Investigating Travel Behavior in Transit-Oriented Development: Toward Sustainable and Multimodal Mobility

(Georgia Institute of Technology, 2021-12-14) Choi, Yunkyung

An extensive literature has shown that transit-oriented development residents (TOD) have lower automobile use and diverse travel modes due to easy access to transit, better walkability, and proximity to various amenities. While such benefits of TOD are generally expected, the degree to which TODs influence travel behavior is still debatable. Besides, TOD implementation differs by context, and not all transit areas are developed along TOD principles. This variation in transit areas leads to different impacts on transportation outcomes. Although different TOD typologies have been developed in past studies, they are limited to a particular city or region. The other ongoing debate in land use and travel behavior field is the emergence of new mobility services that enable users to utilize a mode of transport on an as-needed basis. Recent advances in information technologies have facilitated new mobility services that meet travelers’ diverse needs, such as transportation network companies (TNCs), ridesharing, car sharing, bike sharing, microtransit, and shared autonomous vehicles. While new mobility services are expected to play an important role—either positive or negative—in planning how TODs can be implemented, the impacts and consequences of such services on traditional modes of transport such as public transit are still not well understood. In doing so, this dissertation investigates different modes of transportation in TOD areas by posing the following research questions: 1) do people walk more in transit-oriented developments? 2) are residents more multimodal in transit-oriented developments? and 3) what is the potential impact of new mobility services on public transit demand? For the first question, this dissertation addresses the effect of rail transit access on walking behavior in TOD areas. TODs are compared to other similar areas without rail transit access to determine whether people are more likely to walk in TODs for purposes other than transit use in Atlanta. The second question is addressed by identifying different TOD types on their impacts on residents’ multimodal behavior to capture various conditions of existing TODs and their heterogeneous outcomes. This research identifies different types of 4,400 transit areas—a half-mile buffer area from rail station—in the U.S. and develops several analytic models to explain the multimodal traveler behavior in the 2017 NHTS. The third question examines the potential impacts of TNCs on transit demand in Chicago, with a particular focus on understanding heterogeneity in the effects by employing fixed effects panel regression models. By investigating various travel behavior around transit station areas, this dissertation provides insights on how TODs can be better implemented to promote sustainable and multimodal travel behavior.
Assessing mental wellbeing in urban areas using social media data: understanding when and where urbanites stress and de-stress

(Georgia Institute of Technology, 2021-12-10) Dutt, Florina

Are Americans more stressed out by living in dense, urbanized areas or less dense, car-oriented areas? To answer this question, can we use people's expressions of stress in different environments to understand what kinds of spaces help them de-stress? This study uses stress levels of geolocated tweets to help us answer such inquiries and resolve the longstanding disparities between the field of psychology and urban planning about mental health impacts of cities. This is important because more than 75 percent of Americans are moderately stressed. Long-term stress is associated with mental health disorders, including sleeplessness, anxiety, and depression. Additionally, chronic stress is linked to physical ailments, including high blood pressure, cardiovascular diseases, and diabetes. The psychology literature claims that urban areas witness elevated levels of mental health problems, manifested as stress, mood disorders, and anxiety issues. Density, crowding, traffic, crime, and pollution are identified as stressors associated with urban living conditions. Contending this claim, the urban planning literature positions stress in the context of longer commutes, lack of accessibility, and social isolation that comes with suburban living conditions. Urban Planners and urban designers have advocated for density. With rapid urbanization, 60 percent of the world population will live in urban areas by 2030, making it crucial for urban planners to address these disparities to support the mental wellbeing of the urbanites. This research uses multi-headed attention transformer model to classify tweets (token sequences), and assesses the stress levels of custom-defined assessment grids of ten acres within the city area of Atlanta and Boston. The assessed stress level of these assessment grids is called the mental wellbeing score (MWS). Mental wellbeing score is defined in this research as a measure of `mental wellbeing' of any given grid (higher score is better). Using this measure, the research investigates the relationship between mental wellbeing and built environment characteristics in urban areas to uncover the impact of long-term stress triggered by the conditions of the built environment in urban settings. In summary, the results of the exploration shed light on three critical aspects: 1. Mental wellbeing score increases with increasing urbanness. 2. The mental wellbeing score increases with the increase in the diversity of escape facilities, including green parks, open spaces, and other points of interest. 3. The mental wellbeing score is positively impacted by accessible high-density spaces with high symbolic value. The research also investigates the impact of safety perception and socio-economic status on mental wellbeing scores. The results show that addressing socio-economic disparity, crime, and investment in green infrastructure can improve mental wellbeing of urbanites. The methods and findings of the research show that 'urban areas' can positively impact mental health if designed appropriately. Furthermore, this study can empower urban planners and policymakers to develop tools to assess the mental wellbeing of urbanites, adjust infrastructure needs, and improve the urban amenities that support mental wellbeing.
Machine Learning Driven Emotional Musical Prosody for Human-Robot Interaction

