Statistical Methods and Models for Video-Based Tracking, Modeling, and Recognition
Foundations and Trends in Signal Processing
Constraint k-segment principal curves
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
A generative model and a generalized trust region Newton method for noise reduction
Computational Optimization and Applications
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We have proposed to use the method of principal curves to describe and analyze the interaction among freeway traffic-stream variables and their joint behaviors without utilizing conventional assumptions made on the functional forms of interactions, as in previous studies. As a nonparameter modeling approach, the performance of the proposed method depends only on the data used and involves no assumed knowledge regarding the relationship among the traffic-stream variables. First, we discuss the basic algorithm for data analysis using principal curves and the corresponding data filter algorithm for determining principal curves for application in traffic-steam analysis. Second, a case study is used to compare the performance of the proposed method to that of the classical model proposed by Greenshields; results indicate that the proposed model is better than the classical one in both data accuracy and curve shape. Finally, the traffic-stream models generated with principal curves at different locations and lanes are compared with each others and the three-dimensional traffic-stream models developed from principal curves are discussed. Clearly, our results have demonstrated the feasibility and advantages of applying principal curves in freeway traffic-stream modeling and analysis.