Traffic control systems should cope with the ever increasing demand by determining the situation on the road network and by controlling traffic flows. Emerging cooperative techniques like vehicle-to-infrastructure communication increase the knowledge about road traffic participants and open new channels for delivering information to these participants. However, most cooperative systems require large penetration rates in order to assure their functionality, making the first steps towards their deployment unattractive.
COLOMBO overcomes this hurdle by delivering a set of modern, self-organizing traffic management algorithms designed for being applicable even at low penetration rates, asserting their usability from the very first deployment days on. COLOMBO focuses on two traffic management topics: traffic surveillance and advanced traffic light control algorithms. Herein, cost-efficiency and the reduction of vehicular emissions are the project’s key objectives. Both results lay the foundations for new, cost-effective and comprehensive way to measure and handle traffic. The results of COLOMBO include prototypes for incident and emission monitoring at intersections, for traffic state estimation based on fragmented data collected in low V2X equipment rate scenarios and for the self-organizing traffic control algorithm SWARM. A key aspect in the COLOMBO investigations is the use of advanced optimization techniques for tuning the parameter sets of the traffic control algorithms.
These results have been achieved in tight cooperation of the project partners Graz University of Technology contributing PHEM, the German Aerospace Center DLR issuing SUMO, the University of Bologna who devised SWARM, the Universite libre de Bruxelles which maintains irace and the Graduate School and Research Center in Communication Systems EURECOM.