Author Type

Graduate Student

Date of Award

Spring 2-24-2026

Document Type

Dissertation

Publication Status

Version of Record

Submission Date

April 2026

Department

Computer and Electrical Engineering and Computer Science

College Granting Degree

College of Engineering and Computer Science

Department Granting Degree

Electrical Engineering and Computer Science

Degree Name

Doctor of Philosophy (PhD)

Thesis/Dissertation Advisor [Chair]

Mihaela Cardei

Abstract

UAS systems have emerged as multifaceted technologies with applications across a wide range of sectors. Their ability to access areas that are difficult or unsafe for manned systems has made them invaluable tools in various domains. As a result, UAS have transformed numerous industries, including infrastructure inspection, delivery and logistics, military and defense, as well as precision agriculture and environmental monitoring.

The advancement in UAS technology is fundamentally reliant upon ongoing research efforts in the specialized area of UAS path planning. Optimal flight planning is essential for a UAV to effectively execute its mission’s task safely, effectively, and in congruence with established laws and regulations at the national, regional and municipality levels. This requirement becomes even more complex due to the dynamic environments in which UAVs often operate. They must be able to adapt to navigate through unexpected conditions or obstacles, such as weather changes, geolocation errors, emerging obstructions, emergency events, and speed limitations. The necessity for real-time adaptation and adjustment is therefore a critical research challenge, demanding that effective path planning be complemented by a dynamic rerouting mechanism. This crucial challenge motivates our proposed approach, which is inspired by established real-time optimization logistics models employed in commercial package delivery and supply chain management.

In this dissertation, we formally define the UAS Path Planning with Dynamic Rerouting problem and propose a novel algorithm for path computation that utilizes a space-time graph to compute collision-free trajectories. We also introduce a dynamic rerouting mechanism that activates when an en-route UAS deviates beyond a predefined threshold. The framework integrates a multi-parameter simulation environment encompassing real-world OSM data from complex urban regions such as Miami and Fort Lauderdale. The computational complexity of our path computation algorithm for n aircrafts is O(n T logT), where T is the maximum path duration, demonstrating the algorithm’s scalability with the number of UAS. Performance evaluations were conducted through simulation experiments using a real-world urban maps of the Miami and Fort Lauderdale areas, showcasing the scalability and efficiency of our approach with up to 14,000 UAVs.

This research begins with outlining the motivation, challenges, and broader impacts of UAS path planning. Subsequently, a thorough review of the overall architecture and frameworks underpinning the interconnected network of UAS, UAV, and UTM are performed. The discussion then proceeds with a critical review and analysis of the existing literature in UAS path planning and dynamic rerouting. We first situate the current research within the broader scholarly context. After establishing the current research within the scholarly context, we discuss the motivation and formalize the problem statement thus establishing the necessary foundation for presenting our contributions and evaluating their performance.

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