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.
- 2 English
- Industrial engineering
- Civil engineering
- 1 Data Driven Algorithm
- 1 Dynamic programming
- 1 Engineering
- 1 Lane Based
- 1 Multi-Sensor Data Fusion
- 1 Multi-Sensor Extended Kalman Filter
- 1 Operations research
- 1 Pickup and delivery with synchronized transfers
- 1 Resource hyperprisms
- 1 Ride-sharing service optimization
- 1 Time-dependent shortest path problem
- 1 Traffic Flow Model
- 1 Traffic State Estimation
- 1 Vehicle routing problem with pickup and delivery with time windows
Optimization of on-demand transportation systems and ride-sharing services involves solving a class of complex vehicle routing problems with pickup and delivery with time windows (VRPPDTW). Previous research has made a number of important contributions to the challenging pickup and delivery problem along different formulation or solution approaches. However, there are a number of modeling and algorithmic challenges for a large-scale deployment of a vehicle routing and scheduling algorithm, especially for regional networks with various road capacity and traffic delay constraints on freeway bottlenecks and signal timing on urban streets. The main thrust of this research is constructing hyper-networks to implicitly …
- Mahmoudi, Monirehalsadat, Zhou, Xuesong, Mirchandani, Pitu B, 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