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Transcript of Applications of Weather Uncertainty Information – Transportation 2 nd OS&T Workshop on...
Applications of Weather Uncertainty Information – Transportation
2nd OS&T Workshop on Communicating Uncertainty and Decision Support
4-6 August 2009
Sheldon DrobotNCAR/RAL
Outline
Weather & TransportationThe Maintenance Decision Support System
(MDSS)IntelliDriveSM
Ensembles
Annual Fatalities
74740740074000
Safety
Poor weather conditions contribute to 7,400 deaths and 673,000 injuries in an average year
Mobility
554 million vehicle-hours of delay per year result from snow, ice, and fog
Efficiency
Delays to trucking companies range from $2.2-$3.5 billion annually
Greenhouse gas emissions
Transportation Trends
Surface transportation weather continues to gain national attention
Several road weather initiatives are in progress and new weather information product concepts are being developed
Improved Weather Information NeedsImproved Weather Information Needs Incident Management
Predicting problem areas Placement of response assets Faster cleanup
Construction Paving operations Striping Project scheduling
Emergency Management First responder support Traffic control Identifying impacted corridors
Things we know
Weather forecasts are inherently uncertainSome people want or are willing to receive
(some types of) uncertainty information
Things we don’t know
What kind of information do people want?How best to deliver that information to
people?There is no one “people”
Confidence vs. uncertainty?
Transportation Examples
What is the likelihood of precipitation between 3 PM and 6 PM?
What is the likelihood that the precipitation will be snow or rain or ice?
What is the likelihood that the pavement temperature will be between 30oF and 32oF?
How much confidence do you have in your forecast?
What is MDSS? Began in 1999 after a study discovered a disconnect
between road weather forecasts and the road maintenance community
The weather and transportation communities were brought together to define and develop a system that translates current and predicted road & weather information into recommended maintenance actions
Goal - improve the productivity and cost efficiency of transportation agencies
A prototype was built based on open system principles, which fostered an MDSS market by making that prototype freely available
What is MDSS?
Data IngestModule
Road Wx Forecast and Data Fusion
Module
Road Condition and
Treatment Module
Java-based Display
•Numerical model data•Road Weather Information System (RWIS) data•Miscellaneous observations (e.g., airport)
•Consensus forecast generation
•Road temperature and condition forecasts•Rules of practice for anti-icing and deicing operations•Treatment recommendations
•Delivery of information and data from upstream modules to end users via an interactive Graphical User Interface
Who is Using MDSS?
Prob/Uncertainty in MDSS
AlertsAlerts
Conditional Probabilities
Conditional Probability of Precipitation Type Product
MDSS declared precipitation type
Probability of Precipitation - Overall
Conditional probability of precipitation type
Confidence Cameras!
Forecast Use
The 2” snow forecastUsed by three entities (private road operator,
public road operator, airport authority) in entirely different ways
Highlights the importance of understanding user needs…not everyone needs/wants the same thing
What is IntelliDriveSM?
IntelliDriveSM is a suite of technologies and applications that use wireless communications
IntelliDriveSM applications provide connectivity: with and among vehicles between vehicles and the roadway infrastructure among vehicles, infrastructure, and wireless devices
(consumer electronics, such as cell phones and PDAs) that are carried by drivers, pedestrians, and bicyclists
http://www.intellidriveusa.org
Vehicle Data in IntelliDriveSM
Windshield WiperSetting
Head Lights Status
Sun/Rain Sensor
Antilock Braking System (ABS)
Traction Control
Adaptive Cruise Control (ACC)
Ambient AirTemperature
BarometricPressure
Brake StatusStability Control
Speed and Heading
Location and Elevation
Hours of Operation
http://www.intellidriveusa.org
VDT Data
RSAS data
Vehicle probe messages
Surface weather observations Source: NWS
Gridded radar data
Road segment statistics
Satellite cloud mask data
Precip Algorithm
The VDT
Vehicles measuring “Rain” and “Road Splash”
Is this right?
The AMS APT
AMS has convened an APT to look at mobile weather observations
Part of this will focus on user needs
One more thought
Take Home Points
We are losing lives, mobility, and money because of weather in transportation
Uncertainty/confidence information could have an enormous impact
The time is now
Sheldon DrobotNCAR/RAL