无人机
模拟
噪音(视频)
计算机科学
飞行模拟器
布线(电子设计自动化)
运动规划
航空学
航空航天工程
工程类
嵌入式系统
人工智能
机器人
遗传学
图像(数学)
生物
作者
Qichen Tan,Siyang Zhong,Renhao Qu,Yuhong Li,Peng Zhou,Hong K. Lo,Xin Zhang
标识
DOI:10.1109/mits.2024.3396430
摘要
The vehicle routing problem is common for drone delivery in urban areas, and the routing strategies can impact both transport efficiency and community noise. In this article, we propose an optimization method for drone routing to reduce the en route noise impact during the delivery process. A hybrid cost function is adopted to evaluate the quality of the routing strategies, considering both the noise impact and path length. The en route noise is evaluated based on an efficient flight simulation and noise assessment platform, which enables accurate sound source modeling for a practical delivery drone and sound propagation computation in a realistic urban environment. A three-phase heuristic algorithm is employed to optimize the routing strategy. Large-scale simulations conducted in a representative metropolitan area demonstrate significant reductions in both instantaneous and accumulated noise levels. This article highlights the importance of incorporating noise optimization strategies in urban drone delivery systems to improve public acceptance and sustainable air transport.
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