September 2007Travel Forecasting for New Starts2-1 6. Standard Reporting/QC FTA requirements for New...

September 2007September 2007 Travel Forecasting for New StartsTravel Forecasting for New Starts 2-2-11

6. Standard 6. Standard Reporting/QCReporting/QC

FTA requirements for New StartsFTA requirements for New Starts ImplementationImplementation Thoughts on good practiceThoughts on good practice


FTA RequirementsFTA Requirements

Standard Summit reportsStandard Summit reports– No-Build (2030) versus “today”No-Build (2030) versus “today”– TSM alternative versus No-buildTSM alternative versus No-build– Build alternative versus TSM alternativeBuild alternative versus TSM alternative– Build opening year versus “today”Build opening year versus “today”

QC reportsQC reports– Tests on (1) project and (2) IVTTests on (1) project and (2) IVT– Template on “Travel Forecasts”Template on “Travel Forecasts”

Transit assignment resultsTransit assignment results

*

* = new in 2008

*

*

*


PurposePurpose

Enable routine quality controlEnable routine quality control Support a coherent story for the Support a coherent story for the

projectproject– How is 2030 different from today?How is 2030 different from today?– What would TSM accomplish?What would TSM accomplish?– How much more would the project do?How much more would the project do?– What would the project do in its What would the project do in its

opening year?opening year?


Changes over Time:Changes over Time:ReportsReports No-Build versus TodayNo-Build versus Today Build Opening Year versus TodayBuild Opening Year versus Today

1.0 Demographics1.0 Demographics

2.0 Travel patterns 2.0 Travel patterns

3.0 Travel times 3.0 Travel times

4.0 Transit trips 4.0 Transit trips

5.0 Transit shares5.0 Transit shares


1.0 Demographics1.0 Demographics

General formatGeneral format– By districtBy district– Totals, absolute delta, relative deltaTotals, absolute delta, relative delta

ContentsContents

1.1 Population characteristics1.1 Population characteristics

1.2 Employment characteristics1.2 Employment characteristics

1.3 Supporting statistics1.3 Supporting statistics


Supporting StatisticsSupporting Statistics

Relationships between variablesRelationships between variables– Household size, workers per person, Household size, workers per person,

densities, parking costs, pop/emp densities, parking costs, pop/emp ratio, etc. ratio, etc.

Checks on trip generationChecks on trip generation– ΔΔ p population versus opulation versus ΔΔ trip productions trip productions– ΔΔ employment employment versus versus ΔΔ trip trip

attractionsattractions


2.0 Person Trips2.0 Person Trips

General formatGeneral format– District-to-district District-to-district – Totals, absolute delta, relative deltaTotals, absolute delta, relative delta

ContentsContents2.1 Total person trips2.1 Total person trips

2.2 Home-based work person trips2.2 Home-based work person trips

2.3 Other person trips (as needed)2.3 Other person trips (as needed)


3.0 Travel Times3.0 Travel Times

General formatGeneral format– District-to-district District-to-district – Peak and off-peakPeak and off-peak– Averages, relative delta Averages, relative delta

ContentsContents3.1 Highway travel time3.1 Highway travel time3.2 Transit in-vehicle time3.2 Transit in-vehicle time3.3 Transit total weighted time3.3 Transit total weighted time


Travel Time Travel Time CalculationsCalculations CalculationsCalculations

– District-to-district aggregation of skimsDistrict-to-district aggregation of skims– Divided by district-to-district I-J cells Divided by district-to-district I-J cells

ImpedancesImpedances– Highway: drive-alone timeHighway: drive-alone time– Transit: “best” walk access pathTransit: “best” walk access path– Transit cells: Transit cells: path available in both path available in both

yearsyears


4.0 Transit Trips4.0 Transit Trips


ContentsContents4.1 Total transit trips (all modes)4.1 Total transit trips (all modes)

4.2 Home-based work transit trips4.2 Home-based work transit trips

4.3 Other transit trips 4.3 Other transit trips (as needed)(as needed)

4.4 Guideway trips (by purpose, 4.4 Guideway trips (by purpose, as as neededneeded))


5.0 Transit Shares5.0 Transit Shares


ContentsContents5.1 Home-based work transit shares5.1 Home-based work transit shares

5.2 Other transit shares 5.2 Other transit shares (as needed)(as needed)

5.3 Guideway shares (by purpose, 5.3 Guideway shares (by purpose, as as neededneeded))


Changes between Changes between Alternatives:Alternatives:ReportsReports TSM versus No-BuildTSM versus No-Build Build versus TSMBuild versus TSM Contents for Contents for eacheach mode choice mode choice

runrun1.0 Transit trips1.0 Transit trips

2.0 User benefits2.0 User benefits


1.0 Transit Trips1.0 Transit Trips

General formatGeneral format– District-to-districtDistrict-to-district– Totals, absolute delta, relative deltaTotals, absolute delta, relative delta

Contents for each mode choice runContents for each mode choice run1.1 Transit trips1.1 Transit trips

1.2 Transit trips by “transit 1.2 Transit trips by “transit dependents”dependents”

1.3 Guideway transit trips (as needed)1.3 Guideway transit trips (as needed)


2.0 User Benefits2.0 User Benefits

General formatGeneral format– District-to-districtDistrict-to-district

Contents for each mode choice runContents for each mode choice run2.1 Total user benefits2.1 Total user benefits

2.2 User benefits accruing to “transit 2.2 User benefits accruing to “transit dependents”dependents”


2.0 User Benefits 2.0 User Benefits (cont.)(cont.)

2.3 User benefits accruing to “base” 2.3 User benefits accruing to “base” ridersriders ““Base” = TSM for 2030 Build versus TSMBase” = TSM for 2030 Build versus TSM ““Base” = No-Build for 2030 TSM versus Base” = No-Build for 2030 TSM versus

No-BuildNo-Build

2.4 “Base” riders’ share of user benefits2.4 “Base” riders’ share of user benefits

2.5 Negative user benefits2.5 Negative user benefits

2.6 Negative user benefits as a share of 2.6 Negative user benefits as a share of totaltotal


2.0 User Benefits 2.0 User Benefits (cont.)(cont.)

2.7 Stratified tables2.7 Stratified tables Build alternative transit trips by change in Build alternative transit trips by change in

transit price, separately for CW-CW and MD-MDtransit price, separately for CW-CW and MD-MD

2.8 Frequency distributions 2.8 Frequency distributions Build transit trips by change in transit priceBuild transit trips by change in transit price User benefits by change in transit priceUser benefits by change in transit price All eight (8) access combinationsAll eight (8) access combinations

2.9 Thematic maps of user benefits by zone 2.9 Thematic maps of user benefits by zone for (1) productions and (2) attractionsfor (1) productions and (2) attractions


Quality ControlQuality Control

Summit QC impacts in 2002Summit QC impacts in 2002– Errors in modelsErrors in models– Errors in service plansErrors in service plans– Errors in transit network codingErrors in transit network coding– Base|Build coverage inconsistenciesBase|Build coverage inconsistencies

