高速公路收费车道容量与车辆缴费排队等候时间在相当程度上是成正比的,本文采用机器学习与大数据统计分析的相关技术,通过基于图像的自动车型分类、流量统计、速度检测等方法,结合统计判别与分类预测等技术方案进行高速公路出入口的排队时间预测。将高速公路收费车道容量(开通收费通道的个数与每个通道单车平均收费时间)与车辆缴费排队等候时间进行强关联分析,形成了一种收费车道容量与车辆缴费排队等候时间的车辆畅通模型。 Freeway toll lane capacity and vehicle toll queuing time is proportional to a considerable extent, this paper uses machine learning and big data statistical analysis of related technologies, through image-based automatic vehicle classification, traffic statistics, speed detection and other methods, combined Statistical judgment and classification prediction and other technical solutions for expressway entrance queuing time prediction. The highway toll lane capacity (the number of toll roads opened and the average toll time per cycle) and vehicle toll queuing time strong correlation analysis, the formation of a toll lane capacity and vehicle toll queuing waiting time vehicle flow model .