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This study evaluated the biomechanical performance of a rear-seat inflatable seatbelt system and compared it to that of a 3-point seatbelt system, which has a long history of good real-world performance. Frontal-impact sled tests were conducted with Hybrid III anthropomorphic test devices (ATDs) and with post mortem human subjects (PMHS) using both restraint systems and a generic rear-seat configuration. Results from these tests demonstrated: a) reduction in forward head excursion with the inflatable seatbelt system when compared to that of a 3-point seatbelt and; b) a reduction in ATD and PMHS peak chest deflections and the number of PMHS rib fractures with the inflatable seatbelt system and c) a reduction in PMHS cervical-spine injuries, due to the interaction of the chin with the inflated shoulder belt. These results suggest that an inflatable seatbelt system will offer additional benefits to some occupants in the rear seats.

The objectives of this study were to examine the response, repeatability, and injury predictive ability of the Hybrid III small-female dummy to static out-of-position (OOP) deployments using a depowered driver-side airbag. Five dummy tests were conducted in two OOP configurations by two different laboratories. The OOP configurations were nose-on-rim (NOR) and chest-on-bag (COB). Four cadaver tests were conducted using unembalmed small-female cadavers and the same airbags used in the dummy tests under similar OOP conditions. One cadaver test was designed to increase airbag loading of the face and neck (a forehead-on-rim, or FOR test). Comparison between the dummy tests of Lab 1 and of Lab 2 indicated the test conditions and results were repeatable. In the cadaver tests no skull fractures or neck injuries occurred. However, all four cadavers had multiple rib fractures.

The biomechanical behavior of a harness style 4-point seat belt system in farside impacts was investigated through dummy and post mortem human subject tests. Specifically, this study was conducted to evaluate the effect of the inboard shoulder belt portion of a 4-point seat belt on the risk of vertebral and soft-tissue neck injuries during simulated farside impacts. Two series of sled tests simulating farside impacts were completed with crash dummies of different sizes, masses and designs to determine the forces and moments on the neck associated with loading of the shoulder belt. The tests were also performed to help determine the appropriate dummy to use in further testing. The BioSID and SID-IIs reasonably simulated the expected kinematics response and appeared to be reasonable dummies to use for further testing. Analysis also showed that dummy injury measures were lower than injury assessment reference values used in development of side impact airbags.

Numerical analyses frequently accompany experimental investigations that study injury biomechanics and improvements in automotive safety. Limited by computational speed, earlier mathematical models tended to simplify the system under study so that a set of differential equations could be written and solved. Advances in computing technology and analysis software have enabled the development of many sophisticated models that have the potential to provide a more comprehensive understanding of human impact response, injury mechanisms, and tolerance. In this article, 50 years of publications on numerical modeling published in the Stapp Car Crash Conference Proceedings and Journal were reviewed. These models were based on: (a) author-developed equations and software, (b) public and commercially available programs to solve rigid body dynamic models (such as MVMA2D, CAL3D or ATB, and MADYMO), and (c) finite element models.

An age-dependent, serious-to-fatal (AIS3+), thoracic risk curve was derived and evaluated for frontal impacts. The study consisted of four parts. In Part 1, two datasets of post mortem human subjects (PMHS) were generated for statistical and sensitivity analyses. In Part 2, logistic regression analyses were conducted. For each dataset, two statistical methods were applied: (1) a conventional maximum likelihood method, and (2) a modified maximum likelihood method. Therefore, four statistical models were derived — one for each dataset/statistical method combination. For all of the resulting statistical models (risk curves), the linear combination of maximum normalized sternum deflection and age of the PMHS was identified as a feasible predictor of AIS3+ thoracic injury probability. In Part 3, the PMHS-based risk curves were transformed into test-dummy-based risk curves. In Part 4, validation studies were conducted for each risk curve.

The biomechanical behavior of 4-point seat belt systems was investigated through MADYMO modeling, dummy tests and post mortem human subject tests. This study was conducted to assess the effect of 4-point seat belts on the risk of thoracic injury in frontal impacts, to evaluate the ability to prevent submarining under the lap belt using 4-point seat belts, and to examine whether 4-point belts may induce injuries not typically observed with 3-point seat belts. The performance of two types of 4-point seat belts was compared with that of a pretensioned, load-limited, 3-point seat belt. A 3-point belt with an extra shoulder belt that “crisscrossed” the chest (X4) appeared to add constraint to the torso and increased chest deflection and injury risk. Harness style shoulder belts (V4) loaded the body in a different biomechanical manner than 3-point and X4 belts.

A theoretical, mathematical, risk assessment procedure was developed to estimate the fraction of drivers that incurred head and thoracic AIS3+ injuries in full-engagement frontal crashes. The estimates were based on numerical simulations of various real-world events, including variations of crash severity, crash speed, level of restraint, and occupant size. The procedure consisted of four steps: (1) conduct the simulations of the numerous events, (2) use biomechanical equations to transform the occupant responses into AIS3+ risks for each event, (3) weight the maximum risk for each event by its real-world event frequency, and (4) sum the weighted risks. To validate the risk assessment procedure, numerous steps were taken. First, a passenger car was identified to represent average field performance.