Accelerated on-line calibration of dynamic traffic assignment using distributed stochastic gradient approximation

Huang, E; Antoniou, C; Lopes, J; Wen, Y; Ben-Akiva, M

dc.contributor.author	Huang, E	en
dc.contributor.author	Antoniou, C	en
dc.contributor.author	Lopes, J	en
dc.contributor.author	Wen, Y	en
dc.contributor.author	Ben-Akiva, M	en
dc.date.accessioned	2014-03-01T02:46:40Z
dc.date.available	2014-03-01T02:46:40Z
dc.date.issued	2010	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32767
dc.subject	Case Study	en
dc.subject	Dynamic Traffic Assignment	en
dc.subject	extended kalman filter	en
dc.subject	Stochastic Gradient Descent	en
dc.subject	Real Time	en
dc.subject	Stochastic Gradient	en
dc.subject.other	Computational time	en
dc.subject.other	Dynamic traffic assignments	en
dc.subject.other	Gradient calculations	en
dc.subject.other	Network information	en
dc.subject.other	On-line calibration	en
dc.subject.other	Portugal	en
dc.subject.other	Real-time models	en
dc.subject.other	Route guidance	en
dc.subject.other	Speed-ups	en
dc.subject.other	Stochastic gradient approximations	en
dc.subject.other	Stochastic gradient descent	en
dc.subject.other	Calibration	en
dc.subject.other	Differential thermal analysis	en
dc.subject.other	Intelligent systems	en
dc.subject.other	Online systems	en
dc.subject.other	Real time systems	en
dc.subject.other	Stochastic systems	en
dc.subject.other	Traffic control	en
dc.subject.other	Distributed computer systems	en
dc.title	Accelerated on-line calibration of dynamic traffic assignment using distributed stochastic gradient approximation	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ITSC.2010.5625109	en
heal.identifier.secondary	5625109	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ITSC.2010.5625109	en
heal.publicationDate	2010	en
heal.abstract	Dynamic Traffic Assignment (DTA) system [Ben-Akiva et al., 1991] [Mahmassani, 2001] benefits travelers by providing accurate estimate of current traf-fic conditions, consistent anticipatory network information as well as reliable route guidance. Over the years, two types of model adjustment schemes have been studied - DTA off-line calibration [Balakrishna, 2006] [Toledo et al., 2003] [van der Zijpp, 1997] and DTA online calibration [Antoniou et al., 2007] [Wang et al., 2007] [Ashok and Ben-Akiva, 2000]. The on-line calibration of DTA system allows real-time model self-corrections and has proven to be a useful complement to off-line calibration. In this paper, we explore distributed gradient calculations for the speed-up of on-line calibration of Dynamic Traffic Assignment (DTA) systems. Extended Kalman Filter (EKF) and Stochastic Gradient Descent (GD) are examined and their corresponding distributed versions (Para-EKF and Para-GD) are proposed. A case study is performed on a 25-km expressway in Western Portugal. We empirically show that the application of distributed gradient calculation significantly reduce the computational time of online calibration and thus provide attractive alternatives for speed-critical real-time DTA systems. ©2010 IEEE.	en
heal.journalName	IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC	en
dc.identifier.doi	10.1109/ITSC.2010.5625109	en
dc.identifier.spage	1166	en
dc.identifier.epage	1171	en