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原文传递 Mining Vehicle Classifications from the Columbus Metropolitan Freeway Management System, Executive Summary.

题名：	Mining Vehicle Classifications from the Columbus Metropolitan Freeway Management System, Executive Summary.
作者：	B., Coifman; B., Huang; K., Redmill; M., Wu
关键词：	Highway Traffic Monitoring; Loop Detectors; Mining Vehicles; Pavement Design; Traffic Control; Traffic Safety; Vehicle Classification; Vehicle Length Measurement
摘要：	This work sought to leverage the existing real-time traffic monitoring infrastructure of the CMFMS to collect length based, vehicle classification data. The individual vehicle actuation data were collected from the 69 detector stations in the CMFMS. The first 46 detector stations were installed on I-70/I-71 during Phase I of the CMFMS, completed in 2001. Only 35% of the Phase I detector stations have dual loop detectors, for the most part these stations were deployed with one dual loop detector station every mile, and two single loop detector stations between dual loop stations. Another 23 detector stations were installed on SR 315 / I-270 / I-70 / I-670 during Phase II of the CMFMS, completed in 2006. The Phase II stations were deployed at a much lower density than those from Phase I and roughly 90% of the Phase II detector stations have dual loop detectors. The primary thrust of this work was extracting classification data for the previous ten years from the archived PVR data. While length based classification from dual loop detectors is common, it relies in finely tuned detectors. The focus of this task was on the details of extracting the classifications, establishing and implementing the desired level of confidence, developing approaches to handle data outages, establishing links with multiple stations and fusing data from those stations, developing tools to aggregate and report the data in the format(s) desired by ODOT, and several other related implementation tasks. The CMFMS detectors are not finely tuned, but we have developed tools using the PVR data to identify problems and in most cases correct for them.
报告类型：	科技报告