Matching Items (430)
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Description
The emerging multimodal mobility as a service (MaaS) and connected and automated mobility (CAM) are expected to improve individual travel experience and entire transportation system performance in various aspects, such as convenience, safety, and reliability. There have been extensive efforts in the literature devoted to enhancing existing and developing new

The emerging multimodal mobility as a service (MaaS) and connected and automated mobility (CAM) are expected to improve individual travel experience and entire transportation system performance in various aspects, such as convenience, safety, and reliability. There have been extensive efforts in the literature devoted to enhancing existing and developing new methodologies and tools to investigate the impacts and potentials of CAM systems. Due to the hierarchical nature of CAM systems and associated intrinsic correlated human factors and physical infrastructures from various resolutions, simply considering components across different levels into a single model may be practically infeasible and computationally prohibitive in operation and decision stages. One of the greatest challenges in existing studies is to construct a theoretically sound and computationally efficient architecture such that CAM system modeling can be performed in an inherently consistent cross-resolution manner. This research aims to contribute to the modeling of CAM systems on layered transportation networks, with a special focus on the following three aspects: (1) layered CAM system architecture with a tight network and modeling consistency, in which different levels of tasks can be efficiently performed at dedicated layers; (2) cross-resolution traffic state estimation in CAM systems using heterogeneous observations; and (3) integrated city logistics operation optimization in CAM for improving system performance.
ContributorsLu, Jiawei (Author) / Zhou, Xuesong (Thesis advisor) / Pendyala, Ram (Committee member) / Xue, Guoliang (Committee member) / Mittelmann, Hans (Committee member) / Arizona State University (Publisher)
Created2022
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Description
This study examines the outcomes of roundabouts in the State of Arizona. Two types of roundabouts are introduced in this study, single-lane roundabouts and double-lane roundabouts. A total of 17 roundabouts across Arizona were chosen upon several selection criteria and according to the availability of data for roundabouts in Arizona.

This study examines the outcomes of roundabouts in the State of Arizona. Two types of roundabouts are introduced in this study, single-lane roundabouts and double-lane roundabouts. A total of 17 roundabouts across Arizona were chosen upon several selection criteria and according to the availability of data for roundabouts in Arizona. Government officials and local cities’ personnel were involved in this work in order to achieve the most accurate results possible. This thesis focused mainly on the impact of roundabouts on the accident rates, accident severities, and any specific trends that could have been found. Scottsdale, Sedona, Phoenix, Prescott, and Cottonwood are the cities that were involved in this study. As an overall result, both types of roundabouts showed improvements in decreasing the severity of accidents. Single-lane roundabouts had the advantage of largely reducing the overall rate of accidents by 18%, while double-lane roundabouts increased the accident rate by 62%. Although the number of fatalities was very small, both types of roundabouts were able to stop all fatalities during the analysis periods used in this study. Damage rates increased by 2% and 60% for single-lane and double-lane roundabouts, respectively. All levels of injury severities dropped by 44% and 16% for single-lane and double-lane roundabouts, respectively. Education and awareness levels of the public still need to be improved in order for people to be able to drive within the roundabouts safely.
ContributorsSouliman, Beshoy (Author) / Mamlouk, Michael (Thesis advisor) / Kaloush, Kamil (Committee member) / Zhou, Xuesong (Committee member) / Arizona State University (Publisher)
Created2016
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Description
This dissertation investigates congestion mitigation during the ingress of a planned special event (PSE). PSEs would impact the regular operation of the transportation system within certain time periods due to increased travel demand or reduced capacities on certain road segments. For individual attendees, cruising for parking during a PSE could

This dissertation investigates congestion mitigation during the ingress of a planned special event (PSE). PSEs would impact the regular operation of the transportation system within certain time periods due to increased travel demand or reduced capacities on certain road segments. For individual attendees, cruising for parking during a PSE could be a struggle given the severe congestion and scarcity of parking spaces in the network. With the development of smartphones-based ridesharing services such as Uber/Lyft, more and more attendees are turning to ridesharing rather than driving by themselves. This study explores congestion mitigation during a planned special event considering parking, ridesharing and network configuration from both attendees and planner’s perspectives.

Parking availability (occupancy of parking facility) information is the fundamental building block for both travelers and planners to make parking-related decisions. It is highly valued by travelers and is one of the most important inputs to many parking models. This dissertation proposes a model-based practical framework to predict future occupancy from historical occupancy data alone. The framework consists of two modules: estimation of model parameters, and occupancy prediction. At the core of the predictive framework, a queuing model is employed to describe the stochastic occupancy change of a parking facility.

