Highway Data Highway Data WorkshopWorkshopFebruary, 2010

Highway Data Services BureauHighway Data Services Bureau

New York State Department of TransportationNew York State Department of Transportation

50 Wolf Road, 3-250 Wolf Road, 3-2

Albany, New York 12232Albany, New York 12232

(518) 457-1965(518) 457-1965

Welcome back to theWelcome back to the……

THIS MORNINGTHIS MORNING

Functional Class Map ViewerFunctional Class Map Viewer Newest Data on the WebNewest Data on the Web Traffic Data Traffic Data

Analysis/ForecastingAnalysis/Forecasting– Project Level ForecastsProject Level Forecasts– Traffic Assignment ModelingTraffic Assignment Modeling– Vehicle Miles of TravelVehicle Miles of Travel

Functional Class Maps Functional Class Maps --A proposed approach for the next A proposed approach for the next updateupdate Old approachOld approach

– Static pdf imagesStatic pdf images Difficult to produceDifficult to produce Do not reflect subsequent approved changesDo not reflect subsequent approved changes

Proposed approachProposed approach– Functional Class ViewerFunctional Class Viewer

Based on an approved FC systemBased on an approved FC system Approved changes applied immediatelyApproved changes applied immediately Updated GIS files readily availableUpdated GIS files readily available

Functional Class Functional Class ViewerViewer Internet-based viewerInternet-based viewer Based on approved system as Based on approved system as

encoded in a GIS-based fileencoded in a GIS-based file Link to original approval documentLink to original approval document Revisions noted by link to approval Revisions noted by link to approval

memosmemos Revised GIS data regularly Revised GIS data regularly

distributeddistributed http://wvmoap22/fc/

Data on the WebData on the Web

Highway DataHighway Data Detailed Inventory ListingsDetailed Inventory Listings Functional Class MapsFunctional Class Maps Highway Mileage ReportHighway Mileage Report

Traffic DataTraffic Data Traffic Data ReportTraffic Data Report Hourly Traffic Volume FilesHourly Traffic Volume Files Reference and Factor FilesReference and Factor Files

Highway Data Services Highway Data Services BureauBureau

www.nysdot.gov

– A to Z Site IndexA to Z Site Index

Select “H” Select “H”

– Select “Highway Data Services Select “Highway Data Services Bureau”Bureau”

Other NYSDOT LinksOther NYSDOT Links

https://www.nysdot.gov/divisions/https://www.nysdot.gov/divisions/

policy-and-strategy/darb/dai-unit/policy-and-strategy/darb/dai-unit/ttssttss– FHWA/FTA approved Urban AreasFHWA/FTA approved Urban Areas– Census-based Urban AreasCensus-based Urban Areas– Metropolitan Planning AreasMetropolitan Planning Areas– Statewide Annual VMT since 1920Statewide Annual VMT since 1920

Other NYSDOT LinksOther NYSDOT Links

https://www.nysdot.gov/divisions/https://www.nysdot.gov/divisions/

policy-and-strategy/darb/dai-unit/policy-and-strategy/darb/dai-unit/ttssttss

Traffic Change in New York StateTraffic Change in New York State– Change in Traffic on NYS Bridges, Change in Traffic on NYS Bridges,

Thruway and Roads, January 2010Thruway and Roads, January 2010– Contains transit and other data as Contains transit and other data as

well as traffic datawell as traffic data

Other NYSDOT LinksOther NYSDOT Links

https://www.nysdot.gov/divisions/https://www.nysdot.gov/divisions/

operating/oom/transportation-operating/oom/transportation-systems/manualssystems/manuals– Qualifying and Access Highways Qualifying and Access Highways

(trucks)(trucks)– Touring Route BookTouring Route Book

https://www.nysdot.gov/divisions/https://www.nysdot.gov/divisions/

engineering/design/dqab/rmmengineering/design/dqab/rmm– Reference Marker ManualReference Marker Manual

Other NYSDOT LinksOther NYSDOT Links

https://www.nysdot.gov/main/https://www.nysdot.gov/main/bridgedatabridgedata– Bridge information (BIN, condition, location)Bridge information (BIN, condition, location)

http://gisweb2/strviewer/http://gisweb2/strviewer/– Viewer showing location of all bridges and Viewer showing location of all bridges and

culverts with condition ratings and postingsculverts with condition ratings and postings– Only available internally (Intradot)Only available internally (Intradot)

