Data Driven Urban Traffic Prediction for Winter Performance Measurements

Project status

In progress

Start date: 08/01/14
End date: 12/31/16

Researcher(s)

Principal investigator:

Co-principal investigator:

About the research

Prediction of traffic speed drop under severe weather in an urban setting is important in measuring the performance of winter highway maintenance programs in the city. We propose to develop traffic models on urban road networks for prediction of speed drop during winter weather events. This work is built on our previous and current work on point level modeling and prediction of traffic speed drops during weather for performance evaluation in rural areas. A multivariate spatial-temporal autoregressive model will be developed to accommodate the more complex road network structure in urban environments, and weather forecasting data and global positioning system (GPS) information from snow plows will be integrated into the model to provide more accurate prediction.

Sponsor(s)/partner(s)

Sponsor(s):

  • Iowa Department of Transportation
  • Midwest Transportation Center
  • USDOT/OST-R