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The laboratory test method commonly known as “random vibration” is almost always used for Squeak & Rattle testing in today's automotive applications due to its obvious advantages: the convenience in simulating the real road input, the relatively low cost, and efficiency in obtaining the desired test results. Typically, Loudness N10 is used to evaluate the Squeak & Rattle (S&R) performance. However, due to the nature of random distribution of the excitation input, the repeatability of the loudness N10 measurements may vary significantly. This variation imposes a significant challenge when one is searching for a fine design improvement solution in minimizing S&R noise, such as a six-sigma study. This study intends to investigate (1) the range of the variations of random vibration control method as an excitation input with a given PSD, (2) the possibility of using an alternate control method (“time-history replication”) to produce the vibration of a given PSD for a S&R evaluation.

Rollovers are an important vehicle safety issue. Various technologies have been developed to help prevent rollovers from occurring, but the evaluation of rollover resistance typically involves vehicle-handling tests that are conducted on flat road surfaces with a uniform or split coefficient of friction. The purpose of this study is to determine the precipitating events leading to rollovers by analyzing real-world rollover crashes. This is a first step in identifying and developing vehicle tests that are representative of the principal driving scenarios leading to rollovers. The sequence of events leading to rollovers was determined from 63 in-depth investigated cases in the NASS-CDS database from 1995-1999. The sequence was evaluated by vehicle maneuvers, vehicle stability, surface type, road and shoulder transition condition, posted and estimated speeds, vehicle type and driver injury severity.

Traffic engineers use time-of-day travel time databases to characterize normal travel times on roads. This information is used by traffic management centers together with information from sensors in the highway to identify problems and to make alternate route recommendations. In this paper, the travel time database concept is extended to a vehicle-to-vehicle communications network for traffic and safety information, wherein the travel time database is generated and stored by vehicles in the network, and used by the vehicles to identify abnormal traffic conditions. This infrastructure-free approach is attractive due to the potential to eliminate highway sensor and sensor maintenance costs, which are major factors that limit the growth of traffic information beyond major roadways in urban regions. Initial work indicates that database storage requirements in the vehicle should be manageable.