Quasi-Sparsity Based Origin-Destination Demand Estimation- [electronic resource]
Quasi-Sparsity Based Origin-Destination Demand Estimation- [electronic resource]
- Material Type
- 단행본
- 0016934799
- Date and Time of Latest Transaction
- 20240214101655
- ISBN
- 9798380327695
- DDC
- 385
- Author
- Wang, Jingxing.
- Title/Author
- Quasi-Sparsity Based Origin-Destination Demand Estimation - [electronic resource]
- Publish Info
- [S.l.]: : University of Washington., 2023
- Publish Info
- Ann Arbor : : ProQuest Dissertations & Theses,, 2023
- Material Info
- 1 online resource(131 p.)
- General Note
- Source: Dissertations Abstracts International, Volume: 85-03, Section: B.
- General Note
- Advisor: Ban, Xuegang Jeff.
- 학위논문주기
- Thesis (Ph.D.)--University of Washington, 2023.
- Restrictions on Access Note
- This item must not be sold to any third party vendors.
- Abstracts/Etc
- 요약A good knowledge of the Origin-Destination (OD) demand matrix has been always important in various transportation applications, including simulation studies, transportation planning, traffic operations and control, and etc. For a large real network, the OD demand matrix may have certain quasi-sparsity property, i.e., the majority of the OD pairs have small demands while only a small portion of OD pairs have large demands. Inspired by Compressed Sensing technique, this dissertation proposes a Quasi-Sparsity Origin-Destination (QSOD) framework to explore such quasi-sparsity property of large-scale OD demand matrices. Three QSOD models (the fixed-mapping QSOD model, the bi-level QSOD model, and the distributionally robust QSOD model) are established under such QSOD framework. The results theoretically and numerically demonstrate that under certain conditions the estimated OD demands will share the same quasi-sparsity with the prior OD demands, and the estimated demands of most OD pairs (of a large-size network) will be equal to their prior values or zeros (or a very small value). Such findings provide important practical insights for OD estimation: one may only require the prior OD demands can capture the relative magnitude of the true OD demands of the network, which makes it much easier to prepare prior OD matrix in practice. The comparison between QSOD models and other existing OS estimation studies, and the integration of multi-sourced data for OD estimation under the QSOD framework are also discussed in this study.
- Subject Added Entry-Topical Term
- Transportation.
- Subject Added Entry-Topical Term
- Civil engineering.
- Index Term-Uncontrolled
- Quasi-sparsity property
- Index Term-Uncontrolled
- Transportation network
- Index Term-Uncontrolled
- Origin-Destination
- Added Entry-Corporate Name
- University of Washington Civil and Environmental Engineering
- Host Item Entry
- Dissertations Abstracts International. 85-03B.
- Host Item Entry
- Dissertation Abstract International
- Electronic Location and Access
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- 소장사항
-
202402 2024
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