Simplified Data Driven Methods for FTA Small Starts Project Evaluation

Jeffrey Roux (AECOM)

Prasad Pulaguntla (AECOM)

May 8, 2013

Agenda

• Richmond Broad Street BRT Project Overview

• The Challenge

• Approach

• Bump on the Road

• Project extensions

• Lessons Learned

• Acknowledge MANY contributions to the study

February 17, 2012

SERPM 6.7 Development

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Broad Street Corridor

• Broad Street is THE bus corridor in Richmond, VA with 17,000 daily transit trips.

• Broad Street serves as main GRTC artery in Downtown

• Today: bus bunching, sub-standard lanes and accidents result in a relatively slow and unreliable journey.

• Full BRT saves up to 3 min. on local bus trips and 6 min. on BRT/express bus trips

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Problem Statement

•Existing conditions– 48 buses/direction/peak hour within downtown RIC– Current service is “local” stopping every block– Narrow Parking lane (8’) dedicated to buses in peak-

period (with poor enforcement) Problems

– High bus volumes with multiple routes entering the trunk line lead to bus bunching and low reliability

– Existing narrow downtown bus lanes cause conflicts and accidents

– Conga-line conditions leads to very slow travel times

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Goals and Objectives

•Provide more attractive transit service– Improve travel times– Reduce accidents– Improve customer experience/amenities– Improve system efficiency– Improve reliability– Improve convenience, efficiency of transfers– Expand market

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Project Tactics• BRT trunk line to provide a higher quality transit service:

– Higher quality, low floor, branded vehicles– Formal BRT transit stops

• Formal branded shelters• Off-board fare collection

– Dedicated bus lanes for half of corridor to speed trips– Traffic signal priority– Trunk line BRT is 6 min faster to Downtown (vs. express bus without

priority treatments) and 14 min faster compared to local bus.

• Consolidated bus stops in Downtown for ALL buses– Downtown operations consolidate to three stops– Multi-platform boarding– Local buses are 3 min. faster through Downtown

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The Challenge

•Prepare patronage forecast & FTA Project Justification materials for Small Starts application

•Off the shelf tools (in 2010):– VDOT Richmond/Tri-Cities Forecasting Model (RTFM):

• Highway focused forecasting model• Very good representations of highway travel speeds• Basic transit network and limited mode choice

capabilities– Fall 2009 GRTC On-Board Survey

•Approach: Develop data-driven approach from RTFM networks and on-board surveys

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Data Driven Approach – Two Elements

• Transit Networks:– Recoded RTFM Transit Networks (CUBE

TP+/TRNBUILD)– Calibrated bus travel times from VDOT peak/off-peak

highway travel times (equations of motion)

• On-Board Transit Survey – Trip Tables:– VDRPT surveyed GRTC routes in Fall ’09– Comprehensive picture of GRTC existing markets

• Approach: Measure how existing riders (surveyed) impacted by project and estimate new riders through representation of transit network changes

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Transit Network Development

Recoded RTFM Transit Networks to Reflect Nov. ‘09 Service (survey):– Separate peak/off-peak transit networks:

• Peak (7-9 AM)• Off-Peak (10-2 PM)

– Correct route routing (including loops through D’town)– Zone splits in project corridor – Properly reflect stop locations– Developed bus speed relationships, using equations of

motion based approach:• AM Peak – Congested highway travel times• Off-Peak – Free flow highway travel times

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Bus Travel Time Validation

Approach: Accurately represent bus travel speeds by pivoting off of RTFM highway speeds

Process built “equation of motion” approach to replicate current scheduled travel times of all buses:– Used typical bus acceleration/deceleration rates– Calibrated an average “dwell” times per stop– Process worked very well as virtually all buses are within 15% or (3-

4 min.) of scheduled end-to-end running times

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2009 GRTC On-Board Survey4,500 completed surveys representing 32,900 GRTC boardings:– Included VCU and non-VCU bus routes– For approach we processed:

• Trip Ends (Productions and Attractions)• Mode of Access (PNR, drop-off and walk)• Time of Day (peak & off-peak)• Converted boardings to linked trips

