基于多元数据融合的线圈数据修补应用研究

Study on Loop Data Patching Base on the Multi-Source Data Fusion

现有的道路交通信息系统中,线圈作为其中埋设数量最多、分布最广的车流采集方式,是上海道路交通运行评价的主要数据来源。基于多元数据的采集环境,以线圈数据存在的问题为基础,从应用的角度,研究线圈数据的修补方法,主要包括数据筛选、修补和多元数据融合的三方面内容,为支撑道路交通评估提供可靠分析基础。

In the existing road traffic detection system, Loop has the largest amount of equipment. Loop data provide the primary source to support Shanghai monthly traffic congestion evaluation and prediction. But loop data has its own drawback. Now in the multi-source collection environment, we study the solution to solve the problem by data filtering, patch and data fusion. It provide a reliable basis to support road traffic assessment.