Urban traffic congestion prediction based on routes information

Traffic congestion represents an important problem in crowded urban areas. It leads to travel delays, increased fuel consumption and higher level of pollution. This paper proposes a technique for congestion prediction in urban traffic. It uses event based routes selection and relies on information collected by a sensor network. Simulation experiments with more than 50 traffic patterns over eight crowded intersections demonstrate promising results.