TY - JOUR
T1 - The Prediction of Autonomous Vehicle Occupants’ Pre-Crash Motion during Emergency Braking Scenarios
AU - Diederich, Alexander
AU - Bastien, Christophe
AU - Blundell, Mike
N1 - This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
PY - 2023/12
Y1 - 2023/12
N2 - This research investigates a computational method, which can assist the development of occupants’ passive safety in future autonomous vehicles, more particularly in the definition of head kinematics in rotated seat arrangement during emergency braking. To capture these head motions, the methodology utilised an Active Human Model, whose head kinematics were validated in a previous work in 3-point and lapbelt restraint configuration scenarios. A sled model was then built where the seat backrest angle (SBA) and the seat orientation, modelled by rotating the acceleration angle (AA), could be adjusted to represent various “living room” seating conditions. A Design of Experiments study was then performed by varying AA from 0° to 360° in steps of 22.5° and SBA from 20° to 60° in steps of 8°. The responses were subsequently converted into a Reduced Order Model (ROM), which was then successfully validated through a comparison with the kinematic responses predicted with simulations. In terms of simulation time it was found that the ROM was able to calculate the head kinematics in 3 seconds instead of the 1.5 hours taken using Simcenter Madymo, without compromising predicted responses accuracy. This research has provided a unique method to define head kinematics corridors for seated occupants in autonomous vehicle interiors, including maximum head excursion, head kinematics as a function of time, and define for the first time a) the safe “no-contact” head envelope within the cabin interior, and b) capture the seated scenarios where head proximity to airbag systems could be of concern, following emergency braking.
AB - This research investigates a computational method, which can assist the development of occupants’ passive safety in future autonomous vehicles, more particularly in the definition of head kinematics in rotated seat arrangement during emergency braking. To capture these head motions, the methodology utilised an Active Human Model, whose head kinematics were validated in a previous work in 3-point and lapbelt restraint configuration scenarios. A sled model was then built where the seat backrest angle (SBA) and the seat orientation, modelled by rotating the acceleration angle (AA), could be adjusted to represent various “living room” seating conditions. A Design of Experiments study was then performed by varying AA from 0° to 360° in steps of 22.5° and SBA from 20° to 60° in steps of 8°. The responses were subsequently converted into a Reduced Order Model (ROM), which was then successfully validated through a comparison with the kinematic responses predicted with simulations. In terms of simulation time it was found that the ROM was able to calculate the head kinematics in 3 seconds instead of the 1.5 hours taken using Simcenter Madymo, without compromising predicted responses accuracy. This research has provided a unique method to define head kinematics corridors for seated occupants in autonomous vehicle interiors, including maximum head excursion, head kinematics as a function of time, and define for the first time a) the safe “no-contact” head envelope within the cabin interior, and b) capture the seated scenarios where head proximity to airbag systems could be of concern, following emergency braking.
KW - Occupant protection
KW - autonomous vehicles
KW - active human body models
KW - machine learning
KW - reduced order modelling
UR - http://www.scopus.com/inward/record.url?scp=85148087989&partnerID=8YFLogxK
U2 - 10.1177/09544070231153262
DO - 10.1177/09544070231153262
M3 - Article
SN - 0954-4070
VL - 237
SP - 3304
EP - 3312
JO - Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
JF - Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
IS - 14
ER -