GOVERNMENT

Smart City Traffic Operations & Urban Planning

Find the hidden variables behind gridlock and crash-prone corridors.

Municipal transportation departments face immense challenges adapting legacy infrastructure to population booms and shifting commuter habits. Urban planners can upload years of intersection sensor data, public transit ridership logs, traffic accident reports, and historical roadwork schedules. The platform evaluates this geospatial data to uncover the hidden variables that cause gridlock, cross-tabulating time-of-day metrics with specific intersection geometries and weather events.

City engineers can ask natural language questions to pinpoint why particular corridors suffer disproportionate accident rates. By generating research-grade reports backed by statistical significance, transportation boards can intelligently allocate infrastructure budgets, optimize signal sequencing, and design safer, more efficient cities.

AI Report

Congestion & Safety Drivers

This report analyzes 6 years of sensor, ridership, incident, and roadwork data across 240 intersections.

Skewed-angle intersections drive 41% of peak gridlock,¹ rising to 53% during rain events² and cascading to 3 downstream corridors.³

Signal timing recurs as a safety factor. It precedes 27% of injury collisions,⁴ and 3 in 5 of those occur in the evening peak.⁵

Location Intelligence

Use Steeped AI's location intelligence to multiply basic intersection coordinates with surrounding commercial density and elevation data, building a far richer picture of traffic flow. Geography stops being a coordinate pair and becomes an explanatory variable.

US Census Balancing

Use Steeped AI's census balancing and state-level weighting to correct demographic blind spots in public transit data, so new bus routes and bike lanes serve chronically underrepresented neighborhoods rather than the districts that complain loudest.

Statistical Significance Testing

Steeped AI's automated significance testing runs false discovery rate correction to confirm that a proposed change in signal timing will yield a mathematically proven improvement. Capital budgets commit only to changes the statistics support.

Talk to Your Data

Steeped AI's talk to your data lets city planners conversationally query massive traffic datasets and instantly surface the most critical congestion metrics. A question about one corridor returns ranked, cited findings pulled from the real sensor record.

Predictive Power Score

Steeped AI's regression predictive power turns complex statistics into a single percentage per relationship, showing which intersection attributes genuinely forecast collisions and delay. Engineering priorities follow the variables that measurably move outcomes.

Reporting & Citations

Steeped AI's reporting and citations produces the board-ready report, with every conclusion carrying a numbered citation back to the sensor reading or incident record behind it. A transportation board can audit a budget recommendation line by line.

Traffic Finding Citations

¹ 41% of "skewed intersections" hit "peak gridlock"

² 33% of "rain events" extended "corridor delay"

³ 27% of "injury collisions" followed "signal timing"

⁴ 24% of "transit gaps" fell in "under-served tracts"

⁵ 19% of "roadwork windows" overlapped "peak flow"

⁶ 15% of "delays" cascaded from "one corridor"

⁷ 8% of "crashes" clustered at "Corridor 7"

The insights are already in your data.

Ask your data anything. Get real findings ranked by impact, with AI reports your team can present and share on the spot.