Conflict-Free Flight Scheduling Using Strategic Demand Capacity Balancing for Urban Air Mobility Operations
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| Format: | Preprint |
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2025
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| author | Hemmati, Vahid Ayalew, Yonas Mohammadi, Ahmad Ahmari, Reza Kebria, Parham Homaifar, Abdollah Saif, Mehrdad |
| author_facet | Hemmati, Vahid Ayalew, Yonas Mohammadi, Ahmad Ahmari, Reza Kebria, Parham Homaifar, Abdollah Saif, Mehrdad |
| contents | In this paper, we propose a conflict-free multi- agent flight scheduling that ensures robust separation in con- strained airspace for Urban Air Mobility (UAM) operations application. First, we introduce Pairwise Conflict Avoidance (PCA) based on delayed departures, leveraging kinematic principles to maintain safe distances. Next, we expand PCA to multi-agent scenarios, formulating an optimization approach that systematically determines departure times under increasing traffic densities. Performance metrics, such as average delay, assess the effectiveness of our solution. Through numerical simulations across diverse multi-agent environments and real- world UAM use cases, our method demonstrates a significant reduction in total delay while ensuring collision-free operations. This approach provides a scalable framework for emerging urban air mobility systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_11854 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Conflict-Free Flight Scheduling Using Strategic Demand Capacity Balancing for Urban Air Mobility Operations Hemmati, Vahid Ayalew, Yonas Mohammadi, Ahmad Ahmari, Reza Kebria, Parham Homaifar, Abdollah Saif, Mehrdad Multiagent Systems Numerical Analysis In this paper, we propose a conflict-free multi- agent flight scheduling that ensures robust separation in con- strained airspace for Urban Air Mobility (UAM) operations application. First, we introduce Pairwise Conflict Avoidance (PCA) based on delayed departures, leveraging kinematic principles to maintain safe distances. Next, we expand PCA to multi-agent scenarios, formulating an optimization approach that systematically determines departure times under increasing traffic densities. Performance metrics, such as average delay, assess the effectiveness of our solution. Through numerical simulations across diverse multi-agent environments and real- world UAM use cases, our method demonstrates a significant reduction in total delay while ensuring collision-free operations. This approach provides a scalable framework for emerging urban air mobility systems. |
| title | Conflict-Free Flight Scheduling Using Strategic Demand Capacity Balancing for Urban Air Mobility Operations |
| topic | Multiagent Systems Numerical Analysis |
| url | https://arxiv.org/abs/2511.11854 |