城市空中交通战略冲突解决中的声明式问题求解
Declarative Problem Solving in UAM Strategic Deconfliction
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中文总结 AI 辅助
针对城市空中交通战略冲突解决难题，提出基于回答集编程的方法，聚焦时间同步与路线优化，通过与约束编程对比测试，发现ASP在中小规模案例中执行快、扩展性好，CP内存稳定但随复杂度降低。
中文摘要 AI 辅助
城市空中交通（UAM）需求增长给空域管理带来挑战，尤其是在人口密集的大都市地区。随着无人机、空中出租车和直升机等飞行器数量增加，空中碰撞风险以及与现有空中交通和障碍物冲突增多。我们提出基于回答集编程（ASP）的战略冲突解决方法，聚焦无冲突飞行计划的时间同步和路线优化。该解决方案与约束编程（CP）进行基准测试，强调可扩展性和资源使用。结果表明，ASP在中小规模案例中执行更快、扩展性更好，而CP内存稳定但随复杂度下降。
英文摘要
The growing demand for Urban Air Mobility (UAM) introduces significant challenges in airspace management, particularly within densely populated metropolitan regions. As the number of aerial vehicles-such as drones, air taxis, and helicopters-continues to rise, so does the risk of mid-air collisions and conflicts with existing air traffic and obstacles. Ensuring safe and efficient UAM operations requires robust strategic deconfliction mechanisms. We propose an Answer Set Programming (ASP) based approach for strategic deconfliction, focusing on time synchronization and route optimization for conflict-free flight plans. The solution is benchmarked against Constraint Programming (CP), emphasizing scalability and resource use. Results show that ASP offers faster execution and better scalability for small to medium cases, while CP maintains stable memory but degrades with complexity.
发表机构
- Polytechnic University of Bari（巴里理工大学）
- University of Bari Aldo Moro（巴里阿尔多·莫罗大学）
机构由 AI 辅助整理，请以论文原文为准。
