Multiclass Origin-Destination Estimation Using Multiple Data Types
| dc.contributor.author | Zhao, Qing | en_US |
| dc.contributor.chair | Turnquist, Mark Alan | en_US |
| dc.contributor.committeeMember | Gao, Huaizhu | en_US |
| dc.contributor.committeeMember | Topaloglu, Huseyin | en_US |
| dc.date.accessioned | 2013-09-05T15:57:03Z | |
| dc.date.available | 2018-05-27T06:00:31Z | |
| dc.date.issued | 2013-05-26 | en_US |
| dc.description.abstract | Estimating O-D tables for trucks is of substantial interest due to different emission characteristics, pavement damage, etc of trucks. This thesis proposes a bilevel optimization model and corresponding solution method for static multi-class O-D estimation using various types of data. Limited memory BFGS method with bounded constraints is used for solving the upper level optimization, which is used to derive O-D table entries by minimizing the sum of squared differences between observations from different data sources and the predictions of those values. A probit model is assumed in the lower-level stochastic user equilibrium problem for flow prediction. Extensive experiments have been performed on a test network with different types of link count sensors and turning movements. The tests verify the problem formulation and solution algorithm, and offer important insights into the multiclass O-D estimation process with different types of data available. | en_US |
| dc.identifier.other | bibid: 8267567 | |
| dc.identifier.uri | https://hdl.handle.net/1813/34070 | |
| dc.language.iso | en_US | en_US |
| dc.subject | OD estimation | en_US |
| dc.subject | Multiclass | en_US |
| dc.subject | Multiple data | en_US |
| dc.title | Multiclass Origin-Destination Estimation Using Multiple Data Types | en_US |
| dc.type | dissertation or thesis | en_US |
| thesis.degree.discipline | Civil and Environmental Engineering | |
| thesis.degree.grantor | Cornell University | en_US |
| thesis.degree.level | Master of Science | |
| thesis.degree.name | M.S., Civil and Environmental Engineering |
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