English

StreetReaderAI: Making Street View Accessible Using Context-Aware Multimodal AI

Human-Computer Interaction 2025-09-29 v4 Artificial Intelligence

Abstract

Interactive streetscape mapping tools such as Google Street View (GSV) and Meta Mapillary enable users to virtually navigate and experience real-world environments via immersive 360{\deg} imagery but remain fundamentally inaccessible to blind users. We introduce StreetReaderAI, the first-ever accessible street view tool, which combines context-aware, multimodal AI, accessible navigation controls, and conversational speech. With StreetReaderAI, blind users can virtually examine destinations, engage in open-world exploration, or virtually tour any of the over 220 billion images and 100+ countries where GSV is deployed. We iteratively designed StreetReaderAI with a mixed-visual ability team and performed an evaluation with eleven blind users. Our findings demonstrate the value of an accessible street view in supporting POI investigations and remote route planning. We close by enumerating key guidelines for future work.

Keywords

Cite

@article{arxiv.2508.08524,
  title  = {StreetReaderAI: Making Street View Accessible Using Context-Aware Multimodal AI},
  author = {Jon E. Froehlich and Alexander Fiannaca and Nimer Jaber and Victor Tsaran and Shaun Kane},
  journal= {arXiv preprint arXiv:2508.08524},
  year   = {2025}
}

Comments

Accepted to UIST'25; v2. Fixed a missing word in the PDF; v3. Fixed a typo in an author's name; v4. Changed system name and title

R2 v1 2026-07-01T04:45:21.847Z