STOPS
presented to
FPTA/FDOT/CUTR Professional Development Workshop
presented by
Jim Ryan, FTA
Bill Woodford, RSG
David Schmitt, AECOM
June 4, 2014
Parts of the Presentation
• Trips-on-project forecasting
• How STOPS works
• Making STOPS work for you
• Experience thus far with STOPS applications
2
Trips-on-Project Forecasting
• Topics
– FTA motivations
– Options for project sponsors
– Implications for FTA reviews
– Availability of STOPS and tech support
– Plans for upgrades and extensions
3
FTA Motivations
• Streamlining
– Project-evaluation measures
• Mobility trips on project (total, transit-dependent)
• Environment change in auto vehicle-miles traveled
• Cost effectiveness project cost per trip on project
– Travel forecasting
• FTA to provide a simplified method
• Simplified method to be “good enough”
• Reductions in level of effort (sponsors and FTA)
4
FTA Motivations (continued)
• Resulting design standards for STOPS – Focus on the purpose: trips on major-capital projects
• Urban fixed-guideways: BRT, streetcar, LR, CR, HR
– Use readily-available inputs • Do not require any primary data collection
• Rely on public, standardized data sources where possible
– Keep it simplified for users • Provide a graphical user interface
• Limit the number of switches, levers, and dials
– Make it reasonably accurate • Calibrate with data on many existing systems/lines
• Adjust to local conditions
5
Options for Project Sponsors
• Project sponsors may prepare forecasts with:
– Regional travel models
– Incremental models
– STOPS
• Sponsors may provide to FTA forecasts from:
– Regional travel models only
– Incremental travel models only
– STOPS only
– Any combination of the above
Augmented with “special market” models, as needed
Augmented with “special market” models, as needed
6
Implications for FTA Reviews
Source of forecast
FTA review of submitted forecasts
Transit rider survey data
Properties of the travel model
Validation vs. current riders
Plausibility of forecasts
Regional model
Incremental model
STOPS
Substantial scrutiny
Modest scrutiny
Limited scrutiny 7
Note that these reviews pertain
to formally submitted forecasts.
They do not reflect any
informal technical assistance
that may have been provided
by FTA staff.
Availability of STOPS and Tech Support
• Download from the FTA website
– http://www.fta.dot.gov/grants/15682.html
– Software
– User guide
– Sample application
• Request help (after good-faith local effort)
– Pete Mazurek (FTA; contact info on STOPS page)
– Assistance from FTA contractor at FTA discretion
8
Plans for Upgrades and Extensions
• STOPS version 2.0
– More recent worker flows (ACS? LEHD?)
– Special markets
– On-screen editing of transit lines
– Additional calibration data
– Automated disaggregation of overly large zones
• Software for incremental approach – “Steps”
– Grounded in rider survey data
– Incremental mode choice
– Many other components taken from STOPS 9
How STOPS works
• Topics
– Overview
– Data sources
– Calibration(s)
10
Overview
• Modified 4-step model structure; trip based
– Zone-to-zone travel markets
– Three trip purposes (HBW, HBO, NHB)
– Peak and off-peak transit service levels
– Walk, PnR, KnR access to transit
– Stratified by household auto-ownership
• Modifications
– CTPP data rather than trip generation & distribution
– GTFS rather than coded transit network
– Peak highway impedances from MPO model
11
Overview (continued)
12
Hwy times, dists
Calculation
Trn times, xfers
Trn load
GTF path
GTF networkDemographics
Travel flows
Mode choice
Flows by mode
Delta auto VMT Trn summariesFlow summaries
External file
Internal file
STOPS model
CTPP (ACS)
Adaptations
