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

AuthorsGarcía-Aunon, Pablo; Jesús Roldán, Juan; Barrientos, Antonio
KeywordsAerial swarms
Smart cities
Traffic monitoring
Behavior-based control
Issue Date3-Nov-2018
PublisherElsevier BV
CitationCognitive Systems Research 54: 273-286 (2019)
AbstractTraffic 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 the 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.
Publisher version (URL)https://doi.org/10.1016/j.cogsys.2018.10.031
Appears in Collections:(CAR) Artículos
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