基于手机信令的城市道路交通状态实时预测

为准确、实时预测道路交通状态，通过分析影响交通的因素，利用决策树算法对速度和环境因素等数据进行建模，确定交通拥堵发生的规则，在此基础上结合实时的移动用户和环境因素数据对交通状态进行预测。以中国河北保定城区为例进行实验，验证了该方法的有效性。同时，研究发现，基于决策树算法进行道路交通状态预测的方法具有较好的扩展性。

Real-time forecasting urban traffic state based on cell phone signaling

In order to make accurate and real-time prediction of traffic state, the factors influencing traffic is analyzed and the decision tree algorithm is adopted to model the data of velocity and environmental fac-tors to determine the rules of traffic congestion. Then, according to the real-time mobile users and envi-ronmental factors data, the traffic state is predicted with the generated rules. Experiment in Baoding City, Hebei Province proves the effectiveness of the proposed method. It is also found that the method based on decision tree algorithm has a high expansibility.