022
Original language	French
Awarding Institution	École de technologie supérieure
Supervisor	Yvan Petit (Supervisor) & Nicolas Bailly (Co-supervisor)