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Tanker trucks are commonly used for transporting liquid material including chemical and petroleum products. On the one hand, tanker trucks are susceptible to rollover accidents due to the high center of gravity when they are loaded and due to the liquid sloshing effects when the tank is partially filled. On the other hand, tanker truck rollover accidents are among the most dangerous vehicle crashes, frequently resulting in serious to fatal driver injuries and significant property damage, because the liquid cargo is often hazardous and flammable. Therefore, effective schemes for tanker truck rollover avoidance are highly desirable and can bring a considerable amount of societal benefit. Yet, the development of such schemes is challenging, as tanker trucks can operate in various environments and be affected by manufacturing variability, aging, degradation, etc. This paper considers the use of Learning Reference Governor (LRG) for tanker truck rollover avoidance.

Although over 800 references to child and infant anthropometry are in the literature, most have limited validity and application to current populations. Functional measures required by industry and government for federal safety standards for design of dummies, child products, furniture, or protective devices such as restraint systems have either been incomplete, inadequate, or nonexistent. Some of the limitations influencing validity of existing data have been outlined for the potential user. As a start toward obtaining necessary functional anthropometric data, The University of Michigan is currently conducting a study sponsored by the U.S. Consumer Product Safety Commission to obtain valid nationwide measurements on a representative U.S. population from birth to age 12 years. In this study some 41 measurements, including many functional measures, as well as seated and supine whole-body centers of gravity, are being taken utilizing a new automated anthropometric minicomputer system.