NCAR

Winter Road Maintenance Decision SupportSystem (MDSS) Prototype Development

Presented by

Bill Mahoney

National Center for Atmospheric Research

MDSS Objective

To utilize state-of-the-art atmospheric scienceand engineering approaches to address andimprove theperformanceof the roadmaintenancepractitioner.

Current Capabilities and Practice

The highway maintenance managers currently usenewspapers, Weather Channel, USA Today, NWS, andprivate meteorologists to make decisions.

Road weather informationsystems are not integratedwith road managementsystems. The winter roadmaintenance decisionprocess is generallyreactive in nature.

MDSS Goals

• Capitalize on existing road weather data sources.

• Augment data sources wherethey are weak.

• Fuse data to make anintegrated andunderstandable presentationof road conditions.

• Provide diagnostic and prognostic information.

MDSS Goals (continued)

• Provide display capability for the conditionof the roadway.

• Develop a decision support tool that providesrecommendations on road maintenancecourses of action together with anticipatedconsequences of action or inaction.

• Provide all the above on a single platform.

Maintenance Decision Support System (MDSS) Project

MITLincoln Lab

Bob Hallowell

Federal Highways Administration (FHWA)Office of Transportation Operation (HOTO)

Paul PisanoRudy Persaud

Mitretek Systems

Gary Nelson

Cold Regions Research & Engineering Lab (CRREL)MDSS Programmatic Lead Lab

George Blaisdell (Project Mgr.)

National Centerfor Atmospheric Research (NCAR)

MDSS Technical Lead Lab

Bill Mahoney (Project Mgr.)Rich Wagoner (Oversight)

Multiple Contracts

Single Contract

NOAANational Severe

Storms Lab

John Cortinas

NOAAForecast Systems

Lab

Paul Schultz

NOAAEnvironmentalTechnologies

Lab

Dan Wolfe

Project Schedule

FY2000: Requirements AnalysisTechnology Review by Labs

FY2001: Conceptual Prototype Development(storyboard concepts & user feedback)

FY2002: Functional Prototype DevelopmentDemonstrationDocumentationTechnology Release

MDSS Project Constraints

• Development period: 2-Years• Development resources: $1.8M• System complexity: Multiple Labs

• Maturity of core components• Operational data availability and integration• Disparity in user requirements• Complicated validation process• Complicated technology transfer process

MDSS Schedule

Rapid Prototypingand Testing

Testing, Advice,Direction

FY 00 Award(Prototype)Award= $900,000

9/30/00 9/30/01 9/30/02 9/30/03FY01 FY02 FY03

DevelopmentPlan:Award + 30 days

ConceptualPrototype

Various Developmentand Operational Test Options

VAMSDOTs

CommercialDeployment

9/30/04

Further Releases?

Ongoing Stakeholder Participation/Operation

Release 1

MDSS Functional PrototypeComponents

MDSS Prototype Components

WeatherData

AdvancedWeather

Capabilities DecisionSupport

Logic

Display

DOT Operations Data

RoadCondition

Module

External SystemInterface

MDSS Prototype Focus Areas

Weather Component Focus :

• Event start and stop times• Surface temperature• Precipitation type• Precipitation rate• Precipitation accumulation• Conditional probabilities• Surface wind speed• Surface wind direction• Surface visibility

MDSS Prototype Focus Areas

Road Component Focus:

• Pavement temperature and trends• Pavement chemical concentration• Road mobility index• Pavement contamination(liquid, snow, ice, etc.)

MDSS Prototype Focus Areas

Decision Support System Component Focus:

• Monitor weather & road conditions• Monitor probability & intensity of weather threat• Treatment options & timing• Crew scheduling & managing crew shifts• Dispatch crews to treat roadway• Post event clean up

Translation of Environmental Data to RoadCondition Information

Environmental Data

Road condition information providedat user configurable locations along the road.

Road condition algorithmsconvert environmentaldata at road points

MDSS Functional Prototype Components

Road Weather Forecast System - NCAR

Precipitation Type - NSSL

Rules of Practice Module – CRREL & LL

Maintenance Decision Support System

Ensemble ForecastingFSL

Mesoscale Weather ModelsFSL/NSSL

Eight primary components

Road Chemical Concentration - CRREL

Road Mobility Index - CRREL

Road Surface Temperature - CRREL

Engineering Approach for MDSS

Eta ModelMRF ModelAVN ModelNGM MOSSatelliteMETARSRadar MosaicSYNOPLightning

DICAST Processor Wx Output:

Wind SpeedWind DirectionRHAir TempPrecip RatePrecip TypeLightningRadar MosaicVisibilityDew PointPrecip AccumCloud CoverInsolationNWS Advisories

NWS AdvisoriesOthers TBD

Road Condition Module:

Road FrictionRoad TemperatureSnow Drift

DSS Processor

Display

Demonstration

Data Interface to External Systems

Pass through Data

DOT “Wx” Data:

Video ImagesESS (Wx stations)

DOT Ops Data:

StaffEquipmentTreatment StocksTraffic DensityTraffic SpeedPavement Characteristics

Others TBD

DataIngest

Forecast Module A

Forecast Module B

Forecast Module C

Forecast Module D

Forecast Module N

.

.

.

Integrator

PostProcessing

ForecastProduct

Standard Wx Data

Ensemble Forecasts

Rules of PracticeModule

“NOAA”Weather Data

DOT Wx Data

DOTOperations

Data

Road ConditionModule

Rules of Practice

Decision Support

BrowserDisplay

Internet - Intranet

.

