Matching Items (4)
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- All Subjects: Transportation
- Genre: Academic theses
- Creators: Branaghan, Russell
Description
As urban populations become increasingly dense, massive amounts of new 'big' data that characterize human activity are being made available and may be characterized as having a large volume of observations, being produced in real-time or near real-time, and including a diverse variety of information. In particular, spatial interaction (SI) data - a collection of human interactions across a set of origins and destination locations - present unique challenges for distilling big data into insight. Therefore, this dissertation identifies some of the potential and pitfalls associated with new sources of big SI data. It also evaluates methods for modeling SI to investigate the relationships that drive SI processes in order to focus on human behavior rather than data description.
A critical review of the existing SI modeling paradigms is first presented, which also highlights features of big data that are particular to SI data. Next, a simulation experiment is carried out to evaluate three different statistical modeling frameworks for SI data that are supported by different underlying conceptual frameworks. Then, two approaches are taken to identify the potential and pitfalls associated with two newer sources of data from New York City - bike-share cycling trips and taxi trips. The first approach builds a model of commuting behavior using a traditional census data set and then compares the results for the same model when it is applied to these newer data sources. The second approach examines how the increased temporal resolution of big SI data may be incorporated into SI models.
Several important results are obtained through this research. First, it is demonstrated that different SI models account for different types of spatial effects and that the Competing Destination framework seems to be the most robust for capturing spatial structure effects. Second, newer sources of big SI data are shown to be very useful for complimenting traditional sources of data, though they are not sufficient substitutions. Finally, it is demonstrated that the increased temporal resolution of new data sources may usher in a new era of SI modeling that allows us to better understand the dynamics of human behavior.
A critical review of the existing SI modeling paradigms is first presented, which also highlights features of big data that are particular to SI data. Next, a simulation experiment is carried out to evaluate three different statistical modeling frameworks for SI data that are supported by different underlying conceptual frameworks. Then, two approaches are taken to identify the potential and pitfalls associated with two newer sources of data from New York City - bike-share cycling trips and taxi trips. The first approach builds a model of commuting behavior using a traditional census data set and then compares the results for the same model when it is applied to these newer data sources. The second approach examines how the increased temporal resolution of big SI data may be incorporated into SI models.
Several important results are obtained through this research. First, it is demonstrated that different SI models account for different types of spatial effects and that the Competing Destination framework seems to be the most robust for capturing spatial structure effects. Second, newer sources of big SI data are shown to be very useful for complimenting traditional sources of data, though they are not sufficient substitutions. Finally, it is demonstrated that the increased temporal resolution of new data sources may usher in a new era of SI modeling that allows us to better understand the dynamics of human behavior.
ContributorsOshan, Taylor Matthew (Author) / Fotheringham, A. S. (Thesis advisor) / Farmer, Carson J.Q. (Committee member) / Rey, Sergio S.J. (Committee member) / Nelson, Trisalyn (Committee member) / Arizona State University (Publisher)
Created2017
Description
The Federal Flight Deck Officer (FFDO) program was mandated legislatively, as part of the Homeland Security Act of 2002. This study replicated earlier research that investigated pilots’ opinions of the current state of the FFDO program based on interviews. A Likert survey was created to allow simpler quantitative collection and analysis of opinions from large groups of pilots. A total of 43 airline pilots participated in this study. Responses to the Likert questions were compared with demographics, searching for significance through a Pearson chi-square test and frequencies were compared to earlier research findings. Significant chi-square results showed that those familiar with the program were more likely to agree the program should continue, it was effective, the screening and selection process of program applicants was adequate and the Federal Air Marshal Service’s management of the FFDO program was effective. Those with Military experience were more likely to disagree it was reasonable that FFDOs were required to pay for their own room and board during training or train on their own time. All those who shared an opinion agreed there should be a suggestion medium between FFDOs and their management. Unlike the prior study, all those familiar with the program agreed the weapons transportation and carriage procedures were adequate. Furthermore, all those who shared an opinion found the holster locking mechanism adequate, which was another reversal of opinion from the prior study. Similar to the prior study, pilots unanimously agree FFDOs were well trained and agreed that the program was effective and should continue.
ContributorsFerrara, Marc, M.S (Author) / Niemczyk, Mary (Thesis advisor) / Nullmeyer, Robert (Committee member) / Branaghan, Russell (Committee member) / Arizona State University (Publisher)
Created2017
Description
This study exmaines the effect of in-vehicle infotainment display depth on driving performance. More features are being built into infotainment displays, allowing drivers to complete a greater number of secondary tasks while driving. However, the complexity of completing these tasks can take attention away from the primary task of driving, which may present safety risks. Tasks become more time consuming as the items drivers wish to select are buried deeper in a menu’s structure. Therefore, this study aims to examine how deeper display structures impact driving performance compared to more shallow structures.
