Scenarios discovery : robust transportation policy analysis in Singapore using microscopic traffic simulator
Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2013.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2013
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| Online Access: | http://hdl.handle.net/1721.1/82852 |
| _version_ | 1826210649977389056 |
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| author | Song, Xiang, Ph. D. Massachusetts Institute of Technology |
| author2 | Moshe E. Ben-Akiva and Tomer Toledo. |
| author_facet | Moshe E. Ben-Akiva and Tomer Toledo. Song, Xiang, Ph. D. Massachusetts Institute of Technology |
| author_sort | Song, Xiang, Ph. D. Massachusetts Institute of Technology |
| collection | MIT |
| description | Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2013. |
| first_indexed | 2024-09-23T14:53:18Z |
| format | Thesis |
| id | mit-1721.1/82852 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T14:53:18Z |
| publishDate | 2013 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/828522019-04-11T08:07:11Z Scenarios discovery : robust transportation policy analysis in Singapore using microscopic traffic simulator Robust transportation policy analysis in Singapore using microscopic traffic simulator Song, Xiang, Ph. D. Massachusetts Institute of Technology Moshe E. Ben-Akiva and Tomer Toledo. Massachusetts Institute of Technology. Department of Civil and Environmental Engineering. Massachusetts Institute of Technology. Department of Civil and Environmental Engineering. Civil and Environmental Engineering. Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2013. Cataloged from PDF version of thesis. Includes bibliographical references (pages 99-101). One of the main challenges of making strategic decisions in transportation is that we always face a set of possible future states due to deep uncertainty in traffic demand. This thesis focuses on exploring the application of model-based decision support techniques which characterize a set of future states that represent the vulnerabilities of the proposed policy. Vulnerabilities here are interpreted as states of the world where the proposed policy fails its performance goal or deviates significantly from the optimum policy due to deep uncertainty in the future. Based on existing literature and data mining techniques, a computational model-based approach known as scenario discovery is described and applied in an empirical problem. We investigated the application of this new approach in a case study based on a proposed transit policy implemented in Marina Bay district of Singapore. Our results showed that the scenario discovery approach performs well in finding the combinations of uncertain input variables that will result in policy failure. by Xiang Song. S.M.in Transportation 2013-12-06T20:49:20Z 2013-12-06T20:49:20Z 2013 Thesis http://hdl.handle.net/1721.1/82852 863398869 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 101 pages application/pdf a-si--- Massachusetts Institute of Technology |
| spellingShingle | Civil and Environmental Engineering. Song, Xiang, Ph. D. Massachusetts Institute of Technology Scenarios discovery : robust transportation policy analysis in Singapore using microscopic traffic simulator |
| title | Scenarios discovery : robust transportation policy analysis in Singapore using microscopic traffic simulator |
| title_full | Scenarios discovery : robust transportation policy analysis in Singapore using microscopic traffic simulator |
| title_fullStr | Scenarios discovery : robust transportation policy analysis in Singapore using microscopic traffic simulator |
| title_full_unstemmed | Scenarios discovery : robust transportation policy analysis in Singapore using microscopic traffic simulator |
| title_short | Scenarios discovery : robust transportation policy analysis in Singapore using microscopic traffic simulator |
| title_sort | scenarios discovery robust transportation policy analysis in singapore using microscopic traffic simulator |
| topic | Civil and Environmental Engineering. |
| url | http://hdl.handle.net/1721.1/82852 |
| work_keys_str_mv | AT songxiangphdmassachusettsinstituteoftechnology scenariosdiscoveryrobusttransportationpolicyanalysisinsingaporeusingmicroscopictrafficsimulator AT songxiangphdmassachusettsinstituteoftechnology robusttransportationpolicyanalysisinsingaporeusingmicroscopictrafficsimulator |