Incorporating Inclement Weather Impacts on Traffic Estimation and Prediction

Traffic simulation models should reflect a wide variety of operating and environmental conditions in order to be useful in estimation and prediction of real world traffic behavior. One area that traffic simulations have to accurately model is the effect that weather has on driver behavior and traffic flow characteristics. Recently, the Northwestern University and the University of Virginia have addressed this deficiency by investigating observed impacts of weather on both the supply and demand of traffic networks. This paper has two research purposes: to present the methodology for incorporating weather impacts into the DYNASMART-P traffic estimation and prediction tool and to assess the relative accuracy and fidelity of the developed weather module. The results indicate that the weather adjustment factor module developed by the Northwestern University is capable of reducing overestimation of vehicle speeds from 2 mph to 1 mph for light rain conditions and reducing the absolute error in estimating speeds during heavy rain by 33% when compared against simulations performed using normal parameters. Additionally, of the three scenarios tested for two different weather conditions, the weather adjustment factor method consistently produced the smallest root mean squared error between simulated and observed speeds.


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 12p
  • Monograph Title: 18th ITS World Congress, Orlando, 2011. Proceedings

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Filing Info

  • Accession Number: 01487194
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jun 25 2013 11:06AM