(Georgia Institute of Technology, 2021-11-18) Savery, Richard

This dissertation presents a method for non-anthropomorphic human-robot interaction using a newly developed concept entitled Emotional Musical Prosody (EMP). EMP consists of short expressive musical phrases capable of conveying emotions, which can be embedded in robots to accompany mechanical gestures. The main objective of EMP is to improve human engagement with, and trust in robots while avoiding the uncanny valley. We contend that music - one of the most emotionally meaningful human experiences - can serve as an effective medium to support human-robot engagement and trust. EMP allows for the development of personable, emotion-driven agents, capable of giving subtle cues to collaborators while presenting a sense of autonomy. We present four research areas aimed at developing and understanding the potential role of EMP in human-robot interaction. The first research area focuses on collecting and labeling a new EMP dataset from vocalists, and using this dataset to generate prosodic emotional phrases through deep learning methods. Through extensive listening tests, the collected dataset and generated phrases were validated with a high level of accuracy by a large subject pool. The second research effort focuses on understanding the effect of EMP in human-robot interaction with industrial and humanoid robots. Here, significant results were found for improved trust, perceived intelligence, and likeability of EMP enabled robotic arms, but not for humanoid robots. We also found significant results for improved trust in a social robot, as well as perceived intelligence, creativity and likeability in a robotic musician. The third and fourth research areas shift to broader use cases and potential methods to use EMP in HRI. The third research area explores the effect of robotic EMP on different personality types focusing on extraversion and neuroticism. For robots, personality traits offer a unique way to implement custom responses, individualized to human collaborators. We discovered that humans prefer robots with emotional responses based on high extraversion and low neuroticism, with some correlation between the humans collaborator’s own personality traits. The fourth and final research question focused on scaling up EMP to support interaction between groups of robots and humans. Here, we found that improvements in trust and likeability carried across from single robots to groups of industrial arms. Overall, the thesis suggests EMP is useful for improving trust and likeability for industrial, social and robot musicians but not in humanoid robots. The thesis bears future implications for HRI designers, showing the extensive potential of careful audio design, and the wide range of outcomes audio can have on HRI.
White Spatial Planning Practices: Deconstructing Narratives around Race, Space, and Privilege

(Georgia Institute of Technology, 2021-10-29) OConnell, Katie

Racial inequality in the United States persists across multiple measures of health, wealth, and education despite changes in laws and policies to end de jure segregation. One reason is the way representations of space reproduces cycles of benefit to white people. This dissertation seeks to answer a central question: What is the role of white privilege in the production of space? To answer the overarching question in this dissertation, I ask four supporting questions 1) what are the changes in Black-white equality since the 1950s across multiple measures, including education, criminal justice, citizenship rights, health, housing, and poverty? 2) what is the relationship between abstract space and white privilege? 3) what have been the dominant discourses used in Atlanta's planning-related documents that ultimately justified the displacement of Black communities during urban renewal and the BeltLine redevelopment projects? 4) what counter-narratives did Black communities in Atlanta use to challenge white spatialities? A better understanding of whiteness and space guides planners to reframe urban problems not as the disadvantages found in communities of color but that of reproducing benefits for white people.
Shape Machine: shape embedding and rewriting in visual design

