Application of adaptive single-exponent smoothing for short-term traffic flow prediction
自适应单指数平滑法在短期交通流预测中的应用

Short-term traffic flow prediction is a key technique to realize the transportation planning and management. Because of the simple calculation and the small number of observation data, the exponential smoothing is extensively applied as an important forecast method. However, in the traditional method, there is no theoretical method for selecting the smoothing coefficient. We propose an adaptive single-exponent smoothing approach to optimize the smoothing coefficient automatically based on the approximate dynamic programming. With rigorous analysis, it is shown that the proposed prediction scheme guarantees the convergence. The simulation results validate the effectiveness of the proposed algorithm.