基于收费数据的高速公路交通拥挤自动判别方法

针对高速公路交通拥挤日益严重的现象，通过对收费数据的深层挖掘和高效利用，提出了基于滚动时间序列的行程时间数据合成方法，以此为基础构建了交通拥挤指数，并基于交通拥挤指数的变化特征对拥挤持续时间进行了在线估计；结合收费站布局的时空特征，设计了基本路段和复合路段融合的高速公路交通拥挤自动判别方法．实证分析表明，该方法在判别率提高到96．52％，误判率降低到0．43％的同时，判别时间减少了74％，而且收费数据的获取成本为零．

The automatic traffic congestion identification of freeway based on charging date

In view of increasingly serious traffic congestion on freeway, a synthesis method of travel time date was proposed based on the rolling time sequence and charging data, and on which this paper built a traffic congestion index and estimated the duration time according to the changing characteristics of the index. Moreover, taking the spatial and temporal characteristics of toll station layout into account, a method of automatic traffic congestion identification on freeway was designed by merging basic links with composite links. Empirical analysis shows that this method can improve the recognizing rate to 96.52% and reduce the false recognizing rate to 0.43%, at the same time, the recognizing time is declined by 74%, and the cost of charging date is zero.