FTA analysesFTA analyses– User benefits unrelated to the projectUser benefits unrelated to the project– User benefits other than transit IVT deltasUser benefits other than transit IVT deltas

routine

case by case


Quality Control Report Quality Control Report 11 Share of UBs directly related to Share of UBs directly related to

projectproject1.1. Best paths by transit access (walk, drive)Best paths by transit access (walk, drive)

2.2. UBs based on local models & best pathsUBs based on local models & best paths

3.3. I-J cells with path on the project (0/1)I-J cells with path on the project (0/1)

4.4. UBs in I-J cells with project pathsUBs in I-J cells with project paths

5.5. Project UB share = step4 UBs / step2 UBsProject UB share = step4 UBs / step2 UBs

Summit district-to-district reportsSummit district-to-district reports Project UB share < 80% Project UB share < 80% ‘splaining ‘splaining


Quality Control Report Quality Control Report 22 Share of UBs caused by Share of UBs caused by ΔΔ transit transit

IVTIVT6.6. With best paths from Report 1: replace With best paths from Report 1: replace

guideway-path IVT with IVT from baseline guideway-path IVT with IVT from baseline alternativealternative

7.7. Rerun mode choice and SummitRerun mode choice and Summit

8.8. IVT UB share = step2 UBs / best-path UBsIVT UB share = step2 UBs / best-path UBs

Summit district-to-district reportsSummit district-to-district reports ΔΔIVTIVT share < 80% share < 80% ‘splaining ‘splaining


Example: Example: Honolulu Fixed Honolulu Fixed GuidewayGuideway


Travel Forecast TemplateTravel Forecast TemplateInputs by Trip PurposeInputs by Trip Purpose

Daily transit trips, base and buildDaily transit trips, base and build Daily person trips (base = build)Daily person trips (base = build) Daily hours of user benefits (UBs)Daily hours of user benefits (UBs) Positive UB hours from coverage changesPositive UB hours from coverage changes

– MD-CW, NT-CW and NT-MD groupsMD-CW, NT-CW and NT-MD groups Daily hours of UBs changed by cappingDaily hours of UBs changed by capping Daily hours of UBs for transit dependentsDaily hours of UBs for transit dependents


Travel Forecast TemplateTravel Forecast TemplateInputs for Special MarketsInputs for Special Markets

Project trips per event dayProject trips per event day UB hours per event dayUB hours per event day Transit passenger miles per event dayTransit passenger miles per event day Number of event days per yearNumber of event days per year


Travel Forecast TemplateTravel Forecast TemplateOther InputsOther Inputs

Daily project tripsDaily project trips– Standard purposes, no special marketsStandard purposes, no special markets– Lowest socio-economic class Lowest socio-economic class

(representation of transit dependents)(representation of transit dependents) Daily project passenger milesDaily project passenger miles

– Standard purposes, no special marketsStandard purposes, no special markets– Transit dependentsTransit dependents

Project length (miles)Project length (miles) Annualization factor (days/year)Annualization factor (days/year)


Travel Forecast TemplateTravel Forecast TemplateOutputs-Standard Outputs-Standard PurposesPurposes Daily new transit tripsDaily new transit trips

– % distribution of total new transit % distribution of total new transit tripstrips

% distribution of daily UBs% distribution of daily UBs % distribution of daily baseline transit % distribution of daily baseline transit

tripstrips % UBs lost to capping% UBs lost to capping % UBs accruing to lowest socio-% UBs accruing to lowest socio-

economic classeconomic class


Travel Forecast TemplateTravel Forecast TemplateOutputs-Special MarketsOutputs-Special Markets

% distribution of total new special-% distribution of total new special-market annual transit tripsmarket annual transit trips

% distribution of total special-market % distribution of total special-market annual UBsannual UBs

Minutes of UBs per project tripMinutes of UBs per project trip


Travel Forecast TemplateTravel Forecast TemplateOutputs-Quality Control Outputs-Quality Control ChecksChecks Minutes of UBs per daily project tripMinutes of UBs per daily project trip

– Before cappingBefore capping– After cappingAfter capping

% UBs coverage related% UBs coverage related % UBs from special markets% UBs from special markets % of project trips that are new transit % of project trips that are new transit

tripstrips Project’s average trip distance / project Project’s average trip distance / project

lengthlength


Transit Assignment ResultsTransit Assignment Results

Production/attraction formatProduction/attraction format Total riders (linked trips) and Total riders (linked trips) and

boardings (unlinked trips) by modeboardings (unlinked trips) by mode Guideway station ONs and OFFs by Guideway station ONs and OFFs by

direction and mode of accessdirection and mode of access Directional transit rider load Directional transit rider load

volumes between stationsvolumes between stations Station to station transit ridersStation to station transit riders


Ons, Offs, and Load Ons, Offs, and Load VolumesVolumes


Mode of Access by StationMode of Access by Station


Thoughts on Good Thoughts on Good PracticePractice Boundaries for summary districtsBoundaries for summary districts Changes over timeChanges over time Changes between alternativesChanges between alternatives Thematic mapsThematic maps Desire-line plotsDesire-line plots


Summit DistrictsSummit Districts

Generally, between 15 and 20 for Generally, between 15 and 20 for reportingreporting

Smaller near project; larger elsewhereSmaller near project; larger elsewhere Thematic maps of UBs Thematic maps of UBs district district

boundariesboundaries Corridor (for making-the-case discussion)Corridor (for making-the-case discussion)

– Aggregations of districtsAggregations of districts– Perhaps immediate and broader corridorsPerhaps immediate and broader corridors

Different structures for special analysisDifferent structures for special analysis


Changes over TimeChanges over Time

Identify/justify very high or very low % Identify/justify very high or very low % changeschanges

Comparisons to observed growth trendsComparisons to observed growth trends Roadway and transit supply checksRoadway and transit supply checks Roadway and transit speed checksRoadway and transit speed checks Transit passenger PMT and PHT checksTransit passenger PMT and PHT checks


Changes between Changes between AlternativesAlternatives

Identify/justify large changes in zone to Identify/justify large changes in zone to zone mode shareszone mode shares

Examine zone-to-zone pairs with major Examine zone-to-zone pairs with major negative user benefits or high “per negative user benefits or high “per rider” positive user benefitsrider” positive user benefits


Thematic MapsThematic Maps

Zonal population, employment, trip end Zonal population, employment, trip end and transit mode share changesand transit mode share changes

User benefits per impacted transit trip User benefits per impacted transit trip production or attractionproduction or attraction

Percent of zone’s transit riders with a Percent of zone’s transit riders with a change in user benefitschange in user benefits

Positives separate from negativesPositives separate from negatives


Desire Line PlotsDesire Line Plots

District-to-district “bandwidth” lines for District-to-district “bandwidth” lines for those pairs representing 25, 50, and those pairs representing 25, 50, and 75% of all user benefits75% of all user benefits

District-to-district lines for those pairs District-to-district lines for those pairs with some zone-to-zone negative with some zone-to-zone negative benefitsbenefits


7. Lifting the Cap7. Lifting the Cap

FTA requirements for New StartsFTA requirements for New Starts BackgroundBackground Analytical approach to adjusting Analytical approach to adjusting

the capthe cap



Cap on per-trip Cap on per-trip transittransit user benefits user benefits– Applied to CW-CW and MD-MD trips I-JApplied to CW-CW and MD-MD trips I-J– (“Off-diagonal” UBs handled separately)(“Off-diagonal” UBs handled separately)– Standard cap = Standard cap = ±45 ±45 weightedweighted minutes minutes

