A. James Clark School of Engineering
Permanent URI for this communityhttp://hdl.handle.net/1903/1654
The collections in this community comprise faculty research works, as well as graduate theses and dissertations.
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Item Examination of US Transportation Public-Private Partnership Experience: Performance and Market(2024) Zhang, Kunqi; Cui, Qingbin; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Worldwide, public-private partnership (P3) project performance and benefits accrued to market participants are understudied. Focusing on the US, this dissertation examines the country’s transportation P3 experience through three empirical studies comparing P3 to design-bid-build (DBB), the traditional delivery method. Throughout, the Information Source for Major Projects database, built by a University of Maryland team in which the author led the data collection effort, served as the data source. In the first study, the researchers examined P3 cost and time performance using piecewise linear growth curve modeling, recognizing that past cross-sectional studies had produced mixed results. With 133 major transportation projects, the longitudinal analysis confirmed P3’s time performance advantage and efficiency diffusion effecting cost savings in DBB, where efficiency diffusion was a new term describing the spillover and internalization of technical and managerial innovations inducing an efficient outcome. The second study used social network analysis to investigate collaboration patterns among different types of players in the P3 market (i.e., public sponsors, special purpose vehicles, investors, lenders, advisors, contractors, and professional service firms). With 135 projects and 1009 organizations, data found that both P3 and DBB networks are small worlds. Exponential random graph modeling revealed that practicing in the DBB market helps firms participate in P3 projects and that large firms (vis-à-vis small/medium-sized firms) are not privileged. The third study, further exploring the P3 market, focused on the Disadvantaged Business Enterprise (DBE) program. Administered by the US Department of Transportation, the program promotes the participation of small, disadvantaged firms in federal-aid projects. Linear regressions on 134 contracts showed that P3 associates with higher DBE goals in terms of percentage of dollars to be awarded to DBEs, whereas the delivery method does not affect the actual attainment. Overall, the findings justify continued policy support towards P3 implementation.Item Econometric Evaluation of Transportation Policies: Decarbonization and Electrification(2024) Burra, Lavan Teja; Cirillo, Cinzia; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The transportation sector, one of the largest contributors to global energy-related emissions, is undergoing a major transition. Governments worldwide are implementing stringent fuel economy and emissions standards, promoting the adoption of electric vehicles--a key technology for decarbonizing the transport sector--through various policy measures. This dissertation contains four chapters, studying the effects of such policies implemented across major vehicle markets and evaluating their effectiveness, with a particular focus on the electrification of light-duty passenger vehicle fleet. The first chapter explores whether multi-car households shift mileage to the most fuel-efficient car in response to increasing driving costs, which carries implications for designing effective fuel economy standards. The second chapter investigates the potential interaction between purchase subsidies given to consumers in buying electric vehicles (EVs) and expanding the public charging network. The third chapter focuses on the effectiveness of purchase subsidies for EV buyers and quantifies the free-rider share, given that this is a commonly employed policy measure worldwide. The final chapter explores the differential effects of level 2 and level 3 chargers, as well as the distributional impacts of public charging network on driving EV uptake across various demographic groups and built environment characteristics. Overall, the chapters in this dissertation employ travel survey data, longitudinal and big data analysis, causal identification, optimal policy design, counterfactual simulations, and a combination of data and economic reasoning to glean insights on the effectiveness and equitable aspects of policies aiming to decarbonize and electrify the transportation sector.Item ANALYZING REDISTRIBUTION OF FEDERAL DISASTER AID THROUGH MACHINE LEARNING(2023) Bryant, Adriana Yanmei; Reilly, Allison; Niemeier, Deb; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Natural disasters are on the rise and will be costly for both the United States government and its citizens. The record-breaking year of 2020 left $1 billion worth of damages in the wake of twenty-two different events (FEMA, 2023). As costs due to disasters increase in the coming decades, the livelihoods of all citizens, especially those most vulnerable are at risk. It is known that natural disasters exacerbate current standing social vulnerabilities and