Applications of Data Fusion on Travel Speed from Heterogeneous Sources
Date Issued
2007
Date
2007
Author(s)
Chang, Chia-Wen
DOI
zh-TW
Abstract
Real time traffic data acquisition has been the core and basis of all development of the advanced traffic management system (ATMS). For the goal of predicting traffic speed by spot and linear parameters, the traffic information sources in the framework of system should include roadside detectors data from taxi fleets as probe vehicles and historical data to generate traffic data for the main artery of urban area. According to the architecture, this paper describes the technique of using data fusion of active and passive information that combines adopt the spot and linear data to become their characteristics for estimation of traffic speed based on entropy and optimum weight that satisfies needs for all the potential public and private users.
Through the development of traffic data fusion process, the proposed fusion model will be used for the data collection, fusion and analysis of traffic information. The process is composed of three consecutive computational steps. The first step is data screening that uses to reduce inaccuracy of outliers in system. The second step is to transfer data on the same basis – space mean speed, classify and individualize the data, and the latter can measure the probabilities in several sample sets and produce the entropy. The third step is to apply the optimum weight rule to generate weight allocation for travel speed from different sources.
The experimental results reveal that good fusion results are obtained through the proposed data processing. This paper not only puts emphasis on reviewing the layout of surveillance technologies but finds the frequency and the applicative length of the main artery suitable model.
Subjects
資料融合
路段行駛速率
最佳權重法
Data Fusion
Travel Speed
Optimum Weight
Type
thesis
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