5 AMS Weather & Climate Enterprise Summer Meeting 2009 What is IntelliDrive SM ? IntelliDrive SM combines leading edge technologies: –advanced wireless communications, –on-board computer processing, –advanced vehicle-sensors, –GPS navigation, –smart infrastructure, and others to identify threats and hazards on the roadway, and communicate this to drivers via alerts and warnings At IntelliDrive SM ’s core is a networked environment supporting high speed transactions: –among vehicles (V2V), –between vehicles and the infrastructure (V2I) or –between vehicles and handheld devices (V2D) that enable numerous safety and mobility applications
6 AMS Weather & Climate Enterprise Summer Meeting 2009 Research Objectives To determine the value of vehicle probe data in improving road weather services Questions to address via research –Is the probe data of sufficient quality? –What are the minimum # of samples and minimum sampling period per road segment to get valid results? Develop Vehicle Data Translator (VDT) –Parse and filter probe data –QC probe data –Disseminate quality checked probe data (‘weather’ elements) –Generate statistically valid weather & road condition information per road segment
7 AMS Weather & Climate Enterprise Summer Meeting 2009 Observed Data Elements Barometric PressureRain (Rain Sensor) External Air TemperatureSun (Sun Sensor) Relative HumidityPavement Temperature Input Data Elements Date (Year, Month, Day)Brake Status Time (Hour, Minute, Second)Brake Boost Location (Lat/Lon)Accelerometer (lat., long.) ElevationYaw Rate Vehicle HeadingHeadlight Status Vehicle VelocityTraction Control Hours of OperationStability Control Wiper StatusRate of Change of Steering Anti-lock Braking Sys StatusImpact Sensor Adaptive cruise control radarAmbient Noise Level Short-range wide beam radarCamera imagery Vehicle Data Elements
8 AMS Weather & Climate Enterprise Summer Meeting 2009 The VDT Concept Functions Parsing Filtering Quality Checking Data integration Statistical processing Data export VDT Data Parser Processing Cache Data Filtering Algorithms Data Quality Checking Statistical Processing Output Queue Ancillary Data Data Subscribers Data Networ k
9 AMS Weather & Climate Enterprise Summer Meeting 2009 Initial Focus of Weather Research Air temperature Barometric pressure Precipitation occurrence (yes, no) Precipitation intensity (none to heavy) Precipitation type (liquid, frozen) Pavement condition (slippery yes/no) Fog (likely, not likely)
11 AMS Weather & Climate Enterprise Summer Meeting 2009 Preliminary QC Result Summary Temperature trends meet expectations –Cooler after thunderstorms –Gradients realistic Temperature accuracy mixed, but promising Desire temperature reporting precision to at least 0.5C (~1F) Desire air pressure reporting precision to at least 0.1 mb (hPa) Statistical processing and rigorous QC are required!
12 AMS Weather & Climate Enterprise Summer Meeting 2009 Vehicle Temperature vs. ASOS KDTW Temperature (C) Vehicle Temperature (C) Correlation = 0.97 Bias = -0.90 MAE = 1.40
13 AMS Weather & Climate Enterprise Summer Meeting 2009 Conclusions & Next Steps USDOT Efforts –Publish initial findings –Collect more data –Enhance the Vehicle Data Translator Support the AMS APT, NoN, CIOS, etc. Upcoming activities –IntelliDrive SM Policy and Institutional Issues Workshop & Webinar, Sept. 2 nd, Detroit, MI (www.itsa.org/intellidriveworkshop.html)www.itsa.org/intellidriveworkshop.html –Clarus Stakeholder meeting, Sept. 14-15, Charlotte, NC