FTA adjustment of capFTA adjustment of cap– Case-by-case considerationCase-by-case consideration– Based on demonstration of actual Based on demonstration of actual

project benefits > 45 weighted project benefits > 45 weighted minutes/tripminutes/trip


BackgroundBackground

The creature from the swamp – 2002 The creature from the swamp – 2002 – Early Summit testing of 12-15 projectsEarly Summit testing of 12-15 projects– Large problems with Large problems with mostmost forecasts forecasts

Model properties (bizarre guideway Model properties (bizarre guideway constants)constants)

Alternatives (inconsistent baselines)Alternatives (inconsistent baselines)

– Prospect of few rated projects in 2002Prospect of few rated projects in 2002– ““Cap” to salvage Cap” to salvage somesome project ratings project ratings

Model-related problems Model-related problems large UB/trip large UB/trip No pending New Starts decision No pending New Starts decision

X



Near-term applicationNear-term application– Adjust/remove cap where appropriateAdjust/remove cap where appropriate– CriteriaCriteria

Large project-caused user benefits per tripLarge project-caused user benefits per trip Absence of large spurious benefitsAbsence of large spurious benefits

Longer-term FTA aspirationLonger-term FTA aspiration– The swamp dries upThe swamp dries up– The creature moves awayThe creature moves away Soon?


Analytical ApproachAnalytical Approach

Sources of benefitsSources of benefits– Based on best paths, Base and BuildBased on best paths, Base and Build– Computation of time savingsComputation of time savings

TSTStottot = build transit trips x (imped = build transit trips x (impedbas bas – – impedimpedbldbld))

TSTSivt ivt = build transit trips x (IVT= build transit trips x (IVTbasbas – IVT – IVTbldbld) ) where:where: imped = total weighted imped = total weighted

impedanceimpedance

IVT = in-vehicle timeIVT = in-vehicle time



Inspection of time savingsInspection of time savings– Total versus IVT-causedTotal versus IVT-caused– Fraction on I-J paths on projectFraction on I-J paths on project– D-to-D trips with large per-trip time D-to-D trips with large per-trip time

savingssavings– Detailed analysis of illustrative pathsDetailed analysis of illustrative paths

Anticipated outcomeAnticipated outcome– ΔΔIVT IVT usuallyusually the cause of most benefits the cause of most benefits– Project in path for most benefitsProject in path for most benefits



∞∞

9090

7575

6060

4545

3030

1515

1515 3030 4545 6060 7575 9090 ∞∞

Time Savings: Total versus In-Vehicle Time

Delta IVT

(min.)

Delta Total Weighted Time (min)

capOK

Requires explanation

May need explanation

May need some clean-up

Distribution of time savings across cells determines course of action



ImplementationImplementation– Custom-written programsCustom-written programs– Reporting features of forecasting Reporting features of forecasting

software?software?– SummitSummit

Track record on cap increasesTrack record on cap increases– Largely IVT-caused: yes increased for allLargely IVT-caused: yes increased for all– Largely service-policy caused: noLargely service-policy caused: no– Largely walk/xfer caused: yesLargely walk/xfer caused: yes


Example: NY East-Side AccessExample: NY East-Side Access– Long Island RailroadLong Island Railroad– Now: to Penn Station onlyNow: to Penn Station only– Project: also to Grand Central StationProject: also to Grand Central Station– Analysis Analysis No cap No cap

~All 45+minute changes to east side~All 45+minute changes to east side ~All had much shorter walks, many fewer xfers ~All had much shorter walks, many fewer xfers IVT changes contributed a modest share of UBsIVT changes contributed a modest share of UBs


SummarySummary

Cap exists to ward off swamp Cap exists to ward off swamp creaturescreatures

Projects with large per-trip UBsProjects with large per-trip UBs– Demonstration of real project causesDemonstration of real project causes– Usually Usually ΔΔIVT, but not alwaysIVT, but not always

Soon(?): routine QC of forecasts will Soon(?): routine QC of forecasts will eliminate need to capeliminate need to cap


8. CTPP-based QC 8. CTPP-based QC ForecastsForecasts

FTA requirements for New StartsFTA requirements for New Starts BackgroundBackground ApplicationApplication ExamplesExamples



No requirement for sketch QC No requirement for sketch QC forecastforecast

Other relevant requirementsOther relevant requirements– Plausible forecastsPlausible forecasts– Analysis of uncertaintiesAnalysis of uncertainties

Potentially desirable applicationsPotentially desirable applications– Starter linesStarter lines– Unfortunate track recordsUnfortunate track records



Motivation – to learn from experienceMotivation – to learn from experience– New Starts projects over the past 20 yearsNew Starts projects over the past 20 years– Presumption of available insightsPresumption of available insights– Simple model: markets Simple model: markets ridership experience ridership experience

Purpose – to provide a:Purpose – to provide a:– Synthesis of accumulated general experienceSynthesis of accumulated general experience– Readily available & consistent method and Readily available & consistent method and

datadata– Low-cost source of a Low-cost source of a secondsecond number number– Way to address entirely new park/ride optionsWay to address entirely new park/ride options



Aggregate Rail Ridership Aggregate Rail Ridership Forecasting (Forecasting (ARRFARRF) Model) Model– Sponsored by FTA; developed by Sponsored by FTA; developed by

AECOMAECOM– Based on recently built projectsBased on recently built projects

Light rail (11 projects)Light rail (11 projects) Commuter rail (9 projects)Commuter rail (9 projects)


ARRF – Key ElementsARRF – Key Elements

1.1. CTPP CTPP workers workersijij

2.2. GISGIS workers workersijij served by rail line served by rail line Home buffers: Home buffers:

6 mi. PNR station 6 mi. PNR station 2 mi. other station2 mi. other station

Work buffers: walk 1 mi.Work buffers: walk 1 mi.

3.3. Model Model total riders total ridersijij on rail on rail


ARRF – Key Elements ARRF – Key Elements (cont’d)(cont’d)

LRT modelLRT model– Total ridersTotal ridersijij on rail = function of on rail = function of

WorkersWorkersijij

Workplace densityWorkplace density Direction length of LRT lineDirection length of LRT line


ARRF – Key Elements ARRF – Key Elements (cont’d)(cont’d)

CR modelCR model– Total ridersTotal ridersijij on rail = function of on rail = function of

WorkersWorkersijij by income class by income class Average system speedAverage system speed Train-miles per mileTrain-miles per mile Connection to fixed-guideway Connection to fixed-guideway

distributor distributor


ApplicationApplication

1.1. Obtain basic input filesObtain basic input files

2.2. Determine the socio-economic characteristics of Determine the socio-economic characteristics of the geographythe geography

3.3. Prepare the CTPP Part 3 flow dataPrepare the CTPP Part 3 flow data

4.4. Determine the relationships between rail stations Determine the relationships between rail stations & geography& geography

5.5. Run Run RailMarketRailMarket program to determine the program to determine the number of work for both live & work nearby rail number of work for both live & work nearby rail stationsstations

