Freeway traffic flow prediction based on hidden Markov model

Nowadays, scientific and reasonable traffic volume prediction plays an important role especially in the traffic infrastructure planning. In the recent research, establishing a robust mathematical model for traffic volume prediction becomes a challenging problem. In our research, Hidden Markov Model (HMM) is constructed based on the numeral characteristics of monthly traffic volume for each freeway in Jiangsu Province. By analyzing the Markov property of the monthly flat peak traffic volume and the nonlinear effect of the monthly peak traffic volume, we further predict the future monthly traffic volume. Compared with the traditional models, our proposed model has significant advantages in some evaluation indicator, such as MRE, MAE, RMSE. Further more, The construction of this model only depends on the numerical characteristics of historical traffic volume data, which has the advantages of convenience as well as broad application prospects.