Wayfinding Decision Situations: A Conceptual Model and Evaluation

  • Ioannis Giannopoulos
  • Peter Kiefer
  • Martin Raubal
  • Kai-Florian Richter
  • Tyler Thrash
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8728)


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.


Genetic Algorithm Cognitive Load User Model Spatial Ability Decision Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ioannis Giannopoulos
    • 1
  • Peter Kiefer
    • 1
  • Martin Raubal
    • 1
  • Kai-Florian Richter
    • 2
  • Tyler Thrash
    • 3
  1. 1.Institute of Cartography and GeoinformationETH ZürichZürichSwitzerland
  2. 2.Department of GeographyUniversity of ZürichZürichSwitzerland
  3. 3.Department of Humanities, Social and Political Science, Cognitive ScienceETH ZürichZürichSwitzerland

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