6.6. Enter the information from Enter the information from RailMarketRailMarket into the into the model spreadsheetmodel spreadsheet


ApplicationApplication

Aggregate test of reasonablenessAggregate test of reasonableness– Guideway ridership onlyGuideway ridership only– Worker-flows as proxy for overall Worker-flows as proxy for overall

marketsmarkets Not a replacement for local modelsNot a replacement for local models

– Unique markets and transit contextsUnique markets and transit contexts– Locally defined purpose and needLocally defined purpose and need– Ridership potential Ridership potential ≠≠ project merit project merit


Materials AvailableMaterials Availablefrom FTAfrom FTA Detailed documentationDetailed documentation

– Part-1: Model Application GuidePart-1: Model Application Guide– Part-2: Input Data Development Part-2: Input Data Development

GuideGuide– Part-3: Model Calibration ReportPart-3: Model Calibration Report

RailMarketRailMarket program program Spreadsheets: LRT and CRSpreadsheets: LRT and CR [email protected]@dot.gov


Example ARRF Example ARRF ApplicationsApplications Five ExamplesFive Examples

David Schmitt, AECOM ConsultDavid Schmitt, AECOM Consult

Three ExamplesThree Examples Yasasvi Popuri, Cambridge SystematicsYasasvi Popuri, Cambridge Systematics


ARRF ApplicationsARRF Applications

Dave SchmittDave Schmitt

AECOM ConsultAECOM Consult


Applications – City AApplications – City A

New rail line between CBD and New rail line between CBD and suburban activity centers; strong suburban activity centers; strong corridor bus ridership & servicecorridor bus ridership & service

Compared ARRF LRT model with travel Compared ARRF LRT model with travel demand model resultsdemand model results

ResultsResults– ARRF LRT model results were 100% higher ARRF LRT model results were 100% higher

than travel demand model estimatesthan travel demand model estimates– Stronger motivation to investigate transit Stronger motivation to investigate transit

model parameters; subsequently identified model parameters; subsequently identified issues with walk- and auto-access issues with walk- and auto-access connector methodologyconnector methodology


Applications – City A Applications – City A (cont’d)(cont’d)

ConclusionsConclusions– ARRF model may partially explain ARRF model may partially explain

attractiveness of rail over existing attractiveness of rail over existing bus servicebus service

– TDM path-builder probably better at TDM path-builder probably better at evaluating bus/rail competition:evaluating bus/rail competition: Equal service levels for bus & railEqual service levels for bus & rail Buses are just as close or closer to Buses are just as close or closer to

corridor activity centerscorridor activity centers


Applications – City BApplications – City B

New rail line between CBD and New rail line between CBD and suburban residential areassuburban residential areas

Used ARRF to develop rationale Used ARRF to develop rationale for alternative-specific constant for alternative-specific constant

Results on next slide…Results on next slide…


Ridership Forecasts – Ridership Forecasts – City BCity B

WalkWalk Drive/ Drive/ Drop-OffDrop-Off TotalTotal

ARRFARRF 14,79414,794 6,5486,548 21,34221,342

TDM ModelTDM Model

(no bias)(no bias)11,52011,520 4,5564,556 16,07616,076

TDM ModelTDM Model

(7.5 minute walk, 15 (7.5 minute walk, 15 minute drive)minute drive)

13,14513,145 6,3416,341 19,48719,487

TDM ModelTDM Model

(10 minute walk, 15 (10 minute walk, 15 minute drive)minute drive)

14,77014,770 6,2776,277 21,04721,047


Applications – City CApplications – City C

Streetcar in low density urban activity Streetcar in low density urban activity center; existing service is local & center; existing service is local & primarily captive marketprimarily captive market

ARRF LRT model compared with travel ARRF LRT model compared with travel demand model (2000 trip tables, 2030 demand model (2000 trip tables, 2030 networks)networks)


Applications – City C Applications – City C (cont’d)(cont’d)

ResultResult– Aggregate model forecast 120% higher than travel Aggregate model forecast 120% higher than travel

demand modeldemand model

ConclusionConclusion– ARRF model may partially explain attractiveness of ARRF model may partially explain attractiveness of

rail over existing service, but does not well-rail over existing service, but does not well-represent benefits of project since:represent benefits of project since:

The project mode is different than calibrated modeThe project mode is different than calibrated mode Lack of choice market not consistent with LRT sample Lack of choice market not consistent with LRT sample

citiescities


Applications – City DApplications – City D

Commuter rail between two adjacent Commuter rail between two adjacent metropolitan areas; some express bus metropolitan areas; some express bus service to each CBD, but no service service to each CBD, but no service between CBD’sbetween CBD’s

Commuter rail ARRF model compared Commuter rail ARRF model compared with travel demand model (2000 trip with travel demand model (2000 trip tables, 2030 networks) applied to tables, 2030 networks) applied to eacheach CBDCBD


Applications – City D Applications – City D (cont’d)(cont’d)

ResultResult– Aggregate model forecast 130% higher than travel Aggregate model forecast 130% higher than travel

demand modeldemand model

ConclusionConclusion– ARRF model may partially explain ARRF model may partially explain

attractiveness of rail over existing attractiveness of rail over existing commuter bus service, but does not commuter bus service, but does not well-represent benefits of project well-represent benefits of project since lack of service between CBDs since lack of service between CBDs unlike CR sample citiesunlike CR sample cities


Applications – City EApplications – City E

New commuter rail line to high mode New commuter rail line to high mode share CBD with established “choice share CBD with established “choice market” commuter bus service from market” commuter bus service from large park and ride facilitieslarge park and ride facilities

Commuter rail ARRF model compared Commuter rail ARRF model compared with travel demand model (2000 trip with travel demand model (2000 trip tables, 2030 networks) appliedtables, 2030 networks) applied


Applications – City E Applications – City E (cont’d)(cont’d)

ResultResult– Aggregate model forecast 30% lower Aggregate model forecast 30% lower

than travel demand modelthan travel demand model

ConclusionConclusion– Existing commuter (“choice”) Existing commuter (“choice”)

market in corridor stronger than CR market in corridor stronger than CR sample citiessample cities


Applications in Milwaukee, Kansas Applications in Milwaukee, Kansas City,City,

and St. Louisand St. Louis

Yasasvi PopuriYasasvi Popuri

Cambridge SystematicsCambridge Systematics


OverviewOverview

Recent ARRF applicationsRecent ARRF applications– Kenosha-Racine-Milwaukee (WI)Kenosha-Racine-Milwaukee (WI)

– Kansas City, St. Louis, MOKansas City, St. Louis, MO

– Madison, WIMadison, WI

– Indianapolis, INIndianapolis, IN

General insights from ARRF applicationGeneral insights from ARRF application– Second data pointSecond data point

– Support for model re-evaluationSupport for model re-evaluation


Kenosha-Racine-Milwaukee


KRM ServiceKRM Service

ARRF vs. current UPN ridership.ARRF vs. current UPN ridership.– UPN:UPN: 26,000 daily trips 26,000 daily trips– ARRF estimate:ARRF estimate: 21,000 daily trips 21,000 daily trips

