Matching Items (55)
Description
Excessive weight gain during pregnancy is a significant public health concern and has been the recent focus of novel, control systems-based interventions. Healthy Mom Zone (HMZ) is an intervention study that aims to develop and validate an individually tailored and intensively adaptive intervention to manage weight gain for overweight or obese pregnant women using control engineering approaches. Motivated by the needs of the HMZ, this dissertation presents how to use system identification and state estimation techniques to assist in dynamical systems modeling and further enhance the performance of the closed-loop control system for interventions.
Underreporting of energy intake (EI) has been found to be an important consideration that interferes with accurate weight control assessment and the effective use of energy balance (EB) models in an intervention setting. To better understand underreporting, a variety of estimation approaches are developed; these include back-calculating energy intake from a closed-form of the EB model, a Kalman-filter based algorithm for recursive estimation from randomly intermittent measurements in real time, and two semi-physical identification approaches that can parameterize the extent of systematic underreporting with global/local modeling techniques. Each approach is analyzed with intervention participant data and demonstrates potential of promoting the success of weight control.
In addition, substantial efforts have been devoted to develop participant-validated models and incorporate into the Hybrid Model Predictive Control (HMPC) framework for closed-loop interventions. System identification analyses from Phase I led to modifications of the measurement protocols for Phase II, from which longer and more informative data sets were collected. Participant-validated models obtained from Phase II data significantly increase predictive ability for individual behaviors and provide reliable open-loop dynamic information for HMPC implementation. The HMPC algorithm that assigns optimized dosages in response to participant real time intervention outcomes relies on a Mixed Logical Dynamical framework which can address the categorical nature of dosage components, and translates sequential decision rules and other clinical considerations into mixed-integer linear constraints. The performance of the HMPC decision algorithm was tested with participant-validated models, with the results indicating that HMPC is superior to "IF-THEN" decision rules.
Underreporting of energy intake (EI) has been found to be an important consideration that interferes with accurate weight control assessment and the effective use of energy balance (EB) models in an intervention setting. To better understand underreporting, a variety of estimation approaches are developed; these include back-calculating energy intake from a closed-form of the EB model, a Kalman-filter based algorithm for recursive estimation from randomly intermittent measurements in real time, and two semi-physical identification approaches that can parameterize the extent of systematic underreporting with global/local modeling techniques. Each approach is analyzed with intervention participant data and demonstrates potential of promoting the success of weight control.
In addition, substantial efforts have been devoted to develop participant-validated models and incorporate into the Hybrid Model Predictive Control (HMPC) framework for closed-loop interventions. System identification analyses from Phase I led to modifications of the measurement protocols for Phase II, from which longer and more informative data sets were collected. Participant-validated models obtained from Phase II data significantly increase predictive ability for individual behaviors and provide reliable open-loop dynamic information for HMPC implementation. The HMPC algorithm that assigns optimized dosages in response to participant real time intervention outcomes relies on a Mixed Logical Dynamical framework which can address the categorical nature of dosage components, and translates sequential decision rules and other clinical considerations into mixed-integer linear constraints. The performance of the HMPC decision algorithm was tested with participant-validated models, with the results indicating that HMPC is superior to "IF-THEN" decision rules.
ContributorsGuo, Penghong (Author) / Rivera, Daniel E. (Thesis advisor) / Peet, Matthew M. (Committee member) / Forzani, Erica (Committee member) / Deng, Shuguang (Committee member) / Pavlic, Theodore P. (Committee member) / Arizona State University (Publisher)
Created2018
Description
Improvised explosive devices (IEDs) have become a major threat to military personnel in recent years. In the United States Army, Mission Payload Operators (MPOs) operate cameras from unmanned aerial vehicles (UAVs) to detect the threat of IEDs using real-time images received. Previous researchers obtained the expert knowledge of twelve MPOs at Fort Huachuca and learned that they rely on "behavioral signatures," the behavioral and environmental cues associated with IED threat rather than the IED itself (Cooke, Hosch, Banas, Hunn, Staszewski & Fensterer, 2010). To the best of our knowledge, no formal MPO training exists and all training is acquired on-the-job. The end goal is to create training systems for future MPOs using cognitive engineering based on expert skill (CEBES) that focus on detection of behavioral cues associated with IED threats. The complexity and dynamicity of cues associated with IED emplacement is to be noted, as such cues are influenced by sociocultural knowledge and often develop over significant periods of time. A dynamic full motion video simulation environment has been created, and embedded with cues elicited from expert MPOs. A three-part simulation has been created. The next step is verifying critical cues MPOs identify and focus on using eye tracking equipment.