Potential RIS ViewerPotential RIS Viewer

Currently in developmentCurrently in development Hope to eventually offer via the Hope to eventually offer via the

InternetInternet Links RIS data to GIS, orthoimagery, Links RIS data to GIS, orthoimagery,

PhotologPhotolog Links from within RIS or directly Links from within RIS or directly

through viewer interfacethrough viewer interface

THIS MORNINGTHIS MORNING

Functional Class Map ViewerFunctional Class Map Viewer Newest Data on the WebNewest Data on the Web Traffic Data Traffic Data

Analysis/ForecastingAnalysis/Forecasting– Project Level ForecastsProject Level Forecasts– Traffic Assignment ModelingTraffic Assignment Modeling– Vehicle Miles of TravelVehicle Miles of Travel

An Overview of Traffic An Overview of Traffic Data Analysis & Data Analysis &

ForecastingForecasting

HDSB ForecastingHDSB Forecasting Current year estimatesCurrent year estimates

– Matrix processMatrix process– Traffic Data ForecasterTraffic Data Forecaster

HPMS HPMS – Current year estimatesCurrent year estimates– VMT estimatesVMT estimates

All based on linear regressionAll based on linear regression

US VMT Growth Since 1984US VMT Growth Since 1984

NYS VMT Growth Since 1920NYS VMT Growth Since 1920

Traffic Count DataTraffic Count DataWhat is collected

VolumeVolume Vehicle ClassificationVehicle Classification SpeedSpeed Weigh-in-MotionWeigh-in-Motion

Traffic Count StationsTraffic Count StationsWhere it is collected

COMPREHENSIVE COVERAGECOMPREHENSIVE COVERAGE State Highways/State SystemState Highways/State System National Highway System National Highway System All Other Federal Aid Eligible RoadsAll Other Federal Aid Eligible Roads

SEGMENT SPECIFICSEGMENT SPECIFIC Highway Performance Monitoring SystemHighway Performance Monitoring System NHS Intermodal ConnectorsNHS Intermodal Connectors Bridges, Railroad CrossingsBridges, Railroad Crossings Sampling of non-Federal Aid highwaysSampling of non-Federal Aid highways

County counting partnership, MPOsCounty counting partnership, MPOs

Traffic Count CoverageTraffic Count CoverageWhen it is collected

State Highways/State System – 3 yrsState Highways/State System – 3 yrs HPMS Samples – 3 yrsHPMS Samples – 3 yrs National Highway System – 3 yrsNational Highway System – 3 yrs

Including Intermodal ConnectorsIncluding Intermodal Connectors

Federal Aid eligible roads – 6 yrsFederal Aid eligible roads – 6 yrs Bridges, Railroad Crossings – 5 yrsBridges, Railroad Crossings – 5 yrs Sampling of non-Federal Aid roads – 6 yrsSampling of non-Federal Aid roads – 6 yrs Special needs – on demandSpecial needs – on demand

Traffic Count DataTraffic Count DataHow it is collected

Continuous versus short countsContinuous versus short countsContinuousContinuous

About 175 sitesAbout 175 sites Daily and other temporal patternsDaily and other temporal patterns Design hour volume factorsDesign hour volume factors

Short (coverage) countsShort (coverage) counts Large quantity at low costLarge quantity at low cost Stations covering about 30,000 Stations covering about 30,000

milesmiles

Some of the Data UsersSome of the Data UsersWhy it is collected

Internal Users of Traffic DataInternal Users of Traffic Data

Planners – MPOs, Policy & Planning Div.Planners – MPOs, Policy & Planning Div. AADT, hourly, quarter hourAADT, hourly, quarter hour CNAM, BNAM, PNAM, traffic assignment modelsCNAM, BNAM, PNAM, traffic assignment models

Designers – scope and scaleDesigners – scope and scale AADT, DHV/DDHV, % trucks, turn movesAADT, DHV/DDHV, % trucks, turn moves

Traffic Engineers – safety analysesTraffic Engineers – safety analyses Maintenance/Construction - MPOTMaintenance/Construction - MPOT

Some of the Data UsersSome of the Data UsersWhy it is collected

External UsersExternal Users

Air quality planners/researchersAir quality planners/researchers Transportation researchers - Transportation researchers - professors professors