Public fileNotes: -- Demographics, travel flows, and travel times are zone-to-zone -- Networks and loaded volumes are link-based -- “Adaptations” include translation to the year of the forecast plus: -- Conversion of worker flows to Home-Based-Work trip flows -- Scaling of HBW flows to represent Home-Based-Other flows -- Development of Non-Home-Based flows from HB transit trip ends
Highway Supply Demand Transit Supply
Data Sources
• Public
– Census: CTPP 2000 and Census 2010
– General Transit Feed Specification (GTFS)
• MPO
– Zone-specific population and employment
– Zone-to-zone highway travel times and distances
• Sponsor
– Coordinates of station locations on the project
– Service plan for the project and its integration
13
Calibration(s)
• Nationally calibrated; local adjustments
– National: against ridership on 24 FG systems
– Local transit:
• Against CTPP HBW attraction district-level transit shares
• Against total transit ridership
– Local fixed-guideway: against station counts
14
National Calibration
15
Metro area Comm. rail Heavy rail Light rail Streetcar BRT Total
Atlanta 1 1
Charlotte 1 1
Denver 1 1
Phoenix 1 1
San Diego 1 2 3
Salt Lake City 1 1 1 3
Subtotal 2 1 6 0 1 10
Fixed-guideway systems with rider-survey datasets
National Calibration (continued)
16
Metro area Comm. rail Heavy rail Light rail Streetcar BRT Total
Kansas City 1 1
Houston 1 1
Minneapolis 1 1 2
Nashville 1 1
Norfolk 1 1
Portland 1 1 1 3
San Jose 1 1
Seattle 1 1 1 3
St. Louis 1 1
Subtotal 4 0 7 2 1 14
Total 6 1 13 2 2 24
Fixed-guideway systems with rider counts
National Calibration (continued)
17 0
50000
100000
150000
200000
250000
300000
0 50000 100000 150000 200000 250000 300000
STO
PS
Mo
de
led
Rid
ers
hip
Observed Ridership
These results reflect
the national
calibration and the
individual local
adjustments to total
transit ridership but
NOT the adjustment to
local station counts.
Calibration results
Weekday fixed-guideway trips
Making STOPS Work for You
• Topics
– Resource requirements
– Inputs – things you should know
– Reports and other outputs
18
Resource Requirements
• Inputs - CTPP worker flows - GTF transit file(s) – and edits - MPO population/employment - MPO highway times / distances
• Staff - Journeyman travel forecaster
• Computer - Mid-range laptop
• Other models - Special-market models if needed
• Time - Setup: ≈2 weeks (actual effort, not calendar)
- Forecasts: 1-3 days/scenario 19
4-8GB RAM 500-1000GB storage + floating-point performance
Inputs – Things You Should Know
• CTPP 2000
– Need to know the geography type
– Need all states relevant to your project
– Available for download on the FTA STOPS webpages
• Census 2010 block-boundary file
– Yes, 2010; it describes density of current street grid
– Available for download on the FTA STOPS webpages
20
Inputs – Things You Should Know (continued)
• GTFS data
– Current system
• From every transit agency relevant to your project
• Check for publicly available data from your agency at http://code.google.com/p/googletransitdatafeed/wiki/PublicFeeds
• If not listed, check with your transit agency
– Changes (project, project-integration, future year)
• No on-screen editor available
• Text-editing of the various GTFS data files
• Prioritization of changes to be coded
• Planned upgrade in Version 2.0 21
Inputs – Things You Should Know (continued)
• MPO files
– Population and employment by zone
• Consistent series: 2000, current year, horizon years
• Formatted in a GIS file: zone boundaries & their attributes
• Care needed to ensure consistency if merging MPO files
– Zone-to-zone highway impedances
• Consistent series: current year, horizon years
• MPO files in format generated by travel-model software
• Need conversion to CSV format (large files!)
