Broadening Access to Transportation Safety Data with Generative AI: A Schema-Grounded Framework for Spatial Natural Language Queries

Researchers introduced a schema-grounded AI interface for transportation safety analysis that turns natural-language questions into deterministic spatial database queries.

The system was tested on a Massachusetts safety dataset covering crash records, roadway attributes, schools, bus stops, crosswalks, and municipal boundaries.

All queries executed successfully, and the validation layer corrected errors in 29% of cases, improving reliability without losing reproducibility.

The approach could make transportation safety data easier to use for agencies and communities while keeping results auditable and trustworthy.