基于饱和度的路网交通态势实时辨识

Real-time identification of the road network traffic state based on saturation

提出一种基于交通饱和度的路网交通态势辨识方法。通过预测交叉口排队长度和交通流量,得到交叉口和路段的饱和度。再利用层次K-Means聚类方法,对路网饱和度进行了聚类分析,由饱和度与服务水平的关系来确定各类对应的交通态势。根据路网饱和度均值,将热力图的点分布密集程度制作成交通态势热力图,对曲靖市麒麟区路网的交通态势预测进行了验证。研究结果表明:该方法可以实现路网交通态势实时辨识,并可弥补数据缺失情况下的交通态势辨识误差的不足,增加结果的可靠度。

A road network traffic state identification method based on traffic saturation is proposed.The intersection and segment saturation are calculated by predicting the arrival traffic and queue length.The road network saturation is performed by the hierarchical K-Means clustering method,and the traffic state is known according to the relationship between saturation and service level.The traffic situation heat map is generated according to the point distribution intensity of the road network saturation mean to the heat map.Taking Qilin District in Qujing as an example to conduct prediction experiments,the results show that the method can realize the real-time identification of the road traffic state,and can compensate for the lack of data loss and increase the credibility.