为实时获得道路交通状况并对车辆运行进行调度,开发一个基于支持向量机(SVM)的公交车辆到站时间预测模型,并以大连市23路公交车为例对该模型进行检验.结果表明,本文提出的SVM模型比历史平均模型(HMP)和神经网络模型(ANN)的预测精度更高. In order to obtain real-time road traffic conditions and schedule vehicle operation, a bus arrival time forecasting model based on Support Vector Machine (SVM) is developed, and the model is tested by taking Bus 23 in Dalian as an example. The proposed SVM model has higher prediction accuracy than the historical average model (HMP) and neural network model (ANN).