The increasing demand for Urban Air Mobility (UAM) has introduced a new layer of complexity in managing airspace, particularly in densely populated metropolitan areas. As the number of air vehicles, including drones, air taxis, and helicopters, continues to grow, the risk of mid-air collisions and conflicts with other air traffic and obstacles increases. Strategic deconfliction is critical to ensuring safe and efficient UAM operations. This paper proposes an Answer Set Programming (ASP) solution to real-world strategic deconfliction problem in UAM with respect to time synchronization and optimization of the flight route so that all flights are in deconfliction. The ASP solution is compared with a Constraint Programming (CP) approach, investigating the efficiency of both approaches through scalability tests and comparing the respective time and memory requirements. The results show that ASP generally offers faster execution and better scalability for small to medium-sized problems, while CP exhibits a more consistent memory usage but struggles significantly with the execution time as the problem complexity increases.
Sterlicchio et al. (2026) studied this question.