Modelling of Traffic Flow with Bayesian Autoregressive Model with Variable Partial Forgetting

0356536 - ÚTIA 2011 CZ eng K - Conference Paper (Czech conference)
Dedecius, Kamil - Nagy, Ivan - Hofman, Radek
Modelling of Traffic Flow with Bayesian Autoregressive Model with Variable Partial Forgetting.
CTU Workshop 2011. Praha: ČVUT v Praze, 2011, s. 1-11.
[CTU Workshop 2011. Praha (CZ), 01.02.2011-01.02.2011]
Grant - others:ČVUT v Praze(CZ) SGS 10/099/OHK3/1T/16
Institutional research plan: CEZ:AV0Z10750506
Keywords : Bayesian modelling * traffic modelling
Subject RIV: BB - Applied Statistics, Operational Research
http://library.utia.cas.cz/separaty/2011/AS/dedecius-modelling of traffic flow with bayesian autoregressive model with variable partial forgetting.pdf

Computing the future road traffic intensities in urban and suburban areas is considered inthis paper. The statistical properties of the traffic flow advocate the use of a low-order lin- ear autoregressive models, in which the previous intensities determine the following ones. To achieve adaptivity, the Bayesian modelling framework was chosen. The regression coefficients are considered random, hence they are modelled using a suitable distribution. A significant improvement of the overall modelling performance is further reached with techniques allowing the parameters vary by modification of their distribution. We present the partial forgetting method, allowing to individually track the parameters even in the case of their different variability rate.
Permanent Link: http://hdl.handle.net/11104/0195032