用量子退火优化城市空中交通车队路径与调度。
Routing and Scheduling Optimization for Urban Air Mobility Fleet Management using Quantum Annealing
- 将路径规划建模为最大权独立集问题，适配量子退火硬件。
- 在新加坡空域模拟中提升空域利用率，实现无冲突调度。
- 适合关注智能交通与量子计算应用的科研人员。
城市空中交通（UAM）因交通拥堵及其环境与经济影响日益增长。高效管理城市高密度空域交通对保障安全与运行效率至关重要。本文提出一种面向大规模UAM车队的城市空中交通路由与调度框架，通过数学优化方法规划高效且无冲突的车辆路径。将路径规划建模为最大权独立集问题，从而可利用量子退火等专用优化硬件，近年该技术取得显著进展。方法在专为新加坡空域设计的交通管理仿真器中验证，结果表明该方案通过分散区域交通流量提升了空域利用率。本研究拓展了优化技术在UAM交通管理中的应用前景。
原文摘要 · Abstract (English)
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.
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