& students, public & non-profit agencies& students, public & non-profit agencies Realtors/developersRealtors/developers LawyersLawyers Health researchersHealth researchers New York State PoliceNew York State Police

Available DataAvailable Data

AADT – Inventories, TDR, TDV, MatrixAADT – Inventories, TDR, TDV, Matrix Hourly – Interval data on InternetHourly – Interval data on Internet Class, Speed – reports on TDV, data Class, Speed – reports on TDV, data

files files on requeston request Adjustment factors – axle, “seasonal”Adjustment factors – axle, “seasonal” DHV, DDHV, K factor/d factorDHV, DDHV, K factor/d factor Vehicle Miles of TravelVehicle Miles of Travel

– HPMS estimates by FC by Urban AreaHPMS estimates by FC by Urban Area

Vehicle ClassificationsVehicle ClassificationsBased on axle spacing via speed with which tubes are crossedBased on axle spacing via speed with which tubes are crossed

1 Motorcycles1 Motorcycles 2 Passenger Cars2 Passenger Cars 3 Two axle, four tire trucks3 Two axle, four tire trucks 4 Buses4 Buses 5 Two axle, six tire5 Two axle, six tire 6-10 Single trailer, varying no. of 6-10 Single trailer, varying no. of

axlesaxles 11-13 Double trailer, varying axles11-13 Double trailer, varying axles

Vehicle ClassificationsVehicle Classifications

““Seasonal” adjustmentsSeasonal” adjustments - Monthly Variations - Monthly Variations

Use continuous counter dataUse continuous counter data

Calculate 12 monthly averages of Calculate 12 monthly averages of the daily traffic (MADT)the daily traffic (MADT)

Average 12 MADTs to get an Annual Average 12 MADTs to get an Annual Average of the Daily Traffic (AADT)Average of the Daily Traffic (AADT)

Ratio of each MADT to AADT gives Ratio of each MADT to AADT gives monthly factormonthly factor

““Seasonal” adjustmentsSeasonal” adjustments - Daily Variations - Daily Variations

Calculate using only weekdays (Mon to Fri Calculate using only weekdays (Mon to Fri noon)noon)

Calculate using only weekend trafficCalculate using only weekend traffic

Yields three sets of adjustment factorsYields three sets of adjustment factors– Full week or seven day, weekday, weekendFull week or seven day, weekday, weekend

Daily variations are “lost” in monthly Daily variations are “lost” in monthly calculationscalculations

Weekday factors most commonly usedWeekday factors most commonly used

Seven day factors show true “seasonality”Seven day factors show true “seasonality”

Factor GroupsFactor Groups Stations stratified into FG based on Stations stratified into FG based on

1980’s analyses1980’s analyses Minimal seasonality (commuter dominated)Minimal seasonality (commuter dominated) Some seasonalitySome seasonality Highly seasonalHighly seasonal

Even winter resorts show summer Even winter resorts show summer peakspeaks

Region 7 reassessment in late 1990’sRegion 7 reassessment in late 1990’s ““Flattening” of curvesFlattening” of curves NY metro area is “average” (FG = 30)NY metro area is “average” (FG = 30)

Design Hour VolumesDesign Hour Volumesand Directional Design Hour Volumesand Directional Design Hour Volumes

3030thth highest hour highest hour Used for scaling capital projectsUsed for scaling capital projects Continuous counters used to calculate Continuous counters used to calculate

DHV and DDHV factors (K and d)DHV and DDHV factors (K and d) Good for system analyses but Good for system analyses but

questionable for project levelquestionable for project level Site specific three-day high-hour Site specific three-day high-hour

versus ADT may give better project versus ADT may give better project resultsresults

Design Hour VolumesDesign Hour Volumesand Directional Design Hour Volumesand Directional Design Hour Volumes

3030thth highest hour is used as a result highest hour is used as a result of NCHRP studyof NCHRP study

Example: count station 26 0120 in Example: count station 26 0120 in UticaUtica

Highest Hour=Highest Hour= 39913991 3030thth Hour= Hour= 37803780 100100thth Hour= Hour= 36403640 200200thth Hour= Hour= 35233523

