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Human models are viable methods of introducing human factors and ergonomic objectives into the design process at an early stage. Used correctly, they allow users to simulate and analyze potential human-machine interactions saving time and money. As with any model, mistakes can be made. The primary sources of error stem from incorrect use and misinterpretation of the results by the analyst. The development of three-dimensional human modeling software has only compounded these issues by adding a digital subject, itself a human model. This complicates the interpretation and use of these tools by layering one human model on top of another. The purpose of this paper is to highlight common categories of misuse and misinterpretation of digital human models as well as to propose a method for improving user understanding of human models through formal documentation of critical components.

Size is one of the most basic and important factors when determining fit for people. Many methods used to test occupant fit and accommodation rely on a traditional set of three different sized manikins - 5th, 50th and 95th percentiles. Anthropometry, the study of human size dimensions, however, is a complex multivariate problem. Real people, real drivers are a mixture of dimensions tall thin, short, stout, etc. This paper examines population anthropometry and these traditional percentiles specific to vehicular seat design.