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NCTR is located at the Center for Urban Transportation Research (CUTR) at the University of South Florida. CUTR is recognized as one of the country's Best Workplaces for CommutersSM      


Research Project Description

Center Identification Number:

Project Title: FSUTMS Mode Choice Modeling: Factors Affecting Transit Use and Access

Principal Investigator: 

Principal Investigators: 

Dennis Hinebaugh, Transit Program Director 

Project Contact: 

Dr. Fang Zhao, PhD., P.E., Assoc. Professor/Assoc. Director Lehman Center for Transportation Research, FIU 


National Center for Transit Research (NCTR) at the Center for Urban Transportation Research (CUTR) 
University of South Florida 
Tampa, Florida 

External Project Contact: 

Ike Ubaka, Public Transportation Office, FDOT 


I. Project Objective

To develop a better understanding of significant factors that affect transit ridership and attempt to quantify such variables. This project will identify a set of variables that may be incorporated into FSUTMS modal split procedure that will result in improvement of transit ridership forecast by FSUTMS.

II. Project Abstract

It is difficult to obtain accurate transit forecast from four-step models, resulting in unrealistic expectations. Some possible causes include scarce of transit ridership information, omission of socioeconomic and other important factors in models, in accurate estimation of transit walk and auto access. With the aid of GIS technologies, this project will investigate the feasibility of incorporating more explanatory variables that have been known to significantly influence transit ridership in the existing FSUTMS modal split module to improve the predictive power of the model.

III. Task Descriptions

It is the intent of the NCTR at CUTR to subcontract this Work Order with the Lehman Center for Transportation Research at Florida International University.

Task 1 - Literature Review

A review of current FSUTMS mode choice models and existing literature on transit ridership forecasting will be conducted. The focus will be on transit ridership forecast, including the methodologies and the variables used. These methodologies will be evaluated based on their complexity, the results produced, the data requirements, relevance to FSUTMS, and ease of adaptation for FSUTMS. Results from this task will be summarized in Technical Memorandum 1.

Task 2 - Identification of Potential Explanatory Variables

In this task variables that potentially have a causal relationship with transit ridership will be identified. In addition to the variables currently used in FSUTMS, results from Task 1 will help identify additional variables. Potential variables will include characteristics of the trip to be made, characteristics of the person making the trip, characteristics of the household the person resides, characteristics of the household area (origin), characteristics of the transportation system, characteristics of the destination area of the trip. Potential variables will be evaluated based on two major considerations, i.e., whether data for the variables are readily available or can be collected easily and economically for both base and forecast years, and whether variables can be quantified accurately and reliably. Findings from this task will also be reported in Technical Memorandum 1.

Task 3 - Identification and Selection of Study Area(s)

In this task, suitable study areas will be identified. It is expected that the study area(s) will be located in the Southeast Florida region including the Miami-Dade and Broward counties. Description and justification of the study area(s) will be provided in Technical Memorandum 2, which will be submitted to the project managers for approval.

Task 4 - Data Acquisition, Collection and Processing

Data pertaining to the identified variables and study area(s) will be acquired/collected and processed in this task. Potential data include origin-destination trip survey data from the Southeast Florida Travel Characteristics Study, transit onboard survey from FDOT, socioeconomic data, land use data, DOQQs, transit route information, transit ridership data, and the 1995 NPTS. The data collection results will be reported in Technical Memorandum 3.

Task 5 - Transit Accessibility Evaluation

For this task, the urban forms will be studied from the viewpoint of transit walk accessibility, with GIS utilized as the primary analysis tool. The task will involve the selection of a set of TAZs that have various characteristics in terms of land use, street configuration, and presence and types of barriers. Analysis will then be made based on information such as street configuration, land use type, land use pattern, land use intensity, and transit onboard survey to derive typical accessibility measures for different types of land uses that may be used for base year model calibration and future year forecast. Auto access to transit will also be studied to determine the typical lengths of auto access links, and other possible factors that influence the distance a transit user may be willing to drive for accessing transit services. The results of this task will be reported in Technical Memorandum 4.

Task 6 - Selection of Explanatory Variables

In this task, variables that are significant in predicting transit ridership will be determined. Various modeling techniques will be used to test the significance of the variables in terms of their ability to influence transit ridership. Two types of analysis distinguished by their use of data sources will be performed. The first will be based on the trip survey data from the Southeast Florida Travel Characteristics Study. The second type of analysis will be based on the NPTS database.

Task 7 - Preparation of Final Report and Research Dissemination

The final report will summarize the findings and present the recommendations including how modelers around the state can use the information from this project to better calibrate and structure their mode split module in FSUTMS.

IV. Project Schedule, Milestones

Project Start Date: 





















Task 1




















Task 2




















Task 3




















Task 4




















Task 5




















Task 6




















Task 7





















V. Total Project Budget

Inventory and Analysis of Advanced Public Transportation

Systems in Florida

Budget Categories

State Share

Institute Director Salary


Faculty Salaries


Administrative Staff Salaries


Other Staff Salaries


Graduate Student Salaries


Undergraduate Salaries


Staff Benefits


Total Salaries and Benefits


Permanent Equipment


Expendable Equipment and Supplies


Domestic Travel


Foreign Travel


Computer Costs


Other Costs


Total Direct Costs


Indirect Costs (FIU)


Total Costs (Subcontract FIU)


Indirect Costs (USF) 




Notes: This budget does not reflect any federal participation.

The project team will include faculty, students, and secretarial and other support staff who will work directly on the project and whose costs are reflected in the direct costs of the project as listed above.


VI. Student Involvement

Graduate students will be used to collect, enter, and compile data and assist in the data analysis.

VII. Relationship to Other Research Projects

A number of research projects funded by FDOT and USDOT are relevant to this project. They deal with assessment of transit system modeling in the State of Florida, development of a short term transit ridership model that integrates transit demand and supply, transit level of service, and definition of transit capacity and service quality. The results of these projects will be carefully examined and incorporated into this research when useful.

VIII. Technology Transfer Activities/Peer Review

The results of this analysis will be provided to the FDOT through a series of technical memoranda and a final report. Copies of the final report will be provided to the Research Office, the State Public Transportation Administrator, Manager of the Transit Office, and the Florida Model Task Force members.

IX. Potential Benefits of the Project

The benefits of the project include identification and quantification of factors that affect transit ridership. This information can then be used to improve the travel demand models in better forecasting of transit use.

X.  TRB Keywords

Public transit, modeling, demand estimation, FSUTMS



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