Detection of incidents and events in urban networks


Thomas, T. and Berkum, E.C. van (2009) Detection of incidents and events in urban networks. IET Intelligent Transport Systems, 3 (2). pp. 198-205. ISSN 1751-956X

open access
Abstract:Events and incidents are relatively rare, but they often have a negative impact on traffic. Reliable travel demand predictions during events and incident detection algorithms are thus essential. The authors study link flows that were collected throughout the Dutch city of Almelo. We show that reliable, event-related demand forecasting is possible, but predictions can be improved if exact start and end times of events are known, and demand variations are monitored conscientiously. For incident detection, we adopt a method that is based on the detection of outliers. Our algorithm detects most outliers, while the fraction of detections due to noisy data is only a few percent. Although our method is less suitable for automatic incident detection, it can be used in an urban warning system that alerts managers in case of a possible incident. It also enables us to study incidents off-line. In doing so, we find that a significant fraction of traffic changes route during an incident.
Item Type:Article
Copyright:© IEEE
Engineering Technology (CTW)
Research Group:
Link to this item:
Official URL:
Export this item as:BibTeX
HTML Citation
Reference Manager


Repository Staff Only: item control page

Metis ID: 249296