Noise-aware and equitable urban air traffic management: An optimization approach

IF 7.6 1区 工程技术 Q1 TRANSPORTATION SCIENCE & TECHNOLOGY
Zhenyu Gao , Yue Yu , Qinshuang Wei , Ufuk Topcu , John-Paul Clarke
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引用次数: 0

Abstract

Urban air mobility (UAM), a transformative concept for the transport of passengers and cargo, faces several integration challenges in complex urban environments. Community acceptance of aircraft noise is among the most noticeable of these challenges when launching or scaling up a UAM system. Properly managing community noise is fundamental to establishing a UAM system that is environmentally and socially sustainable. In this work, we develop a holistic and equitable approach to manage UAM air traffic and its community noise impact in urban environments. The proposed approach is a hybrid approach that considers a mix of different noise mitigation strategies, including limiting the number of operations, cruising at higher altitudes, and ambient noise masking. We tackle the problem through the lens of network system control and formulate a multi-objective optimization model for managing traffic flow in a multi-layer UAM network while concurrently pursuing demand fulfillment, noise control, and energy saving. Further, we use a social welfare function in the optimization model as the basis for the efficiency-fairness trade-off in both demand fulfillment and noise control. We apply the proposed approach to a comprehensive case study in the city of Austin and perform design trade-offs through both visual and quantitative analyses.

噪声感知和公平的城市空中交通管理:优化方法
城市空中交通(UAM)是客货运输的一个变革性概念,在复杂的城市环境中面临着若干整合挑战。在启动或扩大城市空中交通系统时,社区对飞机噪音的接受程度是其中最明显的挑战之一。妥善管理社区噪声是建立环境和社会可持续发展的无人机空中交通系统的基础。在这项工作中,我们开发了一种全面、公平的方法来管理城市环境中的空中交通及其社区噪声影响。所提出的方法是一种混合方法,考虑了各种不同的噪声缓解策略,包括限制运营次数、在更高的高度巡航和环境噪声掩蔽。我们从网络系统控制的角度来解决这个问题,并制定了一个多目标优化模型,用于管理多层 UAM 网络中的交通流,同时追求需求满足、噪声控制和节能。此外,我们将优化模型中的社会福利函数作为需求满足和噪声控制中效率-公平权衡的基础。我们将提出的方法应用于奥斯汀市的综合案例研究,并通过直观和定量分析进行设计权衡。
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来源期刊
CiteScore
15.80
自引率
12.00%
发文量
332
审稿时长
64 days
期刊介绍: Transportation Research: Part C (TR_C) is dedicated to showcasing high-quality, scholarly research that delves into the development, applications, and implications of transportation systems and emerging technologies. Our focus lies not solely on individual technologies, but rather on their broader implications for the planning, design, operation, control, maintenance, and rehabilitation of transportation systems, services, and components. In essence, the intellectual core of the journal revolves around the transportation aspect rather than the technology itself. We actively encourage the integration of quantitative methods from diverse fields such as operations research, control systems, complex networks, computer science, and artificial intelligence. Join us in exploring the intersection of transportation systems and emerging technologies to drive innovation and progress in the field.
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