Autonomous Aerial Vehicles, Validation, Testing, Modeling and Simulation, Formal Methods
Autonomous aerial vehicles (AAV) have the potential to have market disruptions for various industries such as ground delivery and aerial transportation. Hence, the USAF has called for increased level of autonomy. There has been a significant progress in artificial intelligence engines, complex and non-deterministic system components, which are at the core of the autonomous aerial platforms. Traditional testing and validation methods fall short of satisfying the requirement of testing such complex systems. Therefore, to achieve highly or fully autonomous capabilities, a major leap forward in the validation is required. The key challenges are the localization of problems, development of object models for perception and the creation of a safety measure. A similar challenge exists in ground autonomous vehicles (AVs), where there is a significant investment in recent years. However, there are important differences in the environmental and regulatory conditions between these two domains. In this paper, we present a validation framework that uses modeling and simulation and formal methods for solving the issues in the validation of AAVs. We define a novel abstraction stack using separation of concerns and create a testing plan using techniques such as constrained pseudo-random test generation, random walks and functional assertions. The system aims to assess the creation of an evolving safety measure and a licensing structure.
Scholarly Commons Citation
Akbas, M. I.
Testing and Validation Framework for Autonomous Aerial Vehicles.
Journal of Aviation/Aerospace Education & Research, 30(1).