| Sensor | Speed | Flow | Occupancy |
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Operations Report
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| Pollutant | Instant Rate | Today Cumul. | All-Time Cumul. |
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LATTICE
UNLV Traffic Intelligence Platform
LATTICE is an integrated real-time traffic monitoring, emissions estimation, and speed prediction platform developed at the UNLV Transportation Research Center. The system processes live sensor data from the Nevada FAST system across over 500 detectors on Las Vegas metropolitan freeways, providing actionable intelligence for traffic management and air quality assessment.
The platform combines three core capabilities: real-time traffic state monitoring with lane-level analysis, comprehensive emissions tracking using EMFAC emission factors for 20+ pollutants, and GMAN deep learning predictions for speed forecasting at multiple horizons. All data is visualized through an interactive web dashboard with live updates via WebSocket connections.
Tarek Bin Zahid
UNLV Transportation Research Center
UNLV Transportation Research Center
Howard R. Hughes College of Engineering
University of Nevada, Las Vegas
Real-time speed, flow, and occupancy data from 500+ loop detectors. Includes corridor filtering, network metrics, per-lane analysis, live trend charts, and sensor drill-down capabilities with 24-hour historical data.
EMFAC-based emission factors for 20+ pollutants (CO₂, NOₓ, PM2.5, PM10, CO, SOₓ, and more). Network totals, per-sensor breakdown, daily/cumulative tracking, heat map visualization, and 24-hour timeline playback.
GMAN deep learning model for multi-horizon speed forecasts (+15, +30, +45, +60 minutes). Includes model accuracy metrics, per-sensor predictions, current vs predicted comparisons, and prediction history visualization.
Leaflet-based map with real-time markers, emissions heat layers, timeline scrubbing, sensor selection, corridor filtering, and responsive charts. Live WebSocket updates and export capabilities.