Wisconsin OnlyWisconsin Only– Service is close to ARRF defaultsService is close to ARRF defaults– ARRF estimate:ARRF estimate: 2,800 daily riders 2,800 daily riders

Entire Corridor in WI and ILEntire Corridor in WI and IL– Existing UPN Existing UPN andand proposed KRM service proposed KRM service– ARRF forecasts: Entire corridor ARRF forecasts: Entire corridor minusminus Existing Existing

UPNUPN– ARRF estimate:ARRF estimate: 4,500 daily riders 4,500 daily riders


KRM Service KRM Service ARRF vs. Model ARRF vs. Model ResultsResults

KRM WI KRM WI Only Only

(RCI = 0.5)(RCI = 0.5)

KRM – WI & KRM – WI & ILIL

(RCI = 1)(RCI = 1)

UPNUPN

(Obs = (Obs = 26,000)26,000)

ARRFARRF 2,8002,800 4,5004,500 21,00021,000

KRM Model-KRM Model-20022002 4,4004,400 5,9005,900 25,07525,075


KRM ServiceKRM ServiceConclusionsConclusions

ARRF for existing UPN lower than ARRF for existing UPN lower than observedobserved– Existing UPN service (not a “new” New Start)Existing UPN service (not a “new” New Start)

ARRF for KRM lower than modelARRF for KRM lower than model– KRM as a natural “extension” of UPNKRM as a natural “extension” of UPN

Take a second look at the model:Take a second look at the model:– Trip interchangesTrip interchanges– Transit trip interchangesTransit trip interchanges– PnR and walk access patternsPnR and walk access patterns


Kansas City – I-70 Kansas City – I-70 CorridorCorridor



Traditional suburb-to-CBD commuter rail Traditional suburb-to-CBD commuter rail – Low proposed level of rail serviceLow proposed level of rail service– Location of downtown terminalLocation of downtown terminal– ““What if” scenarios for frequencyWhat if” scenarios for frequency

ARRF offered a set of “second data ARRF offered a set of “second data points”points”– Introduced after model forecasts were completedIntroduced after model forecasts were completed– Independent estimate of model results and Independent estimate of model results and

sensitivitysensitivity



3 Peak 3 Peak Direction Direction

TrainsTrains

3 Peak + 3 3 Peak + 3 Reverse Reverse TrainsTrains

4 Peak + 4 4 Peak + 4 Reverse Reverse TrainsTrains

ARRF ARRF Riverfront Riverfront TerminalTerminal

815815 1,0201,020 1,1251,125

ARRF ARRF Downtown Downtown TerminalTerminal

1,0601,060 1,3301,330 1,4601,460

Model results with Riverfront TerminalModel results with Riverfront Terminal– 4 peak trains, two-way, and $2.50 fare: 4 peak trains, two-way, and $2.50 fare: 1,244 1,244

ridersriders


Kansas City – I-70 Kansas City – I-70 Corridor Corridor ConclusionsConclusions

ARRF used as a second data pointARRF used as a second data point ARRF used for testing ridership ARRF used for testing ridership

sensitivity to:sensitivity to:– Terminal locationTerminal location– Frequency of serviceFrequency of service

Reasonable agreement b/w ARRF and Reasonable agreement b/w ARRF and modelmodel


St. Louis Alternatives Analysis


St. Louis St. Louis Alternatives AnalysisAlternatives Analysis Data point in ARRF calibrationData point in ARRF calibration On-going study On-going study LRTLRT version of ARRF: markets only, no LOS version of ARRF: markets only, no LOS ARRF applied for 2000 and 2006 MetroLinkARRF applied for 2000 and 2006 MetroLink

– Lower ARRF forecasts for 2000 and 2006Lower ARRF forecasts for 2000 and 2006– Strong impact of special generator trips (ball games, Strong impact of special generator trips (ball games,

airport trips)airport trips)

2002 MetroLink

2006 MetroLink

ARRF 30,600 60,400Observed 42,000 ~80,000


St. LouisSt. LouisAlternatives AnalysisAlternatives Analysis

The “build” alignment treated as an The “build” alignment treated as an incremental version to the 2006 MetroLink.incremental version to the 2006 MetroLink.– Growth of 43% from 2006 no-build ridershipGrowth of 43% from 2006 no-build ridership– Ridership of 26,000 without any adjustmentsRidership of 26,000 without any adjustments

Model currently being refinedModel currently being refined– Lower forecast than ARRFLower forecast than ARRF– Examine speeds on competing bus routesExamine speeds on competing bus routes– Examine highway speedsExamine highway speeds

2006 MetroLink2006 MetroLink +

Proposed AlignmentARRF 60,400 86,200Observed ~80,000


ARRF InsightsARRF Insights

Market assessment toolMarket assessment tool Second data pointSecond data point Sets the stage to re-evaluate model Sets the stage to re-evaluate model

– Total trips produced Total trips produced – Trip interchange patternsTrip interchange patterns– Transit trip patternsTransit trip patterns– Sensitivity to frequencySensitivity to frequency– Speeds on competing transit and highway facilitiesSpeeds on competing transit and highway facilities


9. Alternative-Specific 9. Alternative-Specific EffectsEffects

FTA requirements for New StartsFTA requirements for New Starts ImplementationImplementation Three examplesThree examples



MotivationsMotivations– Correct the “new New Starts” disadvantageCorrect the “new New Starts” disadvantage– Respond to recent evidenceRespond to recent evidence

Positive guideway constants in “well-scrubbed” Positive guideway constants in “well-scrubbed” modelsmodels

Higher-than-explainable BRT ridership impacts (LA, Higher-than-explainable BRT ridership impacts (LA, KC)KC)

ApproachApproach– Attributes rather than modesAttributes rather than modes

– Differential constant and CDifferential constant and Civtivt discount discount

– Post-mode-choice applicationPost-mode-choice application



ApplicabilityApplicability– 2007: “new New Starts” guideways2007: “new New Starts” guideways– 2008: guideway elements of 2008: guideway elements of

baselinesbaselines Stations: amenities and brandingStations: amenities and branding Vehicles: amenities and brandingVehicles: amenities and branding Dynamic arrival informationDynamic arrival information Exclusive runningExclusive running Other attributesOther attributes


Attributes, Not ModesAttributes, Not Modes

Attributes not found in modelsAttributes not found in models AlternativeAlternative-specific conditions-specific conditions

– Important: missing attributesImportant: missing attributes– Not important: labels like “BRT” or Not important: labels like “BRT” or

“CR”“CR”– Effects on ridership and mobility Effects on ridership and mobility

benefitsbenefits Guideway-only vs. guideway+local Guideway-only vs. guideway+local

busbus

Someone, please, define these “modes.”


Constant and CConstant and Civtivt Discount – FTADiscount – FTAMaximum Maximum

Alternative-Specific Alternative-Specific Effect versus Local Bus Effect versus Local Bus

(mins.)(mins.)

