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OFCM Session 6 – Urban Test Beds Vehicles as Mobile Platforms

OFCM Session 6 – Urban Test Beds Vehicles as Mobile Platforms. Andrew Stern Consulting Meteorologist FHWA Road Weather Management Team Noblis, Inc., Falls Church, VA. July 9, 2008 – Fairfax, VA 12th Annual GMU Conference on Atmospheric Transport & Dispersion Modeling

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OFCM Session 6 – Urban Test Beds Vehicles as Mobile Platforms

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  1. OFCM Session 6 – Urban Test BedsVehicles as Mobile Platforms Andrew Stern Consulting Meteorologist FHWA Road Weather Management Team Noblis, Inc., Falls Church, VA July 9, 2008 – Fairfax, VA 12th Annual GMU Conference on Atmospheric Transport & Dispersion Modeling Contact: astern@noblis.org; 703-610-1754

  2. Annual Weather Related Fatalities 10 year average: 1997-2006

  3. Annual Weather Related Fatalities 10 year average: 1997-2006

  4. ESS Owned by State DOTs An Environmental Sensor Station (ESS) is any site with sensors measuring atmospheric conditions, pavement conditions, and/or water level conditions.

  5. Vehicle-based data: • Speed (mph) • Pressure (in Hg) • Air Temperature (F) • Wiper State • 0=Off • 1-5=Intermittent • 13=On Low • 14=On High ESS Vehicle • ESS Data • Wind Speed/Dir • Air Temp/RH • Road Temp Pre-VII Proof of Concept Research June 1 2007 • Setup: • Vehicle heading west along I-80/Ohio Tnpk (white triangle) • Subset of vehicle sensor data are captured • Data are correlated with radar each volume • Road weather station data are also captured (green triangle)

  6. Wiper State: Off Vehicle Air Temp Vehicle Pressure Vehicle Speed ESS Air Temp ESS Road Temp

  7. Vehicle-based Probe Data Elements Accelerometer Data (steering & yaw) Windshield Wiper State & Speed Barometric Pressure GPS Position, Heading, Elevation & Vehicle Speed Brake Status & Boost Headlight Status External Air Temperature Anti-lock Braking System Vehicle Traction Control Vehicle Stability Control Fog Light Status

  8. DTR Thermal Profile (Air Temp) near Dulles Tysons Tysons

  9. Congestion Modifying Road Temps Snap Shot

  10. Weather Data Translator

  11. Derived Observations • Combines vehicle-based data with in situ or remote-sensed data to infer or derive a new field. Potential fields include: Derived Elements Sources • Air temperature • Precipitation occurrence (yes, no) • Precipitation intensity (none(NP), • light(LGT), moderate(MDT), heavy(HVY)) • Precipitation type (liquid, frozen) • Barometric pressure • Pavement condition (not slippery, slippery) • Frictional Index (0.0 – 1.0) • Vehicle Speed Obs Ta, ESS Wiper, Radar Wiper, Radar Obs Ta, ESS Obs Pr, ESS Obs VTC/VSC Derived Obs Speed

  12. Research Questions • How many probe data samples are needed to obtain quality observations? • How often should vehicle-based observations be generated? • Should observations be synchronized to clock time or radar volume times? • How long should a road segment be? • Should these definitions be consistent in urban & rural regions, during commuting times & at night?

  13. Our Vision • Increasing quality surface observation data density from thousands to millions Credit: Kevin Petty, NCAR

  14. Contact Information • FHWA Road Weather Policy • Paul Pisano, Team Leader, Road Weather • Paul.Pisano@dot.gov, 202-366-1301 • VII/Road Weather Program • Pat Kennedy, Transportation Specialist • Pat.Kennedy@dot.gov, 202-366-9498 • Technical Consultant • Andy Stern, Meteorologist, Noblis, Inc. • astern@noblis.org, 703-610-1754

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