Design Hour VolumesDesign Hour VolumesK*d and K FactorsK*d and K Factors

Factor GroupFactor Group DDHVDDHV DHVDHV

3030 6.1%6.1% 10.2%10.2%

4040 6.7%6.7% 11.6%11.6%

6060 8.7%8.7% 14.2%14.2%

Vehicle Miles of TravelVehicle Miles of TravelHPMS Statewide EstimatesHPMS Statewide Estimates

Vehicle Miles of TravelVehicle Miles of TravelHPMS Urban Area EstimatesHPMS Urban Area Estimates

AIR QUALITY INPUTSTravel Speeds

Originally based on 1990 estimations of speedVehicle Miles of Travel

Should be “based on HPMS” traffic dataVehicle Classifications

Axle-based classifications collectedFuel and weight based data not field collected

Project Level Forecasts Basic techniques

Traffic Assignment Models Selected concepts & impact on forecasts

Vehicle Miles of Travel Estimates

HPMS estimates and ad hoc approaches

Design forecast needs Growth rates Using site specific traffic data

Turning movements MPT “forecasts”

Forecast parameters Historical traffic data Trend analysis Consistency with other forecasts

Constrained vs. Unconstrained Model coordination

Time frame Date of completion/opening of project Date of forecast life (design life) of project Complex projects may include multiple

Time frame Date of completion/opening of project Date of forecast life (design life) of project Complex projects may include multiple

Multiple forecasts No build Each build alternative

Different alternatives may result in differing forecast parameters

Time Frame Build/no-build forecasts % Trucks Awareness of design thresholds

Mainline Turn lane

Awareness of generators/constraints

Most typical forecasting approach Simple or compound

Simple: AADT x [1+(rate x # yrs)] Compound: AADT x (1+rate)exp[# yrs] Past patterns indicate Simple is most

realistic Generic or site-specific rates Rural Forecasting Method

Nathan Erlbaum, 457-2967

Very common is to assume 1 or 2% Trend line from specific station/stations Growth rates from Matrix/HPMS processes

Stratified by Region and Functional Class Generate a rate using Traffic Data

Forecaster Need for rigor depends on sensitivity of

project to variations in the forecasts

Growth rate of 1% per yearMatrix growth of 1.37%

Forecast ranges from ~31,000 to ~46,000 DDHV at 6% ranges from ~1600 to ~2800 Capacity for a multi-lane urban arterial is

about 800 vehicles/lane/hour2 lanes ~1600 3 lanes ~2400 4 lanes ~3200

This forecast could yield a need for a four, six, or eight lane arterial based on the assumptions

Which forecast do you use? ANSWER:

Use Your Professional Judgment

Use appropriate sites for source data

More data is better for trending Continuous count data is best

Generic DHV, DDHV factors used as default

Prefer site specific estimates of DHV, even with short counts

7-8 8-9 9-10 10-11

11-12

12-1 1-2 2-3 3-4 4-5 5-6 6-7 ADT

1343

1527

1086

1104

1227

1396

1413

1417

1730

1735

1712

1231

21895

644 734 626 644 787 756 743 782 901 1139

926 62011766

1987

2261

1712

1748

2014

2152

2156

2199

2631

2874

2638

1851

33661DHV factor 2874 / 33661 = 8.5%DDHV factor 1735 / 33661 = 5.1%Dir Split 1735 / 2874 = 60/40

AADT 30,050DHV 8.5% x 30050 = 2600 DDHV 5.1% x 30050 = 1530

Estimate of DDHV using generic 6%: 30,050 x 0.06 = 1800

Estimate of DDHV using short count high hour: 30,050 x 0.05 = 1500

Arterial capacity ~800/lane/hour Two lanes = 1600/hour

Capacity is a threshold value of concern

Factor Group 30, generic DDHV factor - 6%

High Hour/ADT factor from short count-5.1%

30th highest hr from adjacent cc site-5.2%

Needed data for Route 17 and a connecting County Road for the I-86 project Designers questioned the AADTs

Found continuous count stations on Route 17 near the project area

Used Monthly adjustment patterns from three local cc stations to adjust the ADT from Route 17 and CR counts to a new AADT estimate

