Authors:Ingo Thomsen;Yannick Zapfe andSven Tomforde

Affiliation:Intelligent Systems, Christian-Albrechts-Universität zu Kiel, 24118 Kiel, Germany

Keyword(s):Organic Traffic Control, Traffic Flow Analysis, Traffic Incident Detection, Traffic Management.

Abstract:The traffic demands in urban road networks can fluctuate immensely. The Organic Traffic Control (OTC) offers a resilient traffic management to control such traffic demands. An additional challenge is the detection of unforeseen traffic incidents. To enhance the capabilities of OTC accordingly, we outline a traffic incident algorithm based on DBSCAN, a density-based clustering algorithm: In a simulated urban road network, equipped with traffic light controllers at intersections, vehicle detectors are used to gather traffic flow data. The clustering of this time series data to detect simulated road blockages is expanded using various filters. This extension of the initial clustering is the result of an manual evaluation process, which shows the principal applicability of this approach.