Pedestrian Route Choice Model Estimated from Revealed Preference GPS Data

This study presents a pedestrian route choice model estimated from revealed preference Global Positioning System (GPS) data. The authors extend existing pedestrian route preference work by treating the choice of which path to take as a single, utility maximizing decision from a discrete set of alternatives. The authors find that this traditional travel demand modeling method can be usefully applied to walk travel. Predicted routes could be used as inputs in more precise measurements of pedestrian accessibility. Such measures should be more adept at accounting for individual projects in planning scenarios. In addition to the model’s applications, some interesting findings about pedestrian route preferences are revealed. The authors find that pedestrians are sensitive to attributes of the walking network, intersection crossing aids, and elements of the street and block face environment along urban routes. People walking are willing to go out of their way to use more attractive facilities, but their tolerance for detours is limited, perhaps more so than for cyclists. Crossing aids must be densely placed along major streets to be useful. Neighborhood-scale commercial streets might serve as both attractive destinations and walking routes. Alleyways and unpaved streets do not seem to be useful to pedestrians, who only will use them if the distance saved is large. Terrain is perceived as a barrier only when very steep, and then only in the uphill direction. Finally, the authors find that joint travelers may prefer more direct routes than solo travelers. The authors find no significant differences in route preferences for female pedestrians.