Noise-Aware UAV Path Planning in Urban Environment with Reinforcement Learning
This research presents a comprehensive approach for mitigating noise pollution from Unmanned Aerial Vehicles (UAVs) in urban environment by using Reinforcement Learning (RL) for flight path planning. Focusing on the city of Turin, Italy, the study utilizes its diverse urban architecture to develop a...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Engineering Proceedings |
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| Online Access: | https://www.mdpi.com/2673-4591/90/1/3 |
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| author | Shahin Sarhan Marco Rinaldi Stefano Primatesta Giorgio Guglieri |
| author_facet | Shahin Sarhan Marco Rinaldi Stefano Primatesta Giorgio Guglieri |
| author_sort | Shahin Sarhan |
| collection | DOAJ |
| description | This research presents a comprehensive approach for mitigating noise pollution from Unmanned Aerial Vehicles (UAVs) in urban environment by using Reinforcement Learning (RL) for flight path planning. Focusing on the city of Turin, Italy, the study utilizes its diverse urban architecture to develop a detailed 3D occupancy grid map, and a population density map. A dynamic noise source model adjusts noise emissions based on the UAV velocity, while acoustic ray tracing simulates noise propagation in the environment. The Deep Deterministic Policy Gradient (DDPG) algorithm optimizes flight paths, minimizing the noise impact, and balancing both the path length and the population density located under the UAV path. The simulation results demonstrate significant noise reduction, suggesting scalability and adaptability for global urban environments, contributing to sustainable urban air mobility by addressing noise pollution. |
| format | Article |
| id | doaj-art-cdf30a101bef413fb3c1cbe26a6bbda7 |
| institution | Kabale University |
| issn | 2673-4591 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj-art-cdf30a101bef413fb3c1cbe26a6bbda72025-08-20T03:26:56ZengMDPI AGEngineering Proceedings2673-45912025-03-01901310.3390/engproc2025090003Noise-Aware UAV Path Planning in Urban Environment with Reinforcement LearningShahin Sarhan0Marco Rinaldi1Stefano Primatesta2Giorgio Guglieri3Department of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, ItalyDepartment of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, ItalyDepartment of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, ItalyDepartment of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, ItalyThis research presents a comprehensive approach for mitigating noise pollution from Unmanned Aerial Vehicles (UAVs) in urban environment by using Reinforcement Learning (RL) for flight path planning. Focusing on the city of Turin, Italy, the study utilizes its diverse urban architecture to develop a detailed 3D occupancy grid map, and a population density map. A dynamic noise source model adjusts noise emissions based on the UAV velocity, while acoustic ray tracing simulates noise propagation in the environment. The Deep Deterministic Policy Gradient (DDPG) algorithm optimizes flight paths, minimizing the noise impact, and balancing both the path length and the population density located under the UAV path. The simulation results demonstrate significant noise reduction, suggesting scalability and adaptability for global urban environments, contributing to sustainable urban air mobility by addressing noise pollution.https://www.mdpi.com/2673-4591/90/1/3UAVnoise mitigationreinforcement learningpath planningDDPGUAM |
| spellingShingle | Shahin Sarhan Marco Rinaldi Stefano Primatesta Giorgio Guglieri Noise-Aware UAV Path Planning in Urban Environment with Reinforcement Learning Engineering Proceedings UAV noise mitigation reinforcement learning path planning DDPG UAM |
| title | Noise-Aware UAV Path Planning in Urban Environment with Reinforcement Learning |
| title_full | Noise-Aware UAV Path Planning in Urban Environment with Reinforcement Learning |
| title_fullStr | Noise-Aware UAV Path Planning in Urban Environment with Reinforcement Learning |
| title_full_unstemmed | Noise-Aware UAV Path Planning in Urban Environment with Reinforcement Learning |
| title_short | Noise-Aware UAV Path Planning in Urban Environment with Reinforcement Learning |
| title_sort | noise aware uav path planning in urban environment with reinforcement learning |
| topic | UAV noise mitigation reinforcement learning path planning DDPG UAM |
| url | https://www.mdpi.com/2673-4591/90/1/3 |
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