Parametric Modeling and Evaluation of Departure and Arrival Air Routes for Urban Logistics UAVs
With the rapid development of the low-altitude economy, the intensive take-offs and landings of Unmanned Aerial Vehicles (UAVs) performing logistics transport tasks in urban areas have introduced significant safety risks. To reduce the likelihood of collisions, logistics operators—such as Meituan, A...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/9/7/454 |
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| Summary: | With the rapid development of the low-altitude economy, the intensive take-offs and landings of Unmanned Aerial Vehicles (UAVs) performing logistics transport tasks in urban areas have introduced significant safety risks. To reduce the likelihood of collisions, logistics operators—such as Meituan, Antwork, and Fengyi—have established fixed departure and arrival air routes above vertiports and designed fixed flight air routes between vertiports to guide UAVs to fly along predefined paths. In the complex and constrained low-altitude urban environment, the design of safe and efficient air routes has undoubtedly become a key enabler for successful operations. This research, grounded in both current theoretical research and real-world logistics UAV operations, defines the concept of UAV logistics air routes and presents a comprehensive description of their structure. A parametric model for one-way round-trip logistics air routes is proposed, along with an air route evaluation model and optimization method. Based on this framework, the research identifies four basic configurations that are commonly adopted for one-way round-trip operations. These configurations can be further improved into two optimized configurations with more balanced performance across multiple metrics. Simulation results reveal that Configuration 1 is only suitable for small-scale transport; as the number of delivery tasks increases, delays grow linearly. When the task volume exceeds 100 operations per 30 min, Configurations 2, 3, and 4 reduce average delay by 88.9%, 89.2%, and 93.3%, respectively, compared with Configuration 1. The research also finds that flight speed along segments and the cruise segment capacity have the most significant influence on delays. Properly increasing these two parameters can lead to a 28.4% reduction in the average delay. The two optimized configurations, derived through further refinement, show better trade-offs between average delay and flight time than any of the fundamental configurations. This research not only provides practical guidance for the planning and design of UAV logistics air routes but also lays a methodological foundation for future developments in UAV scheduling and air route network design. |
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| ISSN: | 2504-446X |