ContributorsKnobloch, Ashley Kay (Author) / Cooke, Nancy (Thesis director) / Branaghan, Russ (Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor) / Human Systems Engineering (Contributor)
Created2014-12
Description
The knowledge of cognitive processes of teams and how they work as a system, has drastically broadened in recent years. However, few researchers have applied their findings to an orchestral setting. In the current study, team cognition was observed and analyzed based off an 8th grade orchestra, in addition to the middle and highest-level orchestras at a junior high and high school in the Arizona Public School system. It was found, that in the 8th grade orchestra, most communication is either given or received in the form of auditory cues both verbal and musical. Regardless of skill level, groups that have higher interactions during practices have better performances.
ContributorsColeman, Pamela Brooke (Author) / Cooke, Nancy (Thesis director) / Craig, Scotty (Committee member) / Human Systems Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
In Nepal, a viable solution for environmental management, food and water security is the production of biochar, a carbon material made of plants burned in low oxygen conditions. Currently, the biochar is manufactured into charcoal briquettes and sold on the market for energy usage, however this may not provide the best value for community members who make less than a dollar a day and sell the biochar for as little as 16 cents per kilogram. This thesis seeks to improve the price of biochar and help their livelihoods as well as explore innovative solutions. One way to improve biochar while addressing water security problems is to create activated carbon, which uses its heightened porosity to adsorb contaminants from water or air. Activated carbon is also worth 100x the price of biochar. This thesis evaluates the mass content of biochar produced in Nepal, comparing it to literature values, and performed gravimetric and thermogravimetric analysis, comparing it to Activated Charcoal. Analysis of the biochar system used in Nepal reveals that the byproduct of biochar, biofuels, is highly underutilized. The higher heating value of biochar is 17.95 MJ/kg, which is much lower than other charcoals which burn around 30 MJ/kg. Low volatile content, less than 5% in biochar, provides a smokeless briquette, which is favorable on the market, however low heating value and misutilizations of biofuels in the solution indicate that creating a briquette is not the best use for biochar. Ash content is really high in this biochar, averaging around 12% and it may be due to the feedstock, a composite between Mikania and Lantana, which have 5.23% and 10.77% ash content respectively. This does not necessarily indicate a poor quality biochar, since ash values can vary widely between charcoals. Producing activated charcoal from this biochar is a favored solution; it will increase the price of the biochar, provide water security solutions, and be an appropriate process for this biochar, where heating value and underutilization of biofuel byproducts pose a problem.
ContributorsCayer, Joelle Marie Caroline (Author) / Chhetri, Netra (Thesis director) / Henderson, Mark (Committee member) / Deng, Shuguang (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Separation of carbon dioxide and methane for the upgrade of natural gas through use of pressure swing adsorption could potentially save large amounts of energy from the current, costly process of cryogenic distillation and provides greater cost effectiveness for carbon dioxide capture, and provide larger product flowrates than membrane permeation separation. The purpose of this study is to analyze the effects of varying initial conditions of a MatLab simulation, courtesy of Mai Xu, a graduate student at ASU, designed to use Langmuir isotherms, mass transfer equations, and adsorbent and gas properties to simulate a pressure swing adsorption process with a mixture of methane and carbon dioxide gas feed. The effects that will be varied are the adsorption/desorption time, pressurization/depressurization time, adsorption feed composition, desorption purge composition, adsorption pressure, desorption pressure, adsorption flow rate, and desorption flow rate. The study found that the trends in methane purity and production generally follow the trends predicted by literature and relevant equations, with pressure boundaries being the largest impacting factor. In addition there was a markedly inverse correlation between purity of methane product and the productivity of the system. This trend was only violated in one instance, at very low vacuum pressure during desorption, which could indicate an area that requires further study. Overall, the main areas of improvement in pressure swing adsorption for this system would be improving the selectivity of adsorption of carbon dioxide over methane, which requires improvement and change of the adsorbent, and more extreme vacuum pressures during desorption, both of which will increase methane yield and reduce operating costs.
