Investigating the Determinants of Autonomous Vehicles and Their Potential Impacts on Travel Behaviors and Land Use Distribution
Autonomous Vehicles (AVs) are imminent and they are not in people’s dreams now. Now the burning questions the research community is interested in include how quickly AVs would be implemented for public use, whether people would accept them, and how AVs would change the ecosystem of transportation and the built environment. Stimulated by these questions, this dissertation aims to investigate the factors that influence people’s Behavioral Intention (BI) to adopt AVs and Shared AVs (SAVs). In addition, this study is intended to investigate the potential impacts of AVs on land use patterns and people’s travel behaviors. This dissertation consists of six papers as discussed hereunder.The first article presents a state-of-the-art literature review to understand people’s perceptions and opinions of AVs and the factors that influence AV adoption. Results show that the socioeconomic profile of individuals and their household, their psychological factors (e.g., usefulness, ease of use, risk), and knowledge and familiarity with AV technologies would affect AV adoption. Additionally, urban form (e.g., density, land use diversity), transportation factors (e.g., travel mode, distance, and time), affinity to new technology, and institutional regulations would influence the AV adoption rate.The second review study critically analyzes the extant literature and summarizes the short, medium, and long-term effects of AVs based on a SWOT (Strength, Weakness, Opportunity, and Threat) analysis. Results show that AV would influence transportation and human mobility by reducing vehicle ownership, Vehicle Miles Traveled (VMT), congestion, travel costs, energy use, and increasing accessibility, mobility, safety and security, and revenue generation for commercial operators. AVs would encourage dispersed urban development, reduce parking demand, and enhance network capacity. Additionally, AVs would increase the convenience and productivity of passengers by providing amenities for multitasking opportunities.The third paper investigates the key factors that influence people’s tendency to purchase and use personal AVs after collecting data from the 2019 California Vehicle Survey. Results from the Structural Equation Model (SEM) indicate that working-age adults, children, household income, per capita income, and educational attainment are positively associated with AV purchase intention. Similarly, psychological factors (e.g., perceived enjoyment, usefulness, and safety), prior knowledge of AVs, and experience with emerging technologies significantly influence people’s BI to purchase AVs. This study finds that family structure and psychological factors are the most influential factors in AV purchase intention of households than the built environment, other socioeconomic, and transportation factors.The fourth paper investigates the key elements of a household’s intentions to use pooled SAVs using the SEM framework. Collecting data from the 2019 California Vehicle survey, this study finds that higher educational attainment, income, labor force participation, Asian population, and urban living are negatively associated with SAVs. In contrast, young and working-age adults are positively associated with SAVs. Study results also show that people who prefer public transportation, car-sharing, ride-hailing, and ride-sharing services are likely to use SAVs. The perceived usefulness, enjoyment, safety associated with AVs, and prior knowledge of AVs significantly influence people to use SAVs. The study concludes that people’s travel behaviors, positive attitudes to shared mobility, and psychological features are the key determinants of SAVs.The fifth paper studies the potential impacts of AVs on the spatial distribution of household and employment locations using the existing Swindon model of the TRANUS urban simulation platform. Results show that the adoption of AVs encourages people to live outside of the city center by increasing convenience and reducing travel costs. On the other hand, AVs would increase employment opportunities in the city center by inducing more economic activities. This study finds that AVs would allow densification of the existing city center by releasing extra space from parking land areas along with peripheral new development over time.With the same TRANUS simulation platform, the sixth paper aims to assess the potential impacts of AVs on people’s travel behaviors such as trip generation, travel distance, travel time, and travel costs. Results indicate that AVs would intensify people’s overall travel demand by increasing accessibility. On the other hand, AVs are likely to reduce vehicle ownership, travel distance, travel time, travel costs, and vehicle hours traveled by reducing solo driving and by inducing shared mobility. AVs also have the potential to reduce public and active transportation.This study makes significant contributions by unraveling critical issues of AVs and their short-, medium-, and long-term impacts. The findings will be helpful for policymakers and professionals to implement appropriate policies to manage travel demand and urban growth, and to urban and transportation scholars in the understanding of the complex mutual relationships between transportation, mobility, and the conditions of urban environments.