, Professor, UMD-Electrical Engineering
Collection of vehicle classification data is considered an essential part of traffic monitoring programs. The objective of this project was to integrate the raw classification data generated by the Minnesota Department of Transportation (MnDOT) Regional Transportation Management Center (RTMC) into the existing volume data managed by the Traffic Forecasting and Analysis (TFA) section under the Office of Transportation System Management (OTSM). RTMC manages a large number of traffic sensors in the Twin Cities freeway network and continuously collects a huge amount of traffic data. Recently, it added Wavetronix radar sensors, from which length-based classification and speed data are generated in addition to typical volume and occupancy data generated by loop detectors. This project integrated this classification data into the existing TFA volume data, which could save cost and time for TFA in the future by using existing classification data. The project team also integrated the RTMC speed data for the locations where it was available. The final deliverable of this project was a software tool called detHealth_app, from which users can retrieve classification and speed data in addition to volume/occupancy data in multiple formats including Federal Highway Administration (FHWA) format. The detHealth_app program was thoroughly tested and has been successfully used by MnDOT TFA.