Modeling Slope as a Contributor to Route Selection in Mountainous Areas

Slope exerts a powerful influence on the route selection processes of humans. Attempts to model human movement in hilly and mountainous terrain which have largely focused on least-time route transformations can be improved by incorporating research suggesting that humans systematically overestimate slopes. Such research suggests that cost functions derived from slope should be more expensive than time derivations alone would indicate. This paper presents a method for empirically estimating cost functions for slopes. We use the method to predict routes and paths that are more likely to be selected by humans based on their perceptions of slope. An evaluation of the method found that it successfully predicts road, track and trail locations over a variety of conditions and distances.