An Intelligent Traffic Flow Progression Model for Predictive Control Applications: A Proposed Approach for Making Short-term Traffic Flow Predictions, Using a Recurrent, Multi-task Learning Neural Network Model, to Transform Traffic Light Controllers from Adaptive to Predictive with Minimal Hardware Changes

This study explores the possibility of developing a short-term traffic flow prediction model that can be used to convert installed adaptive controllers to predictive controllers with minimal hardware changes. By using the prediction model’s outputs to virtually trigger vehicle loop detectors, the outputs of an adaptive controller can be...