关键词: 城市交通, 交通状态, 城市快速路, 最大熵模型, 预测, 模式分类

Abstract: The traffic state forecasting is an important basis for the traffic-induced system and traffic information dissemination system. The paper proposes a new forecasting method based on the maximum entropy model towards the urban freeway. The maximum entropy model can get the weights for the different features by the data training, and predict the road traffic state level directly. This method can fuse the temporal and spatial features efficiently, regardless of the relativity between the different features, which make this model more adaptable. The experiment results show that this traffic state prediction method can achieve a high accuracy. The success of this model prove that the traffic state prediction problem can be resolved through the pattern classification method, which enhances the methods of traffic state forecasting.

Key words: urban traffic, traffic state, urban freeway, maximum entropy model, forecast, pattern classification