Memorandum To Shi-Chiang Li, Hui Zhao (FDOT D4) Pages 29 CC Scott Seeburger (FDOT D4), David Schmitt (CTG) Subject Southeast Florida STOPS Planning Model – Calibration Memo From Sujith Rapolu and Ashutosh Kumar (CTG), Hongbo Chi (AECOM) May 31st, 2016 (minor updates: July 19th, 2016 nd Date and November 22 , 2016) AECOM and Connetics Transportation Group (CTG) were asked by the Florida Department of Transportation (FDOT) District 4 to develop a STOPS (Simplified Trips on Project Software) planning model for the tri-county region of Southeast Florida. The latest version of the Southeast Florida Regional Planning Model (SERPM) version 7 is not informed of transit rider travel patterns in some aspects to be reliably used for project-level ridership forecasting. Thus, the Southeast Florida (SEFL) STOPS Planning Model is implemented to supplement the need for ridership forecasts for transit projects. This memorandum summarizes the calibration results for the SEFL STOPS Planning model. The document describes the various inputs and parameters in STOPS, followed by the calibration results for all the major transit agencies in the tri-county region. A comparison with the results from SERPM 7 and SERPM 6.7.3 is included in the Appendix. A separate user guide has been developed which contains instructions on how to apply this model for a specific fixed-guideway transit project. STOPS Inputs and Parameters STOPS is a limited implementation of the conventional “4-step” travel demand model. It is a tool developed by the Federal Transit Administration (FTA) to quantify the measures used by FTA to evaluate and rate New Starts and Small Starts projects. STOPS Version The modeling team used the beta version of STOPS 2.00 (build date: 02/19/2016) for implementing the plannning model for Southeast Florida. This version of STOPS is still in development and is expected to be officially released by FTA soon. The major difference between this version and the official version 1.50 is that the 2006-2010 American Community Survey (ACS) data is included for analysis in addition to the 2000 CTPP data being used in version 1.50. The regional model takes advantage of the ACS data. 1 Definition of Current Year All the results presented in this memo are for the ‘current year’. The current year is defined as the most recent year for which input data is available. Since a recent rider survey was not available on all the agencies being modeled, for the regional model, the current year represents year 2015 in terms of population and employment data. The auto skims used in STOPS are from the 2010 Southeast Florida Regional Planning Model (SERPM) version 7.061. All the transit routes in the tri-county region are from the year 2015. The ridership data, such as the regional transit boardings, and stop level Automatic Passenger Counter (APC) data are also from the year 2015. Hence, the year 2015 is referred to as the “current year” for the SEFL STOPS Planning model. Transit Network STOPS uses the General Transit Feed Specification (GTFS) format to represent the transit service. The SEFL STOPS Planning model includes the 2015 year GTFS data for Miami- Dade Transit (MDT), Broward County Transit (BCT) and South Florida Regional Transportation Authority (SFRTA) and 2013 year GTFS data for Palm Tran. These files represent the “existing scenario” in STOPS. There were no significant changes between 2013 and 2015 on Palm Tran routes and hence a newer GTFS file would have very little impact on the results presented here. The GTFS data has scheduled time-tables for Tri-Rail, Metrorail, Metromover in downtown Miami, Miami International Airport people mover and all local, limited stop and express buses operated by the three bus agencies, including the I-95 and I-595 express buses. The GTFS data does not include Tri-Rail shuttles, BCT community buses and any other buses/trolleys operated by the cities. The ridership on these routes is not very significant in comparison to the overall regional transit ridership and hence the lack of these routes in the SEFL STOPS Planning model will not affect the calibration results. In addition, the calibration targets excluded ridership on these shuttles. MPO Auto Skims STOPS uses zone-to-zone current year peak period automobile travel times from the regional travel demand forecasting model. The modeling team obtained these skims from the 2010 year SERPM 7.061 model. The demographic and highway network changes between 2010 and 2015 are not that significant to have any meaningful impact at the regional level on the findings presented in this document. MPO Population and Employment Data The modeling team obtained the 2015 MPO population and employment data from SERPM 7.061 by interpolating the 2010 and 2040 Long Rang Transportation Plan (LRTP) data. In addition to the current year data, STOPS