.

.

DataIngest

Forecast Module A

Forecast Module B

Forecast Module C

Forecast Module D

Forecast Module N

ForecastIntegrator

PostProcessor

ForecastProduct

WeatherParameter

Output

Point & TimeSpecificOutput

Road Weather Forecast System

Functional Prototype - Cycles

The functional prototype will operate in threeprimary modes:

1) Provide results with no maintenance actions.

2) Provide results based on automatedmaintenance recommendations (rules ofpractice).

3) Allow user to modify maintenancerecommendations.

MDSS Functional PrototypeSystem Flow

RWFS[Point/Beat Specific]

Road TempSnow Depth

ChemicalConcentration

Snow Depth&

Chemicals

ChemicalApplication

Net RoadMobility

Rules ofPractice

Accept?Yes

No

edit

Plow

New RoadState

MDSS Component Overview

National Center for Atmospheric ResearchResearch Application Program

NCAR/RAP

Road Weather Forecast System

Sample Environmental Prediction Sites

All observationalweather data arenecessary to improveforecasts!

The system will bedesigned utilize alldata availableincluding: DOT, NWS,DoD, air quality, andhydrology networks.

Environmental prediction parameters will begenerated along the road.

The Road WeatherForecast Systemwill generate pointspecific forecastsof environmentalparameters alongroad corridors.

Example: Precipitation Type

MDSS

Snow depthAccumulation

MDSS

Single PointTime Series

Mesoscale Modeling&

EnsembleForecast System

NOAAForecast Systems Laboratory

&National Severe Storms Laboratory

Forecast Systems LaboratoryEnsemble Forecasting

Models:

EtaMM5RAMS

Initialization:

AVNEtaRUC

9-MemberOutput

RoadWeatherForecastSystem

Cold Regions Research and EnvironmentalLaboratory

CRREL

CRREL - Salt Concentration Model

Illustrates thesensitivity of saltconcentration withtime during apredicted weatherevent for multipletreatment options.

0 6 12 18 24 30 36 42 48

TIME, HOURS

0

5

10

15

20

25

30

35

SA

LTC

ON

CE

NT

RA

TIO

N,P

ER

CE

NT

BY

WE

IGH

T

0

10

20

30

40

PA

VE

ME

NT

TE

MP

ER

AT

UR

E,D

EG

RE

EF

AH

RE

NH

EIT

RainSnowOne time 400 lb/lane mi100 lb/lane mi @ 3 hrs250 lb/lane mi @ 6 hrs400 lb/ln mi and 100 @ 3hrs

Fully Saturated Solution

Ice-SolutionPhase Line

Pavement Temperature

MidnightWednesday

MidnightTuesday

MidnightThursday

Two-Day Friction Coefficient HistoryWith and Without Treatment

Prediction Point #3F

rict

ion

Co

effi

cien

t

3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

Time Since Awareness (hrs)

0

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

RecommendedMaintenance Efforts

Level of Service 1

CRREL

No Treatment

3:30 am

3:30 am

3:30 am

3:30 am 3:15 am

3:15 am

B

C

A

4:00 am

4:00 am

RoundRoad

15INTERSTATE

17

17

15INTERSTATE

!

CrewTrucksMaterial StocksTruck Routes

StandardCustom

Road StatusLogistics Matrix

!!

Roads Overlays Treatments TimeLine Resources

Game Plan

Sample: Route Specific Guidance

Treat. Start TimeCall @ Route Segment Driver Truck ID Dress & Load Treat. Rate/TLM

9:00 pm Monday midnight Mon/Tue 3 :15 am TuesdayA 2,3,4 Sam Salter Mack X NaCl, pw-8g. CaCl 400 lbs

Notes: Drive reverse route

9:00 pm Monday 1:00 am Tuesday 3:15 am TuesdayC 8,9,10 Polly Plowgirl Mack Z Sand (ballast) Plow only

9:00 pm Monday 1:30 am Tuesday 3:30 am TuesdayB 6,7 Gary Grippy Mack Y Seg. 7: Sand 1200 lbs

Notes: Ford Seg. 6: NaCl 400 lbs

BASED ON RECOMMENDED TREATMENTS

Material Stocks

11 tons to be usedinitial treatment

5 tons to be usedinitial treatment

30 gallons to be usedinitial treatment

10 tons

40 tons

250 gallons

120 tons

Engine blown

NaCl

CaCl

CaCl liquid

Abrasives

RoundRoad

15

17

17

15

Roads Overlays Treatments TimeLine Resources

Game Plan – Initial

What are the special features of the MDSS?

Special Features of the MDSS

• Takes advantage of standard & road weather sensor datavia intelligent data integration.

• Utilizes an automated, high resolution forecast systemwith advanced data fusion techniques.

• Merges environmental & operational data within the DSS.

• Provides decision guidance in decision space andprovides recommended courses of action and allowsusers to evaluate other courses of action.

MDSS Technology Applications

Winter Maintenance

Emergency Management

Traffic Management

Hurricane Evacuation

Weed SprayingSweeping Operations

Controlled Burns

Public Notification

Pavement Marking

Paving Operations

Warning Preparation

MDSS CoreTechnology

Summary

The MDSS Project is an ambitious project that posesseveral challenges and risks.

Road weather initiatives requirenew and augmented researchand development activities andthe application of new techniques.

The meteorological communitymust also become smarter on theneeds of the road maintenancemanager as they pertain toweather related decision making.