ETDs

This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.

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Crossroads --- A Time-Sensitive Autonomous Intersection Management Technique

Description
For autonomous vehicles, intelligent autonomous intersection management will be required for safe and efficient operation. In order to achieve safe operation despite uncertainties in vehicle trajectory, intersection management techniques must consider a safety buffer around the vehicles. For truly safe operation, an extra buffer space should be added to account…

For autonomous vehicles, intelligent autonomous intersection management will be required for safe and efficient operation. In order to achieve safe operation despite uncertainties in vehicle trajectory, intersection management techniques must consider a safety buffer around the vehicles. For truly safe operation, an extra buffer space should be added to account for the network and computational delay caused by communication with the Intersection Manager (IM). However, modeling the worst-case computation and network delay as additional buffer around the vehicle degrades the throughput of the intersection. To avoid this problem, AIM, a popular state-of-the-art IM, adopts a query-based approach in which the vehicle requests to enter at a certain arrival time dictated by its current velocity and distance to the intersection, and the IM replies yes
o. Although this solution does not degrade the position uncertainty, it ultimately results in poor intersection throughput. We present Crossroads, a time-sensitive programming method to program the interface of a vehicle and the IM. Without requiring additional buffer to account for the effect of network and computational delay, Crossroads enables efficient intersection management. Test results on a 1/10 scale model of intersection using TRAXXAS RC cars demonstrates that our Crossroads approach obviates the need for large buffers to accommodate for the network and computation delay, and can reduce the average wait time for the vehicles at a single-lane intersection by 24%. To compare Crossroads with previous approaches, we perform extensive Matlab simulations, and find that Crossroads achieves on average 1.62X higher throughput than a simple VT-IM with extra safety buffer, and 1.36X better than AIM.
ContributorsAndert, Edward (Author) / Shrivastava, Aviral (Thesis advisor) / Fainekos, Georgios (Committee member) / Ben Amor, Hani (Committee member) / Arizona State University (Publisher)
Created2017
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Advancing Knowledge of Mechanically-Fiber Reinforced Asphalt Concrete

Description

The use of reinforcing fibers in asphalt concrete (AC) has been documented in many studies. Published studies generally demonstrate positive benefits from using mechanically fiber reinforced asphalt concrete (M-FRAC); however, improvements generally vary with respect to the particular study. The widespread acceptance of fibers use in the asphalt industry is…

The use of reinforcing fibers in asphalt concrete (AC) has been documented in many studies. Published studies generally demonstrate positive benefits from using mechanically fiber reinforced asphalt concrete (M-FRAC); however, improvements generally vary with respect to the particular study. The widespread acceptance of fibers use in the asphalt industry is hindered by these inconsistencies. This study seeks to fulfill a critical knowledge gap by advancing knowledge of M-FRAC in order to better understand, interpret, and predict the behavior of these materials. The specific objectives of this dissertation are to; (a) evaluate the state of aramid fiber in AC and examine their impacts on the mechanical performance of asphalt mixtures; (b) evaluate the interaction of the reinforcement efficiency of fibers with compositions of asphalt mixtures; (c) evaluate tensile and fracture properties of M-FRAC; (d) evaluate the interfacial shear bond strength and critical fiber length in M-FRAC; and (e) propose micromechanical models for prediction of the tensile strength of M-FRAC. The research approach to achieve these objectives included experimental measurements and theoretical considerations. Throughout the study, the mechanical response of specimens with and without fibers are scrutinized using standard test methods including flow number (AASHTO T 378) and uniaxial fatigue (AASHTO TP 107), and non-standard test methods for fiber extraction, direct tension, semi-circular bending, and single fiber pull-out tests. Then, the fiber reinforcement mechanism is further examined by using the basic theories of viscoelasticity as well as micromechanical models.

The findings of this study suggest that fibers do serve as a reinforcement element in AC; however, their reinforcing effectiveness depends on the state of fibers in the mix, temperature/ loading rate, properties of fiber (i.e. dosage, length), properties of mix type (gradation and binder content), and mechanical test type to characterize M-FRAC. The outcome of every single aforementioned elements identifies key reasons attributed to the fiber reinforcement efficiency in AC, which provides insights to justify the discrepancies in the literature and further recommends solutions to overcome the knowledge gaps. This improved insight will translate into the better deployment of existing fiber-based technologies; the development of new, and more effective fiber-based technologies in asphalt mixtures.
ContributorsNoorvand, Hossein (Author) / Kaloush, Kamil (Thesis advisor) / Underwood, Shane B (Thesis advisor) / Mamlouk, Michael (Committee member) / Mobasher, Barzin (Committee member) / Arizona State University (Publisher)
Created2020