Researchers tested the use of an on-board Global Positioning System (GPS) to collect travel-time data after special events at the Duluth Entertainment Convention Center in Duluth, Minnesota. The report also studies travel-time prediction via the Kalman filter algorithm which provides estimates of existing values, predicts future values of prescribed variables and improves estimates of earlier variables.
The study was conducted to assist Mn/DOT District One and the City of Duluth Traffic Service Center in the performance monitoring, planning and management of the traffic flow following special events at the Duluth Entertainment Convention
Center (DECC). The report focuses on travel-time predictions on the arterial roads adjacent to the DECC. To project travel times that are both accurate and timely, the authors combined the use of test vehicles equipped with an on-board GPS and the application of the Kalman filtering technique to the resulting data. The Kalman filtering technique is a set of mathematical equations that provides an efficient computational (recursive) means of estimating the state of a process in a way that minimizes the mean of the squared error.</p><p> The integration of these collection and assessment tools has the potential for providing valuable travel-time information to motorists making route choices.
Duluth Entertainment Convention Center (DECC) Special Events Traffic Flow Study Phase II: Mobility Monitoring and Performance Measure via Dynamic Travel Time Prediction.
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