I can tell by the way you use your walk: real-time classification of wayfinding performance

  • Authors:

  • Makoto Takemiya;Toru Ishikawa

  • Affiliations:

  • Graduate School of Interdisciplinary Information Studies, The University of Tokyo;Center for Spatial Information Science, The University of Tokyo

  • Venue:
  • COSIT'11 Proceedings of the 10th international conference on Spatial information theory
  • Year:
  • 2011

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Abstract

Wayfinding activities often pose difficulty, especially for people with poor spatial abilities. If wayfinding aides can take into account individual differences during navigation, targeted assistance may be able to improve wayfinding performance. To enable this, the performance of wayfinders must first be classified. This work proposes a novel method that uses a probabilistic scoring function to classify wayfinding performance using only information available in real-time during route traversal. Training data for the classifier was algorithmically generated as routes representing different levels of wayfinding performance. This approach was tested through an empirical study in which people with different abilities walked from a start to a goal. The results show that performance of wayfinders can be reliably classified into two groups-good and poor-and that this classification can be done using only information available during route traversal. Our results suggest that environmental structure plays an important role in wayfinders' route choice.