Monitoring traffic in future cities with aerial swarms: Developing and optimizing a behavior-based surveillance algorithm |
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| Institution: | 1. School of Computer Science and Technology, Wuhan University of Technology, Wuhan 430063, China;2. School of Information, Beijing Wuzi University, Beijing 101149, China;3. Key Laboratory of Grain Information Processing and Control of Ministry of Education, Henan University of Technology, ZhengZhou, China;4. Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science and Technology, Nanjing, China;1. Department of Computer Science, University of Brasilia, Brazil;2. Institute of Informatics, Federal University of Rio Grande do Sul, Brazil |
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| Abstract: | 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 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. |
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| Keywords: | Aerial swarms Smart cities Traffic monitoring Behavior-based control |
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