Abstract
Autonomous vehicles rely heavily on intelligent algorithms for path planning and collision avoidance, and their functionality and dependability can be ensured through formal verification. To facilitate the verification, it is beneficial to decouple the static high-level planning from the dynamic functions like collision avoidance. In this paper, we propose a conceptual two-layer framework for verifying autonomous vehicles, which consists of a static layer and a dynamic layer. We focus concretely on modeling and verifying the dynamic layer using hybrid automata and
, where a continuous movement of the vehicle as well as collision avoidance via a dipole flow field algorithm are considered. In our framework, decoupling is achieved by separating the verification of the vehicle’s autonomous path planning from that of the vehicle autonomous operation in its continuous dynamic environment. To simplify the modeling process, we propose a pattern-based design method, where patterns are expressed as hybrid automata. We demonstrate the applicability of the dynamic layer of our framework on an industrial prototype of an autonomous wheel loader.
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Acknowledgement
The research leading to the presented results has been performed within the research profile DPAC - Dependable Platform for Autonomous Systems and Control project, funded by grant 20150022 of the Swedish Knowledge Foundation that is gratefully acknowledged.
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Gu, R., Marinescu, R., Seceleanu, C., Lundqvist, K. (2019). Towards a Two-Layer Framework for Verifying Autonomous Vehicles. In: Badger, J., Rozier, K. (eds) NASA Formal Methods. NFM 2019. Lecture Notes in Computer Science(), vol 11460. Springer, Cham. https://doi.org/10.1007/978-3-030-20652-9_12
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