From an attendee’s perspective, the probability of finding parking at a particular parking facility is more treasured than occupancy information for parking search. However, it is hard to estimate parking probabilities even with accurate occupancy data in a dynamic environment. In the second part of this dissertation, taking one step further, the idea of introducing learning algorithms into parking guidance and information systems that employ a central server is investigated, in order to provide estimated optimal parking searching strategies to travelers. With the help of the Markov Decision Process (MDP), the parking searching process on a network with uncertain parking availabilities can be modeled and analyzed.

Finally, from a planner’s perspective, a bi-level model is proposed to generate a comprehensive PSE traffic management plan considering parking, ridesharing and route recommendations at the same time. The upper level is an optimization model aiming to minimize total travel time experienced by travelers. In the lower level, a link transmission model incorporating parking and ridesharing is used to evaluate decisions from and provide feedback to the upper level. A congestion relief algorithm is proposed and tested on a real-world network.
ContributorsXiao, Jun, Ph.D (Author) / Lou, Yingyan (Thesis advisor) / Pendyala, Ram (Committee member) / Zhou, Xuesong (Committee member) / Mirchandani, Pitu (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Travel time is the main transportation system performance measure used by the planning community to evaluate the impacts of traffic congestion on infrastructure investment projects and policy development plans. Planners rely on the travel demand model tool estimates for the selection and prioritization of critical and sensitive projects to meet

Travel time is the main transportation system performance measure used by the planning community to evaluate the impacts of traffic congestion on infrastructure investment projects and policy development plans. Planners rely on the travel demand model tool estimates for the selection and prioritization of critical and sensitive projects to meet the fiscally constraint requirements imposed by the Federal Highway Administration (FHWA) on their transportation improvement programs (TIP). While travel demand model estimates have been successfully implemented in the evaluation of project scenarios or alternatives, the application of the methods used in the travel demand model to generate these estimates continues to present a critical challenge, particularly to modelers who have to produce a validated model upon which traffic predictions can be made. The various volume-delay functions (VDFs) including the Bureau of Public Roads (BPR) function, used in the travel demand model to relate traffic volume to travel time, are developed based on system-wide attributes. BPR function in its polynomial form is computationally efficient and simple for implementation in a transport planning software. The planning community has long recognized that the BPR function cannot capture traffic flow dynamics and queue evolution processes. Besides, it has difficulties in using the average travel time measure to describe an oversaturated bottleneck with high density but low throughput. This dissertation aims to propose a simplified and yet effective point-queue based modeling approach built on the cumulative vehicle arrival concept, and the polynomial equation formula, based on Newell’s method, to estimate travel time at a corridor level using real-world speed and count measurements. A traffic state estimation (TSE) method is also proposed to characterize data into various states, such as congested state and uncongested state, using Markov Chain to capture current traffic pattern and Bayesian Classifier to infer congestion effects. As the testbed for the case study, the research selects the Phoenix freeway corridor with year-round traffic data collected from embedded traffic loop detectors. The results and effectiveness of the proposed methods are discussed to shed light on the calibration of link performance function, which is an analytical building block for system-wide performance evaluation.
ContributorsBelezamo, Baloka (Author) / Zhou, Xuesong (Thesis advisor) / Pendyala, Ram (Committee member) / Lou, Yingyan (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Short-notice disasters such as hurricanes involve uncertainties in many facets, from the time of its occurrence to its impacts’ magnitude. Failure to incorporate these uncertainties can affect the effectiveness of the emergency responses. In the case of a hurricane event, uncertainties and corresponding impacts during a storm event can quickly