Maximum Maximum Guideway Guideway

Civt Civt DiscountDiscount

Guideway Attributes that Are Guideway Attributes that Are Different from Local BusDifferent from Local Bus

Guideway(sGuideway(s) ) onlyonly

Guideway(sGuideway(s) + local ) + local

busbus

Any Any GuidewayGuideway

Guideway-like characteristicsGuideway-like characteristics 88 33 Civt x 0.85Civt x 0.85

-- Reliability of vehicle arrival, travel -- Reliability of vehicle arrival, travel timetime

44 22 Civt x Civt x 0.900.90

-- Branding/visibility/learnability-- Branding/visibility/learnability 22 11 ----

-- Schedule-free service-- Schedule-free service 22 00 ----

-- Ride quality-- Ride quality ---- ---- Civt x Civt x 0.950.95

Span of Span of goodgood service service 33 00 ----

Passenger facilitiesPassenger facilities 44 33 ----

-- Amenities at stations/stops-- Amenities at stations/stops 33 22 ----

-- Dynamic schedule information-- Dynamic schedule information 11 11 ----

Vehicle amenitiesVehicle amenities ---- ---- Civt x 0.95Civt x 0.95

Availability of seatAvailability of seat ---- ---- Civt x 0.95Civt x 0.95

Maximum effectMaximum effect 1515 66 Civt x 0.75Civt x 0.75


Post Mode ChoicePost Mode Choice

Track recordTrack record– FTA reviews of 19 New Starts forecastsFTA reviews of 19 New Starts forecasts– Starter lines Starter lines highest risk of highest risk of

overestimateoverestimate ConsequentlyConsequently

– ASE adjustments for user benefits onlyASE adjustments for user benefits only– No change in total or guideway ridershipNo change in total or guideway ridership– No change in walk/bus/auto access modesNo change in walk/bus/auto access modes– JudgmentJudgment on sizing of park-ride lots on sizing of park-ride lots


ImplementationImplementation

Identification of appropriate ASEsIdentification of appropriate ASEs– Sponsor: description of service Sponsor: description of service

attributesattributes– FTA: determination of ASE valuesFTA: determination of ASE values

Detection of paths using the Detection of paths using the projectproject

Detection of guideway-only pathsDetection of guideway-only paths


Paths using the ProjectPaths using the Project

With all-or-nothing impedancesWith all-or-nothing impedances– For each I-J:For each I-J:

B B = If = If bldbldIVTIVTgdwygdwy > > basbasIVTIVTgdwygdwy 1, else 0 1, else 0

ASEASE = B x = B x bldbldtripstripstrntrn x ASC x ASC

+ ASD+ ASDivtivt x ( x (bldbldIVTIVTgdwygdwy - - basbasIVTIVTgdwygdwy))

With probability-weighted With probability-weighted impedancesimpedances– Assignment basedAssignment based– ExampleExample


Guideway-only PathsGuideway-only Paths

Imprecise conventions in most modelsImprecise conventions in most models– Zone walk-access percents for Zone walk-access percents for anyany transit transit– I-J paths for I-J paths for anyany transit transit– Unable to isolate guideway-only pathsUnable to isolate guideway-only paths

FTA conventionFTA convention– Guideway-only ASC for PnR/KnR onlyGuideway-only ASC for PnR/KnR only– Case-by-case exceptions for (1) model Case-by-case exceptions for (1) model

structure or (2) small zones near projectstructure or (2) small zones near project


Guideway-only PathsGuideway-only Paths

Portland streetcarPortland streetcar Subdivision of Subdivision of

zoneszones Low chance of bus Low chance of bus

component if component if IVTIVTbusbus = 0 = 0

FTA agreement on FTA agreement on ASCASCgdwygdwy for walk- for walk-accessaccess


ExamplesExamples

ASEs for BRT with an Older ASEs for BRT with an Older PathbuilderPathbuilder

Jeff Bruggeman, AECOM ConsultJeff Bruggeman, AECOM Consult

ASEs for Streetcar with Multi-pathsASEs for Streetcar with Multi-paths Jennifer John, Portland Tri-Met Jennifer John, Portland Tri-Met

ASEs for BRT with Some RefinementsASEs for BRT with Some Refinements Tom Maziarz, Hartford CRCOGTom Maziarz, Hartford CRCOG


BRT and Path Choice BRT and Path Choice with an Older Pathbuilderwith an Older Pathbuilder

Jeffrey M. BruggemanJeffrey M. Bruggeman

AECOM ConsultAECOM Consult


Nature of AlternativesNature of Alternatives

System with BRT projects to be System with BRT projects to be built parallel to or within right-of-built parallel to or within right-of-way of major highwaysway of major highways

Baseline alternative to be created Baseline alternative to be created with same operating planwith same operating plan

Benefits to flow exclusively from Benefits to flow exclusively from improved speeds on BRT rights-improved speeds on BRT rights-of-wayof-way


Anticipated ResultsAnticipated Results

Buses on BRT guideway Buses on BRT guideway equivalent to a premium transit equivalent to a premium transit mode (so, coded as a different mode (so, coded as a different “mode” in the network)“mode” in the network)

Paths with identical out-of-vehicle Paths with identical out-of-vehicle times between baseline and buildtimes between baseline and build

Travel time benefits only on the Travel time benefits only on the BRT guideway onlyBRT guideway only


Nature of ProblemNature of Problem

Some BRT routes circulate before and/or Some BRT routes circulate before and/or after travel on BRT guidewayafter travel on BRT guideway

Some arterial routes diverge at BRT Some arterial routes diverge at BRT entry points with some bus-trips using entry points with some bus-trips using the BRT facilities and others continuing the BRT facilities and others continuing on an arterialon an arterial

Path builder finds off-guideway Path builder finds off-guideway differences between baseline and build, differences between baseline and build, causing negative user benefitscausing negative user benefits

Cause: breaking of combined headwaysCause: breaking of combined headways


Nature of the ProblemNature of the Problem

ON OFF

Headway?

ON OFFHeadway

? BRT guideway

Arterial street

BRT all-stops

Local bus

BRT integrated


Flagging Guideway Flagging Guideway PathsPaths Same mode-code for all bus routes Same mode-code for all bus routes

in network and path-buildingin network and path-building Transit line file parsed to determine Transit line file parsed to determine

usage of guidewayusage of guideway Pseudo-fare links coded for each Pseudo-fare links coded for each

guideway link traversed by each guideway link traversed by each lineline

Result: detection of both “guideway Result: detection of both “guideway all-stops” and “guideway express” all-stops” and “guideway express” routesroutes


Path ConditioningPath Conditioning

Single path built with all routes Single path built with all routes treated as local bustreated as local bus

Fare links skimmedFare links skimmed as they are as they are encountered on pathencountered on path

Fare conditioning programFare conditioning program– Paths using at least one fare links – BRT Paths using at least one fare links – BRT – Paths using no fare links – local or Paths using no fare links – local or

expressexpress


Mode ChoiceMode Choice

Mode choice model considers Mode choice model considers express, local, and BRT choicesexpress, local, and BRT choices

Express-bus choice is from a Express-bus choice is from a separate path-building step for separate path-building step for expresses that do not use the expresses that do not use the BRT guidewayBRT guideway

““Silver bullet” added to utility Silver bullet” added to utility expression for BRT pathsexpression for BRT paths


Current FTA NeedsCurrent FTA Needs

Latest FTA guidance does not allow Latest FTA guidance does not allow for “silver bullet” within model to for “silver bullet” within model to create higher ridershipcreate higher ridership

