Matching Items (101)
Residential Choice’s Impact on Sustainable Transportation Options: A Study in the Phoenix Metro Area
Description
This study adds to the literature about residential choice and sustainable transportation. Through the interviews and the personal stories gathered, there was diversity shown in the residential location choice process. We also noticed that “commute” means different things to different households, and that many people did not consider their commute to work to be a primary factor determining their final home location. Moreover, many people were willing to increase their commute time, or trade access to desirable amenities for a longer commute. Commuting time to work was one example of the tradeoffs that homeowners make when choosing a home, but there were also others such as architectural type and access to neighborhood amenities. Lastly, time constraints proved to be a very significant factor in the home buying process. Several of our households had such strict time constraints that limited their search to a point of excluding whole areas. Overall, our study sheds light on transportation’s role in residential choice and underscores the complexity of the location choice process.
ContributorsKats, Elyse Nicole (Author) / Salon, Deborah (Thesis director) / Kuminoff, Nicolai (Committee member) / School of Sustainability (Contributor) / School of Geographical Sciences and Urban Planning (Contributor) / School of Community Resources and Development (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Motorcycle fatalities have been increasing at a faster rate than the number of motorcycles being registered in the United States. There is limited analysis on the causes of fatal motorcycle crashes, specifically regarding different demographics, certain driver behavior, and various crash characteristics. It is important to be aware of how these factors relate to each other during a fatal motorcycle crash. This analysis focuses on these factors and explores potential steps to decrease motorcycle fatality rates using research and data from the Fatality Analysis Reporting System (FARS) from the National Highway Traffic Safety Administration (NHTSA), and data from the National Household Travel Survey (NHTS). Based on this data, there are noticeable trends between different genders and age groups. According to the analysis, males have a higher fatality rate than females, and their fatal crashes tend to involve multiple driver infractions such as drinking, speeding, not wearing a helmet, and driving without a license. Similarly, younger drivers have a higher fatality rate than older drivers, and their fatal crashes tend to involve multiple driver infractions. Although older drivers involved in fatal crashes usually drive more cautiously, they tend to be involved in single-vehicle crashes more often than younger drivers. Moving forward, implementing certain training programs directed towards particular demographics has the potential to decrease motorcycle rider fatalities.
ContributorsMoran, Sarah Elizabeth (Co-author) / Santilli, Amy (Co-author) / Pendyala, Ram (Thesis director) / Khoeini, Sara (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Approximately 1% of the total working population within the United States bikes as their primary mode of commute. Due to recent increased in bicycle facilities as well as a focus on alternative modes of transport, understanding the motivations and type of people who bike to work is important in order to encourage new users.
In this project, a literature review was completed as well as data analysis of the National Household Travel Survey (NHTS) in order to find specific populations to target. Using these target populations, it is suggested that advertising and workplace encouragement occur to persuade more people to bike to work. Through data analysis it was found that the most impactful variables were the region of the country, gender, population density, and commute distance. Bicycle commuters statistically had fewer vehicles in their households and drove less miles annually.
There were five main target groups found through this analysis; people who bike for other reasons besides work and live in a city with more than 4,000 people per square mile, young professionals between 19-39, women in regions with separated bicycle facilities, those with low vehicle availability, and environmentally conscious individuals. Working to target these groups through advertising campaigns to encourage new users, as well as increasing and improving bicycle facilities, will help create more new bicyclists.
In this project, a literature review was completed as well as data analysis of the National Household Travel Survey (NHTS) in order to find specific populations to target. Using these target populations, it is suggested that advertising and workplace encouragement occur to persuade more people to bike to work. Through data analysis it was found that the most impactful variables were the region of the country, gender, population density, and commute distance. Bicycle commuters statistically had fewer vehicles in their households and drove less miles annually.
There were five main target groups found through this analysis; people who bike for other reasons besides work and live in a city with more than 4,000 people per square mile, young professionals between 19-39, women in regions with separated bicycle facilities, those with low vehicle availability, and environmentally conscious individuals. Working to target these groups through advertising campaigns to encourage new users, as well as increasing and improving bicycle facilities, will help create more new bicyclists.
ContributorsImbus, Eileen Elizabeth (Author) / Khoeini, Sara (Thesis director) / Pendyala, Ram (Committee member) / Civil, Environmental and Sustainable Eng Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Transportation around campus on time is crucial for in-person college students looking to succeed in their studies. Unfortunately, inequities have arisen between the ability of able-bodied students to get to and from class and permanently or temporarily disabled students looking to do the same. ASU’s solution to this problem, the Disability Access and Resource Transportation (DART) service, does not adequately address the needs of its targeted customers properly. Unfortunately, student surveys and anecdotal evidence from students’ lived experiences have demonstrated that DART often leaves students waiting for more than half an hour for a ride, causes students to miss class, and is altogether unreliable in today’s age where punctuality is key to success. Our goal in our thesis project was to create an equal on-campus transportation playing field for students with and without mobility issues so that a students’ ability to get around campus would never serve as a hindrance to his/her ability to, at a minimum, earn a degree; ideally empowering all students to thrive regardless of their personal circumstances.