– Consistency in geographic definitions
• MPO files must use consistent zone definitions
• MPO files and CTPP data may use different zones
22
Reports and Other Outputs
• Main STOPS report
– Calibration summary
– District-to-district and station-to-station flows
• Total linked transit trips
• Incremental linked transit trips: Build minus No-build
• Linked transit trips that use the project
– Station volumes
• By mode of access at the production end of the trip
• Parallel tabulations of existing, No-build, and Build volumes
– District-to-district changes in person-miles of travel in automobiles
23
Reports and Other Outputs (continued)
• Graphical outputs
– Trip ends (productions or attractions) selected by:
• Existing, No-build, Build, project, trip gains, or trip losses
• Attraction district or production district
• Transit path-type
• Access mode
• Trip purpose
• Household auto-ownership
24
Experience Thus Far with STOPS
• Topics
– Initial applications
– Plausibility of forecasts
• For existing fixed-guideways in current year’s No-build
• For proposed projects
– Ongoing refinements to STOPS
– Some lessons learned
25
Initial Applications (known to FTA)
26
Metro area CR HR LR SC BRT Metro Area CR HR LR SC BRT
Salt Lake City 1 1* Raleigh / Durham 1 1
Phoenix 1* Charlotte 1
Denver 1* Albuquerque 1
Lexington 1 Indianapolis 1
Washington 1 1 Buffalo 1 1
Chicago 1 Cleveland 1 1
Seattle 1 Northern Indiana 1
Kansas City 1 1 Sacramento TBD
SF Bay Area 1 Houston TBD
Phoenix-Tucson 1 Dallas / Ft. Worth TBD
South Florida 1 1 Twin Cities TBD
Totals 5 1 3 6 10
* Applications prepared by FTA contractors
Plausibility of Trips-on-Project Forecasts
• Existing fixed-guideways
– Constrained to actual volumes (for station groups)
• Close matches where useful count data are available
• Accurate predictions for (4 of 4) recently opened projects whose station-count data were not available to STOPS
• Proposed projects (not in Florida)
– Compared to forecasts from local methods
• Two cases of STOPS > local by 40 percent
• Three cases of STOPS ≈ local within 10 percent
• Two cases of STOPS < local by 50 percent
• One case of STOPS < local by 80 percent
– Note that all STOPS and local forecasts < 18k
27
Ongoing Refinements to STOPS
• Version 1.01 (September 2013)
• Version 1.02 (February 2014) – User control of application subarea within metro area
– Ability to process GTFS calendar_dates file
– Tabulation of trips-on-project measure for bus projects
– New report on total boardings for every route
– New index to reports
– Formatting of intermediate files as binary rather than text to reduce file sizes and processing times
28
Ongoing Refinements to STOPS (continued)
• Version 1.03 (under development) – Higher maximum #stations: 10,000 total, 360 in sta-sta report
– Capability to split CTPP zones
– Early warning of #zones or #stations exceeding limits
– Faster pathbuilding (now 1/3 of v1.02 time for large systems)
• Fewer KnR connections to bus stops
• Smarter tree pruning
– New report on impedances for selected paths
– Revised mode-of-access reporting for stations
– Downsized station-to-station reporting
– Others to be determined? 29
Some Lessons Learned
• STOPS applications need understanding and care
– District definitions
– Clone selections
– Station grouping
– Classification of BRT projects: bus vs. fixed guideway
– Regional unlinked trips required
– Data, not “data”
– Need for consistent zone-level SE forecasts
– Art of calibration to existing station volumes 30
Some Lessons Learned (continued)
• Largest lesson learned, so far:
– We’re all still learning about trips-on-project forecasting with STOPS.
– Written guidance is limited – largely because guidelines are still emerging.
– STOPS users must be experienced enough to recognize anomalies as potential problems.
– FTA will continue to support aggressively the ramp-up of STOPS applications.
