Inter-urban Short-term Traffic Congestion Prediction |
Common terms and phrases
0-minute prediction horizon 30 min prediction a.m. peak aggregation level algorithm Amersfoort ANN models architecture ARMA models artificial neural networks Beekbergen AM peak Beekbergen morning peak Beekbergen PM bottleneck detector calibrated chapter cloverleaf junction congestion indicator congestion prediction data set data sub-sets described developed DTM measures error false alarm evaluation false alarm percentages feed-forward forecasting freeway function Fuzzy Logic hidden neurons Hoevelaken PM peak HR RW Huisken hypothesis induction loop infrastructure input data input variables Intelligent Transportation Systems Kalman filtering learning epochs Linear Regression loop detectors mean speed min 10 min minutes MLF ANNs MLR models modellen morning peak period motorway naïve method naïve models neurons non-linear occupancy optimum outperformed output parameters patterns performance PM peak period prediction horizon Figure R-L RSW sensors series analysis significance supervised learning target data target detector test set traffic congestion traffic management travel time prediction upstream values zijn