Graduation Year

2010

Document Type

Thesis

Degree

M.S.C.E.

Degree Granting Department

Civil and Environmental Engineering

Major Professor

Abdul Pinjari

Co-Major Professor

Steven E. Polzin

Committee Member

Xuehao Chu

Keywords

transit demand modeling, trip rates, special generator, trip attraction

Abstract

TBEST is a comprehensive third generation transit demand forecasting model, developed by the FDOT Public Transit Office (PTO) to help transit agencies in completing their Transit Development Plans (TDPs). The on-going project funded by FDOT, related to TBEST, aims at further enhancing the capabilities of the TBEST model based on additional opportunities identified by the research team. The project focuses on enhancing TBEST’s capabilities in following areas: 1) Improving the precision of socio- demographic data by using property appraisal data (parcel data) and, 2) Improving the quality of data regarding trip attraction. Based on the improvement areas, this study aims at performing an exploratory analysis to 1) Identify the differences in activity levels (population and employment) within transit stop buffers due to change in input data i.e. from aggregate census data to disaggregate parcel data. 2) Explore various strategies (development of employment based trip attraction and, parcel land use based trip attraction and exploring how special generators are dealt with in the past studies) to enhance the trip attraction capability of the TBEST model. The results obtained from this analysis provide insights on the strategies and helps define suggestions to further enhance the precision of TBEST model. The results show that use of parcel level data improves the accuracy in capturing the activity levels within the catchment area of each stop. The results also suggest use of parcel land use based trip attraction for stops with special generators or use of interaction variable (interaction between special generator dummy and size (square footage etc.) of the special generator) to enhance the trip attraction capability of the TBEST model.

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