(Georgia Institute of Technology, 2021-07-27) Hong, Tzu-Chieh Kurt

Shape grammar interpreters have been studied for more than forty years addressing several areas of design research including architectural, engineering, and product design. At the core of all these implementations, the operation of embedding – the ability of a shape grammar interpreter to search for subshapes in a geometry model even if they are not explicitly encoded in the database of the system – resists a general solution. It is suggested here that beyond a seemingly long list of technological hurdles, the implementation of shape embedding, that is, the implementation of the mathematical concept of the “part relation” between two shapes, or equivalently, between two drawings, or between a shape and a design, is the single major obstacle to take on. This research identifies five challenges underlying the implementation of shape embedding and shape grammar interpreters at large: 1) complex entanglement of the calculations required for shape embedding and a shape grammar interpreter at large, with those required by a CAD system for modeling and modifying geometry; 2) accumulated errors caused by the modeling processes of CAD systems; 3) accumulated errors caused by the complex calculations required for the derivation of affine, and mostly, perspectival transformations; 4) limited support for indeterminate shape embedding; 5) low performance of the current shape embedding algorithms for models consisting of a large number of shapes. The dissertation aims to provide a comprehensive engineering solution to all these five challenges above. More specifically, the five contributions of the dissertation are: 1) a new architecture to separate the calculations required for the shape embedding and replacement (appropriately called here Shape Machine) vs. the calculations required by a CAD system for the selection, instantiation, transformation, and combination of shapes in CAD modeling; 2) a new modeling calibration system to ensure the effective translation of geometrical types of shapes to their maximal representations without cumulative calculating errors; 3) a new dual-mode system of the derivation of transformations for shape embedding, including a geometric approach next to the known algebraic one, to implement the shape embedding relation under the full spectrum of linear transformations without the accumulated errors caused by the current algorithms; 4) a new multi-step mechanism that resolves all cases of indeterminate embeddings for shapes having fewer registration points than those required for a shape embedding under a particular type of transformation; and 5) a new data representation for hyperplane intersections, the registration point signature, to allow for the effective calculation of shape embeddings for complex drawings consisting of a large number of shapes. All modules are integrated into a common computational framework to test the model for a particular type of shapes – the shapes consisting of lines in the Euclidean plane in the algebra U12.
A FORMALIZED URBAN PROSUMER MODEL: SUPPORT OF AUTOMATED SIMULATION AND DESIGN OPTIMIZATION

(Georgia Institute of Technology, 2021-07-26) Jung, Yun Joon

Many global cities have announced ambitious net-zero energy consumption targets or net-zero CO2 emissions plans. It is well recognized that this can only be realized through a mix of measures such as efficiency improvements at the sites of consumption and decentralized energy generation, storage and delivery mechanisms. This transition will not happen without major changes to energy supply networks, especially in the way they enable frictionless inclusion of renewable energy sources and local supply, for instance through microgrids. At the urban scale, buildings constitute the major consumers of electricity and their integration through building-to-building and building-to-grid controls is crucial to realize efficient energy sharing in urban energy networks. Over the last decade, the building energy simulation domain has moved its focus from traditional local studies to urban energy studies. The main objective of this thesis is to make a contribution to this growing research domain, especially in enabling the simulation of energy supply networks in a robust manner and at a large scale. It is possible to simulate such networks with customized software but considering that there is no systematic way to specify urban energy models (especially with multiple concurrent control topologies), the simulation software has to be hand-customized which leads to opaque simulations that moreover are hard to use for rapid variant explorations. The thesis argues that this can be overcome by the development of an urban prosumer (UP) schema that facilitates the specification and automated mapping of an urban energy network into simulations, focusing on the effective specification of controls outside the software. At a high level, the UP schema is comprised of a physical and a logical layer. The physical layer conceptualizes existing urban energy networks using directed graphs for energy transport between nodes. The logical layer conceptualizes how the dynamic processing (reasoning) of sensor data leads to instructions to a set of actuators that execute the control. In doing so, two levels of control are distinguished: (a) “private” (mostly rule-based) control such as the internal HVAC system following temperature setpoints, (b) “public” control that is exposed to the rest of the network and thus within the scope of the UP schema. Public control can be either rule-based or optimal control, the latter driven by an appropriate optimality criterion, defined at a network scale. In design situations, the optimality criterion is not limited to control variables but can also include design parameters, such as building design parameters, solar installation sizes, community battery size, and the number of EV charging stations. Mixed-integer non-linear programming (MINLP) is used to solve optimal control problems. The genetic algorithm is employed to solve design optimization problems. The case studies using the UP schema for ten Georgia Tech campus buildings are presented. The purpose of the case studies is to prove that the UP schema can facilitate simulations involving different levels of controls. The simulations target optimal energy decisions for the selected campus buildings in the presence of PV and electricity battery. Additionally, three residential buildings in California are chosen to investigate how the design and control parameters act together to avoid the power outage situation with the embedded UP schema in the simulation platform.
Measuring Street-Level Walkability through Big Image Data and Its Associations with Walking Behavior