Jan Feb Mar

April

May

June

July Aug

Sept

Oct Nov

Dec

FG40 0.8 0.8 0.9 0.9 1.1 1.1 1.2 1.2 1.1 1.0 0.9 0.8Avg 0.8 0.9 0.9 1.1 1.2 1.2 1.5 1.5 1.2 1.2 1.2 0.99631 0.8 0.9 0.9 1.1 1.3 1.2 1.5 1.6 1.3 1.2 1.3 0.99632 0.8 0.8 0.9 1.0 1.1 1.1 1.4 1.4 1.1 1.1 1.0 0.9

Not easy to project Use same proportions as in existing turn

count If 5% of traffic turns left today, assume 5%

left turns in future ….if it makes sense! Known growth patterns Known restrictions

May need alternative methods Trip generation, “professional judgment”

Maintenance and Protection of Traffic Require much more site & date specificity Require construction year estimates May need per lane volumes Required to determine volumes for

Detours Number of lanes Time of day for restrictions

Traffic Assignment Traffic Assignment ModelingModeling

Four Step ProcessFour Step Process Trip GenerationTrip Generation Trip DistributionTrip Distribution Mode ChoiceMode Choice Route AssignmentRoute Assignment

Traffic Assignment Traffic Assignment ModelingModeling Daily vs peak period modelingDaily vs peak period modeling Productions/attractionsProductions/attractions

ProductionsProductionsAttractionsAttractions

– AMAM HomeHome Work placeWork place– NoonNoon Home/workHome/work

Restaurants/shopsRestaurants/shops– PMPM Work/shopsWork/shops HomeHome

Trip GenerationTrip Generation

Productions/attractionsProductions/attractions– Census dataCensus data– Land use dataLand use data

““Trip Generation, 8th Edition: An Trip Generation, 8th Edition: An ITE Informational Report “ITE Informational Report “

Traffic Analysis ZonesTraffic Analysis Zones

Productions/attractions “loaded” Productions/attractions “loaded” at centroid of TAZsat centroid of TAZs

Centroids connected to networkCentroids connected to network Familiarity with TAZ structure and Familiarity with TAZ structure and

linkages could be critical to linkages could be critical to evaluation of model outputevaluation of model output

Traffic Analysis ZonesTraffic Analysis Zonesand Census Tractsand Census Tracts

Traffic Analysis ZoneTraffic Analysis Zone– Should focus around highwaysShould focus around highways

Census Blocks & TractsCensus Blocks & Tracts– Focus on boundaries of convenienceFocus on boundaries of convenience

Center of streetsCenter of streets RR linesRR lines Visible demarcationsVisible demarcations

Loading the NetworkLoading the Network

All or nothingAll or nothing Pre-loadPre-load IterativeIterative Constrained vs. unconstrainedConstrained vs. unconstrained

Calibration & Calibration & ImpedancesImpedances Calibrating to existing dataCalibrating to existing data ““Friction” based on attributesFriction” based on attributes

– Real or artificial impedancesReal or artificial impedances FFactors actors UUsed to sed to DDecrease ecrease GGaps in aps in

EEstimationstimation– Differences and RatiosDifferences and Ratios

NOCoTSNOCoTS New bridgeNew bridge

Use of Model OutputUse of Model Output

FHWA course – 5 full daysFHWA course – 5 full days Most useful for relative comparisonsMost useful for relative comparisons

– Between forecast yearsBetween forecast years– Between alternativesBetween alternatives– Between various pathsBetween various paths

Provides another tool in forecastingProvides another tool in forecasting Best use as systems analysis toolBest use as systems analysis tool

Vehicle Miles of Vehicle Miles of TravelTravel--HPMS VMT estimates--Air quality VMT estimates--Developing ad hoc estimates

What is it?

VMT = annual Vehicle Miles of Travel DVMT = Daily Vehicle Miles of Travel Sometimes seen as VDT (Vehicle Distance of

Travel) to make it unit neutral

It is an additive measure of cumulative travelAADT and other measures are actually rates

which are time and location dependent Use of VMT eliminates that dependency

VMT Estimation

VMT = AADT x segment lengthCan be calculated for State System where

traffic counts are relatively comprehensiveEstimated for non-State Federal aid eligible

highways within HPMS using Sample expansion

Stratified by Urban, Rural, Small Urban areas

VMT Accuracy

Within HPMS, accuracy is affected by Sample “adequacy” and quality of “current year estimates” of AADT

