Operations Research, Systems Engineering and Industrial Engineering Commons^™

Drivers’ Hazard Avoidance During Vehicle Automation: Impact Of Mental Models And Implications For Training, Ganesh Pai Mangalore

Doctoral Dissertations

Advanced Driver Assistance Systems (ADAS) are vehicle automation systems that have become more accessible and prevalent in vehicles in recent years. But the introduction of such technologies introduces new human factors challenges. Past literature suggests that users of vehicle automation lack the necessary and appropriate knowledge about their automation system. This may play a negative role in their hazard avoidance abilities when driving with automation features. Improving mental models and knowledge could generally lead to safer interactions with vehicle automation systems, but any effort to develop hazard avoidance skills when driving with vehicle automation is impeded by the lack of …

Resource Allocation In Subsidy Welfare Programs: Managerial Insights For Nonprofits, Governments, And Service Providers, Wei Wei

Doctoral Dissertations

Subsidy welfare programs provide financial assistance to economically disadvantaged individuals and families to access essential and life-altering services (e.g., education, child care, and housing) that they might not otherwise have access to. Access to these services is considered critical to achieving a better and more sustainable future for all. As such, these high-quality services are directly related to several United Nations Sustainable Development Goals, which were adopted as a universal call to action to end poverty, save the planet and improve the lives and prospects of everyone, everywhere." In particular, the need for these affordable and high-quality services has been …

Mining High Impact Combinations Of Conditions From The Medical Expenditure Panel Survey, Arjun Mohan

Masters Theses

The condition of multimorbidity — the presence of two or more medical conditions in an individual — is a growing phenomenon worldwide. In the United States, multimorbid patients represent more than a third of the population and the trend is steadily increasing in an already aging population. There is thus a pressing need to understand the patterns in which multimorbidity occurs, and to better understand the nature of the care that is required to be provided to such patients.

In this thesis, we use data from the Medical Expenditure Panel Survey (MEPS) from the years 2011 to 2015 to identify …

Capacity Planning For Heterogeneous Patient Populations In Primary Care And Specialty Networks, Prashant Meckoni

Doctoral Dissertations

Access to primary care has a direct impact on morbidity and mortality, and is strongly influenced by indirect waiting time: the delay between the requested and allotted appointment day. Our models describe the heterogeneous appointment seeking patterns of a primary care patient panel using stochastic processes parameterized to reflect the diversity of primary care visit rates in the US. For capacity planning, we estimate the distribution of daily appointments, and show that the distribution variability can be reduced by heuristics that use patient flexibility regarding the day of the appointment. For delays, we demonstrate that in a first-come, first-served system, …

A Digital Twin Framework For Production Planning Optimization: Applications For Make-To-Order Manufacturers, Ron Mallach

Doctoral Dissertations

In this dissertation, we develop a Digital Twin framework for manufacturing systems and apply it to various production planning and scheduling problems faced by Make-To-Order (MTO) firms. While this framework can be used to digitally represent a particular manufacturing environment with high fidelity, our focus is in using it to generate realistic settings to test production planning and scheduling algorithms in practice. These algorithms have traditionally been tested by either translating a practical situation into the necessary modeling constructs, without discussion of the assumptions and inaccuracies underlying this translation, or by generating random instances of the modeling constructs, without assessing …

Water Resources Planning Under Deep Uncertainty For Physically, Socially, And Politically Complex Systems, Sarah St. George Freeman

Doctoral Dissertations

Water supply systems, particularly those of large cities, are complex systems linking supply, regulatory and distribution infrastructure, and points of use. Despite their physical complexities, it is infrequent that full supply, distribution, end use, and feedbacks therein are considered in an integrated manner. These complex systems-of-systems face large uncertainties related to physical aspects such as degradation of infrastructure, changing demand, and climate variability and change. Though great, such physical uncertainties often pale in comparison to the those related to the human systems in place to manage them and yet uncertainty in the decision-making landscape is often grossly simplified in our …

