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Center for Urban Transportation Research | University of South Florida The TBEST Framework for Data Analysis and Forecasting Rodney P. Bunner October 16,

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Presentation on theme: "Center for Urban Transportation Research | University of South Florida The TBEST Framework for Data Analysis and Forecasting Rodney P. Bunner October 16,"— Presentation transcript:

1 Center for Urban Transportation Research | University of South Florida The TBEST Framework for Data Analysis and Forecasting Rodney P. Bunner October 16, 2013 Public Transit Modeling

2 Agenda 1.Motivation and Use 2.GIS Specifications 3.TBEST Framework Components a)Data Management b)Data Interoperability c)Data Requirements d)Model Engine e)Analysis and Reports 4.Next Steps

3 Motivation  FDOT/planners wanted a software tool for short-term transit service planning – designed specifically for transit.  Serve as FDOT provided ridership estimation technique for State mandated Transit Development Plans (TDPs)  Transit Boardings Estimation and Simulation Tool (TBEST) has been in production for several years and is on its 4 th Major Version (4.1).  FDOT is continually supporting the improvement of TBEST.

4 TBEST in Florida Major Benefits:  Standardized modeling method to ensure consistency and equity among agencies  TBEST reduces burden on FDOT for evaluating a variety of ridership estimation methodologies  TBEST reduces burden on agencies to prepare and conduct more expensive and complex modeling efforts  Leverage TBEST data and software framework to support multiple transit agency tasks: Mobility Studies NTD Route Miles Market Analysis Network Accessibility Service Planning Comprehensive Operational Analysis (COA) Grant Applications FTA Title VI Analysis

5 TBEST Elsewhere Various projects inside and outside of Florida: RVTD (Oregon) Calibration and Implementation Los Angeles Metro Calibration CAT (Savannah) Strategic Plan TheT (Ft. Worth) Model Development LYNX (Orlando) Service Planning Implementation PennDOT Pilot Project PeopleMover (Anchorage, AK)

6 TBEST GIS Specifications Desktop application requiring ArcGIS 10.1 Basic license Utilizes ArcGIS Engine for map display, spatial analysis and network editing SQL Server 2008 R2 (Express or Enterprise editions) No Network Analyst or ArcSDE required Utilizes ESRI Map Services, Bing Maps or preformatted.mxd for base map No fee for TBEST except ArcGIS license

7 Components – Data Management TBEST manages data specific to individual transit systems Each transit system is composed of scenarios which contain editable routes, segments, stops, socio- economic data and network attributes Validation specific to each transit system All GIS/database files managed internally Download pre-formatted SE data, transit systems and model definition packages Easily create current or future year scenarios TBEST managed Transit Systems

8 Components – Data Management TBEST User Interface

9 Components – Data Interoperability GTFS Import – Imported networks for FL agencies with GTFS feeds – Utilized nationally in Ft. Worth, RVTD, Los Angeles, Savannah GTFS Export – Export TBEST “planning” network into GTFS – Added TBEST attributes to exported data including ridership and stop amenities ArcGIS – Export TBEST maps and data into ArcGIS – Import route alignments into TBEST from outside data sources – Export “loaded networks” into geodatabases

10 Components – Data Requirements O RIGINAL D ATA R EQUIREMENTS Census 2000 Employment – FDOT provided InfoUSA address-based data Manually coded Route Network Special Generator Specification C URRENT D ATA R EQUIREMENTS Census 2010 American Community Survey Employment – FDOT provided InfoUSA address-based data – Optionally include locally provided zonal data Land Use – Florida Department of Revenue parcel data ITE Trip Generation Tables GTFS network import and full network editor Special Generator and Stop Amenity Specification

11 Components – Model Engine Micro-level model which simulates transit ridership at the level of the individual stop: by route, direction and time period Designed to capture both walk access market and network accessibility Model equations estimate direct and transfer boardings Accommodate service features of fare, speed, frequency, etc. Accommodate fundamental differences in route types (local, circulator, express) Automated Validation – Users supply observed ridership and TBEST calculates model application adjustments…allows TBEST to adapt to different urban locations without developing new model equations (transferable)

12 Components – Model Engine Multiple Model Management Users are able to maintain multiple model structures which can be applied to model scenarios Editable Model Structures Users can add, delete or modify coefficients, land use trip rates, and network and market accessibility parameters Available Models

13 Components – Model Engine BRT Sensitivity - Users specify the implementation level of specific route-level BRT characteristics and TBEST will adjust base ridership forecasts with an empirically derived adjustment factor

14 Components – Analysis and Reports Stop, Segment, Route and Regional distribution reports with supporting maps

15 Components – Analysis and Reports Scenario Comparison and Mobility Threshold service recommendations

16 Components – Analysis and Reports TDP Summary Report - Summarizes annual service area pop, employment, performance, and service for all scenarios in a TBEST transit system

17 Components – Analysis and Reports Land Use Market Analysis

18 Components – Analysis and Reports Socio-Economic Market Analysis

19 Components – Analysis and Reports Network Accessibility Analysis

20 Steps Underway October 2013 – Release TBEST 4.1 – Contains online Video Tutorials – Classroom training early 2014 January 2014 – Enhanced FTA Title VI and Environmental Justice Analysis and Reporting June 2014 – Parcel Editor – Integrate Observed Ridership for COA support October 2014 – Network Accessibility Composite Measures

21 C ONTACT I NFORMATION Rodney Bunner Transportation Technology Specialist Steven Polzin, Ph.D. Director Mobility Policy Research Thank You! Xuehao Chu, Ph.D. Senior Research Associate


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