Data Driven Urban Traffic Prediction for Winter Performance Measurements
- Mark Kaiser | Iowa State University
Start date: 08/01/14
End date: 12/31/16
- Iowa Department of Transportation
- Midwest Transportation Center
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.