StopFinder: Improving the Experience of Blind Public Transit Riders with Crowdsourcing
Sanjana Prasain · 2011 · The Proceedings of the 13th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/2049536.2049629
Summary
This doctoral consortium paper presents StopFinder, a mobile system that uses crowdsourcing to collect and provide information about non-visual landmarks around bus stops for blind public transit riders. The research addresses a fundamental challenge: while people who are blind often depend on public transit for daily travel, finding the exact location of bus stops is a major barrier to independent use. The system builds on the author's prior work with GoBraille, a Braille-based Android application for bus stop information that revealed through user interviews the critical importance of reliable, accurate landmark information — not just stop locations but details about shelters, garbage cans, benches, and the relative positions of these features. StopFinder moves beyond the Braille note-taker approach to a smartphone-based platform, making the information accessible via text-to-speech on iPhones, which the author identified as the most widely used smartphone among blind transit riders.
Key findings
The system employs a two-pronged design: sighted transit riders using the OneBusAway app contribute landmark data through a graphical, game-like interface with movable icons for shelters, benches, and other features placed over a static map of each bus stop. This crowdsourced visual data is then converted into descriptive text for blind users. For blind riders, the system provides the landmark information via a text-to-speech interface on their smartphones, eliminating the need for expensive Braille note-takers. User studies from the earlier GoBraille project confirmed that blind riders prioritize reliable, accurate, and concise landmark descriptions for navigating to bus stops, and that access to this information enhances both their safety and sense of independence. The approach leverages existing transit app infrastructure and the waiting time of sighted riders to build coverage at scale.
Relevance
StopFinder demonstrates a practical model for using crowdsourcing to bridge accessibility gaps in public infrastructure. Rather than requiring expensive specialized hardware or professional surveys, it harnesses the contributions of sighted transit users to create information that blind riders need. This approach has broader implications for accessible transportation and wayfinding — the same crowdsourcing model could be applied to other navigation contexts where environmental descriptions are needed but not available through standard mapping data. The work also highlights an important design principle: accessibility solutions are most effective when integrated into mainstream platforms that sighted people already use, rather than built as standalone assistive tools with limited adoption.
Tags: blindness and low vision · crowdsourcing · navigation · public transportation · mobile accessibility · wayfinding · independent living