ContributorsCook, Alexander Charles (Author) / Deng, Shuguang (Thesis director) / Mu, Bin (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Carbon capture is an essential way to reduce greenhouse gas emissions. One way to decrease the emissions is through the use of adsorbents such as zeolites. Dr. Dong-Kyun Seo’s group (School of Molecular Sciences, Arizona State University) synthesized the nanostructured faujasite (NaX). The zeolite was characterized using Scanning Electron Microscopy (SEM) and the physisorption properties were determined using ASAP 2020. ASAP 2020 tests of the nano-zeolite pellets at 77K in a liquid N2 bath determined the BET surface area of 547.1 m2/mol, T-plot micropore volume of 0.2257 cm3/g, and an adsorption average pore width of 5.9 Å. The adsorption isotherm (equilibrium) of CH4, N2, and CO2 were measured at 25ºC. Adsorption isotherm experiments concluded that the linear isotherm was the best fit for N2, and CH4 and the Sips isotherm was a better fit than the Langmuir and Freundlich isotherm for CO2. At 25ºC and 1 atm the zeolite capacity for CO2 is 4.3339 mmol/g, 0.1948 mmol/g for CH4, and 0.3534 mmol/g for N2. The zeolite has a higher CO2 capacity than the conventional NaX zeolite. Breakthrough experiments were performed in a fixed bed 22in, 0.5 in packing height and width at 1 atm and 298 K with nano-zeolite pellets. The gas chromatographer tested and recorded the data every two minutes with a flow rate of 10 cm3/min for N2 and 10 cm3/min CO2. Breakthrough simulations of the zeolite in a fixed bed adsorber column were conducted on MATLAB utilizing varying pressures, flow rates, and fed ratios of various CO2, N2 and CH4. Simulations using ideal adsorbed solution theory (IAST) calculations determined that the selectivity of CO2 in flue gas (15% CO2 + 85% N2) is 571.79 at 1 MPa, significantly higher than commercial zeolites and literature. The nanostructured faujasite zeolite appears to be a very promising adsorbent for CO2/N2 capture from flue gas and the separation of CO2/N2.
ContributorsClark, Krysta D. (Author) / Deng, Shuguang (Thesis director) / Green, Matthew (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Workplace productivity is a result of many factors, and among them is the setup of the office and its resultant noise level. The conversations and interruptions that come along with converting an office to an open plan can foster innovation and creativity, or they can be distracting and harm the performance of employees. Through simulation, the impact of different types of office noise was studied along with other changing conditions such as number of people in the office. When productivity per person, defined in terms of mood and focus, was measured, it was found that the effect of noise was positive in some scenarios and negative in others. In simulations where employees were performing very similar tasks, noise (and its correlates, such as number of employees), was beneficial. On the other hand, when employees were engaged in a variety of different types of tasks, noise had a negative overall effect. This indicates that workplaces that group their employees by common job functions may be more productive than workplaces where the problems and products that employees are working on are varied throughout the workspace.
ContributorsHall, Mikaela Starrantino (Author) / Pavlic, Theodore P. (Thesis director) / Cooke, Nancy (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Hydrothermal Liquefaction of Algae represents one of many pathways for the sustainable replacement of fossil fuels in transportation. When processing and researching algal biofuel, determination of the higher heating value (HHV) is paramount. Bomb calorimetry represents to current method for direct determination of HHV. When determining HHV’s indirectly, the industry standard is using one of many linear correlations relating elemental composition to HHV. Most of these correlations were developed from coal industry data, meaning that they do not necessarily fit algal product data well. In this study bomb calorimetry data and CHNS/O elemental composition data were collected for Chlorella, Micract, GS 5587.1, Kirchnella, and Gal 87.1 MM8 algae species. This data was added to CHNS/O and HHV values for other algal products in literature, and utilized to test the accuracy of the Dulong, Gumz, Vandralek and Boie correlations for algae products. Several preliminary algae specific correlations were proposed through a linear regression model of the data. Of the 5 samples tested, Kirchnella exhibited the highest HHV (23.2405 ± 0.0216 MJ/kg) and Chlorella exhibited the lowest (20.2055 ± 0.0484 MJ/kg). For both the experimental, and literature CHNS/O vs HHV data, the Vandralek and Boie correlations provided the best approximations in this study. For the totality of the data collected and researched in this study, 6 of 8 proposed correlations outperformed the Vandralek equation for HHV approximation. The most promising proposed correlations incorporated multiple linear regressions for elemental fractions of CHS, CHSO and CHNSO. Being that only 20 distinct algal product samples were regressed to create the proposed correlations, more data should be incorporated before publication of a final correlation. This study should serve as a starting point for the compilation of an exhaustive database for algal product assay and HHV data.
