Enhanced dynamic origin-destination matrix updating with long-term flow information

Stathopoulos, A; Tsekeris, T

dc.contributor.author	Stathopoulos, A	en
dc.contributor.author	Tsekeris, T	en
dc.date.accessioned	2014-03-01T02:42:46Z
dc.date.available	2014-03-01T02:42:46Z
dc.date.issued	2004	en
dc.identifier.issn	0361-1981	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31065
dc.subject	Origin Destination	en
dc.subject.classification	Engineering, Civil	en
dc.subject.classification	Transportation	en
dc.subject.classification	Transportation Science & Technology	en
dc.subject.other	Cost effectiveness	en
dc.subject.other	Economic and social effects	en
dc.subject.other	Information analysis	en
dc.subject.other	Least squares approximations	en
dc.subject.other	Mathematical models	en
dc.subject.other	Matrix algebra	en
dc.subject.other	Problem solving	en
dc.subject.other	Statistical methods	en
dc.subject.other	Traffic surveys	en
dc.subject.other	Census data	en
dc.subject.other	Flow information	en
dc.subject.other	Origin-destination (O-D) trip matrices	en
dc.subject.other	Time-recursive mechanisms	en
dc.subject.other	Motor transportation	en
dc.title	Enhanced dynamic origin-destination matrix updating with long-term flow information	en
heal.type	conferenceItem	en
heal.identifier.primary	10.3141/1882-19	en
heal.identifier.secondary	http://dx.doi.org/10.3141/1882-19	en
heal.language	English	en
heal.publicationDate	2004	en
heal.abstract	The problem of updating dynamic origin-destination (O-D) matrices by exploiting a long-term time series of link traffic counts in large-scale transportation networks without the need for surveys or census data is investigated. Different time-recursive mechanisms for analysis of these data to enhance the performance of the models currently used to synthesize within-day dynamic O-D matrices are suggested. The efficiency of the proposed procedure is investigated with respect to different formulations and related solution algorithms (based on entropy maximization and generalized least-squares). The impacts of different assumptions on model performance are also examined. These include the length of the time scale in which the flow information is updated and the selection of the week-day for which the flow information is collected. The results of the statistical analysis and the model performance measures demonstrate that the proposed time-recursive procedure for an information updating period of 2 years can produce an improved prior O-D matrix that may significantly enhance the subsequent updating of dynamic O-D matrices corresponding to a series of days of the week.	en
heal.publisher	TRANSPORTATION RESEARCH BOARD NATL RESEARCH COUNCIL	en
heal.journalName	Transportation Research Record	en
heal.bookName	TRANSPORTATION RESEARCH RECORD	en
dc.identifier.doi	10.3141/1882-19	en
dc.identifier.isi	ISI:000227334100019	en
dc.identifier.issue	1882	en
dc.identifier.spage	159	en
dc.identifier.epage	166	en