Vehicle Infrastructure Integration (VII): Scientific Challenges

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Presentation transcript:

Vehicle Infrastructure Integration (VII): Scientific Challenges Kevin R. Petty Bill P. Mahoney Richard R. Wagoner National Center for Atmospheric Research VII Weather Applications Workshop Boulder, Colorado Feb. 22, 2006

Vehicle Infrastructure Integration (VII) BENEFIT: VII enables tactical and strategic response to weather related surface transportation hazards. Synoptic Scale Highs, Lows, Fronts Nor’easters Hurricanes, tropical storms Thunderstorms Mesoscale Tornadoes Microscale Black ice, Fog

VII Weather Application Development: Expected Challenges Data comprehension Data quality and accuracy Data volume Spatial distribution Complex terrain Data fusion Quality checking Algorithm and Concept Development

Data Quality and Accuracy Sensor placement is likely to result in variability in certain parameters (e.g. temperature, rain, sun)

Data Quality and Accuracy Sensor type can also lead to differences in measured parameters: Range Data type Precision Resolution Accuracy Account for biases Vehicle knowledge Privacy Rain Sensor Suppliers: Bosch Denso Kostal TRW Valeo Thermister Thermocouple

Data Volume Determine how to utilize large amounts of data Averaging Wipers=on/high Averaging Over distance Over time Equivalent to a point measurement (replicating ASOS) 28°F 36°F Wipers=off Wipers=on/low 35°F Wipers=off

Urban Versus Rural Environments A major challenge exists in terms of rural regions. How do we create applications that work equally well in urban and rural environments? 38°F Wipers=on/high 28°F 36°F Wipers=off Wipers=on/low Regional car types 35°F Wipers=off

Urban Versus Rural Coverage Population Centers Snow/Ice Light rain Thunderstorms Heavy rain Tornadoes Dust storms Fog

Complex Terrain Data variations Elevation Terrain separation Quality checking

Data fusion 6 mins./10 mins. Disparate Data Processing time Algorithm initiation intervals 15 minutes 1 hr with specials Model Dependent 38°F 28°F 36°F 35°F

Quality Checking What is truth? 28°F 38°F Quality checks on mobile platform data (Clarus like) Sensor test range Spatial test (terrain) Climatology Persistence (privacy) Step test 36°F 35°F Mobile Sensors ASOS/AWOS What is truth? Radar Satellite