StreetTest

StreetTest is a web + mobile AI-assisted urban design app that lets cities and consultants quickly prototype “quick-build” street interventions (bike lanes, curb extensions, bus lanes, parklets) and estimate impacts before committing to construction. Users draw changes on a map or import a corridor, then the app runs lightweight scenario modeling using available traffic counts, speed data, crash history, and curb regulations. It outputs a plain-language brief: expected travel-time shifts, safety risk flags, curbside conflicts, and an implementation checklist. The goal is not perfect simulation; it’s fast, defensible decision support for early-stage design and public meetings. It also generates shareable visuals (before/after cross-sections and simple render overlays) and a feedback link for residents. This is realistic for small teams because it relies on existing open data and third-party mobility datasets where available, and it focuses on corridor-level decisions rather than citywide digital twins.