Browsing by Author "Miller, Erika, advisor"
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Item Open Access Evaluating factors that impact situation awareness and takeover responses during cyberattacks on connected and automated vehicles(Colorado State University. Libraries, 2022) Aliebrahimi, Somayeh, author; Miller, Erika, advisor; Bradley, Thomas, committee member; Batchelor, Ann, committee member; Clegg, Benjamin, committee memberAutonomous vehicles offer many potential benefits; however, this expansion of cyber-physical systems into transportation also introduces a new potential vulnerability in terms of cybersecurity threats. It is therefore important to understand the role vehicle occupants can play in preventing and responding to cyberattacks. The objectives of this study are to (1) evaluate how drivers respond to unexpected cyberattacks on automated vehicles, (2) evaluate how cybersecurity knowledge affects situation awareness (SA) during cyberattacks on automated driving, and (3) evaluate how the type of cyberattack affects a drivers' response. A driving simulator study with 20 participants was conducted to measure drivers' performance during unexpected cyberattacks on a SAE Level 2 partially-autonomous vehicle and the infrastructure in the driving environment. The scenarios were developed specifically for use in this study. Each participant experienced four driving scenarios, each scenario with a different cyberattack. Two cyberattacks were directly on the vehicle and two were on the infrastructure. Situation Awareness Global Assessment Technique (SAGAT) was used to measure participants' situation awareness during the drives and at the time of the cyberattacks. Participant takeover responses to the cyberattacks were collected through the driving simulator. Participants also completed a cybersecurity knowledge survey at the end of the experiment to assess their previous overall cyber awareness and experience with autonomous vehicles. Most of the participants noticed the cyberattacks, however only about half of the participants chose to take over control of the vehicle during the attacks, and in one attack no one overtook the automation. Results from ANOVAs showed significantly higher SA for participants with greater familiarity with cybersecurity terms and vehicle-to-everything technology. In addition, SA scores were significantly higher for participants who believed security systems (i.e., firewall, encryption) are important and for those who felt protected against cybercrimes. The present results suggest that increased cybersecurity knowledge can cause a high level of situation awareness during automated driving, which can help drivers to control unexpected driving situations due to cybersecurity attacks. Additionally, the results show that drivers are more likely to takeover control of their automated vehicle for cyberattacks that have known adverse outcomes, such as failing to stop at a stop sign or traffic signal or when their vision is obscured.Item Open Access Human systems integration of agricultural machinery in developing economy countries: Sudan as a case study(Colorado State University. Libraries, 2022) Ahmed, Hamza, author; Miller, Erika, advisor; Owiny, James, committee member; Simske, Steve, committee member; Jablonski, Becca, committee member; Herber, Daniel, committee memberWidespread adoption of agricultural machinery for developing economy countries is commonly regarded as a fundamental component of pro-poor growth and sustainable intensification. Mechanized farming can also improve perceptions of farming and mitigate rural-out migration. However, many traditional farmers do not have access to machinery and/or the machinery is cost prohibitive. This study applies the systems engineering approach to identify human-systems integration (HSI) solutions in agricultural practices to more effectively adapt technologies to satisfy traditional farmers' needs. A treatment control study was conducted on 36 farms in Sudan, Africa, over three farming seasons: 2019 (baseline), 2020, and 2021. The treatment group farmers (N = 6) were provided with agricultural machinery (i.e., tractor, cultivator, planter, and harvester), fuel for the machinery, and training to use the machinery. Farmers were interviewed at the beginning of the study and then after each planting and harvesting season during the study. Findings show that the most significant barriers for technology adoption were culture, security, and maintenance costs. However, they also reported that the most significant challenges in their nonmechanized farming practices were related to labor, safety, and profit margins, all of which could be addressed with machinery. Moreover, the results show that all farmers had similar net profits in 2019, when farming without machinery, while mechanized farming yielded significantly higher net profits ($16.61 per acre more in 2020 and $27.10 per acre more in 2021). Farmers also provided needs and rationales of various design options in tractors and attachments. The findings of this dissertation suggest that, despite the initial resistance to using agricultural machinery, the farmers were pleased by their experience after using farming machinery and expressed an even more accepting attitude from their children towards this new farming