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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.
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Monitoring CPS at Runtime - A Case Study in the UAV Domain
Unmanned aerial vehicles (UAVs) are becoming increasingly pervasive in everyday life, supporting diverse use cases such as aerial photography, delivery of goods, or disaster reconnaissance and management. UAVs are cyber-physical systems (CPS): they integrate computation (embedded software and control systems) with physical components (the UAVs flying in the physical world). UAVs in particular and CPS in general require monitoring capabilities to detect and possibly mitigate erroneous and safety-critical behavior at runtime. Existing monitoring approaches mostly do not adequately address UAV CPS characteristics such as the high number of dynamically instantiated components, the tight integration of elements, and the massive amounts of data that need to be processed. In this paper we report results of a case study on monitoring in UAVs. We discuss CPS-specific monitoring challenges and present a prototype we implemented by extending REMINDS, a framework for software monitoring so far mainly used in the domain of metallurgical plants. Additionally, we demonstrate the applicability and scalability of our approach by monitoring a real control and management system for UAVs in simulations with up to 30 drones flying in an urban area.
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- Award ID(s):
- 1741781
- PAR ID:
- 10097963
- Date Published:
- Journal Name:
- Euromicro Conference on Software Engineering and Advanced Applications
- Volume:
- 2018
- Page Range / eLocation ID:
- 73 to 80
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/SEAA.2018.00022