• Resources to provide hands-on assistance
• Continual updates to the software and user guide 31
STOPS in Florida
• Two known applications, both in southeast Florida:
–Oakland Park BRT
– Tri-Rail Coastal Link (TRCL)
Oakland Park BRT
• Alternatives result from multi-modal AA in District 4 • Existing conditions
– 13.6 mi, 6 LD arterial roadway; 50,000-65,000 AADT – Route 72: 9,000 daily boardings; 15-20 min headways
• Key alternative – Bus Rapid Transit operating in Business Access and Transit (BAT) lane;
15 min headway – Local service continues to operate
• STOPS inputs/parameters – Broward County Transit’s GTFS data – Auto skims from SERPM 6.7.1 – 2000 and 2010 MPO ZDATA – Visibility factor = 0.0-0.2 – Systemwide and corridor-focused transit on-board surveys
Oakland Park BRT
Oakland Park BRT
• STOPS 7,150 project linked trips in current year
• Compared to two other independent forecasts
– SERPM 6.7.1: updated to adequately reflect local bus corridor travel patterns
– Data-driven/Simplified model: based on route-specific transit survey data
STOPS Data-Driven/
Simplified Model SERPM 6.7.1
Project Trips 6,500-7,200 3,900 3,600
Work vs. non-work split 56% vs. 44% n/a 50% vs. 50%
0-car vs. 1+-car split 34% vs. 66% n/a 54% vs. 46%
Walk-/drive-access split 91% vs. 9% 90% vs. 10% 94% vs. 6%
Oakland Park BRT: Findings
• STOPS forecasts are much higher than other two methods, probably a result of the underlying local service and the nature of the corridor
• Trip purpose and access mode results very comparable
Tri-Rail Coastal Link
• Extension to existing Tri-Rail service • Result of Systems Planning Study in District 4 • Existing conditions
– 85-mile corridor – I-95 AADT ranges from XX,XXX to 300,000 – Local bus, express bus and Tri-Rail in corridor today: ~60,000
boardings
• Build Alternative – 20-station extension
• STOPS inputs/parameters – GTFS data from the region’s 4 transit agencies – Auto skims from SERPM 6.7.2 – 2010 and 2040 MPO ZDATA – Visibility factor = 0.5
West Palm Beach/45th St./ Riviera Beach/Lake Park
Oakland Park/Wilton Manors
Palmetto Park Blvd.
CSX
/SFR
C
Atlantic Blvd.
36th St.
79th St.
163rd St.
192nd St.
Ft. Lauderdale Govt. Center
Hollywood/Hallandale
Toney Penna (Jupiter)
PGA Blvd.
Boynton Beach Blvd.
Atlantic Ave.
Hillsboro
Dania Beach/FLL
125th St.
FEC
RR
West Palm Beach Govt. Center/Okeechobee
Lake Worth
Miami Gov’t Center/Overtown
Lake Worth
Deerfield Beach
Pompano Beach
Ft. Lauderdale
Golden Glades
West Palm Beach
Metrorail Transfer
Miami Int’l Airport
Mangonia Park
Boynton Beach
Delray Beach
Boca Raton
Cypress Creek
Hollywood
Ft. Lauderdale/Hollywood Airport
Sheridan Street
Opa-locka
Hialeah Market
PA
LM
BE
AC
H C
OU
NT
Y
BR
OW
AR
D C
OU
NT
Y
MIA
MI-D
AD
E C
OU
NT
Y
KEY
Existing Station
Potential Initial Station
Proposed All Aboard Florida/
Tri-Rail Coastal Link Station
Maintenance and
Layover Facility
Airport
Seaport
Metrorail Green Line
Metrorail Orange Line
Northwood Connection
Pompano Beach Connection
Existing Tri-Rail system
Proposed TRCL
system
TRCL Forecasting Approach
• Local travel model is used for primary forecasts (SERPM 6.7.2)
– Calibrated to local conditions and Tri-Rail’s unique travel markets
• STOPS used to develop auxiliary set of forecasts and assist addressing uncertainty
TRCL STOPS/SERPM Results
STOPS SERPM 6.7.2
Project Trips 13,100 12,400
Work vs. non-work split 40% vs. 60% 61% vs. 39%
0-car vs. 1+-car split 36% vs. 64% 25% vs. 75%
Walk-/drive-access split 60% vs. 40% 40% vs. 60%
STOPS SERPM 6.7.2
Project Trips 16,300 19,600
Work vs. non-work split 38% vs. 62% 68% vs. 32%
0-car vs. 1+-car split 36% vs. 64% 21% vs. 79%
Walk-/drive-access split 59% vs. 41% 37% vs. 63%
Horizon Year (2040)
‘Current’ Year (2013)
TRCL STOPS/SERPM Results (2)
Year STOPS SERPM 6.7.2
Relative Difference
‘Current’ Year 2013 13,100 12,400 + 7%
Opening Year 2020 13,900 13,650 + 2%
Horizon Year 2040 16,300 19,550 - 17%
TRCL: Findings
• STOPS produced aggregate ridership figures similar to local travel models
– However, local models appear to produce more intuitive results for sub-markets (e.g., walk-access, transit dependents)
43
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