ContributorsHabelt, Mark (Author) / Lu, Sharon (Co-author) / Pham, Benjamin (Co-author) / Vohs, Grace (Co-author) / Byrne, Jared (Thesis director) / Thomasson, Anna (Committee member) / Larson, Wiley (Committee member) / Barrett, The Honors College (Contributor) / School of Politics and Global Studies (Contributor) / Department of Military Science (Contributor) / School of International Letters and Cultures (Contributor)
Created2022-05
Description
Transportation around campus on time is crucial for in-person college students looking to succeed in their studies. Unfortunately, inequities have arisen between the ability of able-bodied students to get to and from class and permanently or temporarily disabled students looking to do the same. ASU’s solution to this problem, the Disability Access and Resource Transportation (DART) service, does not adequately address the needs of its targeted customers properly. Unfortunately, student surveys and anecdotal evidence from students’ lived experiences have demonstrated that DART often leaves students waiting for more than half an hour for a ride, causes students to miss class, and is altogether unreliable in today’s age where punctuality is key to success. Our goal in our thesis project was to create an equal on-campus transportation playing field for students with and without mobility issues so that a students’ ability to get around campus would never serve as a hindrance to his/her ability to, at a minimum, earn a degree; ideally empowering all students to thrive regardless of their personal circumstances.
ContributorsPham, Benjamin (Author) / Lu, Sharon (Co-author) / Habelt, Mark (Co-author) / Vohs, Grace (Co-author) / Byrne, Jared (Thesis director) / Larson, Wiley (Committee member) / Barrett, The Honors College (Contributor) / Aviation Programs (Contributor)
Created2022-05
Description
With the advent of new mobility services and technologies, the complexity of understanding the mobility patterns has been gradually intensified. The availability of large datasets, in conjunction with the transportation revolution, has been increased and incurs high computing costs. These two critical challenges require us to methodologically handle complex transportation problems with numerical performance: fast, high-precision solutions, and reliable structure under different impact factors. That is, it is imperative to introduce a new type of modeling strategy, advancing the conventional transportation planning models. In order to do this, we leverage the backbone of the underlying algorithm behind machine learning (ML): computational graph (CG) and automatic differentiation (AD). CG is a directed acyclic graph (DAG) where each vertex represents a mathematical operation, and each edge represents data transfer. AD is an efficient algorithm to analytically compute gradients of necessary functionality. Embedding the two key algorithms into the planning models, specifically parametric-based econometric models and network optimization models, we theoretically and practically develop different types of modeling structures and reformulate mathematical formulations on basis of the graph-oriented representation.
Three closely related analytical and computational frameworks are presented in this dissertation, based on a common modeling methodology of CG abstraction. First, a two-stage interpretable machine learning framework developed by a linear regression model, coupled with a neural network layered by long short-term memory (LSTM) shows the capability of capturing statistical characteristics with enhanced predictability in the context of day-to-day streaming datasets. Second, AD-based computation in estimating for discrete choice models proves more efficiency of handling complex modeling structure than the standard optimization solver relying on numerical gradients, outperforming the standard methods, Biogeme and Apollo. Lastly, CG allows modelers to take advantage of a special problem structure for the feedback loops, a new class of problem reformulation developed through Lagrangian relaxation (LR), which makes CG based model well suited for reaching a high degree of the integrated demand-supply consistency.
Overall, the deep integration of the practically important planning models with the underlying computationally efficient ML algorithms can enhance behavioral understanding of interactions in real-world urban systems, and the proposed differentiable mathematical structures will enable transportation decision-makers to accurately evaluate different demand-side and supply-side scenarios with a higher degree of convergency and optimality in more complex transportation systems.
ContributorsKim, Taehooie (Author) / Pendyala, Ram RP (Thesis advisor) / Zhou, Xuesong XZ (Thesis advisor) / Pan, Rong RP (Committee member) / Lou, Yingyan YL (Committee member) / Arizona State University (Publisher)
Created2021
Description
By the evolution of technologies and computing power, it is possible to capture and save large amounts of data and then find patterns in large and complex datasets using data science and machine learning. This dissertation introduces machine-learning models and econometric models to use in infrastructure transportation projects. Among transportation infrastructure projects, the airline industry and highways are selected to implement the models.The first topic of this dissertation focuses on using machine-learning models in highway projects. The International Roughness Index (IRI) for asphalt concrete pavement is predicted based on the 12,637 observations in the Long-Term Pavement Performance (LTPP) dataset for 1,390 roads and highways in the 50 states of the United States and the District of Columbia from 1989 to 2018. The results show that XGBoost provides a better model fit in terms of mean absolute error and coefficient of determination than other studied models. Also, the most important factors in predicting the IRI are identified.
