Inter-urban short-term traffic congestion prediction
Netherlands TRAIL Research School, 2006 - Technology & Engineering - 272 pages
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0-minute prediction horizon 0min 30 min prediction 5min aggregation level algorithm ANN models ARMA models artiﬁcial neural networks Beekbergen AM peak Beekbergen PM bottleneck detector calibrated classiﬁcation conﬁrmed congestion indicator congestion prediction data set data sub-sets deﬁned described developed DTM measures efﬁciency error percentage evaluation false alarm percentages feed-forward ﬁeld ﬁgure ﬁles ﬁnd ﬁrst forecasting freeway function Fuzzy Logic hidden neurons Hoevelaken PM peak HR L S HR R S Huisken hypothesis identiﬁed induction loop inﬂuence infrastructure input data input variables Intelligent Transportation Systems learning epochs Linear Regression loop detectors mean speed minutes MLF ANNs MLR models modellen motorway naive method naive models neurons non-linear outperformed output parameters performance PM peak period prediction horizon Figure sensors series analysis speciﬁc supervised learning target detector trafﬁc congestion trafﬁc ﬂow trafﬁc management travel time prediction upstream