Systematic Review Of Driver Distraction In The Context Of Advanced Driver Assistance Systems (Adas) & Automated Driving Systems (Ads), Apoorva Pramod Hungund

Masters Theses

Advanced Vehicle Systems promise improved safety and comfort for drivers. Steady advancements in technology are resulting in increasing levels of vehicle automation capabilities, furthering safety benefits. In fact, some of these vehicle automation systems are already deployed and available, but with promised benefits, such systems can potentially change driving behaviors. There is evidence that drivers have increased secondary task engagements while driving with automated vehicle systems, but there is a need for a clearer scientific understanding of any potential correlations between the use of automated vehicle systems and potentially negative driver behaviors.

Therefore, this thesis aims to understand the state …

Decision-Analytic Models Using Reinforcement Learning To Inform Dynamic Sequential Decisions In Public Policy, Seyedeh Nazanin Khatami

Doctoral Dissertations

We developed decision-analytic models specifically suited for long-term sequential decision-making in the context of large-scale dynamic stochastic systems, focusing on public policy investment decisions. We found that while machine learning and artificial intelligence algorithms provide the most suitable frameworks for such analyses, multiple challenges arise in its successful adaptation. We address three specific challenges in two public sectors, public health and climate policy, through the following three essays. In Essay I, we developed a reinforcement learning (RL) model to identify optimal sequence of testing and retention-in-care interventions to inform the national strategic plan “Ending the HIV Epidemic in the US”. …

Improving Young Driver Perceptions Of Vulnerable Road Users Through A Persuasive Intervention, Shashank Mehrotra

Doctoral Dissertations

Vulnerable road users (VRUs), including bicyclists, pedestrians, and road users of other modalities, are at a higher risk of collision with young drivers when a complex traffic situation presents itself. Past research has established the importance of young drivers’ perceptions about VRUs that would encourage safe behavior. This research designed and evaluated a novel persuasive intervention that can help improve the perceptions of young drivers while they interact with VRUs. The study identified young drivers’ perceptions towards VRUs who have been licensed in the past 12 to 18 months through structured interviews. Based on these findings, an interactive intervention was …

Robustness Of Supply Chain Synchronization Strategies, Andrew Frere

Masters Theses

Modern manufacturing systems dealing with complex assemblies with large numbers of parts present particular challenges in the realm of supply chain management. Complex assemblies, such as those found in aerospace and automobile manufacturing, require thousands of parts to come together at the right time for final assembly. The large number of parts, often coming from hundreds of suppliers, combined with unreliable delivery times and high cost of many of these components can lead to incredibly high inventory costs and assembly delays. Typically, variable delays in part delivery are compensated for by either keeping a buffer of safety stock or a …

Comparing And Improving The Design Of Physical Activity Data Visualizations, Peter M. Frackleton

Masters Theses

Heart disease is a leading cause of death in the United States, and older adults are at highest risk of being diagnosed with heart disease. Consistent physical exercise is an effective means of deterring onset of heart disease, and physical activity tracking devices can inspire greater activity in older adults. However, physical activity tracking device abandonment is quite common due to limitations on what can be learned from the activity data that is collected. Better data visualization of physical data presents an opportunity to surpass these limitations. In this thesis, a task-based human subject study was performed with three different …

Modeling Portfolios Of Low Carbon Energy Generation Under Deep Uncertainty, Franklyn Kanyako

Doctoral Dissertations

In the 2015 Paris Agreement, nearly every country pledge through the Nationally Determined Contributions (NDCs) increased adoption of low carbon energy technologies in their energy system. However, allocating investments to different low carbon energy technologies under rising demand for energy and budget constraints, uncertain technical change in these technologies involves maneuvering significant uncertainties among experts, models, and decision-makers. We examine the interactions of low carbon energy sources (LCES) under the condition of deep uncertainty. Deep uncertainty directly impacts the understanding of the role of low carbon energy technologies in climate change mitigation and how much R&D investment should be allocated …

Enabling Declarative And Scalable Prescriptive Analytics In Relational Data, Matteo Brucato

