Development and Evaluation of Deep Learning Predictive Traffic Intelligence Models

The aim of the thesis is to demonstrate the feasibility of predicting traffic conditions up to 60 minutes into the future during free flow and high congestion times. The accurate system can identify total hours lost from delays, Increase productivity and economic activity due to the reduction of wasted time spent in traffic and reduce the amount of CO2 Greenhouse Gas emissions created during delays that could have been avoided. Thus, it can create smarter, safer, and more productive journeys for customers, and increase the efficiency of existing assets.