Field evaluation of a mobile app for assisting blind and visually impaired travelers to find bus stops
September 19, 2023 Β· Declared Dead Β· π Translational Vision Science & Technology
"No code URL or promise found in abstract"
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Authors
Shrinivas Pundlik, Prerana Shivshanker, Tim Traut-Savino, Gang Luo
arXiv ID
2309.10940
Category
cs.HC: Human-Computer Interaction
Citations
6
Venue
Translational Vision Science & Technology
Last Checked
4 months ago
Abstract
Purpose: It is reported that there can be considerable gaps due to GPS inaccuracy and mapping errors if blind and visually impaired (BVI) travelers rely on digital maps to go to their desired bus stops. We evaluated the ability of a mobile app, All_Aboard, to guide BVI travelers precisely to the bus-stops. Methods: The All_Aboard app detected bus-stop signs in real-time via smartphone camera using a neural network model, and provided distance coded audio feedback to help localize the detected sign. BVI individuals used the All_Aboard and Google Maps app to localize 10 bus-stop locations in Boston downtown and another 10 in a sub-urban area. For each bus stop, the subjects used the apps to navigate as close as possible to the physical bus-stop sign, starting from 30 to 50 meters away. The outcome measures were success rate and gap distance between the app-indicated location and the actual physical location of the bus stop. Results: The study was conducted with 24 legally blind participants (mean age [SD]: 51[14] years; 11 (46%) Female). The success rate of the All_Aboard app (91%) was significantly higher than the Google Maps (52%, p<0.001). The gap distance when using the All_Aboard app was significantly lower (mean [95%CI]: 1.8 [1.2-2.3] meters) compared to the Google Maps (7 [6.5-7.5] meters; p<0.001). Conclusion: The All_Aboard app localizes bus stops more accurately and reliably than GPS-based smartphone navigation options in real-world environments.
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