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This paper presents a dimensionality reduction of the online calibration problem that is based on principal components to overcome this limitation. To demonstrate this approach, the origin\u2013destination flow estimation problem is formulated in relation to its principal components. The efficacy of the procedure was tested with real data on the Singapore Expressway network in an open-loop framework. A reduction in the problem dimension by a factor of 50 was observed with only a 2% loss in estimation accuracy. Further, the computational times were reduced by an order of 100. The procedure led to better predictions, as the principal components captured the structural spatial relationships. This work has the potential to make the online calibration problem more scalable. <\/jats:p>","DOI":"10.3141\/2667-10","type":"journal-article","created":{"date-parts":[[2017,12,11]],"date-time":"2017-12-11T20:32:42Z","timestamp":1513024362000},"page":"96-107","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":18,"title":["Reducing the Dimension of Online Calibration in Dynamic Traffic Assignment Systems"],"prefix":"10.1177","volume":"2667","author":[{"given":"A. Arun","family":"Prakash","sequence":"first","affiliation":[{"name":"1-180, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139"}]},{"given":"Ravi","family":"Seshadri","sequence":"additional","affiliation":[{"name":"Singapore\u2013Massachusetts Institute of Technology Alliance for Research and Technology, 1 Create Way, No. 09-01, Singapore 138602, Singapore"}]},{"given":"Constantinos","family":"Antoniou","sequence":"additional","affiliation":[{"name":"Technical University of Munich, Arcisstrasse 21, Munich 80333, Germany"}]},{"given":"Francisco C.","family":"Pereira","sequence":"additional","affiliation":[{"name":"Technical University of Denmark, Building 116, Room 123A, Kongens Lyngby 2800, Denmark"}]},{"given":"Moshe E.","family":"Ben-Akiva","sequence":"additional","affiliation":[{"name":"1-181, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139"}]}],"member":"179","published-online":{"date-parts":[[2017,1,1]]},"reference":[{"key":"bibr1-2667-10","unstructured":"BalakrishnaR. 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