Sustainable development of large urban transportation infrastructure networks : management optimization and incorporation of autonomous vehicles
Abstract/Contents
- Abstract
- At the nexus of environmental, social, and economic sustainability, transportation infrastructures have a large sustainability footprint. Because of the large sustainability footprint, he effect of sustainable development on transportation infrastructures can have a great impact. This dissertation focuses on management optimization frameworks for the sustainable development of transportation infrastructure and urban transportation infrastructure networks. It first introduces optimizing sustainability at the facility-level and presents a framework for probabilistic sustainability design of reinforced concrete transportation infrastructure incorporating optimization of maintenance programs. The framework adopts a life-cycle optimization model (LCO) automating the repair and limit state selection process to minimize sustainability impact. A case study is presented which computes the probability that the optimal maintenance scheme allowing more degradation will meet the CO\textsubscript{2}-eq emission reduction target of the UN Intergovernmental Panel on Climate Change (IPCC) by 2050. Then, on the network-level, this dissertation provides a formulation of sustainable development as a multi-objective problem with short-term and long-term objectives, and presents a multi-objective optimization framework for the sustainable development of transportation infrastructure networks. The maintenance and seismic retrofit of highway bridges of Santa Clara County, California, within the transportation network of San Francisco Bay Area are presented as case studies. The NSGA-ii genetic algorithm is used to search for the optimal maintenance and retrofit of the highway bridges within the network. A new fitness memorization technique is proposed with an improved NSGA-ii, which provides a robust evaluation of solutions in multi-objective stochastic optimization problems. Finally, this dissertation investigates how the introduction of autonomous vehicles could change the sustainable maintenance decision-making process, as an example of the potential impact of new technology on managerial actions towards sustainable development. The improvement in road capacity by introducing autonomous passenger cars into the transportation systems is quantified using fundamental equations that characterize traffic flow. A case study is presented on the possible impact of autonomous vehicles on the San Francisco Bay Area transportation network and its sustainable maintenance decisions. A framework is proposed for robust decision-making on sustainable maintenance decision taking new technology advancement like autonomous driving into consideration.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2017 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Shen, Bo |
|---|---|
| Associated with | Stanford University, Civil & Environmental Engineering Department. |
| Primary advisor | Lepech, Michael |
| Thesis advisor | Lepech, Michael |
| Thesis advisor | Baker, Jack W |
| Thesis advisor | Kiremidjian, Anne S. (Anne Setian) |
| Advisor | Baker, Jack W |
| Advisor | Kiremidjian, Anne S. (Anne Setian) |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Bo Shen. |
|---|---|
| Note | Submitted to the Department of Civil and Environmental Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2017. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2017 by Bo Shen
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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