Acquisition of Traffic Flow Density Using Multi-source Data Fusion

摘要：

Traffic flow density is one of the most important parameters in traffic flow theory. It provides basic data for urban traffic management and control. However, it is highly difficult to directly collect real-time traffic flow density. The existing methods are simple in form, which are not suitable for complex traffic situations. The main purpose of this paper is to studying acquisition method of realtime traffic flow density by fusing Floating Car Data (FCD) and geomagnetic detection data. Least Squares Support Vector Regression (LS-SVR), which has properties such as global convergence and strong generalization capacity, is introduced to accomplish multi-source data fusion. The experimental result indicated that our approach has higher estimation accuracy than the traditional models.

关键词： velocity density truffle flow data fusion LS-SVR

作者: Zhu Tehao Chen Feng

作者单位: Department of Automation University of Science and Technology of China Hefei, China Department of Automation University of Science and Technology of China Hefei. China

会议类型: 国际会议

会议名称: 2012 International Conference on Measurement,Information and Control(2012测量、信息与控制国际会议 ICMIC2012)

会议地点: 哈尔滨

会议语种:英文

页码: 595-599

在线出版日期: 2012-05-18（万方平台首次上网日期，不代表论文的发表时间）