Graduation Semester and Year

2022

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Urban Planning and Public Policy

Department

Urban and Public Affairs

First Advisor

Qisheng Pan

Second Advisor

Sharareh Kermanshachi

Abstract

Transportation systems are vital in providing accessibility and mobility to city residents. Auto-oriented transportation systems have faced several challenges, including traffic congestion, crashes, and environmental pollution. Proponents of mass transit systems present them as a sustainable alternative to private automobiles. Although mass transit offers several benefits, these benefits are not very significant in rural, midsized, and low-density cities due to low public transit ridership. New modes of public transit, such as demand-responsive transport (DRT), also called on-demand public transport, have recently gained popularity across the United States. DRT systems are used in several mid-sized cities, either as an alternative to fixed route transit systems or in support of them by providing first and last-mile connections. This dissertation explores three questions about the DRT systems, including their usage, acceptance, integration, and safety impacts, using a wide range of data and methodologies. The first chapter introduces the topic, the broad research background, and the research questions. An outline of the dissertation is also presented. The second chapter investigates the usage and adoption of Shared Autonomous Vehicles (SAVs) – a demand-responsive transport system using an SAV pilot project in Arlington, TX, as a case study. The project is named RAPID (Rideshare, Automation, and Payment Integration Demonstration), which started operations in March 2021. This study used real-time trip-level ridership data from the RAPID project, surveyed the SAV riders, and developed a study based on ordered logistic regression to estimate the determinants of ridership frequency. The data analysis of real-time ridership data revealed that the spatial distribution of activities and service accessibility are important factors in forming current users’ travel patterns. The findings from the Order Logistic Regression showed that users from higher-income households are less likely to be frequent riders of the RAPID service. The impact of the usual mode of transportation on RAPID usage showed that those who usually walk, bike, or utilize the on-demand ridesharing services are likely to use SAVs more frequently than private vehicle users. The users with higher levels of safety perception are also more likely to be frequent users of the service. The findings of this study could provide planners with a better understanding of the SAV ridership patterns and guide decision-makers in establishing and adopting the appropriate policies for future SAV implementation projects. The second and the third chapters of this dissertation aim to analyze the impacts of ridesharing services on the number of traffic crashes and injuries using two DRT services, RideAustin in Austin, TX, and Via Arlington in Arlington, TX, as the case studies. We used an Interrupted Time Series Analysis (ITSA) and the Difference-in-Difference (diff-in-diff) analysis approach to investigate how these services were related to the number of traffic crashes and injuries in Austin and Arlington, respectively. The findings from both studies showed that the DRT systems were related to fewer traffic crashes and severe injuries. In the case of Austin, TX, these impacts would be more significant if the number of trips per block group was relatively higher. Via Arlington's availability was associated with fewer weekly traffic crashes and injuries in Arlington. The fourth chapter investigates the potential benefits of integrated DRT services by examining the three DRT services in Arlington, TX. We first identified the spatial patterns of the ridership on a localized scale by adopting the geographically weighted regression (GWR) for existing paratransit service, i.e., Handitran. Then, assuming that the existing ridership will be combined in the future with the shared autonomous vehicles, we looked at integration options based on the spatial patterns of supply and demand and payment options for the riders. The analysis results of the trip data suggest that the paratransit service, Handitran, is currently used by a small proportion of the eligible population, whose travel patterns vary in terms of age. The results of the GWR model indicate that the significant determinants of Handitran usage are the percentage of older adults, racial distribution, and household vehicle ownership; the coefficients of these factors vary across the city. The results of hot-spot analyses reveal that the integration of the services will improve the efficiency of the existing transportation system by responding to the excess rider demand, particularly in the downtown area. Finally, the study describes the policy implications of AV integration for government agencies, service providers, and other stakeholders. It also suggests future research topics. The final chapter summarizes the policy implications based on the research findings in this study and discusses some future research opportunities.

Keywords

Shared autonomous vehicles, On-demand ridesharing, Demand responsive transport services, Mobility on demand, Traffic safety, Time series analysis, Ordered logistic regression

Disciplines

Architecture | Urban, Community and Regional Planning

Comments

Degree granted by The University of Texas at Arlington

Additional Files
31455-2.zip (3159 kB)
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