ContributorsCopp, Connor Joseph (Author) / Deng, Shuguang (Thesis director) / Muppaneni, Tapaswy (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
This honors thesis is focused on two separate catalysis projects conducted under the mentorship of Dr. Javier Pérez-Ramírez at ETH Zürich. The first project explored ethylene oxychlorination over supported europium oxychloride catalysts. The second project investigated alkyne semihydrogenation over nickel phosphide catalysts. This work is the subject of a publication of which I am a co-author, as cited below.
Project 1 Abstract: Ethylene Oxychlorination
The current two-step process for the industrial process of vinyl chloride production involves CuCl2 catalyzed ethylene oxychlorination to ethylene dichloride followed by thermal cracking of the latter to vinyl chloride. To date, no industrial application of a one-step process is available. To close this gap, this work evaluates a wide range of self-prepared supported CeO2 and EuOCl catalysts for one-step production of vinyl chloride from ethylene in a fixed-bed reactor at 623 773 K and 1 bar using feed ratios of C2H4:HCl:O2:Ar:He = 3:3 6:1.5 6:3:82 89.5. Among all studied systems, CeO2/ZrO2 and CeO2/Zeolite MS show the highest activity but suffer from severe combustion of ethylene, forming COx, while 20 wt.% EuOCl/γ-Al2O3 leads to the best vinyl chloride selectivity of 87% at 15.6% C2H4 conversion with complete suppression of CO2 formation and only 4% selectivity to CO conversion for over 100 h on stream. Characterization by XRD and EDX mapping reveals that much of the Eu is present in non-active phases such as Al2Eu or EuAl4, indicating that alternative synthesis methods could be employed to better utilize the metal. A linear relationship between conversion and metal loading is found for this catalyst, indicating that always part of the used Eu is available as EuOCl, while the rest forms inactive europium aluminate species. Zeolite-supported EuOCl slightly outperforms EuOCl/γ Al2O3 in terms of total yield, but is prone to significant coking and is unstable. Even though a lot of Eu seems locked in inactive species on EuOCl/γ Al2O3, these results indicate possible savings of nearly 16,000 USD per kg of catalyst compared to a bulk EuOCl catalyst. These very promising findings constitute a crucial step for process intensification of polyvinyl chloride production and exploring the potential of supported EuOCl catalysts in industrially-relevant reactions.
Project 2 Abstract: Alkyne Semihydrogenation
Despite strongly suffering from poor noble metal utilization and a highly toxic selectivity modifier (Pb), the archetypal catalyst applied for the three-phase alkyne semihydrogenation, the Pb-doped Pd/CaCO3 (Lindlar catalyst), is still being utilized at industrial level. Inspired by the very recent strategies involving the modification of Pd with p-block elements (i.e., S), this work extrapolates the concept by preparing crystalline metal phosphides with controlled stoichiometry. To develop an affordable and environmentally-friendly alternative to traditional hydrogenation catalysts, nickel, a metal belonging to the same group as Pd and capable of splitting molecular hydrogen has been selected. Herein, a simple two-step synthesis procedure involving nontoxic precursors was used to synthesize bulk nickel phosphides with different stoichiometries (Ni2P, Ni5P4, and Ni12P5) by controlling the P:Ni ratios. To uncover structural and surface features, this catalyst family is characterized with an array of methods including X-ray diffraction (XRD), 31P magic-angle nuclear magnetic resonance (MAS-NMR) spectroscopy, and X-ray photoelectron spectroscopy (XPS). Bulk-sensitive techniques prove the successful preparation of pure phases while XPS analysis unravels the facile passivation occurring at the NixPy surface that persists even after reductive treatment. To assess the characteristic surface fingerprints of these materials, Ar sputtering was carried out at different penetration depths, reveling the presence of Ni+ and P-species. Continuous-flow three-phase hydrogenations of short-chain acetylenic compounds display that the oxidized layer covering the surface is reduced under reaction conditions, as evidenced by the induction period before reaching the steady state performance. To assess the impact of the phosphidation treatment on catalytic performance, the catalysts were benchmarked against a commercial Ni/SiO2-Al2O3 sample. While Ni/SiO2-Al2O3 presents very low selectivity to the alkene (the selectivity is about 10% at full conversion) attributed to the well-known tendency of naked nickel nanoparticles to form hydrides, the performance of nickel phosphides is highly selective and independent of P:Ni ratio. In line with previous findings on PdxS, kinetic tests indicate the occurrence of a dual-site mechanism where the alkyne and hydrogen do not compete for the same site.
