AI-based Dynamic Re-routing for Dense Low-Altitude Air Traffic Management
Author:
Affiliation:
1. RMIT University,School of Engineering,Melbourne,Australia
2. Khalifa University,Dept. of Aerospace Eng.,Abu Dhabi,UAE
3. Khalifa University,Abu Dhabi,UAE
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10311099/10311100/10311237.pdf?arnumber=10311237
Reference18 articles.
1. Path planner methods for UAVs in real environment
2. A-star path planning simulation for UAS Traffic Management (UTM) application;neto,2021
3. Hybrid AI-based Dynamic Re-routing Method for Dense Low-Altitude Air Traffic Operations
4. Reinforcement Learning-Based Flow Management Techniques for Urban Air Mobility and Dense Low-Altitude Air Traffic Operations
5. A flexible reference point-based multi-objective evolutionary algorithm: An application to the UAV route planning problem
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1. 6G-enabled Situation-Aware ML-assisted UTM (6G-SAMU);2024 International Wireless Communications and Mobile Computing (IWCMC);2024-05-27
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