– Conducted on all routes, except inter-city routes:• Petersburg-Downtown Richmond Express• Fredericksburg-Ashland-Downtown Richmond Express• Not material to Project

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2009 GRTC On-Board Survey Trip Productions

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2009 GRTC On-Board Survey Trip Attractions

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“Traditional” Survey Tabulations

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Table 1: GRTC Regional Bus Service Year 2009 Average Weekday Linked Bus Trips Table 2: VCU Bus Service Year 2009 Average Weekday Linked Bus Trips

Home Based Work (HBW) Trips Home Based Work (HBW) Trips

Period Access Mode 0 Car HH 1+ Car HH Total Period Access Mode 0 Car HH 1+ Car HH TotalPeak Period Walk 2,236 1,972 4,208 Peak Period Walk 10 128 138

Drive 71 1,449 1,520 Drive 4 214 218SubTotal 2,307 3,421 5,728 SubTotal 14 342 356

Off-Peak Period Walk 2,541 1,714 4,255 Off-Peak Period Walk 36 32 68Drive 72 146 218 Drive 0 73 73SubTotal 2,613 1,860 4,473 SubTotal 36 105 141Total 4,920 5,281 10,201 Total 50 447 497

Home Based Other (HBO) Trips Home Based Other (HBO) Trips

Period Access Mode 0 Car HH 1+ Car HH Total Period Access Mode 0 Car HH 1+ Car HH TotalPeak Period Walk 1,359 913 2,272 Peak Period Walk 85 346 431

Drive 35 145 180 Drive 0 71 71SubTotal 1,394 1,058 2,452 SubTotal 85 417 502

Off-Peak Period Walk 2,696 2,021 4,717 Off-Peak Period Walk 253 629 882Drive 71 101 172 Drive 0 91 91SubTotal 2,767 2,122 4,889 SubTotal 253 720 973Total 4,161 3,180 7,341 Total 338 1,137 1,475

Non Home Based (NHB) Trips Non Home Based (NHB) Trips

Period Access Mode 0 Car HH 1+ Car HH Total Period Access Mode 0 Car HH 1+ Car HH TotalPeak Period Walk 873 406 1,279 Peak Period Walk 151 780 931

Drive 28 245 273 Drive 13 726 739SubTotal 901 651 1,552 SubTotal 164 1,506 1,670

Off-Peak Period Walk 1,467 1,153 2,620 Off-Peak Period Walk 245 924 1,169Drive 72 103 175 Drive 21 632 653SubTotal 1,539 1,256 2,795 SubTotal 266 1,556 1,822Total 2,440 1,907 4,347 Total 430 3,062 3,492

Grand Total 11,521 10,368 21,889 Grand Total 818 4,646 5,464

Vehicles/Household

Vehicles/Household

Vehicles/Household

Vehicles/Household

Vehicles/Household

Vehicles/Household

Development of a Base Year 2009 Transit Trip Table

• Developed CUBE/TP+ Survey-Based Trip Table (Fall ‘09)– Stratified by:

• Time of Day (Peak and Off-Peak)• Mode of Access:

–PNR & Walk–KNR treated like walk (with drop-off location treated as PROD

end)• VCU and non-VCU trips stratified

• VCU Trips Stratified Separately– Operates under contract to GRTC– Free w/valid student/staff ID– Main to Downtown Campus shuttles & fringe parking– Policy of VCU students on BRT unknown

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Calibration of Transit Path Weights

• AECOM calibrated TRNBUILD path-building and assignment weights through iterative assignment of transit trip table

• Started with FTA “national experience” weights and tuned

• Final weights used were:– IVTT Weight = 1.0– Waiting/Transfer Waiting Time Weight = 1.5– Walk Time Weight = 2.0– Drive Time Weight = 2.0– Transfer penalty = 6.0 min per transfer– Walk speed = 3 mph

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2009 Weekday Modeled vs. Observed by GRTC Route

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Group Route Number2009 Surveyed

