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An Environmentally Complex Requirement for Safe Separation Distance Between UAVs

Cyber-Physical Systems (CPS) interact closely with their surroundings. They are directly impacted by their physical and operational environment, adjacent systems, user interactions, regulatory codes, and the underlying development process. Both the requirements and design are highly dependent upon a...

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Bibliographic Details
Main Authors: Granadeno, Pedro Antonio Alarcon, Bernal, Arturo Miguel Russell, Al Islam, Md Nafee, Cleland-Huang, Jane
Format: Conference Proceeding
Language:English
Subjects:
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Summary:Cyber-Physical Systems (CPS) interact closely with their surroundings. They are directly impacted by their physical and operational environment, adjacent systems, user interactions, regulatory codes, and the underlying development process. Both the requirements and design are highly dependent upon assumptions made about the surrounding world, and therefore environmental assumptions must be carefully documented, and their correctness validated as part of the iterative requirements and design process. Prior work exploring environmental assumptions has focused on projects adopting formal methods or building safety assurance cases. However, we emphasize the important role of environmental assumptions in a less formal software development process, characterized by natural language requirements, iterative design, and robust testing, where formal methods are either absent or used for only parts of the specification. In this paper, we present a preliminary case study for dynamically computing the safe minimum separation distance between two small Uncrewed Aerial Systems based on drone characteristics and environmental conditions. In contrast to prior community case studies, such as the mine pump problem, patient monitoring system, and train control system, we provide several concrete examples of environmental assumptions, and then show how they are iteratively validated at various stages of the requirements and design process, using a combination of simulations, field-collected data, and runtime monitoring.
ISSN:2770-6834
DOI:10.1109/REW61692.2024.00028