Short-notice disasters such as hurricanes involve uncertainties in many facets, from the time of its occurrence to its impacts’ magnitude. Failure to incorporate these uncertainties can affect the effectiveness of the emergency responses. In the case of a hurricane event, uncertainties and corresponding impacts during a storm event can quickly cascade. Over the past decades, various storm forecast models have been developed to predict the storm uncertainties; however, access to the usage of these models is limited. Hence, as the first part of this research, a data-driven simulation model is developed with aim to generate spatial-temporal storm predicted hazards for each possible hurricane track modeled. The simulation model identifies a means to represent uncertainty in storm’s movement and its associated potential hazards in the form of probabilistic scenarios tree where each branch is associated with scenario-level storm track and weather profile. Storm hazards, such as strong winds, torrential rain, and storm surges, can inflict significant damage on the road network and affect the population’s ability to move during the storm event. A cascading network failure algorithm is introduced in the second part of the research. The algorithm takes the scenario-level storm hazards to predict uncertainties in mobility states over the storm event. In the third part of the research, a methodology is proposed to generate a sequence of actions that simultaneously solve the evacuation flow scheduling and suggested routes which minimize the total flow time, or the makespan, for the evacuation process from origins to destinations in the resulting stochastic time-dependent network. The methodology is implemented for the 2017 Hurricane Irma case study to recommend an evacuation policy for Manatee County, FL. The results are compared with evacuation plans for assumed scenarios; the research suggests that evacuation recommendations that are based on single scenarios reduce the effectiveness of the evacuation procedure. The overall contributions of the research presented here are new methodologies to: (1) predict and visualize the spatial-temporal impacts of an oncoming storm event, (2) predict uncertainties in the impacts to transportation infrastructure and mobility, and (3) determine the quickest evacuation schedule and routes under the uncertainties within the resulting stochastic transportation networks.
ContributorsGita, Ketut (Author) / Mirchandani, Pitu (Thesis advisor) / Maciejewski, Ross (Committee member) / Sefair, Jorge (Committee member) / Zhou, Xuesong (Committee member) / Arizona State University (Publisher)
Created2020
Description

Many upper limb amputees experience an incessant, post-amputation “phantom limb pain” and report that their missing limbs feel paralyzed in an uncomfortable posture. One hypothesis is that efferent commands no longer generate expected afferent signals, such as proprioceptive feedback from changes in limb configuration, and that the mismatch of motor

Many upper limb amputees experience an incessant, post-amputation “phantom limb pain” and report that their missing limbs feel paralyzed in an uncomfortable posture. One hypothesis is that efferent commands no longer generate expected afferent signals, such as proprioceptive feedback from changes in limb configuration, and that the mismatch of motor commands and visual feedback is interpreted as pain. Non-invasive therapeutic techniques for treating phantom limb pain, such as mirror visual feedback (MVF), rely on visualizations of postural changes. Advances in neural interfaces for artificial sensory feedback now make it possible to combine MVF with a high-tech “rubber hand” illusion, in which subjects develop a sense of embodiment with a fake hand when subjected to congruent visual and somatosensory feedback. We discuss clinical benefits that could arise from the confluence of known concepts such as MVF and the rubber hand illusion, and new technologies such as neural interfaces for sensory feedback and highly sensorized robot hand testbeds, such as the “BairClaw” presented here. Our multi-articulating, anthropomorphic robot testbed can be used to study proprioceptive and tactile sensory stimuli during physical finger–object interactions. Conceived for artificial grasp, manipulation, and haptic exploration, the BairClaw could also be used for future studies on the neurorehabilitation of somatosensory disorders due to upper limb impairment or loss. A remote actuation system enables the modular control of tendon-driven hands. The artificial proprioception system enables direct measurement of joint angles and tendon tensions while temperature, vibration, and skin deformation are provided by a multimodal tactile sensor. The provision of multimodal sensory feedback that is spatiotemporally consistent with commanded actions could lead to benefits such as reduced phantom limb pain, and increased prosthesis use due to improved functionality and reduced cognitive burden.

ContributorsHellman, Randall (Author) / Chang, Eric (Author) / Tanner, Justin (Author) / Helms Tillery, Stephen (Author) / Santos, Veronica (Author) / Ira A. Fulton Schools of Engineering (Contributor)
Created2015-02-19
Description

The photoresponse of a TiO2 thin film was significantly improved due to the decrease in the Schottky barrier height between Au and TiO2 via the formation of interface dipoles, which was caused by electrostatically self-assembled PEI on the surface of the TiO2 film.

ContributorsGu, Xuehui (Author) / Meng, Fanxu (Author) / Zhou, Jingran (Author) / Liu, Guohua (Author) / Ruan, Shengping (Author) / Zhang, Haifeng (Author) / Ira A. Fulton Schools of Engineering (Contributor)
Created2013-10-28
Description

Flow diverting devices and stents can be used to treat cerebral aneurysms too difficult to treat with coiling or craniotomy and clipping. However, the hemodynamic effects of these devices have not been studied in depth. The objective of this study was to quantify and understand the fluid dynamic changes that

