All Aboard App Helps Blind Riders Find Their Bus Stops
Author: Massachusetts Eye and Ear Infirmary
Published: 30 Jan 2024 - Updated: 25 Jun 2026
Publication Type: Instructive / Helpful
Contents: Synopsis - Definition - Introduction - Main - Insights, Updates - Related Publications
Synopsis: This research describes a micro-navigation smartphone app called All_Aboard, developed by a team at Mass Eye and Ear to help people who are blind or visually impaired locate their bus stops with greater accuracy than mainstream GPS tools alone. The findings, reported in Translational Vision Science and Technology, carry weight because the app was tested by 24 blind or visually impaired participants across a set route of 10 bus stops at both urban and suburban sites, and the results were measured against Google Maps using localization error and success rate. By pairing standard GPS macro-navigation with computer vision that reads street signs from 30 to 50 feet away, the work points to a practical way to reduce missed buses for travelers with visual impairments, making it of clear interest to people with disabilities, seniors, mobility specialists, and anyone working on accessible public transit.*
At a Glance
- 1 - The All_Aboard app is released to the public for free, with no revenue from sales or in-app ads.
- 2 - Average gap distance was 1.54 meters with All_Aboard, compared with 6.62 meters using Google Maps.
- 3 - The app runs on a deep learning neural network trained on roughly 10,000 bus stop images and currently recognizes stops in 10 major cities and regions.
- Topic Definition: Micro-Navigation
Micro-navigation refers to the final, close-range stage of finding a destination, such as pinpointing the exact location of a bus stop, doorway, or entrance once a traveler is already in the right general area. It differs from macro-navigation, which handles broad route planning between distant points and is handled well by standard GPS. For people who are blind or visually impaired, micro-navigation is often the hardest part of a trip, because GPS-based positioning is not precise enough to confirm whether someone is standing close enough to a stop. Tools that address this gap typically rely on additional sensing, such as a smartphone camera reading nearby signs, paired with audio cues that guide the user the last several feet to their goal.
Introduction
A team of researchers from Mass Eye and Ear have developed a micro-navigation smartphone app to provide assistance to those who are blind or visually impaired (BVI) in finding their bus stops, and a new study found the success rate of the app was substantially higher than that of Google Maps.
Main Content
GPS Systems
Current GPS systems have sufficient macro-navigation for planning routes using public transportation. However, micro-navigation, such as finding the exact locations of bus stops and destinations, remains an issue for people who are BVI, as GPS-based localization for this is less accurate. To combat this problem, the researchers developed a mobile app called All_Aboard, which is meant to be used in conjunction with mainstream GPS systems and focuses on improving micro-navigation.
When a GPS indicates that a BVI user is nearing their destination, that is when All_Aboard should be opened. The app uses the phones' camera to detect street signs from 30 to 50 feet away. It then uses auditory cues to direct the user towards their destination, with the frequency of the sounds changing as they approach the end point.
The app is powered by artificial intelligence, using a deep learning neural network trained on about 10,000 images of bus stops collected in a given city or region. The app is currently capable of recognizing bus stops in 10 major cities/regions around the world.
In the study, 24 BVI individuals used All_Aboard along with Google Maps to navigate a set route with 10 bus stops at an urban (Boston) and suburban site (Newton, Mass.).
The results of the study were measured in terms of localization error and rate of successful localization. Localization error, or gap distance, is defined as the distance between the desired destination and maps marked end point.
The rate of successful localization is the probability of getting close enough to the bus stops. The researchers found that in both urban and suburban locations, All_Aboard had a success rate of 93 percent, whereas Google Maps had a 52 percent success rate. Additionally, the average gap distance with Google Maps was 6.62 meters and 1.54 meters with All_Aboard.
GPS accuracy is supposed to be acceptable in suburban areas, according to Luo, who added it was not initially expected that the performance with Google Maps in Newton, Mass. would be so low. Previous research from Luo and his team found this problem may be due to widespread errors in bus stop location mapping data in Google Maps.
"Our findings suggest that the All_Aboard app could help travelers with visual impairments in navigation by accurately detecting the bus stop, and therefore greatly reducing their chance of missing buses due to standing too far from the bus stops," said Gang Luo, PhD, of the Schepens Eye Research Institute of Mass Eye and Ear.
"This study indicates that computer vision-based object recognition capabilities can be used in a complementary way and provide added benefit to purely mapping-based, macro-navigation services in real-world settings."
Authorship:
Other co-authors include Shrinivas Pundlik and Prerana Shivshanker of Mass Eye and Ear, and Tim Traut-Savino of the The Carroll Center for the Blind.
Disclosures:
The authors declared no potential conflicts of interest with respect to the research. The All_Aboard app evaluated in this study is released to public for free. There is no revenue from app sale or in-app advertisements.
Funding:
The All_aboard app development was funded in part by Microsoft AI4A award.
Insights, Analysis, and Developments
Editorial Note: What makes this project notable is not just the headline accuracy gap, but the reasoning behind it - the researchers traced Google Maps' weaker suburban performance to widespread errors in bus stop location data, then showed that camera-based object recognition can fill that gap rather than replace existing tools. By framing All_Aboard as a complement to mapping services rather than a competitor, the team offers a model for accessible technology that is realistic, low-cost, and built around how blind and visually impaired travelers actually move through a city, and the decision to release the app for free without advertising signals an approach centered on users rather than revenue.*Attribution/Source(s): This quality-reviewed publication was selected for publishing by the editors of Disabled World (DW) due to its relevance to the disability community. Originally authored by Massachusetts Eye and Ear Infirmary and published on 30 Jan 2024, this content may have been edited for style, clarity, or brevity.
* Editorial additions by Ian C. Langtree.