Driver Injury Risk Variability in Finite Element Reconstructions of Crash Injury Research and Engineering Network (CIREN) Frontal Motor Vehicle Crashes

Objective: A 3-phase real-world motor vehicle crash (MVC) reconstruction method was developed to analyze injury variability as a function of precrash occupant position for 2 full-frontal Crash Injury Research and Engineering Network (CIREN) cases.

Method: Phase I: A finite element (FE) simplified vehicle model (SVM) was developed and tuned to mimic the frontal crash characteristics of the CIREN case vehicle (Camry or Cobalt) using frontal New Car Assessment Program (NCAP) crash test data. Phase II: The Toyota HUman Model for Safety (THUMS) v4.01 was positioned in 120 precrash configurations per case within the SVM. Five occupant positioning variables were varied using a Latin hypercube design of experiments: seat track position, seat back angle, D-ring height, steering column angle, and steering column telescoping position. An additional baseline simulation was performed that aimed to match the precrash occupant position documented in CIREN for each case. Phase III: FE simulations were then performed using kinematic boundary conditions from each vehicle's event data recorder (EDR). HIC15, combined thoracic index (CTI), femur forces, and strain-based injury metrics in the lung and lumbar vertebrae were evaluated to predict injury.

Results: Tuning the SVM to specific vehicle models resulted in close matches between simulated and test injury metric data, allowing the tuned SVM to be used in each case reconstruction with EDR-derived boundary conditions. Simulations with the most rearward seats and reclined seat backs had the greatest HIC15, head injury risk, CTI, and chest injury risk. Calculated injury risks for the head, chest, and femur closely correlated to the CIREN occupant injury patterns. CTI in the Camry case yielded a 54% probability of Abbreviated Injury Scale (AIS) 2+ chest injury in the baseline case simulation and ranged from 34 to 88% (mean = 61%) risk in the least and most dangerous occupant positions. The greater than 50% probability was consistent with the case occupant's AIS 2 hemomediastinum. Stress-based metrics were used to predict injury to the lower leg of the Camry case occupant. The regional-level injury metrics evaluated for the Cobalt case occupant indicated a low risk of injury; however, strain-based injury metrics better predicted pulmonary contusion. Approximately 49% of the Cobalt occupant's left lung was contused, though the baseline simulation predicted 40.5% of the lung to be injured.

Conclusions: A method to compute injury metrics and risks as functions of precrash occupant position was developed and applied to 2 CIREN MVC FE reconstructions. The reconstruction process allows for quantification of the sensitivity and uncertainty of the injury risk predictions based on occupant position to further understand important factors that lead to more severe MVC injuries.