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个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:计算机科学与技术学院
办公地点:大连理工大学创新园大厦8-A0824
联系方式:18641168567
电子邮箱:gztan@dlut.edu.cn
Traffic Information Detection Based on Scattered Sensor Data: Model and Algorithms
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论文类型:期刊论文
发表时间:2013-01-01
发表刊物:AD HOC & SENSOR WIRELESS NETWORKS
收录刊物:SCIE、Scopus
卷号:18
期号:3-4,SI
页面范围:225-240
ISSN号:1551-9899
关键字:Intelligent transportation system (ITS); wireless sensor networks (WSN); traffic surveillance; traffic flow theory; traffic congestion-model; nonlinear surface reconstruction; numerical interpolation; scattered data fitting; finite elements method
摘要:This paper presents the mathematical model and algorithms for traffic flow information detection based on proximity sensor networks. Take into account the intrinsic properties of traffic flow and the principle of traffic congestion formation to build an observation model in the intersection and near segments. Based on the analytical model, this paper developed the method and algorithms to estimate traffic parameter with the scattered sensor data, and reconstruct the traffic surface using numerical interpolation and finite elements method. The result is expected to support the optimal global timing for the purpose of traffic light control, real-time traffic state monitoring and evaluation, and try to avoid the traffic congestion before it formation. The performance is analyzed based on the Mobile Century dataset. The simulation result shows that this method can improve the spatial-temporal resolution of traffic detection, and it is helpful to make quantitative analysis of traffic congestion.