Technique would have to be changed Technique would have to be changed to skim amount of path time on to skim amount of path time on guidewayguideway

Could be accommodated by updating Could be accommodated by updating fare flags to reflect link impedancefare flags to reflect link impedance


Isolation of Trips and Isolation of Trips and Travel Time on a Project Travel Time on a Project In a Multipath In a Multipath EnvironmentEnvironment

Jennifer JohnJennifer John

TriMet TriMet

Portland, OregonPortland, Oregon


Multi-path AssignmentMulti-path Assignmentin EMME/2in EMME/2

Several paths between an origin and a Several paths between an origin and a destination are identified destination are identified

Trips are assigned to the paths using Trips are assigned to the paths using probabilities based on weights in the probabilities based on weights in the assignment parameters (in-vehicle, out-assignment parameters (in-vehicle, out-of-vehicle, walk) and headways of the of-vehicle, walk) and headways of the routesroutes

Assignment creates weighted travel time Assignment creates weighted travel time based on proportion of trips on each pathbased on proportion of trips on each path


Portland Streetcar Portland Streetcar ExampleExample


Isolating Streetcar TripsIsolating Streetcar Trips

Multipath assignment results in Multipath assignment results in trips on LRT, bus, and streetcar.trips on LRT, bus, and streetcar.

The project is a streetcar extension.The project is a streetcar extension. How do we isolate information How do we isolate information

about the trips that use the project?about the trips that use the project?– How do we isolate this information How do we isolate this information

from travel on the existing part of the from travel on the existing part of the Streetcar route?Streetcar route?


Isolating Streetcar TripsIsolating Streetcar Trips

In EMME/2In EMME/2– Code Streetcar as unique mode in Code Streetcar as unique mode in

network and transit line codingnetwork and transit line coding– Flag Streetcar routeFlag Streetcar route


Flagging the Streetcar Flagging the Streetcar “Project”“Project”

Total StreetcarTrips for theFull route =

10,500


Flagging the Streetcar Flagging the Streetcar “Project”“Project”

How manyStreetcar tripsAre on ONLY

The new Portion (A-B)Of the route?

A

B


Additional Options Additional Options AssignmentAssignment

Select Line/SegmentSelect Line/Segment– ResultsResults

O/D Matrix of trips for flagged route (or O/D Matrix of trips for flagged route (or portion of route as in the case of an portion of route as in the case of an extension of an existing line)extension of an existing line)


Multipath Assignment Multipath Assignment Results: No FlagsResults: No Flags


Additional Option Additional Option Assignment Results: Assignment Results: Project FlaggedProject Flagged

Total StreetcarTrips for the

Selected Segment

Of route =8,100


Using the Assignment Using the Assignment ResultsResults

Total boardings for the project as Total boardings for the project as isolated in the assignments are isolated in the assignments are used to apply ASE calculationsused to apply ASE calculations– Maximum value of 15 for Guideway Maximum value of 15 for Guideway

ONLYONLY– Maximum value of 6 for Guideway + Maximum value of 6 for Guideway +

local buslocal bus


Guideway ONLY TripsGuideway ONLY Trips

Portion of the O/D results matrixPortion of the O/D results matrix– Isolated by a submatrix of the Isolated by a submatrix of the

additional options assignment resultsadditional options assignment results– Includes only zone-pairs where direct Includes only zone-pairs where direct

walk to/from a streetcar stop is walk to/from a streetcar stop is certaincertain at at bothboth ends of the trip ends of the trip

– Would be eligible for up to 15 minutes Would be eligible for up to 15 minutes (as determined by FTA) of ASE(as determined by FTA) of ASE


Guideway ONLY TripsGuideway ONLY Trips

TAZs in YellowHave direct

Walk access to Project

(no transfers)


Guideway + Local BusGuideway + Local Bus

Portion of the O/D results matrixPortion of the O/D results matrix– Remainder of trips in the matrix that Remainder of trips in the matrix that

do not have direct walk on/off do not have direct walk on/off access to the projectaccess to the project

– Would be eligible for up to 6 minutes Would be eligible for up to 6 minutes (as determined by FTA) of ASE(as determined by FTA) of ASE


Isolating Project Isolating Project In-Vehicle Travel In-Vehicle Travel TimesTimes Used in CUsed in Civtivt Calculations Calculations Project coded as unique modeProject coded as unique mode

– In EMME/2 transit times can be In EMME/2 transit times can be saved out specific to a modesaved out specific to a mode

– Use these transit times along with Use these transit times along with the o/d matrix from the additional the o/d matrix from the additional option assignment to identify travel option assignment to identify travel time on projecttime on project


ConclusionsConclusions

Multi-path environment and ASEsMulti-path environment and ASEs– Feasible applicationFeasible application– In EMME/2, the key is the additional In EMME/2, the key is the additional

option assignmentoption assignment– Full credit for walk-only ASEs also Full credit for walk-only ASEs also

depends on small zonesdepends on small zones


ASEs for the ASEs for the New Britain – Hartford BuswayNew Britain – Hartford Busway

Tom Maziarz & Ming ZhaoTom Maziarz & Ming ZhaoCapitol Region Council of Capitol Region Council of

GovernmentsGovernments


Keys to Hartford’s ApproachKeys to Hartford’s ApproachStart with advantage: Start with advantage: 6 transit skims produced for MC6 transit skims produced for MC

• Walk to guideway – Walk from guideway Walk to guideway – Walk from guideway (WG-WG)(WG-WG)• Walk to guideway – Walk from bus Walk to guideway – Walk from bus (WG-WB)(WG-WB)• Walk to bus – Walk from guideway Walk to bus – Walk from guideway (WB-WG)(WB-WG)• Walk to bus – Walk from bus Walk to bus – Walk from bus (WB-WB)(WB-WB)• DriveDrive to transit (PNR) – Walk from guideway to transit (PNR) – Walk from guideway (DT-WG)(DT-WG)• Drive Drive to transit (PNR) – Walk from guideway to transit (PNR) – Walk from guideway (DT-WB)(DT-WB)

Goal: Goal: Consider individual trip attributes of each O-D pathConsider individual trip attributes of each O-D pathAssign weight for Assign weight for each factoreach factor & for & for each path typeeach path type

• ReliabilityReliability• Branding & LearnabilityBranding & Learnability• Station amenitiesStation amenities• Schedule-free serviceSchedule-free service• Long span of serviceLong span of service• Dynamic schedule informationDynamic schedule information


Keys to Hartford Approach:Keys to Hartford Approach:

Breakdown & isolate path types using combination of: Breakdown & isolate path types using combination of: – 6 skims6 skims– Key data from skims Key data from skims (some newly created)(some newly created)

– Creative analysis of skim data Creative analysis of skim data • Total IVTTotal IVT• IVT on BRT routes IVT on BRT routes (requires separate coding)(requires separate coding)• # Transfers ….# Transfers ….

