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Turn Right: Analysis of Rotation Errors in Turn-by-Turn Navigation for Individuals with Visual Impairments

Published:08 October 2018Publication History

ABSTRACT

Navigation assistive technologies aim to improve the mobility of blind or visually impaired people. In particular, turn-by-turn navigation assistants provide sequential instructions to enable autonomous guidance towards a destination. A problem frequently addressed in the literature is to obtain accurate position and orientation of the user during such guidance. An orthogonal challenge, often overlooked in the literature, is how precisely navigation instructions are followed by users. In particular, imprecisions in following rotation instructions lead to rotation errors that can significantly affect navigation. Indeed, a relatively small error during a turn is amplified by the following frontal movement and can lead the user towards incorrect or dangerous paths. In this contribution, we study rotation errors and their effect on turn-by-turn guidance for individuals with visual impairments. We analyze a dataset of indoor trajectories of 11 blind participants guided along three routes through a multi-story shopping mall using NavCog, a turn-by-turn smartphone navigation assistant. We find that participants extend rotations by 17º on average. The error is not proportional to the expected rotation; instead, it is accentuated for "slight turns" (22.5º-60º), while "ample turns" (60º-120º) are consistently approximated to 90º. We generalize our findings as design considerations for engineering navigation assistance in real-world scenarios.

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  1. Turn Right: Analysis of Rotation Errors in Turn-by-Turn Navigation for Individuals with Visual Impairments

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                • Published in

                  cover image ACM Conferences
                  ASSETS '18: Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility
                  October 2018
                  508 pages
                  ISBN:9781450356503
                  DOI:10.1145/3234695

                  Copyright © 2018 ACM

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                  Publication History

                  • Published: 8 October 2018

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                  ASSETS '18 Paper Acceptance Rate28of108submissions,26%Overall Acceptance Rate436of1,556submissions,28%

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