Pavement Temperature Shortimpending Prediction Based on ARIMA in Winter

Abstract:

Under the effect of other external variables, the fluctuation rule of pavement temperature with time was excavated in the future. Based on the historical data of a traffic meteorological monitoring station, the main affecting factors of pavement temperature were determined, and the shortimpending prediction model of pavement temperature time series was established by applying autoregressive integrated moving average (ARIMA) model in order to predict pavement temperature in a short time. The results show that the predicted average accuracy reaches 81.25% and 99.65% respectively within allowable error range of ±0.5 ℃ and ±1.0 ℃ in the next 3 h. The predicted average accuracy and the mean absolute error are up to 92.50% and 0.15 ℃ respectively within allowable error range of ±0.5 ℃ in the next 1 h.