Kwon, Taek M.2007-08-082007-08-082006-04-01CTS 06-03https://hdl.handle.net/11299/549The Transportation Data Research Laboratory (TDRL) at the University of Minnesota Duluth was established to study archiving and sharing issues of large-scaled data generated by Intelligent Transportation Systems (ITS). The intent was to attain additional benefits of ITS data by archiving and sharing the historic data with public, universities, and government organizations through Internet. In the fiscal year (FY) 2003-04, TDRL completed online automation for the two large sets of transportation data generated by the Minnesota Department of Transportation (Mn/DOT) ITS; they are the traffic data collected from the Transportation Management Center (TMC) in Twin Cities and the statewide road-weather data collected from the Mn/DOT Road Weather Information System (RWIS). These two sets of large data are now available through Internet and can be freely downloaded. Beyond the data archiving and sharing issues, TDRL researchers also participate in other research issues. In FY 2003-04, TDRL developed a method of detecting faulty loop detectors using software based on analysis of archived traffic data. This method was implemented as a software diagnostic tool and utilizes a new decision-tree algorithm that classifies detectors into four classes, i.e., healthy, marginal, suspected, and highly suspected detectors. TDRL also completed a data automation project with the Mn/DOT Office of Transportation Data & Analysis (TDA). This project involves development of an on-line automation system that computes the traditional continuous and short-duration count data using the ITS archived data. Another project completed by TDRL in FY 2003-04 was the development of a raw-signal probing tool for Lineas Weigh-In-Motion (WIM) systems. The signal processing hardware and software for the WIM probe was successfully developed and delivered to the Mn/DOT TDA. The WIM probe allows for analysts to probe various stages of WIM signal processing and determine the status of each WIM channel.82