Intelligent Traffic Control

The transport sector accounts for more than 30% of the CO2 emission coming from the non-quote regulated sectors.  In particular, much of the pollution in cities and (the internationally growing number of) mega-cities comes directly from increased congestion of traffic. As part of the Innovation Center DiCyPS (www.dicyps.dk), researcher from Computer Science and Transport at AAU has developed a disruptive method for intelligent control of traffic lights in intersections utilizing machine-learning applied on-line to traffic-information from radars. Preliminary results based on traffic simulation (of Hobrovej in Aalborg) demonstrates that CO2 emission in intersections may be reduced by more than 20%, while reducing the delay in intersection by 40%.Ongoing field tests (in Grenå/Egå-Havvej, Aarhus) confirms that this disruptive approach to traffic light control reduces delay by 32%.