inequities. Federal disaster aid programs in place are intended to assist those who cannot solely finance their own recovery efforts. This study looks to analyze FEMA’s Public Assistance (PA) program, Individual Assistance (IA) program, and Hazard Mitigation Assistance (HMA) program. It is important that these systems put in place are distributing federal resources as intended because they are funded via people’s taxpayer dollars. This study looks to explore the relationship between disaster aid that is awarded at the county level with respect to the federal income taxes residents of that county pay to the federal government. This is expressed through the creation of the donor-donee ratio. This study also contributes to the literature a new metric of burden, the ratio of expected annual disaster losses of a county and its gross domestic product, which can beutilized as a proxy for coping capacity. The burden metric provides additional useful insight as it is tabulated by FEMA directly and published in their National Risk Index (NRI) at the county level. Over the last decade, this research examines the donor-donee ratio and burden metric over the years 2010 to 2019. Results of mapping the donor-donee ratio and burden metric indicate there is spatial heterogeneity between counties in the United States. The redistribution of federal aid is not only heterogeneous but there are distinct regional patterns where further research could investigate their causality. To investigate the relationship between the redistribution of aid and coping capacity by proxy, this study utilized supervised machine learning to characterize counties. Significant outcomes of the machine learning indicate that most counties across the country received moderate funding and were evaluated as having a moderate burden as well. This does suggest that to some level the redistribution of aid is working as intended. Although upon further digging, it was found that counties that experience high-cost, less frequent events, contain over 50% of the country’s population and lie in metropolitan areas. Upon the application of a logistic regression model, it was found that these counties while associated with higher income, are also associated with higher mobile homes residence. As the risk of these higher costs events increases over the years, it is imperative that vulnerable communities are receiving adequate funding to increase their resilience to future hazards. This study highlights the flows of federal disaster dollars and where these programs allocate funding.Item THE INFLUENCE OF URBAN FORM AT DIFFERENT GEOGRAPHICAL SCALES ON TRAVEL BEHAVIOR; EVIDENCE FROM U.S. CITIES(2016) Nasri, Arefeh; Zhang, Lei; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Suburban lifestyle is popular among American families, although it has been criticized for encouraging automobile use through longer commutes, causing heavy traffic congestion, and destroying open spaces (Handy, 2005). It is a serious concern that people living in low-density suburban areas suffer from high automobile dependency and lower rates of daily physical activity, both of which result in social, environmental and health-related costs. In response to such concerns, researchers have investigated the inter-relationships between urban land-use pattern and travel behavior within the last few decades and suggested that land-use planning can play a significant role in changing travel behavior in the long-term. However, debates regarding the magnitude and efficiency of the effects of land-use on travel patterns have been contentious over the years. Changes in built-environment patterns is potentially considered a long-term panacea for automobile dependency and traffic congestion, despite some researchers arguing that the effects of land-use on travel behavior are minor, if any. It is still not clear why the estimated impact is different in urban areas and how effective a proposed land-use change/policy is in changing certain travel behavior. This knowledge gap has made it difficult for decision-makers to evaluate land-use plans and policies. In addition, little is known about the influence of the large-scale built environment. In the present dissertation, advanced spatial-statistical tools have been employed to better understand and analyze these impacts at different scales, along with analyzing transit-oriented development policy at both small and large scales. The objective of this research is to: (1) develop scalable and consistent measures of the overall physical form of metropolitan areas; (2) re-examine the effects of built-environment factors at different hierarchical scales on travel behavior, and, in particular, on vehicle miles traveled (VMT) and car ownership; and (3) investigate the effects of transit-oriented development on travel behavior. The findings show that changes in built-environment at both local and regional levels could be very influential in changing travel behavior. Specifically, the promotion of compact, mixed-use built environment with well-connected street networks reduces VMT and car ownership, resulting in less traffic congestion, air pollution, and energy consumption.