Applications of Weather Uncertainty Information – Transportation

2nd OS&T Workshop on Communicating Uncertainty and Decision Support

4-6 August 2009

Sheldon DrobotNCAR/RAL

drobot@ucar.edu

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

drobot@ucar.edu