Basic Concept: Basic Concept: break down a path into 3 components break down a path into 3 components – IVT IVT ON the guideway ON the guideway (requires separate coding)(requires separate coding)– IVTIVT ON BRT loop ON BRT loop (requires separate coding)(requires separate coding)– IVT IVT OFF guidewayOFF guidewayProcess yields: Process yields: 12 path types that 12 path types that use the use the

guidewayguideway


Components used to classify path types

BRT loop Walk from BRT bus

Off Guideway IVT

On Guideway IVT

On BRT Loop IVT

Feeder bus with transfer

Walk to bus

Walk to bus

BRT bus (no transfer)

dashed line also illustrates “BRT bus route” (mode 5)


Examples of Path Types

Walk from guideway

Walk to guideway

On Guideway

Most basic path type: 100% On-Guideway

Identifiers:• From WG-WG skim

Alternate ID:• Total IVT = Guideway IVT

Key ID for all 12 path types: • Guideway IVT > 0

WG–WG trip


BRT loopWalk from BRT bus

Walk to bus

On Guideway

On BRT Loop

More complex path type: On-Guideway + On-BRT Loop

WG–WBRT trip

Identifiers:• From WG-WB skim

• WB could be feeder bus or BRT bus• BRT bus egress could be on or off loop

Additional Identifiers:Total IVT = G-way IVT + Loop IVTTotal IVT = Mode 5 IVT (BRT bus)

Transfers = 0



Walk to bus

Off Guideway

On Guideway

On BRT Loop

Another complex path type:Off Guideway + On-Guideway + On-BRT Loop

BRT bus

Identifiers:• From WB-WB skim• Total IVT > G-way IVT + Loop IVT• Total IVT = Mode 5 IVT (BRT bus)

• Transfers = 0

WB–WBRT trip(Single seat trip)


Final example of path type:Off Guideway + On-Guideway + On-BRT Loop

BRT loop Walk from BRT bus

Walk to bus

Off Guideway

On Guideway

On BRT Loop

Feeder bus with transfer

Identifiers:• From WB-WB skim (same as previous slide)

• Total IVT > G-way IVT + Loop IVT (same)

Total IVT > Mode 5 IVT (BRT bus)

Transfers = 1

WB–WBRT trip(with transfer)


Process skim tables to develop trip tables for each path type

• WG-WG trips• WG–WBRT trips• WG-WB trips• .....• ……• …… (12 classes)

Off-G’way IVT

BRT Loop IVT

Guideway IVT

Total IVT skim

• Identify O-D pairs that meet criteria for path type

• Select trips for that O-D pair & enter into trip table for that path type


Results: # HBW Trips by Path Type(only trips that use all or part of guideway)

1 2 3 4 5 6 71-seat ride 1-seat ride 1-seat ride 1-seat ride transfer transfer transferWG-WG WG-WBRT WB-WG WB-WBRT WG-WB WB-WG WB-WBRT

Trips 87 209 221 620 276 1,439 1,749

Access guidewaystation

guidewaystation

BRTbus

BRTbus

guidewaystation

feederbus

feederbus

Egress guidewaystation

loopstation

guidewaystation

loopstation

feederbus

guidewaystation

loopstation

8 9 10 11 121-seat ride 1-seat ride 1-seat ride 1-seat ride transferDG-WG DG-WBRT DB-WG DB-WBRT DG-WB

Trips 316 720 140 483 462

Access guidewaystation

guidewaystation

BRTbus

BRTbus

guidewaystation

Egress guidewaystation

loopstation

guidewaystation

loopstation

feederbus

Walk Access

Drive Access


Assigning attribute weights (constants)

Walk Access Trips1 2 3 4 5 6 7

100% BRT 100% BRT1-seat ride 1-seat ride 1-seat ride 1-seat ride transfer transfer transfer

WG-WG WG-WBRT WB-WG WB-WBRT WG-WB WB-WG WB-WBRT

Reliability 2.0 2.0 1.0 1.0 0.0 0.0 0.0Branding-Learn. 2.0 2.0 0.5 0.5 0.0 0.0 0.0

Schedule-free serv 2.0 2.0 ---- ---- ---- ---- ---- Span of service 2.0 2.0 ---- ---- ---- ---- ----

Station amenities 1.0 1.0 0.5 0.5 0.5 0.5 0.5Dynamic sched info 1.0 1.0 0.0 0.0 0.0 0.0 0.0

Total Constant 10.0 10.0 2.0 2.0 0.5 0.5 0.5

Trips 87 209 221 620 276 1,439 1,749

Benefits (hrs) 14.5 34.8 7.4 20.7 2.3 12.0 14.6constant x trips/60

Attribute Weights in Minutes


Entirely on Guideway or Loop

Receive full benefitof guideway (To degree that busway achieves full functionality)

• Reliability: exclusive ROW• Branding : distinct stations,

etc.• Freq serv: 2-4 min h’dways any

station-station trip• Span of serv: 18 hours • Sta. amenities: covered

platforms, visible, secure• Dynamic schedule info: at

guideway & loop stations

1 2100% BRT 100% BRT1-seat ride 1-seat ride

WG-WG WG-WBrt Max

Reliability 2.0 2.0 4

Branding 2.0 2.0 2

Sched-free serv 2.0 2.0 2

Span of serv 2.0 2.0 3

Sta. amenities 1.0 1.0 3

Dyn. sched info 1.0 1.0 1

Total 10.0 10.0 15

Trips 87 209

Benefits 14.5 34.8

Benefits (hours) = Constant x trips/60 min


Start off-busway on a ‘BRT’ bus Receive some benefit of G’way • Reliability: lose some reliability

with off-busway segment, but start at less congested end

• Branding : some benefit from BRT marketing, bus branding , etc.

• Freq serv: NO – single route• Span of serv: NO – single route• Sta. Amenities: one end of trip• Dynamic schedule info: NO

3 4

1-seat ride 1-seat ride

WB-WG WB-WBRT

Reliability 1.0 1.0Branding-Learn. 0.5 0.5Sched-free serv ---- ---- Span of service ---- ---- Sta. amenities 0.5 0.5

Dyn. sched info 0.0 0.0

Total 2.0 2.0

Trips 221 620

Benefits 7.4 20.7


• All use guideway• But all involve transfer

& feeder bus

• Most guideway benefits compromised by dependence on feeder bus & transfer

• Only 0.5 min credit

5 6 7

transfer transfer transfer

WG-WB WB-WG WB-WBrt

Reliability 0.0 0.0 0.0Branding-Learn. 0.0 0.0 0.0Sched-free serv ---- ---- ---- Span of service ---- ---- ---- Sta. amenities 0.5 0.5 0.5

Dyn. sched info 0.0 0.0 0.0

Total 0.5 0.5 0.5

Trips 276 1,439 1,749

Benefits 2.3 12.0 14.6


Final Thoughts: Will it work with other models?


Walk to bus

Off Guideway

On Guideway

On BRT LoopTRANSFER

Identifiers:• From WB-WB skim• Total IVT > G-way IVT + Loop IVT• Total IVT > Mode 5 IVT• Transfers = 1

Experience in Hartford• Suggests potential to adapt to other areas• Creative use of coding and & analysis of skims allowed

• Better definition of path types• Better assessment of guideway related benefits

September 2007Travel Forecasting for New Starts2-1 6. Standard Reporting/QC FTA requirements for New...

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