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A System of Automatic Generation of Landmark-Based Pedestrian Navigation Instructions and Its Effectiveness for Wayfinding

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Spatial Cognition XI (Spatial Cognition 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11034))

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Abstract

Websites of hotels, restaurants, and other businesses often provide navigation instructions from a nearby railway station. One form of such navigation instructions could combine street-view photographs and verbal directions, which may be intuitive and easy to understand. This study developed a method of generating landmark-based navigation instructions automatically using a digital map database available, and examined their effectiveness in navigating the user in comparison to a commercial GPS-based navigation application. Results showed that participants tended to travel longer distances and deviate from directed routes more frequently when using a GPS-based navigation application; the tendency was greater for people with a poor sense of direction. These people, however, did not have difficulty with wayfinding when using the landmark-based instructions. The present method of providing landmark-based navigation instructions was thus found to help the user, especially people with a poor sense of direction, find their way in a new environment.

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Authors and Affiliations

  1. Graduate School of Interdisciplinary Information Studies, University of Tokyo, Tokyo, Japan

    Jue Wang & Toru Ishikawa

Authors
  1. Jue Wang
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  2. Toru Ishikawa
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Correspondence to Toru Ishikawa .

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Editors and Affiliations

  1. University of Utah, Salt Lake City, Utah, USA

    Sarah Creem-Regehr

  2. University of Bremen, Bremen, Germany

    Johannes Schöning

  3. Pennsylvania State University, University Park, Pennsylvania, USA

    Alexander Klippel

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Wang, J., Ishikawa, T. (2018). A System of Automatic Generation of Landmark-Based Pedestrian Navigation Instructions and Its Effectiveness for Wayfinding. In: Creem-Regehr, S., Schöning, J., Klippel, A. (eds) Spatial Cognition XI. Spatial Cognition 2018. Lecture Notes in Computer Science(), vol 11034. Springer, Cham. https://doi.org/10.1007/978-3-319-96385-3_22

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  • DOI: https://doi.org/10.1007/978-3-319-96385-3_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-96384-6

  • Online ISBN: 978-3-319-96385-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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