Doctoral Dissertations

Constrained optimization problems are at the heart of significant applications in a broad range of domains, including finance, transportation, manufacturing, and healthcare. They are often found at the final step of business analytics, namely prescriptive analytics, to allow businesses to transform a rich understanding of data, typically provided by advanced predictive models, into actionable decisions. Modeling and solving these problems has relied on application-specific solutions, which are often complex, error-prone, and do not generalize. Our goal is to create a domain-independent, declarative approach, supported and powered by the system where the data relevant to these problems typically resides: the database. …

Extracellular Polymeric Substances In Oxygenic Photogranules: Investigation Of Their Role In Photogranulation In A Hydrostatic Environment, Wenye Camilla Kuo-Dahab

Doctoral Dissertations

The purpose of this dissertation was to assess the critical role of extracellular polymeric substances (EPS) in the photogranulation of activated sludge, in a hydrostatic environment. The first section evaluates the fate and dynamics of different fractions of EPS in sludge-based photogranulation under hydrostatic conditions. The study shows that during the transformation of activated sludge into a photogranular biomass, sludge’s base-extractable proteins selectively degrade. Strong correlations between base-extracted proteins and the growth of chlorophyll a and chlorophyll a/b ratio suggest that the bioavailability of this organic nitrogen is linked with selection and enrichment of filamentous cyanobacteria under hydrostatic conditions. The …

Factors Affecting Drivers’ Off-Road Glance Behavior While Interacting With In-Vehicle Voice Interfaces – Insights From A Secondary Data Analysis, Fangda Zhang

Doctoral Dissertations

Given the prevalence of in-vehicle technologies and the critical role of visual attention plays in driving safety, this dissertation work aimed to fill the research gap that 1) little was known about the visual demands associated with a driver engaging with in-vehicle voice interfaces; 2) the concurrent effect of interacting with in-vehicle voice interfaces and other commonly discussed individual-level factors has barely been targeted. This research work was a secondary data analysis based on a large-scale field experiment wherein 144 participants had been recruited and driven a test vehicle while performing a series of tasks using voice-based interfaces. Pre- and …

Optimal Mammography Schedule Estimates Under Varying Disease Burden, Infrastructure Availability, And Other Cause Mortality: A Comparative Analyses Of Six Low- And Middle- Income Countries, Shifali Shifali

Masters Theses

Low-and-middle-income countries (LMICs) have a higher mortality-to-incidence ratio for breast cancer compared to high-income countries (HICs) because of late-stage diagnosis. Mammography screening is recommended for early diagnosis, however, current screening guidelines are only generalized by economic disparities, and are based on extrapolation of data from randomized controlled trials in HICs, which have different disease burdens and all-cause mortality compared to LMICs. Moreover, the infrastructure capacity in LMICs is far below that needed for adopting current screening guidelines. This study analyzes the impact of disease burden, infrastructure availability, and other cause mortality on optimal mammography screening schedules for LMICs. Further, these …

Improving Drivers’ Behaviour When Partial Driving Automation Fails, Yalda Ebadi

Doctoral Dissertations

With the advent of automated vehicle systems, the role of drivers has changed to a more supervisory role. However, it is known that all vehicles with Level 2 (L2) systems have a very specific operational design domain (ODD) and can only function on limited conditions. Hence, it is important for drivers to perceive the situations properly and regain the control from the L2 system when needed. As suggested by past research, designing an informative interface could help drivers in their new supervision and intervention role while driving with L2 vehicles by providing feedback to drivers when hazards or event that …

Robust And Sustainable Energy Pathways To Reach Mexico’S Climate Goals, Rodrigo Mercado Fernandez

Doctoral Dissertations

As countries set climate change goals for adaptation and mitigation efforts, there are many questions regarding to how to reach these targets. These efforts will necessitate the transition of our electricity infrastructure from relying on conventional electricity generation technologies including natural gas, coal and oil, to clean energy generation with renewables. Through the three essays presented in this dissertation, we explore various pathways of development for the electricity system to reach long term climate change goals. We are interested in identifying: Is there a unique optimal development option or are there various? How do different mixes of electricity generation technologies …