Flow diverting devices and stents can be used to treat cerebral aneurysms too difficult to treat with coiling or craniotomy and clipping. However, the hemodynamic effects of these devices have not been studied in depth. The objective of this study was to quantify and understand the fluid dynamic changes that occur within bifurcating aneurysms when treated with different devices and configurations. Two physical models of bifurcating cerebral aneurysms were constructed: an idealized model and a patient-specific model. The models were treated with four device configurations: a single low-porosity Pipeline embolization device (PED) and one, two, and three high-porosity Enterprise stents deployed in a telescoping fashion. Particle image velocimetry was used to measure the fluid dynamics within the aneurysms; pressure was measured within the patient-specific model. The PED resulted in the greatest reductions in fluid dynamic activity within the aneurysm for both models. However, a configuration of three telescoping stents reduced the fluid dynamic activity within the aneurysm similarly to the PED treatment. Pressure within the patient-specific aneurysm did not show significant changes among the treatment configurations; however, the pressure difference across the untreated vessel side of the model was greatest with the PED. Treatment with stents and a flow diverter led to reductions in aneurysmal fluid dynamic activity for both idealized and patient-specific models. While the PED resulted in the greatest flow reductions, telescoping high-porosity stents performed similarly and may represent a viable treatment alternative in situations where the use of a PED is not an option.

ContributorsRoszelle, Breigh (Author) / Gonzalez, L. Fernando (Author) / Babiker, Haithem (Author) / Ryan, Justin (Author) / Albuquerque, Felipe C. (Author) / Frakes, David (Author) / Ira A. Fulton Schools of Engineering (Contributor)
Created2013
Description

Background: Styrene is an important building-block petrochemical and monomer used to produce numerous plastics. Whereas styrene bioproduction by Escherichia coli was previously reported, the long-term potential of this approach will ultimately rely on the use of hosts with improved industrial phenotypes, such as the yeast Saccharomyces cerevisiae.

Results: Classical metabolic evolution was first

Background: Styrene is an important building-block petrochemical and monomer used to produce numerous plastics. Whereas styrene bioproduction by Escherichia coli was previously reported, the long-term potential of this approach will ultimately rely on the use of hosts with improved industrial phenotypes, such as the yeast Saccharomyces cerevisiae.

Results: Classical metabolic evolution was first applied to isolate a mutant capable of phenylalanine over-production to 357 mg/L. Transcription analysis revealed up-regulation of several phenylalanine biosynthesis pathway genes including ARO3, encoding the bottleneck enzyme DAHP synthase. To catalyze the first pathway step, phenylalanine ammonia lyase encoded by PAL2 from A. thaliana was constitutively expressed from a high copy plasmid. The final pathway step, phenylacrylate decarboxylase, was catalyzed by the native FDC1. Expression of FDC1 was naturally induced by trans-cinnamate, the pathway intermediate and its substrate, at levels sufficient for ensuring flux through the pathway. Deletion of ARO10 to eliminate the competing Ehrlich pathway and expression of a feedback-resistant DAHP synthase encoded by ARO4[subscript K229L] preserved and promoted the endogenous availability precursor phenylalanine, leading to improved pathway flux and styrene production. These systematic improvements allowed styrene titers to ultimately reach 29 mg/L at a glucose yield of 1.44 mg/g, a 60% improvement over the initial strain.

Conclusions: The potential of S. cerevisiae as a host for renewable styrene production has been demonstrated. Significant strain improvements, however, will ultimately be needed to achieve economical production levels.

ContributorsMcKenna, Rebekah (Author) / Thompson, Brian (Author) / Pugh, Shawn (Author) / Nielsen, David (Author) / Ira A. Fulton Schools of Engineering (Contributor)
Created2014-08-21
Description

Neural progenitor cells (NPCs) derived from human pluripotent stem cells (hPSCs) are a multipotent cell population that is capable of nearly indefinite expansion and subsequent differentiation into the various neuronal and supporting cell types that comprise the CNS. However, current protocols for differentiating NPCs toward neuronal lineages result in a

Neural progenitor cells (NPCs) derived from human pluripotent stem cells (hPSCs) are a multipotent cell population that is capable of nearly indefinite expansion and subsequent differentiation into the various neuronal and supporting cell types that comprise the CNS. However, current protocols for differentiating NPCs toward neuronal lineages result in a mixture of neurons from various regions of the CNS. In this study, we determined that endogenous WNT signaling is a primary contributor to the heterogeneity observed in NPC cultures and neuronal differentiation. Furthermore, exogenous manipulation of WNT signaling during neural differentiation, through either activation or inhibition, reduces this heterogeneity in NPC cultures, thereby promoting the formation of regionally homogeneous NPC and neuronal cultures. The ability to manipulate WNT signaling to generate regionally specific NPCs and neurons will be useful for studying human neural development and will greatly enhance the translational potential of hPSCs for neural-related therapies.

ContributorsMoya, Noel (Author) / Cutts, Joshua (Author) / Gaasterland, Terry (Author) / Willert, Karl (Author) / Brafman, David (Author) / Ira A. Fulton Schools of Engineering (Contributor)
Created2014-12-09