domingo, 4 de noviembre de 2018

Monitoring traffic in future cities with aerial swarms: developing and optimizing a behavior-based surveillance algorithm




Traffic monitoring is a key issue to develop smarter and more sustainable cities in the future, allowing to make a better use of the public space and reducing pollution. This work presents an aerial swarm that continuously monitors traffic in SwarmCity, a simulated city developed in Unity game engine where drones and cars are modeled in a realistic way. The control algorithm of the aerial swarm is based on six behaviors with twenty-three parameters that must be tuned. The optimization of parameters is carried out with a genetic algorithm in a simplified and faster simulator. The best resulting configurations are tested in SwarmCity showing good efficiencies in terms of observed cars over total cars during time windows. The algorithm reaches a good performance making use of an acceptable computational time for the optimization.


P. Garcia-Aunon, J.J. Roldán and A. Barrientos. “Monitoring traffic in future cities with aerial swarms: developing and optimizing a behavior-based surveillance algorithm”. Cognitive Systems Research, 2018. Impact Factor (2016): 1.425. Article

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