Procedure. Participants complete a lead car following task, where they follow a lead car and attempt to maintain a time headway (TH) of 2 seconds behind the lead car at all times, while avoiding any collisions. Participants experience five conditions where they are given tasks to complete with an in-vehicle infotainment system. There are five conditions, each involving one of five displays with different structures: one-layer vertical, one-layer horizontal, two-layer vertical, two-layer horizontal, and three-layer. Brake Reaction Time (BRT), Mean Time Headway (MTH), Time Headway Variability (THV), and Time to Task Completion (TTC) are measured for each of the five conditions.
Results. There is a significant difference in MTH, THV, and TTC for the three-layer condition. There is a significant difference in BRT for the two-layer horizontal condition. There is a significant difference between one- and two-layer displays for all variables, BRT, MTH, THV, and TTC. There is also a significant difference between one- and three-layer displays for TTC.
Conclusions. Deeper displays negatively impact driving performance and make tasks more time consuming to complete while driving. One-layer displays appear to be optimal, although they may not be practical for in-vehicle displays.
Procedure. Participants complete a lead car following task, where they follow a lead car and attempt to maintain a time headway (TH) of 2 seconds behind the lead car at all times, while avoiding any collisions. Participants experience five conditions where they are given tasks to complete with an in-vehicle infotainment system. There are five conditions, each involving one of five displays with different structures: one-layer vertical, one-layer horizontal, two-layer vertical, two-layer horizontal, and three-layer. Brake Reaction Time (BRT), Mean Time Headway (MTH), Time Headway Variability (THV), and Time to Task Completion (TTC) are measured for each of the five conditions.
Results. There is a significant difference in MTH, THV, and TTC for the three-layer condition. There is a significant difference in BRT for the two-layer horizontal condition. There is a significant difference between one- and two-layer displays for all variables, BRT, MTH, THV, and TTC. There is also a significant difference between one- and three-layer displays for TTC.
Conclusions. Deeper displays negatively impact driving performance and make tasks more time consuming to complete while driving. One-layer displays appear to be optimal, although they may not be practical for in-vehicle displays.
ContributorsGran, Emily (Author) / Gray, Robert (Thesis advisor) / Branaghan, Russell (Committee member) / Carrasquilla, Christina (Committee member) / Arizona State University (Publisher)
Created2018
Description
Future autonomous vehicle systems will be diverse in design and functionality since they will be produced by different brands. In the automotive industry, trustworthiness of a vehicle is closely tied to its perceived safety. Trust involves dependence on another agent in an uncertain situation. Perceptions of system safety, trustworthiness, and performance are important because they guide people’s behavior towards automation. Specifically, these perceptions impact how reliant people believe they can be on the system to do a certain task. Over or under reliance can be a concern for safety because they involve the person allocating tasks between themselves and the system in inappropriate ways. If a person trusts a brand they may also believe the brand’s technology will keep them safe. The present study measured brand trust associations and performance expectations for safety between twelve different automobile brands using an online survey.
The literature and results of the present study suggest perceived trustworthiness for safety of the automation and the brand of the automation, could together impact trust. Results revelated that brands closely related to the trust-based attributes, Confidence, Secure, Integrity, and Trustworthiness were expected to produce autonomous vehicle technology that performs in a safer way. While, brands more related to the trust-based attributes Harmful, Deceptive, Underhanded, Suspicious, Beware, and Familiar were expected to produce autonomous vehicle technology that performs in a less safe way.
These findings contribute to both the fields of Human-Automation Interaction and Consumer Psychology. Typically, brands and automation are discussed separately however, this work suggests an important relationship may exist. A deeper understanding of brand trust as it relates to autonomous vehicles can help producers understand potential for over or under reliance and create safer systems that help users calibrate trust appropriately. Considering the impact on safety, more research should be conducted to explore brand trust and expectations for performance between various brands.
The literature and results of the present study suggest perceived trustworthiness for safety of the automation and the brand of the automation, could together impact trust. Results revelated that brands closely related to the trust-based attributes, Confidence, Secure, Integrity, and Trustworthiness were expected to produce autonomous vehicle technology that performs in a safer way. While, brands more related to the trust-based attributes Harmful, Deceptive, Underhanded, Suspicious, Beware, and Familiar were expected to produce autonomous vehicle technology that performs in a less safe way.
These findings contribute to both the fields of Human-Automation Interaction and Consumer Psychology. Typically, brands and automation are discussed separately however, this work suggests an important relationship may exist. A deeper understanding of brand trust as it relates to autonomous vehicles can help producers understand potential for over or under reliance and create safer systems that help users calibrate trust appropriately. Considering the impact on safety, more research should be conducted to explore brand trust and expectations for performance between various brands.
ContributorsCelmer, Natalie (Author) / Branaghan, Russell (Thesis advisor) / Chiou, Erin (Thesis advisor) / Cooke, Nancy J. (Committee member) / Arizona State University (Publisher)
Created2018