Automated route guidance systems, both web-based systems and en-route systems, have become commonplace in recent years. These systems often replace human-generated directions, which are often incomplete, vague, or in error. However, human-generated directions have the ability to differentiate between easy and complex steps through language in a way that is more difficult in automated systems. This article examines a set of human-generated verbal directions to better understand why some parts of directions are perceived as being more difficult than the remaining steps. Insights from this analysis will lead to recommendations to improve the next generation of automated route guidance systems.

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