Projects per year
Abstract
High-tech giants and start-ups are investing in drone technologies to provide urban air delivery service, which is expected to solve the last-mile problem and mitigate road traffic congestion. However, air delivery service will not scale up without proper traffic management for drones in dense urban environment. Currently, a range of Concepts of Operations (ConOps) for unmanned aircraft system traffic management (UTM) are being proposed and evaluated by researchers, operators, and regulators. Among these, the tube-based (or corridor-based) ConOps has emerged in operations in some regions of the world for drone deliveries and is expected to continue serving certain scenarios that with dense and complex airspace and requires centralized control in the future. Towards the tube-based ConOps, we develop a route network planning method to design routes (tubes) in a complex urban environment in this paper. In this method, we propose a priority structure to decouple the network planning problem, which is NP-hard, into single-path planning problems. We also introduce a novel space cost function to enable the design of dense and aligned routes in a network. The proposed method is tested on various scenarios and compared with other state-of-the-art methods. Results show that our method can generate near-optimal route networks with significant computational time-savings.
| Original language | English |
|---|---|
| Article number | 102872 |
| Journal | Transportation Research Part E: Logistics and Transportation Review |
| Volume | 166 |
| Online published | 9 Sept 2022 |
| DOIs | |
| Publication status | Published - Oct 2022 |
Funding
The work was supported by the Hong Kong Research Grants Council (General Research Fund, Project No. 11215119 & 11209717), Antwork Technology (Project No. 9239015), and City University of Hong Kong Strategic Research Grant (Project No. 7005569).
Research Keywords
- Urban air delivery
- Urban air mobility
- Unmanned aircraft system traffic management
- Multi-path planning
Publisher's Copyright Statement
- This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/
RGC Funding Information
- RGC-funded
Fingerprint
Dive into the research topics of 'A route network planning method for urban air delivery'. Together they form a unique fingerprint.Projects
- 2 Finished
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GRF: Data Intelligence & Fuel Efficiency: A Data-Driven Approach to Manage Uncertainties in Flight Fuel Planning for Airlines
LI, L. (Principal Investigator / Project Coordinator) & HE, Q. (Co-Investigator)
1/01/20 → 28/12/23
Project: Research
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GRF: A Data-Driven Framework for Airspace Congestion Analysis Using Aircraft Tracking Data
LI, L. (Principal Investigator / Project Coordinator) & GU, W. (Co-Investigator)
1/09/17 → 25/02/22
Project: Research