Bayesian data assimilation for improved modeling of road traffic
Netherlands TRAIL Research School, 2010 - Mathematics - 173 pages
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Bayesian calibration and comparison of carfollowing models
Bayesian committee of regression models to predict travel times
8 other sections not shown
accuracy altemative applied approach approximation Bayes Bayesian evidence Bayesian framework Bayesian inference calculated calibration car-following behavior car-following models cells Chapter CHM model combined committee complex computation context layer correct covariance matrix data assimilation data set deﬁned density derived drivers equation error bars error covariance experiment Extended Kalman Filter feed-forward FFNN Figure ﬁlters ﬁnd ﬁt ﬁxed function fundamental diagram G-EKF Gaussian gebruikt gradient Helly model Hessian hidden layer Hinsbergen Hoogendoom hyperparameters identiﬁcation inﬂuences input Intelligent Transportation Systems L-EKF Q I likelihood likelihood function linear Lint LWR model Mackay measurement model q modellen noise optimal output overﬁtting parameters performance posterior distribution posterior probability predict travel prediction intervals prediction models prior real-time recurrent neural networks RMSE road trafﬁc simulation speeds SSNN step test error trafﬁc ﬂow models trafﬁc state estimation Transportation Research Board Transportation Research Record travel time prediction validation values vector weights zijn Zuylen