TEPs-II trains a Neural Network based learning algorithm to mimic the output of a user equilibrium traffic assignment model and to reproduce a relationship between vehicle speed and AADT. The trained model is then used to predict vehicle speed from TEPS-I. Road emissions are estimated based on average speeds, predicted volumes, and average-speed emission factors (EFs).
Learn and read more about TEPs-II theory and application.
This project was supported by The City of Toronto's Transportation Services Division and Atmospheric Fund
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Updated on Feb 28, 2019