Wayfinding Decision Situations: A Conceptual Model and Evaluation

Humans engage in wayfinding many times a day. We try to find our way in urban environments when walking towards our work places or when visiting a city as tourists. In order to reach the targeted destination, we have to make a series of wayfinding decisions of varying complexity. Previous research has focused on classifying the complexity of these wayfinding decisions, primarily looking at the complexity of the decision point itself (e.g., the number of possible routes or branches). In this paper, we proceed one step further by incorporating the user, instructions, and environmental factors into a model that assesses the complexity of a wayfinding decision. We constructed and evaluated three models using data collected from an outdoor wayfinding study. Our results suggest that additional factors approximate the complexity of a wayfinding decision better than the simple model using only the number of branches as a criterion. DOI: https://doi.org/10.1007/978-3-319-11593-1_15 Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-99076 Accepted Version Originally published at: Giannopoulos, Ioannis; Kiefer, Peter; Raubal, Martin; Richter, Kai-Florian; Thrash, Tyler (2014). Wayfinding decision situations: a conceptual model and evaluation. In: Duckham, Matt; Pebesma, Edzer; Stewart, Kathleen; Frank, Andrew U. Geographic Information Science. Berlin: Springer, 221-234. DOI: https://doi.org/10.1007/978-3-319-11593-1_15 Wayfinding Decision Situations: A Conceptual Model and Evaluation Ioannis Giannopoulos1, Peter Kiefer1, Martin Raubal1, Kai-Florian Richter2, and Tyler Thrash3 Institute of Cartography and Geoinformation, ETH Zurich Stefano-Franscini-Platz 5, 8093 Zurich, Switzerland {igiannopoulos,pekiefer,mraubal}@ethz.ch Department of Geography, University of Zurich Winterthurerstr. 190, 8057 Zurich, Switzerland [email protected] Department of Humanities, Social and Political Science, Chair of Cognitive Science, ETH Zurich Clausiusstrasse 59, 8092 Zurich, Switzerland [email protected] Abstract. Humans engage in wayfinding many times a day. We try to find our way in urban environments when walking towards our work places or when visiting a city as tourists. In order to reach the targeted destination, we have to make a series of wayfinding decisions of varying complexity. Previous research has focused on classifying the complexity of these wayfinding decisions, primarily looking at the complexity of the decision point itself (e.g., the number of possible routes or branches). In this paper, we proceed one step further by incorporating the user, instructions, and environmental factors into a model that assesses the complexity of a wayfinding decision. We constructed and evaluated three models using data collected from an outdoor wayfinding study. Our results suggest that additional factors approximate the complexity of a wayfinding decision better than the simple model using only the number of branches as a criterion. Humans engage in wayfinding many times a day. We try to find our way in urban environments when walking towards our work places or when visiting a city as tourists. In order to reach the targeted destination, we have to make a series of wayfinding decisions of varying complexity. Previous research has focused on classifying the complexity of these wayfinding decisions, primarily looking at the complexity of the decision point itself (e.g., the number of possible routes or branches). In this paper, we proceed one step further by incorporating the user, instructions, and environmental factors into a model that assesses the complexity of a wayfinding decision. We constructed and evaluated three models using data collected from an outdoor wayfinding study. Our results suggest that additional factors approximate the complexity of a wayfinding decision better than the simple model using only the number of branches as a criterion.