Using the Federal Transit Administration (FTA) Simplified Trips-on-Project Software (STOPS) for Transit Demand Estimation

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1 Using the Federal Transit Administration (FTA) Simplified Trips-on-Project Software (STOPS) for Transit Demand Estimation presented to 2014 ITE Mid-Colonial District and Mid-Atlantic Section Annual Meeting presented by Cambridge Systematics, Inc. Jay Evans, P.E., AICP and Xuemei Liu, Ph.D. May 19, 2014

2 Overview Project background Introduction to STOPS Project forecast Success factors

3 Project background FTA commissioned Cambridge Systematics (CS) to produce an independent ridership forecast for a streetcar project using STOPS CS assembled the project definition and necessary data to support the application of STOPS with the help of» the transit agency» the Metropolitan Planning Organization (MPO)» FTA and its other contractors Hand-off our STOPS work to the transit agency 3

4 Overview Project background Introduction to STOPS Project forecast Success factors

5 Introduction to Simplified-Trips-on-Project Software (STOPS) A simplified software package released by FTA, which» Quantifies FTA s trips-on-project evaluation measure for FTA major capital funding» Takes advantage of data that are generally available off the shelf to permit a user to develop transit project demand forecasts with relatively modest effort» Produces reporting which permits straightforward review and interpretation of the likely beneficiaries of the proposed transit improvement 5 Source: FTA An Overview of STOPS

6 STOPS internals 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 HBW = Home-Based Work HBO = Home-Based Other NHB = Non-Home Based PnR = Park-and-Ride KnR = Kiss-and-Ride Modifications» CTPP data rather than trip generation and distribution» GTFS rather than coded transit network» Peak highway impedances from MPO model CTPP = Census Transportation Planning Package (2000) GTFS = General Transit Feed Specification 6 Source: FTA Presentation to Florida Model Task Force, March 2014

7 Calibration of STOPS Nationally calibrated; local adjustments» National: against ridership on 24 fixed guideway system» Local transit: Against CTPP HBW attraction district-level transit shares Against total transit ridership» Local fixed-guideway: against station counts Source: FTA Presentation to Florida Model Task Force, March 2014

8 Read more about it Learn more about the calibration, capabilities, and limitations of STOPS in FTA s An Overview of STOPS available via the website 8

9 Overview Project background Introduction to STOPS Project forecast Success factors

10 Project overview Project characteristics» 2.6 mile modern streetcar line» Mixed traffic operations» Stops every 0.25 mile» 12-minute headway during core hours of operation» 10.3 miles per hour operating speed Principal markets for the project» Central Business District (CBD) circulation» University trips» Connection to existing fixed guideway 10

11 Streetcar and existing guideway stations 11

12 STOPS inputs FTA website Census derived data» Shape files for CTPP geography and census blocks» CTPP Parts 1, 2 and 3 in ASCII format» Census 2010 block boundary file Transit agency existing service data» 2013 GTFS timetables» 2012 station boarding counts for existing fixed guideway» 2012 regionwide transit ridership 12

13 STOPS inputs (continued) MPO socioeconomic files and skims» Shape file with zones and 2000 and current population/employment» Current zone-to-zone highway travel time and distance Project sponsor project characteristics» Station locations, park-and-ride, and at-grade versus grade-separated» Service plan with detail sufficient to construct a schedule 13

14 STOPS output Calibration summary District-to-district model summaries, including linked transit trips on fixed guideway/project based on trip purposes, transit modes, access modes and household auto-ownership District-to-district incremental linked transit trips and automobile person-miles of travel change Station-to-station flows 14

15 STOPS output summary trips by purpose, access mode, and automobile ownership HBW HBO NHB All Trip Purpose 15 0 Auto 1 Auto 2+ Auto All Auto Ownership Walk Access KNR Access PNR Access All Access Walk Access KNR Access PNR Access All Access Walk Access KNR Access PNR Access All Access Walk Access KNR Access PNR Access All Access

16 STOPS maps 16

17 STOPS maps (continued) 17

18 STOPS interpretation Explored mode of access and trip purposes» Walk access was dominant» Commuter travel was dominant Explored new transit riders versus simply shifting riders» Location, quantity, and transit-dependent status Calculated and reviewed automobile miles traveled changes» Explored average length of new transit trips 18

19 STOPS considers routine weekday trips Reviewers of STOPS forecasts must be mindful that STOPS considers routine weekday trips by residents It does not consider student travel or visitor travel in geographically specific markets An external method is needed for forecasting university trips or visitor trips if they would be important to a forecast of trips on a specific project In this case, the STOPS ridership forecast for the streetcar was supplemented with a forecast of the university market developed with procedures other than STOPS 19

20 Overview Project background Introduction to STOPS Project forecast Success factors

21 When to use STOPS New Starts or Small Starts projects» Regional model is not currently available or requires efforts beyond the current budget and time constraint to make usable» Quality control to provide a second ridership forecast for comparison to a forecast by other methods STOPS applications require understanding and care» Regional unlinked trips required» Need for consistent zone level socioeconomic forecasts» Art of calibration to existing station volumes

22 Keep in mind capabilities and limitations Fixed guideways, not local buses and not roadways Translation of trip patterns over time based on population and employment, not accessibility STOPS considers routine weekday trips by residents Improved representation of work-trip markets, less certain for others

23 Contact information John (Jay) Evans, P.E., AICP Xuemei Liu, Ph.D. Cambridge Systematics, Inc Hampden Lane, Suite 800 Bethesda, MD