Graduation Semester and Year
Fall 2024
Language
English
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Civil Engineering
Department
Civil Engineering
First Advisor
Dr. Stephen P Mattingly
Abstract
The rapid evolution of transportation technology is fundamentally transforming urban mobility, with profound implications for policy and planning. To comprehensively understand this complex landscape, this research investigates the interconnected impacts of diverse transportation technologies, including shared and non-shared automated vehicles (AVs) across three key dimensions: travel behavior, transportation planning, and socio-economic equity.
This is achieved through the conduct of three studies. The first study quantifies the impact of AVs on vehicle miles travel (VMT), providing critical insights to inform policies aimed at mitigating potential traffic congestion and environmental externalities. By disaggregating the effects of shared and non-shared AVs, the study reveals distinct patterns in VMT increase, highlighting the greater impact of non-shared AVs compared to shared ones. This distinction is crucial as it helps policymakers understand the specific challenges and benefits associated with different AV use models. For instance, non-shared AVs, which are more likely to increase VMT due to empty trips and greater convenience, present a higher risk of exacerbating traffic congestion and environmental impacts. In contrast, shared AVs may offer a more sustainable alternative by potentially lowering the number of vehicles on the road and increasing vehicle occupancy rates.
Additionally, the study identifies key factors influencing VMT variations, such as operating costs, value of travel time (VOTT), system speed, AV penetration rate, vehicle replacement rate, and trip characteristics. By examining these factors, the study provides a nuanced understanding of the conditions under which AV deployment might lead to significant increases in VMT. This nuanced understanding enables more targeted policy interventions, such as incentivizing shared AV usage, implementing dynamic pricing to manage demand, or optimizing public transportation systems to complement AV services. Moreover, by examining the factors contributing to extreme VMT values, the study identifies potential risks and informs strategies to manage unexpected impacts, thereby supporting the development of a more balanced and effective transportation system.
The second study addresses the urgent need for effective transportation planning in an era of rapid technological change. By developing a hierarchical clustering framework for scenario development that integrates diverse transportation technologies, this research equips policymakers with tools to anticipate future trends, assess potential impacts, and make informed decisions. The focus on scenario planning enables the exploration of multiple plausible futures, identification of critical uncertainties, and development of robust strategies to address emerging challenges and opportunities.
By considering a wide range of potential scenarios, the study empowers decision-makers to craft adaptive strategies that can navigate uncertain futures, enhancing the resilience and sustainability of transportation systems. This forward-looking methodology not only prepares stakeholders for a range of possible outcomes but also fosters innovation and flexibility in responding to the evolving transportation ecosystem.
The third study delves into the transformative potential of Shared Automated Vehicles (SAVs) in addressing pressing socio-economic challenges, with a particular focus on enhancing transportation accessibility and economic feasibility. By meticulously assessing the relationship between socio-economic conditions and access to essential opportunities, such as healthcare, education, and food, this research provides a data-driven foundation for policy decisions aimed at reducing disparities. In addition, a financial analysis assesses the economic feasibility of this mobility option and evaluates whether agencies will attain a return on their investment in terms of increased accessibility. The findings highlight how strategically deployed SAVs can serve as a catalyst for bridging accessibility gaps in disadvantaged communities, cost effectively, offering a lifeline to those facing significant transportation barriers.
This study not only underscores the practical benefits of SAVs in improving mobility but also emphasizes their potential to foster social inclusion and economic empowerment. By identifying areas with the greatest need and potential for improvement, the research guides policymakers in creating targeted interventions that augment the quality of life for marginalized populations. Moreover, the study advocates for the integration of SAVs into broader public transportation systems to create a more equitable, affordable, and reliable mobility network. Ultimately, this research positions SAVs as a critical tool for achieving a more just and inclusive society where everyone has the opportunity to thrive, regardless of their socio-economic background.
By broadening the scope to include diverse transportation technologies, this dissertation acknowledges the multifaceted nature of the transportation landscape and its potential impact on the research findings. This approach permits a more comprehensive analysis of the interactions between different modes of transportation and their influence on urban mobility.
To delve deeper into the complexities of these issues and provide actionable insights for policymakers, the following sections outline the research methodologies employed in each study. By systematically examining the data and applying rigorous analytical techniques, this research seeks to uncover the underlying patterns, trends, and relationships that shape the future of transportation.
Keywords
Meta analysis, Scenario planning, Socio-economic impact, Automated vehicles, Shared automated vehicles (SAVs), VMT, Hierarchical clustering, Future of transportation technologies, Accessibility gain
Disciplines
Civil Engineering | Transportation Engineering
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Naz, Farah, "Navigating the Future of Transportation: Comprehensive Analysis of Travel Behavior, Scenario Planning, and Socio-Economic Accessibility for Automated Vehicles and Emerging Transportation Technologies" (2024). Civil Engineering Dissertations. 506.
https://mavmatrix.uta.edu/civilengineering_dissertations/506
Comments
I am indebted to my advisor, Dr. Stephen P. Mattingly, for his invaluable guidance, unwavering support, and constant encouragement throughout my research journey. His expertise, patience, and belief in my abilities have been instrumental in shaping this work. I am immensely grateful for his mentorship and for always encouraging me to pursue my goals with confidence.