Design and evaluation of AI/ML algorithms for multi-drone air traffic management under dynamic, close-to-reality scenarios

• Grant number: 25/09908-2
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: September 01, 2025
• End date: August 31, 2026
• Field of knowledge: Engineering - Electrical Engineering - Telecommunications
• Principal Investigator: Christian Rodolfo Esteve Rothenberg
• Grantee: Mauricio Javier Rodriguez Cesen
• Supervisor: Fredrik Heintz
• Host Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Institution abroad: Linköping University (LiU), Sweden
• Associated to the scholarship: 24/03016-0 - Real-time route planning algorithm for unmanned aerial vehicles: an approach for beyond 5G smart cities, BP.DR

Abstract

Adopting Unmanned Aerial Vehicles (UAVs) in transportation and logistics has led to a competitive market with challenges in aerial traffic management, navigation safety, regulatory compliance, and energy efficiency. In future smart cities connected by 5G and beyond, multiple UAVs will operate in limited airspace, which requires robust route planning algorithms and real-time air traffic management. However, dynamic real-world environment constraints and energy efficiency in multi-drone route planning remain a challenge. This BEPE proposal aims to extend ongoing work in pre-flight planning by incorporating real-time in-flight replanning capabilities based on AI and ML techniques. The focus is on developing adaptive algorithms capable of handling variable constraints such as temporary no-fly zones, adverse weather, and air congestion. These algorithms will be evaluated in an improved version of our UNetyEmu simulator under realistic urban scenarios. The proposed research will contribute to scalable and intelligent drone traffic coordination, supporting safe and efficient UAV operations in smart urban environments. (AU)