Abstract
People often experience difficulty traversing novel environments. Predicting where wayfinders will go is desirable for navigational aids to prevent mistakes and influence inefficient traversals. Wayfinders are thought to use criteria, such as minimizing distance, that comprise wayfinding strategies for choosing routes through environments. In this contribution, we computationally generated routes for five different wayfinding strategies and used the routes to predict subsequent decision points that wayfinders in an empirical study traversed. It was found that no single strategy was consistently more accurate than all the others across the two environments in our study. We next performed real-time classification to infer the most probable strategy to be in use by a wayfinder, and used the classified strategy to predict subsequent decision points. The results demonstrate the efficacy of using multiple wayfinding strategies to dynamically predict subsequently traversed decision points, which has implications for navigational aids, among other real-world applications.
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Takemiya, M., Ishikawa, T. (2013). Strategy-Based Dynamic Real-Time Route Prediction. In: Tenbrink, T., Stell, J., Galton, A., Wood, Z. (eds) Spatial Information Theory. COSIT 2013. Lecture Notes in Computer Science, vol 8116. Springer, Cham. https://doi.org/10.1007/978-3-319-01790-7_9
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DOI: https://doi.org/10.1007/978-3-319-01790-7_9
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