关键词: 交通量预测, 信息融合, 最优权重, 小波分析

Abstract: Since the actual transportation system features in complex time-varying changes and uncertainty of traffic flow changes，the wavelet analysis theory is applied to denoise the original traffic data，which makes the data after denoising is better to reflect the nature of traffic flow and its changing rule. Information fusion technology is able to do integrated treatment of different sensor data，to remove redundancy，to overcome the ambiguity，so it can obtain more comprehensive， more accurate and reliable information than any single data source do. Considering the accuracy and reliability of real-time road traffic prediction，the information fusion prediction method based on wavelet denoising and optimum weight is proposed， using the thought of integrating denoising technology based on wavelet analysis and modern information; furthermore， the experimental results are verified by case studies. Empirical results of the analysis show that the method proposed can improve the accuracy of traffic flow prediction effectively.

Key words: short-time traffic flow prediction, information fusion, optimal weight, wavelet analysis