A stochastic model validated with human test data causally associating target vehicle Delta V, occupant cervicocranial biomechanics, and injury during rear-impact crashes

Even at low to moderate-speeds, rear-end motor vehicle crashes have been strongly associated with occupant cervicocranial biomechanics that lead to head and neck injury. In this paper, we present the development of an analytic mechanics model of occupant head and neck motion as associated with modeled target vehicle Delta V during rear-end vehicular crashes. The inclusion of stochastic mechanical input variables further developed the model beyond the deterministic framework by reflecting aspects of the random nature of real-world crashes and the resulting injuries. This approach led to the characterization of 1000 crash simulations, quantifying Delta V and the resulting probabilistic occupant biomechanics. The model was validated through the direct comparison with 86 published human subject crash tests. Overall, the model slightly underestimated by -2.6% the magnitude of peak head accelerations identified in the literature. The utility of the model allows a forensic biomechanical investigator to customize some of the fundamental input crash parameters and appropriately explore the resulting vehicular mechanics and their direct influence on injury biomechanics.

The view from the road: the contribution of on-road glance-monitoring technologies to understanding driver behavior

Using glance-monitoring technologies for on-road studies is an excellent way to investigate driver behaviors in an ecologically valid setting. Recent advances in glance-monitoring technologies have made it possible to conduct on-road studies of drivers' glance behavior that heretofore were simply not possible. Yet it is not always easy to determine which glance-monitoring technology to use for a particular application. Here, we first identify the generic capabilities of the various glance-monitoring technologies. We then describe how particular glance-monitoring technologies have been used in the field to (a) identify the skill deficiencies of novice and older drivers, (b) evaluate the effectiveness of training programs that are designed to reduce deficits in these skills, and (c) address interface issues both inside (e.g., collision warning systems) and outside (e.g., yield markings) the vehicle. The limitations and advantages of on-road eye-tracking and the associated glance-monitoring technologies are identified throughout. A comparison, where possible, is made between the results of on-road eye-tracking studies of drivers' behaviors and the results of those studies conducted in the laboratory. Overall, the use of appropriate on-road glance-monitoring technologies has greatly enhanced our theoretical understanding of why drivers behave the way they do, and this knowledge has paved the way for significant improvements in road user safety.