ASU Electronic Theses and Dissertations
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 email@example.com.
- 3 Public
- Civil engineering
- 2 Transportation
- 1 Autonomous vehicle
- 1 Bounded rationality
- 1 Data Driven Algorithm
- 1 Engineering
- 1 Industrial engineering
- 1 Lane Based
- 1 Multi-Sensor Data Fusion
- 1 Multi-Sensor Extended Kalman Filter
- 1 Scheduled transportation system
- 1 Shared mobility
- 1 System observability
- 1 Traffic Flow Model
- 1 Traffic State Estimation
- 1 Urban transit system
Recently, automation, shared use, and electrification are proposed and viewed as the “three revolutions” in the future transportation sector to significantly relieve traffic congestion, reduce pollutant emissions, and increase transportation system sustainability. Motivated by the three revolutions, this research targets on the passenger-focused scheduled transportation systems, where (1) the public transit systems provide high-quality ridesharing schedules/services and (2) the upcoming optimal activity planning systems offer the best vehicle routing and assignment for household daily scheduled activities. The high quality of system observability is the fundamental guarantee for accurately predicting and controlling the system. The rich information from the emerging heterogeneous …
- Liu, Jiangtao, Zhou, Xuesong, Pendyala, Ram, et al.
- Created Date
This study explores an innovative framework for a self-sustained traffic operations system using vehicle-to-vehicle (V2V) communications alone. The proposed framework is envisioned as the foundation to an alternative or supplemental traffic operation and management system, which could be particularly helpful under abnormal traffic conditions caused by unforeseen disasters and special events. Its two major components, a distributed traffic monitoring and platoon information aggregation system and a platoon-based automated intersection control system, are investigated in this study. The distributed traffic monitoring and platoon information aggregation system serves as the foundation. Specifically, each equipped vehicle, through the distributed protocols developed, keeps track …
- Li, Peiheng, Lou, Yingyan, Zhou, Xuesong, et al.
- Created Date
Modern intelligent transportation systems (ITS) make driving more efficient, easier, and safer. Knowledge of real-time traffic conditions is a critical input for operating ITS. Real-time freeway traffic state estimation approaches have been used to quantify traffic conditions given limited amount of data collected by traffic sensors. Currently, almost all real-time estimation methods have been developed for estimating laterally aggregated traffic conditions in a roadway segment using link-based models which assume homogeneous conditions across multiple lanes. However, with new advances and applications of ITS, knowledge of lane-based traffic conditions is becoming important, where the traffic condition differences among lanes are recognized. …
- Zhou, Zhuoyang, Mirchandani, Pitu, Askin, Ronald, et al.
- Created Date