(Georgia Institute of Technology, 2021-07-26) Koo, Bon Woo

The built environment characteristics associated with walkability range from neighborhood-level urban form factors to street-level urban design factors. However, many existing walkability measures are primarily based on neighborhood-level factors and lack consideration for street-level factors. Neighborhood-level factors alone can be limited in representing various needs of pedestrians. While pedestrians seek to fulfill their needs for accessibility, safety, comfort, and pleasurability, neighborhood-level factors tend to be limited to capturing the accessibility of the built environment (i.e., having places to go to and being physically connected to those places). The high-order needs (i.e., safety from crime, comfort from vehicular traffic, and aesthetic pleasurability) can be more closely proxied by street-level factors. Also, past studies suggested that certain street-level factors may weaken (or strengthen) the effect of neighborhood-level factors on walking behavior, which can be particularly important for disadvantaged populations who tend to be less responsive to neighborhood-level factors. However, measuring street-level factors often requires extensive manual labor and tends to be resource-intensive, resulting in the omission of street-level factors in widely used walkability measures such as Walk Score. This dissertation uses street view images and computer vision to overcome these challenges in measuring street-level factors and expands the literature by examining their association with walking mode choice. This dissertation first applies a pre-trained computer vision model to street view images and measure mesoscale (i.e., a midlevel spatial scale between macro and microscale) factors of walkability. It finds that the mesoscale factors have a significant contribution to walking mode choice models, and the contribution is greater than that from neighborhood-level factors. Next, the dissertation develops a method for automatically auditing walkability factors in microscale (i.e., the smallest spatial scale that pertains to the most fine-grain design details and their qualities) using the combination of computer vision, street view images, and geographic information systems. The validation results demonstrate moderate to high reliability between audit results by automated audit method and a trained human auditor. Finally, the dissertation uses automatically audited microscale factors to unpack the reasons for the weaker relationship between neighborhood-level factors and disadvantaged populations’ walking behavior. The result shows that microscale factors play a sizable role in moderating the effect of neighborhood-level factors. Collectively, this dissertation demonstrates the potential of using street view images and computer vision for research on the built environment-walking relationship and for collecting data on street-level factors over expansive geographic areas, a task that has traditionally been prohibitively expensive. The theoretical and methodological contributions of this dissertation help urban planners and designers understand the physical condition of their cities at street-level and make targeted interventions that are effective and equitable.
IMPACT OF ELA CALIBRATION METHODS ON BUILDING ENERGY MODEL FIDELITY AND FITNESS

(Georgia Institute of Technology, 2021-05-05) Althobaiti, Mohanned Mutlaq M.

As building performance is increasingly improved and building energy consumption decreases, a greater percentage of the total energy loss of a building occurs through envelope leakage. This leakage is characterized by the effective leakage area or ELA, which is a proxy parameter to what is essentially a complex flow phenomenon through cracks driven by pressure differences. Moreover, different façades and façade parts have different ELA and are typically subjected to different pressure differences in a given wind condition. This poses major challenges to building energy models. Current building performance simulation (BPS) uses software modules that approximately calculate envelope infiltration, but the literature shows that their calibration and validation is still unsatisfactory. In fact, calibration and validation of BPS models is still an important subject of study in our quest to improve the fidelity of simulation-based predictions in various applications. The high level of interaction and subsumption between parameters can result in a model that approximates the measurements well (and thus meets the ASHRAE auditing threshold) but whose “best estimates” of parameters are unreliable. This can be a problem in performance contracting when limits have been agreed on certain parameters such as ELA and U-value. It can also be problematic in the use of the model for certain performance assessments. This thesis exemplifies the underlying issues by comparing the results of direct and indirect calibration at different fidelities. The study focuses on the calibration of building energy models of existing buildings. It does so by conducting calibration for different experiments, i.e., for different sources of data, and for different model fidelities. The calibration is anchored around ELA and its impact on “best estimates” of other parameters is verified. The study is done with explicit quantification of uncertainties in the experiments as well as in model parameters. The two major experiments considered are (a) direct ELA calibration through tracer gas experiments, (b) indirect ELA calibration with consumption data enhanced by spot temperature measurements. Two case studies on existing buildings are performed. The thesis develops a new framework to address calibration and validation for different combinations of data and model fidelity, where each combination leads to probability distributions of the calibration parameter set. For each combination the ultimate aim is to determine the fitness of the resulting building energy model for given application studies such as building energy benchmarking, fault detection, unmet hour verification, etc. This requires the introduction of a novel fitness measure that determines the confidence level of a particular calibrated model for decisions in a predefined building performance assessment scenario. The thesis shows an early example of how to develop and quantify fitness. The results will be meaningful for better understanding façade infiltration, better understanding of the limits of calibrated models, and the way this translates into fitness of the resulting model. The thesis focuses exclusively on existing buildings, but its findings may lead to large scale data sets of calibrated ELA values in existing buildings, that may find their way into better ELA quantification in energy models of new designs.
Composing and Decomposing Electroacoustic Sonifications: Towards a Functional-Aesthetic Sonification Design Framework

