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The air bag safety issues became evident in 1995 and other factors have conjoined to change the climate regarding motor vehicle safety. Traditionally, motor vehicle safety issues have been evaluated based upon the effects upon average adult males. The new climate requires consideration of the effects on persons of differing size and gender. By including consideration of children and women, rulemaking and the applied technologies are able to better optimize safety than is the case when rules are focused only on the average adult male. Automotive electronics serves a key role in the migration from a one-size-fits- all protection to a more customized protection for a variety of occupants. The enhancements have been the most prominent in the area of sensing, be it the sensing and characterization of the crash itself, or the sensing and characterization of occupants in the vehicle.

An objective, biomechanically based assessment is made of the risks of life-threatening brain injury of frontal crash test results. Published 15 ms HIC values for driver and right front passenger dummies of frontal barrier crash tests conducted by Transport Canada and NHTSA are analyzed using the brain injury risk curve of Prasad and Mertz. Ninety-four percent of the occupants involved in the 30 mph, frontal barrier compliance tests had risks of life-threatening brain injury less than 5 percent. Only 3 percent had risks greater than 16 percent which corresponds to 15 ms HIC > 1000. For belt restrained occupants without head contact with the interior, the risks of life-threatening brain injury were less than 2 percent. In contrast, for the more severe NCAP test condition, 27 percent of the drivers and 21 percent of the passengers had life-threatening brain injury risks greater than 16 percent.

This study is an extension of previous work on driver air bag deployment loads which used the mid-size male Hybrid Ill dummy. Both small female and mid-size male Hybrid Ill dummies were tested with a range of near-positions relative to the air bag module. These alignments ranged from the head centered on the module to the chest centered on the module and with various separations and lateral shifts from the module. For both sized dummies the severity of the loading from the air bag depended on alignment and separation of the dummy with respect to the air bag module. No single alignment provided high responses for all body regions, indicating that one test at a typical alignment cannot simultaneously determine the potential for injury risk for the head, neck, and torso. Based on comparisons with their respective injury assessment reference values, the risk of chest injury appeared similar for both sized dummies.

As component and systems sophistication in both cars and trucks increase, improved diagnostic capabilities are required to assure proper and expedient serviceability. Replacement of electrical modules, starter motors, carburetors, fuel injectors and even whole engines or transmissions is encouraged by high labor costs and continued vehicle mobility mandates. The remanufacturing business has grown and components previously discarded now provide valuable core elements to feed the industry. To achieve efficient utilization of capital, equipment and labor, remanufacturers must estimate when this supply of core elements will be available and plan their production schedules accordingly. In order to properly service private individuals and commercial fleets, minimize vehicle downtime and reduce life cycle costs, adaptation of available analytical tools must be made.

Currently, states that are out of compliance with the National Ambient Air Quality Standards must, according to the Clean Air Act Amendments of 1990 (CAAA), develop and implement control strategies that demonstrate specific degrees of reduction in emissions-with the degree of reduction depending upon the severity of the problem. One tool that has been developed to aid regulators in both deciding an appropriate course of action and to demonstrate the desired reductions in mobile emissions is EPA's Mobile 5a emission estimation model. In our study, Mobile 5a has been used to examine the effects of regulatory strategies, as applied to the Northeast United States, on vehicle emissions under worst-case ozone-forming conditions.

Using a combination of engineering test experience, explicit finite-element analysis, and advanced materials characterization, a predictive engineering method has been developed that can assist in the development of active top pads. An active top pad is the component of the instrument panel that covers the passenger airbag module and articulates during a crash event, allowing the airbag to deploy. This paper highlights the predictive analysis method, analytical results interpretation, and suggestions for future development.

Advances in avionics and display technology are significantly changing the cockpit environment in current transport aircraft. The MIT Aeronautical Systems Lab (ASL) has developed a part-task flight simulator specifically to study the effects of these new technologies on flight crew situational awareness and performance. The simulator is based on a commercially-available graphics workstation, and can be rapidly reconfigured to meet the varying demands of experimental studies. The simulator has been successfully used to evaluate graphical microburst alerting displays, electronic instrument approach plates, terrain awareness and alerting displays, and ATC routing amendment delivery through digital datalinks.

The challenge of developing a robust, real-time driver gaze classification system is that it has to handle difficult edge cases that arise in real-world driving conditions: extreme lighting variations, eyeglass reflections, sunglasses and other occlusions. We propose a single-camera end-toend framework for classifying driver gaze into a discrete set of regions. This framework includes data collection, semi-automated annotation, offline classifier training, and an online real-time image processing pipeline that classifies the gaze region of the driver. We evaluate an implementation of each component on various subsets of a large onroad dataset. The key insight of our work is that robust driver gaze classification in real-world conditions is best approached by leveraging the power of supervised learning to generalize over the edge cases present in large annotated on-road datasets.

This paper quantifies the potential of electric propulsion systems to reduce petroleum use and greenhouse gas (GHG) emissions in the 2030 U.S. light-duty vehicle fleet. The propulsion systems under consideration include gasoline hybrid-electric vehicles (HEVs), plug-in hybrid vehicles (PHEVs), fuel-cell hybrid vehicles (FCVs), and battery-electric vehicles (BEVs). The performance and cost of key enabling technologies were extrapolated over a 25-30 year time horizon. These results were integrated with software simulations to model vehicle performance and tank-to-wheel energy consumption. Well-to-wheel energy and GHG emissions of future vehicle technologies were estimated by integrating the vehicle technology evaluation with assessments of different fuel pathways. The results show that, if vehicle size and performance remain constant at present-day levels, these electric propulsion systems can reduce or eliminate the transport sector's reliance on petroleum.

Airbag systems have been part of passenger car and truck programs since the mid-1980's. However, systems designed for medium and heavy duty truck applications are relatively new. The release of airbag systems for medium duty truck has provided some unique challenges, especially for the airbag sensing systems. Because of the many commercial applications within the medium duty market, the diversity of the sensing environments must be considered when designing and calibrating the airbag sensing system. The 2003 Chevrolet Kodiak and GMC TopKick airbag sensing development included significant work, not only on the development of airbag deployment events but also non-deployment events – events which do not require the airbag to deploy. This paper describes the process used to develop the airbag sensing system deployment events and non-deployment event used in the airbag sensing system calibration.