Conflict-Free Four-Dimensional Path Planning for Urban Air Mobility Considering Airspace Occupations
Not on the map. Why?
Abstract (arXiv)
Urban air mobility (UAM) has attracted the attention of aircraft manufacturers, air navigation service providers and governments in recent years. Preventing the conflict among urban aircraft is crucial to UAM traffic safety, which is a key in enabling large scale UAM operation. Pre-flight conflict-free path planning can provide a strategic layer in the maintenance of safety performance, thus becomes an important element in UAM. This paper aims at tackling conflict-free path planning problem for UAM operation with a consideration of four-dimensional airspace management. In the first place, we introduced and extended a four-dimensional airspace management concept, AirMatrix. On the basis of AirMatrix, we formulated the shortest flight time path planning problem considering resolution of conflicts with both static and dynamic obstacles. A Conflict-Free A-Star algorithm was developed for planning four-dimensional paths based on first-come-first-served scheme. The algorithm contains a novel design of heuristic function as well as a conflict detection and resolution strategy. Numerical experiment was carried out in Jurong East area in Singapore, and the results show that the algorithm can generate paths resolving a significant number of potential conflicts in airspace utilization, with acceptable computational time and flight delay. The contributions of this study provide references for stakeholders to support the development of UAM.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 Jul 2021.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 1; 2023: 0; 2024: 0; 2025: 0; 2026: 2.
3 papers.
- 2022Data-Efficient Modeling for Precise Power Consumption Estimation of Quadrotor Operations Using Ensemble Learningcited by 1
- 2026Solution Space Path Planning: A Real-Time Human-Centered Path Planning Algorithm for En-Route Air Traffic Controlcited by 0
- 2026Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learningcited by 0
- 2026Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning13 Jul 2026
- 2026Solution Space Path Planning: A Real-Time Human-Centered Path Planning Algorithm for En-Route Air Traffic Control30 Jun 2026
- 2022Data-Efficient Modeling for Precise Power Consumption Estimation of Quadrotor Operations Using Ensemble Learning23 May 2022