Forecasting Multivariate Road Traffic Flows Using Bayesian Dynamic Graphical Models, Splines and Other Traffic Variables

Forecasting multivariate road traffic flows using Bayesian dynamic graphical models, splines and other traffic variables

Traffic flow data are routinely collected for many networks worldwide. These invariably large data sets can be used as part of a traffic management system, for which good traffic flow forecasting models are crucial. The linear multiregression dynamic model (LMDM) has been shown to be promising for forecasting flows, accommodating multivariate flow time series, while being a computationally simp...

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research publications and other research outputs Forecasting multivariate road traffic flows using Bayesian dynamic graphical models

Traffic flow data are routinely collected for many networks worldwide. These invariably large data sets can be used as part of a traffic management system, for which good traffic flow forecasting models are crucial. The linear multiregression dynamic model (LMDM) has been shown to be promising for forecasting flows, accommodating multivariate flow time series, while being a computationally simp...

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The Open University ’ s repository of research publications and other research outputs Forecasting multivariate road traffic flows using Bayesian dynamic graphical models

Traffic flow data are routinely collected for many networks worldwide. These invariably large data sets can be used as part of a traffic management system, for which good traffic flow forecasting models are crucial. The linear multiregression dynamic model (LMDM) has been shown to be promising for forecasting flows, accommodating multivariate flow time series, while being a computationally simp...

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Forecasting traffic flows in road networks: A graphical dynamic model approach

Congestion on roads is a major problem worldwide. Many roads now have induction loops implanted into the road surface providing real-time traffic flow data. These data can be used in a traffic management system to monitor current traffic flows in a network so that traffic can be directed and managed efficiently. Reliable short-term forecasting and monitoring models of traffic flows are crucial ...

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Multivariate forecasting of road traffic flows in the pres- ence of heteroscedasticity and measurement errors

Multivariate forecasting of road traffic flows in the presence of heteroscedasticity and measurement errors Journal Article How to cite: Anacleto Junior, Osvaldo; Queen, Catriona and Albers, Casper (2013). Multivariate forecasting of road traffic flows in the presence of heteroscedasticity and measurement errors. Journal of the Royal Statistical Society: Series C (Applied Statistics), 62(2) pp....

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Forecasting Multivariate Road Traffic Flows Using Bayesian Dynamic Graphical Models, Splines and Other Traffic Variables

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