In this section
@article{Baker:2024:10.1016/j.aap.2024.107726,
author = {Baker, CE and Martin, P and Montemeglio, A and Li, R and Wilson, M and Sharp, DJ and Ghajari, M},
doi = {10.1016/j.aap.2024.107726},
journal = {Accid Anal Prev},
title = {Inherent uncertainty in pedestrian collision reconstruction: How evidence variability affects head kinematics and injury prediction.},
url = {http://dx.doi.org/10.1016/j.aap.2024.107726},
volume = {208},
year = {2024}
}
TY - JOUR
AB - Reconstructing individual cases from real-world collision data is used as a tool to better understand injury biomechanics and determine injury thresholds. However, real-world data tends to have inherent uncertainty within parameters, such as ranges of impact speed, pre-impact pedestrian stance or pedestrian anthropometric characteristics. The implications of this input parameter uncertainty on the conclusions made from case reconstruction about injury biomechanics and risk is not well investigated, with a 'best-fit' approach more frequently adopted, leaving uncertainty unexplored. This study explores the implications of uncertain parameters in real-world data on the biomechanical kinematic metrics related to head injury risk in reconstructed real-world pedestrian-car collisions. We selected six pedestrian-car cases involving seven pedestrians from the highly detailed GB Road Accident In-Depth Studies (RAIDS) database. The collisions were reconstructed from the images, damage measurements and dynamics available in RAIDS. For each case, we varied input parameters within uncertain ranges and report the range of head kinematic metrics from each case. This includes variations of reconstructed collision scenarios that fits within the constraints of the available evidence. We used a combination of multibody and finite element modelling in Madymo to test whether the effect of input data uncertainty is the same on the initial head-vehicle and latter head-ground impact phase. Finally, we assessed whether the predicted range of head kinematics correctly predicted the injuries sustained by the pedestrian. Varying the inputs resulted in a range of output head kinematic parameters. Real-world evidence such as CCTV footage enabled predicted simulated values to be further constrained, by ruling out unrealistic scenarios which do not fit the available evidence. We found that input data uncertainty had different implications for the initial head-vehicle and latter head-ground impact
AU - Baker,CE
AU - Martin,P
AU - Montemeglio,A
AU - Li,R
AU - Wilson,M
AU - Sharp,DJ
AU - Ghajari,M
DO - 10.1016/j.aap.2024.107726
PY - 2024///
TI - Inherent uncertainty in pedestrian collision reconstruction: How evidence variability affects head kinematics and injury prediction.
T2 - Accid Anal Prev
UR - http://dx.doi.org/10.1016/j.aap.2024.107726
UR - https://www.ncbi.nlm.nih.gov/pubmed/39265379
VL - 208
ER -
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