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Title: Environmental factors in indoor navigation based on real-world trajectories of blind users
Indoor localization technologies can enhance quality of life for blind people by enabling them to independently explore and navigate indoor environments. Researchers typically evaluate their systems in terms of localization accuracy and user behavior along planned routes. We propose two measures of path-following behavior: deviation from optimal route and trajectory variability. Through regression analysis of real-world trajectories from blind users, we identify relationships between a) these measures and b) elements of the environment, route characteristics, localization error, and instructional cues that users receive. Our results provide insights into path-following behavior for turn-by-turn indoor navigation and have implications for the design of future interactions. Moreover, our findings highlight the importance of reporting these environmental factors and route properties in similar studies. We present automated and scalable methods for their calculation and to encourage their reporting for better interpretation and comparison of results across future studies  more » « less
Award ID(s):
1637927
PAR ID:
10304276
Author(s) / Creator(s):
Date Published:
Journal Name:
Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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