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

August 11, 2025 Β· Declared Dead Β· πŸ› ACM Symposium on User Interface Software and Technology

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Authors Jon E. Froehlich, Alexander Fiannaca, Nimer Jaber, Victor Tsaran, Shaun Kane arXiv ID 2508.08524 Category cs.HC: Human-Computer Interaction Cross-listed cs.AI Citations 6 Venue ACM Symposium on User Interface Software and Technology Last Checked 4 months ago
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 360Β° 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.
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