The growing integration of urban air mobility (UAM) for urban transportation and delivery has accelerated due to increasing traffic congestion and its environmental and economic repercussions. Efficiently managing the anticipated high-density air traffic in cities is critical to ensure safe and effective operations. In this study, we propose a routing and scheduling framework to address the needs of a large fleet of UAM vehicles operating in urban areas. Using mathematical optimization techniques, we plan efficient and deconflicted routes for a fleet of vehicles. Formulating route planning as a maximum weighted independent set problem enables us to utilize various algorithms and specialized optimization hardware, such as quantum annealers, which has seen substantial progress in recent years. Our method is validated using a traffic management simulator tailored for the airspace in Singapore. Our approach enhances airspace utilization by distributing traffic throughout a region. This study broadens the potential applications of optimization techniques in UAM traffic management.

翻译：随着交通拥堵及其环境与经济影响的加剧，城市空中交通（UAM）在城市运输与配送领域的融合日益深入。高效管理城市中预期的高密度空中交通，对于确保安全有效的运营至关重要。本研究提出一个路径规划与调度框架，以满足在城市区域运行的大型UAM车队的需求。通过运用数学优化技术，我们为车队规划高效且无冲突的飞行路径。将路径规划问题表述为最大加权独立集问题，使我们能够利用多种算法及专用优化硬件（例如近年来取得显著进展的量子退火器）。我们的方法使用针对新加坡空域定制的交通管理模拟器进行了验证。该方法通过将交通流量分散至整个区域，提升了空域利用率。本研究拓展了优化技术在城市空中交通管理中的潜在应用范围。