VII Weather Related Applications: Feasibility and Concept Development

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VII Weather Related ApplicationsFeasibility and
Concept Development
Kevin R. Petty Bill P. Mahoney Richard R.
Wagoner National Center for Atmospheric
Research ICC 4 Falls Church, Virginia August
9, 2006
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(No Transcript)
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Vehicle Infrastructure Integration (VII)
NCAR, with support from the FHWA and ITS JPO, is
investigating the possibilities of deriving
weather and road condition information from
vehicle data elements.

• Develop an understanding of current and
  anticipated vehicle data elements
• Conduct analysis regarding quantity, quality and
  timeliness of data elements
• Investigate single and multi element requirements
• Investigate methods of combining vehicle data
  elements and other data
• Conduct workshops to facilitate weather related
  VII discussions

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Vehicle Infrastructure Integration (VII)
OBJECTIVE Produce a Feasibility and Concept
Development Report for VII

• Relevant data elements
• Technical issues (challenges, barriers, etc.)
• Contribution to weather and road conditions
• Data load and processing requirements
• Research topics focused on data utilization
• Feasibility of using VII data to improve safety,
  mobility and efficiency

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Methodology

• VII Weather Applications Workshops
• February 22 23, 2006
• June 21, 2006
• Literature Review
• FHWA VII Architecture and Functional Requirements
• Automotive Multimedia Interface Collaboration
  (AMI-C) Documentation
• Event Data Recorder (EDR) Information
• On Board Diagnostics (OBD-II)
• Etc.

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VII Architecture
Courtesy of Booz Allen Hamilton
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Probe Message Processes

• Periodic Data elements that are routinely
  available for collection (e.g. temperature and
  vehicle Speed)
• Event Data elements that are available on a
  irregular basis (e.g. ABS and traction
  control)
• Snapshot a collection of vehicle data elements
  (e.g. temperature, barometric pressure, etc.)
  valid at a specific time
• Periodic
• Event triggered
• Start/Stop
• Event triggered and start/stop snapshots have
  priority over periodic snapshots

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Potential Vehicle Data Elements
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Potential Vehicle Data Elements
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DaimlerChrysler Vehicle Data Elements andDetroit
(DTX) WSR-88D Data
Diagnosing Precipitation
2006-02-16 175452Z
2006-02-16 235452Z
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Weather Improvements Enabled by VII(some
examples)

• Identification of precipitation and type
• Improved delineation of freezing temperatures
• Improved localization of air temperature
• Improved identification of foggy regions
• Improved initialization of surface conditions for
  numerical models
• Reducing radar anomalous propagation
• Reducing false radar returns (e.g., virga)
• Improved knowledge of pavement temperature
• Improved knowledge of pavement conditions

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Radar Based Precipitation Identification

• False precipitation echoes are caused by
  temperature inversions (index of refraction
  gradients)
• Vehicle data (e.g., wiper settings) could be used
  to declare yes or no and be used to clean up
  the radar product.

Anomalous Propagation False Echoes
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Radar Based Precipitation Identification

• Virga (precipitation that does not reach the
  ground) fools DOT personnel who must make
  tactical decisions related to winter maintenance
  and traffic management.
• Vehicle observations (e.g., wiper settings) could
  verify the occurrence of precipitation which
  would be used to clean up the data.

Virga Precipitation not hitting the ground
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Identification of Foggy Regions

• The use of vehicle data (relative humidity, fog
  and head lamp settings, speed, and brake data)
  coupled with other data sets (e.g., satellite,
  surface analysis data) could be used to diagnose
  areas where fog is likely.
• This product concept is challenging!

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Improved High-Resolution Modeling

• As weather models increase in resolution,
  observations will need to increase as well to
  better define the regional/local state of the
  atmosphere.
• Vehicle observations can fill-in the gaps in the
  fixed observation network.
• Surface temperature, pressure, and water vapor
  are critical state variables

Data sparse regions
Weather occurs on very fine scales
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Defining Atmospheric Vertical Profiles

• Vehicle observations in complex terrain can
  provide important vertical information such as
• Freezing level (air temp)
• Cloud top
• Air temperature profiles
• RH profiles
• Road temperature profiles
• Vehicle data are like mini-soundings that could
  be used by models and to support tactical
  operations.

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Boundary Layer Characterization

• Vehicle data can be used to improve the
  characterization of the atmospheric boundary
  layer.
• This will improve the accuracy of
• Plume dispersion
• Air quality assessment

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Diagnosis of Precipitation and Type

• Currently, precipitation type is determined by
  airport observations (METARS) which are few and
  far between!
• Vehicle data (air temperature, and data from
  maintenance or patrol vehicles) would greatly
  improve product accuracy.

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Winter Maintenance Operations

• Vehicle data can be used to diagnose weather and
  road conditions and actual treatments.
• The resultant data could then be automatically
  used in decision support systems such as the
  winter Maintenance Decision Support System (MDSS)

Actual winter maintenance treatments
automatically entered into systems such as the
MDSS
Material Black Ice Road Condition Snow on
Road Weather
Winter maintenance vehicle data entry interface
and MDSS treatment screen.
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VII Research Needs

• Probe Message Processes
• Uptake Rates
• Data Processing
• Data Quality and Accuracy
• Quality Control
• Data Fusion
• Numerical Model Forecasts
• Human Factors

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Road Weather Impact Products

• VII enables tactical and strategic response to
  weather related surface transportation hazards.
• New weather and road condition data (incl. VII
  and Clarus data) should be integrated into a
  seamless information database(s) to support
• 511
• In-vehicle information
• Traveler information
• Highway operations
• Control systems
• Weather Prediction
• Road Condition Prediction
• Etc.

Improving Safety, Mobility and Efficiency