Modeling Of Electrical Grid Systems To Evaluate Sustainable Electricity Generation In Pakistan, Muhammad Mustafa Amjad

Masters Theses

Pakistan has always had a history of severe energy shortfalls, which rose up to an alarming 33% in 2013. This situation was countered by investments in the energy sector through the China Pakistan Economic Corridor (CPEC), which were unfortunately largely based on brown fuels. Although beneficial in the short term, these investments do not bode well for the climate scenario of Pakistan, with various parts of the country already having experienced temperatures rise of 1-3°C. To ensure that the current situation doesn’t exacerbate and is tackled in a timely manner, this research aims to examine how the untapped potential of …

Three Essays On Data-Driven Optimization For Scheduling In Manufacturing And Healthcare, Ekin Koker

Doctoral Dissertations

This dissertation consists of three essays on data-driven optimization for scheduling in manufacturing and healthcare. In Chapter 1, we briefly introduce the optimization problems tackled in these essays. The first of these essays deals with machine scheduling problems. In Chapter 2, we compare the effectiveness of direct positional variables against relative positional variables computationally in a variety of machine scheduling problems and we present our results. The second essay deals with a scheduling problem in healthcare: the team primary care practice. In Chapter 3, we build upon the two-stage stochastic integer programming model introduced by Alvarez Oh (2015) to solve …

Combining Human Factors And Data Science Methods To Evaluate The Use Of Free Text Communication Orders In Electronic Health Records, Swaminathan Kandaswamy

Doctoral Dissertations

Medication errors are a leading cause of death in the United States. Electronic Health Records (EHR) along with Computerized Provider Order Entry (CPOE) are considered promising ways to reduce these errors. However, EHR systems have not eliminated medication errors. Moreover, in some cases they have facilitated errors due to issues such as poor usability and negative effects on clinical workflows. The use of unexpected free text within a CPOE system can serve as a marker that the system does not adequately support clinical workflow. Prior studies have looked at the use of free text within medication orders, but the inclusion …

The Promise Of Vr Headsets: Validation Of A Virtual Reality Headset-Based Driving Simulator For Measuring Drivers’ Hazard Anticipation Performance, Ganesh Pai Mangalore

Masters Theses

The objective of the current study is to evaluate the use of virtual reality (VR) headsets to measure driving performance. This is desirable because they are several orders of magnitude less expensive and, if validated, could greatly extend the powers of simulation. Out of several possible measures of performance that could be considered for evaluating VR headsets, the current study specifically examines drivers’ latent hazard anticipation behavior both because it has been linked to crashes and because it has been shown to be significantly poorer in young drivers compared to their experienced counterparts in traditional driving simulators and in open …

Topology Network Optimization Of Facility Planning And Design Problems, Ravi Ratan Raj Monga

Masters Theses

The research attempts to provide a graphical theory-based approach to solve the facility layout problem. Which has generally been approached using Quadratic Assignment Problem (QAP) in the past, an algebraic method. It is a very complex problem and is part of the NP-Hard optimization class, because of the nonlinear quadratic objective function and (0,1) binary variables. The research is divided into three phases which together provide an optimal facility layout, block plan solution consisting of MHS (material handling solution) projected onto the block plan. In phase one, we solve for the position of departments in a facility based on flow …

Advanced Virtual Reality Headset Based Training To Improve Young Drivers’ Latent Hazard Anticipation Ability, Ravi Agrawal

Masters Theses

Driving safety among young novice driver is one of the largest concern in the transportation domain. Many Paper-based or PC- based training program have been developed over the years to train the young novice driver to improve their driving skills (Hazard Anticipation). This training programs does help young novice driver to improve their situational awareness and so the hazard anticipation skills. But, there is one common problem with most of the currently available training programs. They are not very immersive, because such training program mostly provide plain view of the training scenario’s along with some description about the scenario and …

