Improve Traffic Volume Estimates from MnDOT's Regional Traffic Management Center

Abstract

The Regional Transportation Management Center (RTMC) at the Minnesota Department of Transportation (MnDOT) deploys a large number of traffic detectors in the Twin Cities' freeway network and continuously collects traffic data. While RTMC mainly uses the data for traffic and incident management, the TFA (Traffic Forecasting and Analysis) office uses the same data for monitoring, forecasting, planning, and reporting of transportation applications. RTMC provides current and historical volume data generated from its freeway network, but it does not provide quality information on that data. The objective of this project was to develop a new tool that can quickly explore the quality of detector data. To allow exploration of data quality, 13 detector-health parameters were computed using raw volume and occupancy data and then they were stored in a relational database. The final detector-health system was implemented as a client server-based system, in that a single server served many remote clients through the Internet. This report provides descriptions of the detector-health parameters, principles applied, server implementation, client software, and some analyses and application examples.