v2.00 also requires 2008 year data. The modeling team used the 2010 MPO data as a proxy for the 2008 CTPP-year data. While applying any travel demand model, including the SEFL STOPS Planning model, users should always verify the existing and future land use assumptions in their corridors. District System STOPS uses districts to define a logical grouping of Census TAZs around the transportation corridors. Among other purposes, district definitions are also used for : 1) Growth factoring of the 2006-2010 ACS trips to estimate current and forecast year trips using MPO population and employment, and 2) summarizing and mapping STOPS model output. Figure 2 1 shows the district definitions used for the SEFL STOPS Planning model. These districts in STOPS are user-defined and are project-specific. Users should follow the guidelines mentioned in the STOPS user guide. Figure 1: Districts Definitions for the SEFL STOPS Planning Model 3 Region-wide Boardings STOPS requires the user to input current year regional weekday transit boardings. Table 1 shows the average weekday boardings used in the model. Table 1: Average Weekday Region-wide Ridership Average Availability Weekday Source of stop Unlinked Trips level data? Palm Tran 39,025 October 2014 and February 2015 APC data Yes BCT monthly ridership reports. Average of 12 BCT 117,893 No months in 2015 is used. September to November, 3 month 2015 APC data. This data is scaled to the corresponding 3 month MDT buses 222,184 Yes average bus ridership obtained from the MDT monthly ridership reports. Metrorail 76,664 MDT monthly ridership reports. Average for Yes September to November 2015 is used to be Metromover 34,616 consistent with the APC data for the buses. Yes SFRTA’s monthly operations reports. Average for Tri-Rail 13,757 April-December 2015 is used to be consistent with Yes the reopening of the MIA station in April 2015. Region-wide 504,119 Stop level ridership was available for all agencies except for BCT and the MIA people mover. Regional Linked Transit Trips STOPS also has the ability to calibrate to regional linked transit trips by trip purpose (HBW, HBO, NHB) and market segment (0-car, 1-car, 2+car households). The model doesn’t use regional linked transit trips targets because the survey data wasn’t readily available and as a result, the default STOPS parameters are used. Park-and-Ride (PNR) Locations In addition to the stop-level APC data, the modeling team also coded all PNR locations in the tri-county region. The PNR locations are listed in Appendix C. Station Groups Station groups are a key element of the STOPS internal calibration process. These groups are used for reporting and for aggregations for station-level calibration. The modeling team defined various groups for all the fixed guideway stations and bus stops in the region. The groups are summarized below: · 4 groups for all Tri-Rail stations · 7 groups for all Metrorail stations · 3 groups for Metromover stations 4 · Groups for bus stops with APC data generally align with the district definitions. All bus stops in a given district are coded with the same station group. o 6 groups for Palm Tran bus stops o 11 groups for MDT bus stops, including a separate group for all stops used by the busway routes o There is no stop level data for BCT, and hence no groups have been defined for BCT bus stops The station group calibration in STOPS was set to ‘09- Full Group Calibration’ because a comprehensive stop level database was available on stops covering 80% of the region-wide ridership. SEFL STOPS Planning Model Calibration The model is calibrated for the year 2015. STOPS currently has a limit of 10,000 stations (or bus stops) with counts that can be used for station group calibration. This limit is exceeded when both MDT and Palm Tran bus stops are included. Given the magnitude of boardings on the MDT system in comparison to Palm Tran, only the APC data for MDT is used for calibration purposes in the regional model. The User Guide details the scenarios under which the Palm Tran APC data will be used for calibration. All the calibration results presented in this memo use MDT stop level APC data, in addition to all the fixed guideway station level data. Even without the APC data for Palm Tran, STOPS is able to estimate the boardings on Palm Tran routes reasonably well. Regional Transit Trip Estimates For the existing scenario, STOPS estimates 468,540 region-wide transit boardings. Since the observed boarding is set to 506,046, a regional calibration factor of 1.08 is applied. After this adjustment is done, STOPS estimates 503,202 region-wide boardings and 331,941 linked trips. The region-wide boardings estimate is not exactly equal to the observed boardings target because STOPS also has to calibrate the stop level APC data, resulting in some deviation from the target boardings.