This work is the subject of a publication of which I am a co-author, as cited below.
D. Albani; K. Karajovic; B. Tata; Q. Li; S. Mitchell; N. López; J. Pérez-Ramírez. Ensemble Design in Nickel Phosphide Catalysts for Alkyne Semi-Hydrogenation. ChemCatChem 2019. doi.org/10.1002/cctc.201801430
Project 1 Abstract: Ethylene Oxychlorination
The current two-step process for the industrial process of vinyl chloride production involves CuCl2 catalyzed ethylene oxychlorination to ethylene dichloride followed by thermal cracking of the latter to vinyl chloride. To date, no industrial application of a one-step process is available. To close this gap, this work evaluates a wide range of self-prepared supported CeO2 and EuOCl catalysts for one-step production of vinyl chloride from ethylene in a fixed-bed reactor at 623 773 K and 1 bar using feed ratios of C2H4:HCl:O2:Ar:He = 3:3 6:1.5 6:3:82 89.5. Among all studied systems, CeO2/ZrO2 and CeO2/Zeolite MS show the highest activity but suffer from severe combustion of ethylene, forming COx, while 20 wt.% EuOCl/γ-Al2O3 leads to the best vinyl chloride selectivity of 87% at 15.6% C2H4 conversion with complete suppression of CO2 formation and only 4% selectivity to CO conversion for over 100 h on stream. Characterization by XRD and EDX mapping reveals that much of the Eu is present in non-active phases such as Al2Eu or EuAl4, indicating that alternative synthesis methods could be employed to better utilize the metal. A linear relationship between conversion and metal loading is found for this catalyst, indicating that always part of the used Eu is available as EuOCl, while the rest forms inactive europium aluminate species. Zeolite-supported EuOCl slightly outperforms EuOCl/γ Al2O3 in terms of total yield, but is prone to significant coking and is unstable. Even though a lot of Eu seems locked in inactive species on EuOCl/γ Al2O3, these results indicate possible savings of nearly 16,000 USD per kg of catalyst compared to a bulk EuOCl catalyst. These very promising findings constitute a crucial step for process intensification of polyvinyl chloride production and exploring the potential of supported EuOCl catalysts in industrially-relevant reactions.
