A Hidden Markov Model for short term prediction of traffic conditions on freeways
Hidden Markov Models (HMMs) are employed for short-term freeway traffic prediction. The model defines traffic states in a two-dimensional space. Dynamic changes of traffic conditions are addressed with state transition matrix. The model predicts traffic states directly related to traffic conditions (e.g. breakdown, recovery, etc.). Prediction errors are not impacted by the true traffic state value.
hidden markov models freeway traffic short-term traffic prediction stochastic modeling transition probability clustering analysis second-order statistics