Power System Planning In Disparate Systems: Modeling Sustainability And Electricity Access, Destenie Nock

Doctoral Dissertations

Electricity goals around the world tend to focus on increasing social benefit through one of two avenues: (1) increasing overall system sustainability or (2) increasing access to electricity. These goals guide the transition of the power system. In pursuit of these goals decision makers will need modeling tools that can inform decisions, in a way that is flexible enough to include a wide range of preferences and goals. It is clear that the future generation mix of the power system will change, but the most sustainable solution, will change based on a country's goals. This dissertation will explore the various …

A Computational Simulation Model For Predicting Infectious Disease Spread Using The Evolving Contact Network Algorithm, Buyannemekh Munkhbat

Masters Theses

Commonly used simulation models for predicting outbreaks of re-emerging infectious diseases (EIDs) take an individual-level or a population-level approach to modeling contact dynamics. These approaches are a trade-off between the ability to incorporate individual-level dynamics and computational efficiency. Agent-based network models (ABNM) use an individual-level approach by simulating the entire population and its contact structure, which increases the ability of adding detailed individual-level characteristics. However, as this method is computationally expensive, ABNMs use scaled-down versions of the full population, which are unsuitable for low prevalence diseases as the number of infected cases would become negligible during scaling-down. Compartmental models use …

Forecasting The Cost Of Electricity Generated By Offshore Wind Turbines, Timothy Costa

Masters Theses

To impede the progress of climate change, many policy makers are considering avenues to decarbonize electricity production. In addition to decarbonization, policy makers must consider how the cost of electricity will impact various stakeholders, balancing cost and social benefits. Offshore wind farms have the potential to produce affordable, carbon-free electricity, but they are a relatively new technology. The relative juvenescence of offshore wind lends itself to an uncertain future, regarding production costs. In this thesis, we seek to understand cost drivers behind offshore wind electricity by analyzing historic trends in offshore wind levelized cost of electricity (LCOE) through learning curves, …

The Evacuation Problem In Multi-Story Buildings, Quang Hong Cung

Masters Theses

The pressure from high population density leads to the creation of high-rise structures within urban areas. Consequently, the design of facilities which confront the challenges of emergency evacuation from high-rise buildings become a complex concern. This paper proposes an embedded program which combines a deterministic (GMAFLAD) and stochastic model (M/G/C/C State Dependent Queueing model) into one program, GMAF_MGCC, to solve an evacuation problem. An evacuation problem belongs to Quadratic Assignment Problem (QAP) class which will be formulated as a Quadratic Set Packing model (QSP) including the random flow out of the building and the random pairwise traffic flow among activities. …

Evaluation And Validation Of Distraction Detection Algorithms On Multiple Data Sources, Shashank Mehrotra

Masters Theses

This study aims to evaluate algorithms designed to detect distracted driving. This includes the comparison of how efficiently they detect the state of distraction and likelihood of a crash. Four algorithms that utilize measures of cumulative glance, past glance behavior, and glance eccentricity were used to understand the distracted state of the driver and were validated on two separate data sources (i.e., simulator and naturalistic data). Additionally, an independent method for distraction detection was designed using data mining methods. This approach utilized measures like steering degree, lane offset, lateral and longitudinal velocity, and acceleration. The results showed a higher likelihood …

The Application Of Usability Engineering Methods To Evaluate And Improve A Clinical Decision Support System, Kristine Desotto

Masters Theses

Delays in the process of diagnosing and treating cancer are common and lead to confusion and undesirable outcomes. Care coordinators are often embedded within the system of care to manage follow-up care. Electronic and real-time reminder systems can be used to support the care coordinator’s work, but electronic health record (EHR) usability is known to be poor. This study, completed in collaboration with the Department of Veterans Affairs (VA) Connecticut Healthcare System, evaluated the Cancer Coordination and Tracking System (CCTS), an EHR-linked, web-based tool for cancer care management.

A set of expert-driven and user-driven usability engineering methods was applied to …