Local VMT is more challenging given the difficulty of measuring both baseline traffic and growth

HPMS Sample Domains

Rural – 406 Samples statewide Small Urban – 395 Samples statewide Urbanized – # Samples for each area:

345 New York 76 Elmira

218 Buffalo 201 Poughkeepsie/Newburgh

195 Rochester 60 Glens Falls

208 Albany 43 Ithaca

172 Syracuse 45 Kingston

152 Utica 37 Saratoga Springs

136 Binghamton

Stratification

By Volume Group By Functional Class

Albany Urban Area – 208 Samples

FC Samples

11 44

12 23

14 47

16 41

17 53

VMT Estimation

AADT x length to calculate VMT for Samples

For each Sample Domain / FC / Volume Group, Expansion Factor =

Total length / Sample length VMT Estimate = Sample VMT x Exp Factor Sum VMT Estimates

HPMS VMT Estimation

Entire VMT estimation for Federal Aid roads is based on Sample data (all other traffic counts ignored)

Non-Federal Aid VMT (FC 08, 09, 19) based on adjustment of prior year VMT estimate

HPMS VMT Estimation

Used to be based on adjustments to meet a statewide total VMT estimate

Changed to Sample expansion with assignment of residual then adjustment of residual

Will be changed to full calculation of Federal Aid VMT … if we have the counts

Vehicle Miles of TravelVehicle Miles of Travel

Vehicle Miles of TravelVehicle Miles of Travel

HPMS VMT Estimation

Based on Current Year Estimates Current Year Estimates derived from

Matrix process Matrix process is a 15 year straight line

regression analysis Does not reflect short term changes, but

should it? Depends on purpose

AIR QUALITY INPUTSTravel Speeds

Originally based on 1990 estimations of speed

Vehicle Miles of TravelVehicle Miles of TravelShould be “based on HPMS” traffic dataShould be “based on HPMS” traffic data

Vehicle ClassificationsAxle-based classifications collectedFuel and weight based data not field collected

AIR QUALITY INPUTSTraffic data HPMS VMT estimatesGlobal Insight model output

Time series models using HPMS VMT and socio-demographics to produce urban area forecasts

National Household Travel Survey (NHTS)Estimates of VMT and urban area trip ratesSurveys conducted in 1995, 2001, 2009

AIR QUALITY INPUTSContacts

Nathan Erlbaum, System Performance & Asset Management Bureau 518-457-2967, NErlbaum@dot.state.ny.us

Patrick Lentlie, Office of the Environment518-457-0212, Plentlie@dot.state.ny.us

Uses of VMT Estimates

Planners for estimation of future growth in traffic and in economy

FHWA for funding allocationsNational Highway Traffic Safety Admin for

safety funding allocationsNYSDOT internally for funding distributionsOutside groups to estimate air quality, health,

economic, and travel impacts

Uses of VMT Estimates

Some of these uses require different stratifications than those produced via HPMS

No other “official” VMT estimates are produced by NYSDOT (except those required for Air Quality)

Ad Hoc Estimates of VMT

Requires: All available AADT data Length of system counted Total length of system

Source: Inventory spreadsheets on Internet Other HDSB resources

Highly dependent on stratification for expansion

Example – FC 16, Albany County

Expand with no stratification: Total Mileage – 114 Mileage with AADT – 58 VMT on counted roads – 580,139

580,139 x 114/58 = 1,142,874 VMT

7.6 miles contain HPMS Samples

Example – FC 16, Albany County

Expand stratified by Muni Type:

Unstratified Cities Towns Villages Total

Total Miles 113.9 46.6 60.0 7.4 113.9

Miles counted 57.8 14.9 37.4 5.5 57.8

VMT counted 580,139 135,186 380,244 64,709 580,139

Exp Factor 1.97 3.13 1.60 1.35 --

Expanded VMT 1,142,874 423,132 228,146 87,357 738,635

Stratification

Note: HPMS stratifies by Volume Group which I did not do here

Stratifying by Muni Type illustrates the variability in estimation approach

Similarly, stratification by Functional Class has been shown to yield large variations

Including Volume Group stratification seems to be the best approach

Recommendations

Stratify by several different parameters to see if converge

Include Volume Group as one of the stratification parameters

Check stratification by various parameters against HPMS values for the same Sample domains

Use professional judgment