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Traffic Data Quality Verification and Sensor Calibration for Weigh-in-motion (WIM) Systems

其他書名	Final Report
出版	Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2012
URL	http://books.google.com.hk/books?id=aXOZMwEACAAJ&hl=&source=gbs_api

註釋This project aims to understand the characteristics of WIM measurements, identify different WIM operational modes, and develop mixture models for each operation period. Several statistical data analysis methodologies were explored to detect measurement drifts and support sensor calibration. A mixture modeling technique using Expectation Maximization (EM) algorithm and cumulative sum (CUSUM) methodologies were explored for data quality assurance. An adjusting CUSUM methodology was used to detect data anomaly. The results indicated that the adjusting CUSUM methodology was able to detect the sensor drifts. The CUSUM curves can trigger a potential drifting alert to the WIM manager. Further investigation was performed to compare the CUSUM deviation and the calibration adjustment. However, the analysis results did not indicate any relationship between the computed CUSUM deviation and the calibration adjustment.