Project 2 Abstract: Alkyne Semihydrogenation
Despite strongly suffering from poor noble metal utilization and a highly toxic selectivity modifier (Pb), the archetypal catalyst applied for the three-phase alkyne semihydrogenation, the Pb-doped Pd/CaCO3 (Lindlar catalyst), is still being utilized at industrial level. Inspired by the very recent strategies involving the modification of Pd with p-block elements (i.e., S), this work extrapolates the concept by preparing crystalline metal phosphides with controlled stoichiometry. To develop an affordable and environmentally-friendly alternative to traditional hydrogenation catalysts, nickel, a metal belonging to the same group as Pd and capable of splitting molecular hydrogen has been selected. Herein, a simple two-step synthesis procedure involving nontoxic precursors was used to synthesize bulk nickel phosphides with different stoichiometries (Ni2P, Ni5P4, and Ni12P5) by controlling the P:Ni ratios. To uncover structural and surface features, this catalyst family is characterized with an array of methods including X-ray diffraction (XRD), 31P magic-angle nuclear magnetic resonance (MAS-NMR) spectroscopy, and X-ray photoelectron spectroscopy (XPS). Bulk-sensitive techniques prove the successful preparation of pure phases while XPS analysis unravels the facile passivation occurring at the NixPy surface that persists even after reductive treatment. To assess the characteristic surface fingerprints of these materials, Ar sputtering was carried out at different penetration depths, reveling the presence of Ni+ and P-species. Continuous-flow three-phase hydrogenations of short-chain acetylenic compounds display that the oxidized layer covering the surface is reduced under reaction conditions, as evidenced by the induction period before reaching the steady state performance. To assess the impact of the phosphidation treatment on catalytic performance, the catalysts were benchmarked against a commercial Ni/SiO2-Al2O3 sample. While Ni/SiO2-Al2O3 presents very low selectivity to the alkene (the selectivity is about 10% at full conversion) attributed to the well-known tendency of naked nickel nanoparticles to form hydrides, the performance of nickel phosphides is highly selective and independent of P:Ni ratio. In line with previous findings on PdxS, kinetic tests indicate the occurrence of a dual-site mechanism where the alkyne and hydrogen do not compete for the same site.
This work is the subject of a publication of which I am a co-author, as cited below.
D. Albani; K. Karajovic; B. Tata; Q. Li; S. Mitchell; N. López; J. Pérez-Ramírez. Ensemble Design in Nickel Phosphide Catalysts for Alkyne Semi-Hydrogenation. ChemCatChem 2019. doi.org/10.1002/cctc.201801430
ContributorsTata, Bharath (Author) / Deng, Shuguang (Thesis director) / Muhich, Christopher (Committee member) / Chemical Engineering Program (Contributor, Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
In the next decade or so, there will be a shift in the industry of transportation across the world. Already today we have autonomous vehicles (AVs) tested in the Greater Phoenix area showing that the technology has improved to a level available to the public eye. Although this technology is not yet released commercially (for the most part), it is being used and will continue to be used to develop a safer future. With a high incidence of human error causing accidents, many expect that autonomous vehicles will be safer than human drivers. They do still require driver attention and sometimes intervention to ensure safety, but for the most part are much safer. In just the United States alone, there were 40,000 deaths due to car accidents last year [1]. If traffic fatalities were considered a disease, this would be an epidemic. The technology behind autonomous vehicles will allow for a much safer environment and increased mobility and independence for people who cannot drive and struggle with public transport. There are many opportunities for autonomous vehicles in the transportation industry. Companies can save a lot more money on shipping by cutting the costs of human drivers and trucks on the road, even allowing for simpler drop shipments should the necessary AI be developed.Research is even being done by several labs at Arizona State University. For example, Dr. Spring Berman’s Autonomous Collective Systems Lab has been collaborating with Dr. Nancy Cooke of Human Systems Engineering to develop a traffic testbed, CHARTopolis, to study the risks of driver-AV interactions and the psychological effects of AVs on human drivers on a small scale. This testbed will be used by researchers from their labs and others to develop testing on reaction, trust, and user experience with AVs in a safe environment that simulates conditions similar to those experienced by full-size AVs. Using a new type of small robot that emulates an AV, developed in Dr. Berman’s lab, participants will be able to remotely drive around a model city environment and interact with other AV-like robots using the cameras and LiDAR sensors on the remotely driven robot to guide them.
Although these commercial and research systems are still in testing, it is important to understand how AVs are being marketed to the general public and how they are perceived, so that one day they may be effectively adopted into everyday life. People do not want to see a car they do not trust on the same roads as them, so the questions are: why don’t people trust them, and how can companies and researchers improve the trustworthiness of the vehicles?
Although these commercial and research systems are still in testing, it is important to understand how AVs are being marketed to the general public and how they are perceived, so that one day they may be effectively adopted into everyday life. People do not want to see a car they do not trust on the same roads as them, so the questions are: why don’t people trust them, and how can companies and researchers improve the trustworthiness of the vehicles?
ContributorsShuster, Daniel Nadav (Author) / Berman, Spring (Thesis director) / Cooke, Nancy (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05