The second topic of this dissertation aims to develop machine-learning models to predict customer dissatisfaction in the airline industry. The relationship between measures of service failure (flight delay and mishandled baggage) and customer dissatisfaction is predicted by using longitudinal data from 2003 to 2019 from the U.S. airline industry. Data was obtained from the Air Travel Consumer Report (ATCR) published by the U.S. Department of Transportation. Flight delay is more important in low-cost airlines, while mishandled baggage is more important in legacy airlines. Also, the effect of the train-test split ratio on each machine-learning model is examined by running each model using four train-test splits. Results indicate that the train-test split ratio could influence the selection of the best model.
The third topic in this dissertation uses econometric analysis to investigate the relationship between customer dissatisfaction and two measures of service failure in the U.S. airline industry. Results are: 1) Mishandled baggage has more impact than flight delay on customer complaints. 2) The effect of an airline’s service failures on customer complaints is contingent on the category of the airline. 3) The effect of flight delay on customer complaints is lower for low-cost airlines compared to legacy airlines.
ContributorsDamirchilo, Farshid (Author) / Fini, Elham H (Thesis advisor) / Lamanna, Anthony J (Committee member) / Parast, Mahour M (Committee member) / Sullivan, Kenneth (Committee member) / Arizona State University (Publisher)
Created2021
Description
Transit agencies are struggling to regain ridership lost during the pandemic. Research shows that riding transit was among the most feared activities during the pandemic due to people’s high perceived risk of infection. Transit agencies have responded by implementing a variety of pandemic-related safety measures in stations and vehicles, but there is little literature assessing how these safety measures affect passengers’ perception of safety. This study implements surveys, interviews, and observations in Berlin, Germany to assess how passengers’ demographic characteristics and experiences with safety measures are related to their perception of safety using transit. Females and older age groups were more likely to perceive transit as riskier than males and younger age groups. The results provide little evidence to suggest that safety measures have a significant impact on passengers’ perception of safety, however. If this result is supported by future research, it suggests that transit agency investments in pandemic safety measures may not help them to regain ridership.
ContributorsKatt, Noah (Author) / Salon, Deborah (Thesis advisor) / Meerow, Sara (Committee member) / King, David (Committee member) / Arizona State University (Publisher)
Created2022
Description
Transportation around campus on time is crucial for in-person college students looking to succeed in their studies. Unfortunately, inequities have arisen between the ability of able-bodied students to get to and from class and permanently or temporarily disabled students looking to do the same. ASU’s solution to this problem, the Disability Access and Resource Transportation (DART) service, does adequately address the needs of its targeted customers properly. Unfortunately, student surveys and anecdotal evidence from students’ lived experiences have demonstrated that DART often leaves students waiting for more than half an hour for a ride, causes students to miss class, and is altogether unreliable in today’s age where punctuality is key to success. Our goal in our thesis project was to create an equal on-campus transportation playing field for students with and without mobility issues so that a students’ ability to get around campus would never serve as a hindrance to his/her ability to, at a minimum, earn a degree; ideally empowering all students to thrive regardless of their personal circumstances.
ContributorsLu, Sharon (Author) / Vohs, Grace (Co-author) / Habelt, Mark (Co-author) / Pham, Benjamin (Co-author) / Byrne, Jared (Thesis director) / Larson, Wiley (Committee member) / Balven, Rachel (Committee member) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor) / Department of Information Systems (Contributor)
Created2022-05
Description
The aim of this dissertation is to develop an understanding of the relationships between the daily commute, commuting stress, and Health-Related Quality of Life (HRQOL) based on a case study in Georgetown Guyana. Three separate but connected pieces of work were attempted to accomplish this aim. First, a scoping review was conducted using the Joanna Briggs Guidelines to elucidate the factors that contribute to commuting stress that have already been explored in the literature. This scoping review unearthed 11 factors across three broad categories. The commute-specific factors which contribute to commuting stress include, the length of the commute and the mode of the commute (whether active or non/active). The built environment factors include the levels of traffic congestion, the type of infrastructure that is in place, the landscape that lines the commuting route, and the experience of non-compliant fellow commuters. Personal factors include gender, age, hours of work, and quality of sleep. These factors along with a few others were then tested within a binomial regression framework that utilized data from 427 working adults. The results mirrored what was found in the literature. In addition, there was clarification of the roles of two factors for which the literature appeared to have not comprehensively addressed. These are modes of commute, that is persons who commute by private means are less likely to experience commuter stress than persons who commute via public means. In the third task, the relationship between these novel commute-specific factors and HRQOL. The result of this study demonstrated that persons who used private commuting and who were more satisfied with the commute infrastructure were more likely to have higher HRQOL scores than those who were not satisfied with the commute infrastructure in place and those who used public transportation. The results further demonstrated that commuting stress mediated the relationship between satisfaction with commute infrastructure and HRQOL, but it did not mediate the relationship between commuting mode and HRQOL. To address these issues, it is recommended that action be taken at the micro, meso, and macroeconomic levels. Keywords: urbanization, daily commute, stress, health-related quality of life, Guyana
ContributorsVan-Veen, Davon (Author) / Chhetri, Netra NC (Thesis advisor) / Jamme, Hue-Tam HJ (Committee member) / Ross, Heather HR (Committee member) / Arizona State University (Publisher)
Created2023