The Head AIS 4+ Injury Thresholds for the Elderly Vulnerable Road User Based on Detailed Accident Reconstructions

Abstract

Compared with the young, the elderly (age greater than or equal to 60 years old) vulnerable road users (VRUs) face a greater risk of injury or death in a traffic accident. A contributing vulnerability is the aging processes that affect their brain structure. The purpose of this study was to investigate the injury mechanisms and establish head AIS 4+ injury tolerances for the elderly VRUs based on various head injury criteria. A total of 30 elderly VRUs accidents with detailed injury records and video information were selected and the VRUs’ kinematics and head injuries were reconstructed by combining a multi-body system model (PC-Crash and MADYMO) and the THUMS (Ver. 4.0.2) FE models. Four head kinematic-based injury predictors (linear acceleration, angular velocity, angular acceleration, and head injury criteria) and three brain tissue injury criteria (coup pressure, maximum principal strain, and cumulative strain damage measure) were studied. The correlation between injury predictors and injury risk was developed using logistical regression models for each criterion. The results show that the calculated thresholds for head injury for the kinematic criteria were lower than those reported in previous literature studies. For the brain tissue level criteria, the thresholds calculated in this study were generally similar to those of previous studies except for the coup pressure. The models had higher (>0.8) area under curve values for receiver operator characteristics, indicating good predictive power. This study could provide additional support for understanding brain injury thresholds in elderly people.

Realistic Reference for Evaluation of Vehicle Safety Focusing on Pedestrian Head Protection Observed From Kinematic Reconstruction of Real-World Collisions

“…This could lead to some uncertainties to the predicted magnitudes of head injury criteria. Although there are many shortcomings for this approach, this is one of the reasonable solutions for stiffness assumption and widely used in pedestrian crash reconstructions (Nie et al, 2014;Peng et al, 2012;Wu et al, 2021), and the good match in the AIS level between the predictions and real-world accident data (Figure 5) could support the reliability of this approach. Finally, the parameters such as contact friction coefficients were defined according to the literature, which also led to some uncertainties in the modeling.…”

“…where x is the predictor, a and b are coefficients calculated from Weibull fitting. The AUC (Area Under the Curve) value with a threshold of 0.5 was employed to evaluate the predictive capability of the Weibull models similar to a previous study (Wu et al, 2021). The AUC can be calculated by two measures, namely, false-positive rate (FPR) and true-positive rate (TPR), where FPR refers to the ratio of false-positive cases (the cases that were predicted positive but are actually negative) out of all negative cases and TPR refers to the ratio of true-positive cases (the cases that were predicted positive and are actually positive too) out of all positive cases.…”

“…The multi-body modeling method applied by the MADYMO software (MADYMO, 2013b) was used for kinematic reconstruction of pedestrians involved in the 57 selected cases, where MADYMO pedestrian models (MADYMO, 2013a) scaled to the height and weight of the victims were employed. Similar to previous reconstruction work (Nie et al, 2014;Peng et al, 2013;Wu et al, 2021), each vehicle model was developed based on the geometric data measured from the blueprint or real car of the corresponding accident vehicle, and stiffness characteristics of the components were obtained from impactor test data reported in previous studies (Mizuno et al, 2001;Martinez et al, 2007) according to the available rating results of the vehicle model in subsystem tests.…”

Establishment of a weighted injury criterion for evaluation of multiple types of head severe injuries for vulnerable road users

“…), MPS, and CSDM0.15 predicted 75-100% of head injury in the reconstructed ground impact accidents. In addition, Wu and HAN et al 30 investigated the correlation between those injury predictors and injury risk in an elderly tra c accident and established a head Abbreviated Injury Scale (AIS) 4 + injury tolerance for the elderly by analyzing 30 detailed real-world VRU accidents. Based on these previous studies, the purpose of this paper is to establish a comprehensive weighted head injury evaluation criterion based on head kinematic response and brain tissue response to predict the injury risk of severe and multiple head injury types occurring more accurately in road tra c accidents.…”

Kinetic and Kinematic Features of Pedestrian Avoidance Behavior in Motor Vehicle Conflicts

“…However, it is not realistic to collect accurate information on pedestrian avoidance behavior using this method ( Fredriksson et al, 2010 ). By watching and analyzing real-world accident video records, researchers have recently observed the emergency postures and kinematics of pedestrians in dangerous impact scenarios ( Zou et al, 2020 ; Wu et al, 2021 ). However, the pedestrian avoidance behavior has not been quantified.…”