Analysis of urban traffic patterns using clustering

Mobility is still increasing, as are its corresponding negative side effects such as congestion and air pollution. To be able to take adequate measures to minimize these side effects, it is important to obtain insight into the functioning of the traffic system. In common practice, the traffic analysis process deals with average traffic volumes. However, also the variability of traffic volumes is of crucial importance, for example with regard to travel time reliability, the robustness of the road network and dynamic traffic management. Moreover, until recently, the main focus was on highway systems. Since mobility is also increasing in urban areas, it is also important to obtain insight into the functioning of the urban traffic system. This thesis aims at improving the insight into variations in urban traffic by analysing within and between day variations in traffic volumes.