process. These results demonstrate the importance of developing effective solutions for integrating farming technology into rural farming practices in developing economy countries. More broadly, this study can be used as an HSI framework for identifying design needs and integrating technology into users' lifestyle. The results presented in this dissertation provide a quantified difference between farming with and without machinery, which can provide a financial basis for purchasing and borrowing models, machinery design requirements, and educational value to farmers. Further, the financial values and design requirements can help inform farmers regarding expected costs, returns, and payoffs from tractor adoption. Manufacturers and policymakers can utilize this to promote technology adoption more effectively to farmers in developing economy countries.Item Open Access Optimizing designer cognition relative to generative design methods(Colorado State University. Libraries, 2023) Botyarov, Michael, author; Miller, Erika, advisor; Bradley, Thomas, committee member; Forrest, Jeffrey, committee member; Moraes, Marcia, committee member; Simske, Steve, committee member; Radford, Donald, committee memberGenerative design is a powerful tool for design creation, particularly for complex engineering problems where a plethora potential design solutions exist. Generative design systems explore the entire solution envelope and present the designer with multiple design alternatives that satisfy specified requirements. Although generative design systems present design solutions to an engineering problem, these systems lack consideration for the human element of the design system. Human cognition, particularly cognitive workload, can be hindered when presented with unparsed generative design system output, thereby reducing the efficiency of the systems engineering life cycle. Therefore, the objective of this dissertation was to develop a structured approach to produce an optimized parsing of spatially different generative design solutions, derived from generative design systems, such that human cognitive performance during the design process is improved. Generative design usability foundation work was conducted to further elaborate on gaps found in the literature in the context of the human component of generative design systems. A generative design application was then created for the purpose of evaluating the research objective. A novel generative design solution space parsing method that leverages the Gower distance matrix and partitioning around medoids (PAM) clustering method was developed and implemented in the generative design application to structurally parse the generative design solution space for the study. The application and associated parsing method were then used by 49 study participants to evaluate performance, workload, and experience during a generative design selection process, given manipulation of both the quantity of designs in the generative design solution space and filtering of parsed subsets of design alternatives. Study data suggests that cognitive workload is lowest when 10 to 100 generative design alternatives are presented for evaluation in the subset of the overall design solution space. However, subjective data indicates a caution when limiting the subset of designs presented, since design selection confidence and satisfaction may be decreased the more limited the design alternative selection becomes. Given these subjective considerations, it is recommended that a generative design solution space consists of 50 to 100 design alternatives, with the proposed clustering parsing method that considers all design alternative variables.Item Open Access Techniques in reactive to proactive obsolescence management for C5ISR systems(Colorado State University. Libraries, 2023) Chellin, Matthew D., author; Miller, Erika, advisor; Daily, Jeremy, committee member; Herber, Daniel, committee member; Simske, Steven, committee member; Prawel, David, committee memberObsolescence is a significant challenge for the Command, Control, Communications, Computers, Cyber, Intelligence, Surveillance and Reconnaissance (C5ISR) community. Obsolescence can negatively affect a C5ISR system's cost, schedule, performance, and readiness. This research examines the challenge of obsolescence for C5ISR systems by focusing on the U.S. Army at Aberdeen Proving Ground, Maryland and their industry partners. The objective of this research is to synthesize insights from the experiences of government and industry practitioners that mitigate diminishing manufacturing sources and material shortages (DMSMS) challenges into mitigation techniques. The obsolescence mitigation areas described in this research include proactive and reactive obsolescence mitigation, obsolescence mitigation methods, and the importance of DMSMS contracting language. This research also offers approaches grounded in practitioner experiences to mitigate obsolescence through a proactive obsolescence management model, risk mitigation framework, metrics, modeling & simulation, and systems thinking methods. The combination of the models, methods, and approaches discussed from this research have the potential to achieve greater system readiness, more availability, better maintainability, and lower costs for C5ISR systems.