Browse Topic: Roads and highways
ABSTRACT Commercial OEMs are fast realizing the long awaited dream of self-driving trucks and cars. The technology continues to improve with major implications for the Army. In the near tear, the impact may be most profound for military installations. Many believe, however, that the major limiting factor to wide-spread automated vehicle usage will not be technology but the human element. What happens when humans through no choice of their own are compelled to interact with self-driving vehicles? We propose a mixed-methods research study that examines the complex transportation system from both a technical and social perspective. This study will inform environmental controls (rules of the road and infrastructure modifications) and increase understanding of the social dynamics involved with vehicle acceptance. Findings may pave the way for a reduction in the over $400M the Army spends annually on non-tactical vehicles and the technical improvements, grounded in dual-use use cases will be
From televisions to smartphones, organic light-emitting diodes (OLEDs) are finding their way into many everyday devices. For use in displays, blue OLEDs are also required to supplement the primary colors — red and green. Especially in blue OLEDs, impurities give rise to strong electrical losses, which could be partly circumvented by using highly complex and expensive device layouts
Road roughness is the most important source of vertical loads for road vehicles. To capture this during durability engineering, various mathematical models for describing road profiles have been developed. The Laplace process has turned out to be a suitable model, which can describe road profiles in a more flexible way than e.g., Gaussian processes. The Laplace model essentially contains two parameters called C and ν (to be explained below), which need to be adapted to represent a road with certain roughness properties. Usually, local road authorities provide such properties along a road on sections of constant length, say, 100 m. Often the ISO 8608 roughness coefficient or the IRI (International Roughness Index) are used. In such cases, there are well known explicit formulas for finding the parameters C and ν of the Laplace process, which best fits the road under certain assumptions. Besides local road authorities there are also other sources of roughness data, for instance commercial
Ergonomics plays an important role in automobile design to achieve optimal compatibility between occupants and vehicle components. The overall goal is to ensure that the vehicle design accommodates the target customer group, who come in varied sizes, preferences and tastes. Headroom is one such metric that not only influences accommodation rate but also conveys a visual perception on how spacious the vehicle is. An adequate headroom is necessary for a good seating comfort and a relaxed driving experience. Headroom is intensely discussed in magazine tests and one of the key deciding factors in purchasing a car. SAE J1100 defines a set of measurements and standard procedures for motor vehicle dimensions. H61, W27, W35, H35 and W38 are some of the standard dimensions that relate to headroom and head clearances. While developing the vehicle architecture in the early design phase, it is customary to specify targets for various ergonomic attributes and arrive at the above-mentioned
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