(Georgia Institute of Technology, 2021-05-01) Tsuchiya, Takahiko

The field of sonification invites musicians and scientists for creating novel auditory interfaces. However, the opportunities for incorporating musical design ideas into general functional sonifications have been limited because of the transparency and communication issues with musical aesthetics. This research proposes a new design framework that facilitates the use of musical ideas as well as a transparent representation or conveyance of data, verified with two human subjects tests. An online listening test analyzes the effect of the structural elements of sound as well as a guided analytical listening to the perceptibility of data. A design test examines the range of variety the framework affords and how the design process is affected by functional and aesthetic design goals. The results indicate that the framework elements, such as the synthetic models and mapping destinations affect the perceptibility of data, with some contradictions between the designer's general strategies and the listener's responses. The analytical listening nor the listener's musical background show little statistical trends, but instead imply complex relationships of types of interpretations and the structural understanding. There are also several contrasting types in the design and listening processes which indicate different levels of structural transparency as well as the applicability of a wider variety of designs.
DISADVANTAGED BUSINESS ENTERPRISES: EFFECT OF DECERTIFICATION AND COMPETING IN THE GEORGIA TRANSPORTATION CONSTRUCTION MARKETPLACE

(Georgia Institute of Technology, 2021-04-29) Horsey, Irish L.

The U.S. Department of Transportation (DOT) allocates billions of dollars annually for transportation projects. State Departments of Transportation (SDOT) that receive federal assistance for transportation contracting must meet the requirements of the Code of Federal Regulations (CFR) Title 49: Transportation Part 26 (ECFR, 2016). This regulation ensures that all business enterprises have fair opportunities for federally funded transportation contracting. Therefore, SDOTs are mandated to develop DBE goals for participation of firms, certification of DBE firm eligibility, evaluation of their DOT-assisted contracts for compliance with goals to ensure nondiscrimination in federally assisted procurement. There are eight primary objectives for the DBE program. One of which is to assist the development of firms that can compete successfully in the marketplace outside the DBE program. The DBE program has been a source of controversy since its inception (La Noue, 2008). Research shows that both DBE and non-DBE firms have grievances with the effectiveness of the overall program. Some also believe that the program creates a dependency of its participant and that inputs of knowledge would assist with the growth and development of firms to become independent contractors outside of the program (Beliveau et al., 1991). A number of factors have been presented by prior research that hinder the growth and development of certified DBE firms with a focus on performance, internal impediments, and external impediments of the program. However, there is minimal data on the preparation of DBE firms by SDOTs and their ability to compete in the open market outside of the DBE program. There is value in a study that evaluates the DBE program to determine if it is meeting the referenced objective. This research analyzes the participants of the DBE program and factors that contribute to the decertification of firms and affect their growth and development. Evaluation of certified DBEs, decertified DBEs and program administrators on this specific program objective contributes new data to the body of knowledge. The objective of this study is to evaluate the GDOT DBE program and that of similar SDOTs to determine if the DBE program in Georgia is assisting with the development of firms to compete in the marketplace. The main contribution of this research is to identify factors that assist the growth and development of DBE construction firms who voluntarily decertify and compete independently in the open market and explore the issues of certified firms that prohibit graduation. There are three outcomes of this study that contribute to the body of knowledge: regression models, development and decertification factors, and program administrator recommendations. The results of this research reveal if the program is meeting this objective for Georgia construction transportation projects based on factors obtained from the data analysis. The findings offer improvement to policy regarding the DBE program and government contracting for construction transportation projects.