Boardings 2009 Survey Assignment

Local Routes 1/2 2,343 2,275 3/4 1,658 3,079 5 - 6 3625 3,639 7 1,010 1,391 8 - 10 1,856 1,172 11 155 56 13 312 - 16 630 260 18 249 384 19 294 333 20 32 - 22 327 121 24 430 556 32 2,176 2,520 34 1,649 1,835 53 - 37 1,902 1,676 61 - 62/63 3,304 2,840 67 155 68 19 - 70/71 1,406 1,373 72/73 1,457 1,301 74 902 568 91 219 367 92 17 - 93 63 27 100 - 999 - Express/BRT - Subtotal 26,035 25,928

Group Route Number2009 Surveyed

Boardings 2009 Survey Assignment

Express Routes 26 196 480 27 228 178 28 26 84 29 464 275 64 214 242 65 - 66 169 81 176 82 82 308 371 Subtotal 1,612 1,881

VCU Routes 84 3,162 3,248 86 987 862 87 804 374 95 - 99 577 Subtotal 4,953 5,061

Total 32,600 32,870

Developing Project Forecast/FTA Justification Materials• 2009 demand grown to represent 2015 no-build using MPO estimates

of POP growth

• Development of CUBE/TP+ process where calibrated path-weight parameters are multiplied to create an equivalent IVTT “transit impedance” score for each I-J pair

• Alternative specific effects for BRT built into the transit impedence– 5% discount for BRT IVTT– 5 min. “constant effect” for BRT only riders, 2 min for BRT & Local Bus Riders

• Compare the “transit impedance” between alternative and use an elasticity range of -0.3 (low) to -0.7 (high) to estimate “new” riders through alternative progression (No-Build – TSM Baseline – Build)

• Assign the resulting transit trip tables to the network for project ridership forecasts

• Compare resulting transit impedance to estimate Transit System User Benefits

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Bump in the Road – New PNR Lot

Park-and-Ride at Staples Mill (near end of line)– Scale is small (about 100 spaces)– No existing PNR behavior in corridor - PNR’s are in fringe suburban

areas feeding express buses to Downtown– Since modest number of spaces, we assumed:

• 75% utilized (additional new riders, about 150)• Calculate UB’s by treating these riders as “new” riders (i.e. half the benefit)

Not sophisticated, but how far could we be off?

Bigger transformation would require more sophisticated approach.

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Project Extensions• GRTC used on-board survey data to plan their 2015 bus network

• Refinements to transit networks/procedures were embedded in the VDOT Richmond/Tri-Cities Forecasting Model update (2012) – Bus speeds– Network coding– Path/assignment weights

• On-Board survey used for RTFM mode choice calibration targets

• Comprehensive on-board transit survey allowed us to develop procedures to simulate “non traditional” trips:– Drop-off transit trips to non-formal locations – VCU fringe parking trips

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Summary/Wrap-Up

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• Small Starts project justification requires forecaster to tell the story of the project “who will benefit and why”

• Data driven approach is ideal for developing patronage forecasts for incremental transit service improvements:

– Routed in real traveler patterns, not models– Transparent & easy to articulate benefits of projects– Easy to describe cause and effect in the forecasts– Forecaster can articulate risk by segmenting:

• What is “known” from the survey data (X riders in the corridor who will save at least 5 min. from the project)

• What is not “known” (penetration of choice market, given BRT introduction)

• FTA was very supportive of approach

Acknowledgements Virginia Department of Rail & Public Transportation – Amy Inman

GRTC – Larry Hagin and Scott Clark

VDOT – Rick Tambellini, Juyin Chen and Paul Agnello

FTA – Jim Ryan, Ken Cervenka, Nazrul Islam

AECOM – Jeff Bruggeman

Connectics Transportation Group – Jim Baker

Michael Baker – Lorna Parkins, Scudder Wagg

Parsons Transportation Group – Gibran Hadj-Chikh

VHB - Ram Jagannathan

Project “Graduates” – Chandra Khare, Abishek Komma, Jeremy Raw, Bill Woodford, Mike Lambert, Frank Spielberg and Sharon Hollis

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Thank You!

Jeffrey.Roux@aecom.com

Prasad.Pulaguntla@aecom.com