Dyadic Route Planning and Navigation in Collaborative Wayfinding

Authors Crystal J. Bae , Daniel R. Montello

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Crystal J. Bae
  • University of California, Santa Barbara, USA
Daniel R. Montello
  • University of California, Santa Barbara, USA


We would like to thank our research assistants Liza Benabbas, Karina Jimenez, and Kienna Owen-Quinata, along with all of our participants in this study for their help. We also thank our four anonymous reviewers for their thorough feedback in the preparation of this article.

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Crystal J. Bae and Daniel R. Montello. Dyadic Route Planning and Navigation in Collaborative Wayfinding. In 14th International Conference on Spatial Information Theory (COSIT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 142, pp. 24:1-24:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


The great majority of work in spatial cognition has taken an individual approach to the study of wayfinding, isolating the planning and decision-making process of a single navigating entity. The study we present here expands our understanding of human navigation as it unfolds in a social context, common to real-world scenarios. We investigate pedestrian navigation by pairs of people (dyads) in an unfamiliar, real-world environment. Participants collaborated on a task to plan and enact a route between a given origin and destination. Each dyad had to devise and agree upon a route to take using a paper map of the environment, and was then taken to the environment and asked to navigate to the destination from memory alone. We video-recorded and tracked the dyad as they interacted during both planning and navigation. Our results examine explanations for successful route planning and sources of uncertainty in navigation. This includes differences between situated and prospective planning - participants often modify their route-following on the fly based on unexpected challenges. We also investigate strategies of social role-taking (leading and following) within dyads.

Subject Classification

ACM Subject Classification
  • General and reference → Empirical studies
  • Applied computing → Sociology
  • Applied computing → Psychology
  • Wayfinding
  • Navigation
  • Collaboration
  • Leadership
  • Conversation Analysis


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