# Declarative Problem Solving in UAM Strategic Deconfliction

arXiv: https://arxiv.org/abs/2607.21197 · HTML: https://mlsanity.com/paper/2607.21197/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 29 references that are in the map.
- First posted on arXiv 23 Jul 2026.

## Builds on (most cited first, 8 of 8)

- [Multi-shot ASP solving with clingo](https://mlsanity.com/paper/1705.09811/) (2017)
- [Clingo = ASP + Control: Preliminary Report](https://mlsanity.com/paper/1405.3694/) (2014)
- [Clingo goes Linear Constraints over Reals and Integers](https://mlsanity.com/paper/1707.04053/) (2017)
- [An ASP-based Solution to the Chemotherapy Treatment Scheduling problem](https://mlsanity.com/paper/2108.02637/) (2021)
- [Train Scheduling with Hybrid Answer Set Programming](https://mlsanity.com/paper/2003.08598/) (2020)
- [Integrated Conflict Management for UAM with Strategic Demand Capacity Balancing and Learning-based Tactical Deconfliction](https://mlsanity.com/paper/2305.10556/) (2023)
- [Can Urban Air Mobility become reality? Opportunities, challenges and selected research results](https://mlsanity.com/paper/2309.12680/) (2023)
- [A Framework for Operational Volume Generation for Urban Air Mobility Strategic Deconfliction](https://mlsanity.com/paper/2301.12961/) (2023)

## Abstract (arXiv)

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.