Road Weather Management Program
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Best Practices for Road Weather Management Version 2.0

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Title:

The Use of Weather Data to Predict Non-recurring Traffic Congestion

Abstract:

This project demonstrates the quantitative relationship between weather patterns and surface traffic conditions. Data from two data mines on the University of Washington campus were combined to evaluate the quantitative relationship between freeway speed reduction and rain fall rate as measured by Doppler radar. The radar data were converted into rainfall rate, and the speed data from the inductance loop speed traps were converted into a deviation from normal performance measure. The deviation from normal and the rainfall rate were used to construct an impulse response function that can be applied to radar measurements to predict traffic speed reduction. This research has the potential to accomplish (1) prediction of non-recurring traffic congestion and (2) prediction of conditions under which incidents or accidents can have a significant impact on the freeway system. This project created algorithms and implementations to correlate weather with traffic congestion.

Source(s):

Washington State Transportation Center (TRAC), Prepared for the Washington State DOT

http://www.wsdot.wa.gov/research/reports/fullreports/655.1.pdf

Date: 2006

Author:

Dailey

Keywords:


Rain
Vehicle detection
Traffic modeling
Precipitation

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