It is a spatio-temporal model for traffic volume prediction at stations with medium range traffic counts.
It can handle situations with limited data availability thus avoiding the excessive number of parameters required by multivariate time series models.
This model was tested for several case studies in the City of Toronto. The result clearly showed that generated traffic volumes have a magnitude and variation similar to observed traffic counts.
This project was supported by The City of Toronto's Transportation Services Division and Atmospheric Fund
Copyright © 2019 Traffic Emission Prediction scheme (TEPs) - All Rights Reserved.
Updated on Feb 28, 2019