All ETDs from UAB

Advisory Committee Chair

Virginia P Sisiopiku

Advisory Committee Members

Andrew Sullivan

Da Yan

Document Type

Thesis

Date of Award

2020

Degree Name by School

Master of Science in Civil Engineering (MSCE) School of Engineering

Abstract

In the recent years, the use of Transportation Network Companies (TNCs) such as Uber/Lyft as a mode of travel has been growing at a significant pace. Despite the rapid growth of several TNC markets, analyses of potential and actual impacts of TNCs presence on preferences and travel patterns of TNC-aware users are still very limited. Such analyses require detailed trip data which are not easily available due to privacy concerns, as well as technical and financial feasibility issues. To address some of these issues, the objective of this study was to document the factors that influence transportation users in the Birmingham, AL region to select TNCs such as Uber/Lyft for completing typical day trips. In order to meet the study objective, a travel diary questionnaire survey was developed in accordance with the Institute of Transportation Engineers (ITE) Manual on Transportation Engineering Studies and used to obtain information about travel preferences, typical trips, and demographic data. The Qualtrics Research Core tool was used to develop the questionnaire and administer the survey. The questionnaire was used to survey over 451 transportation users in the Birmingham Metro Area. The survey participants provided detailed trip information for a typical 24-hr day along with demographic data and travel preference information. The analysis of responses shed light on users’ awareness, usage and proliferation of TNC services in the region. The survey responses were used to understand the leading reasons and conditions driving the use of TNCs services in the Birmingham Metro Area. The document introduces the scope of the study, describes the study approach, discusses findings from the analysis of responses, and summarizes conclusions, and impacts. The findings provide high-resolution micro-level indicators of travel preferences and behaviors in a TNC-served area, which is a much-needed type of information for researchers and planning agencies.

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