Short term traffic congestion prediction using publically available traffic data: a case study on Timisoara

By using data gathered from real-life traffic situations combined with concepts of machine learning, the purpose of our work is to determine patterns and, consequently, try to predict future traffic congestion caused by anomalies such as accidents. The results will be compared to the actual data in order to assess the accuracy of the implemented solution.