Abstract
Autonomous vehicles operate in dynamic environments continuously encountering safety-critical scenarios. This necessitates employing methodologies that can handle these scenarios and ensure safety of the vehicle as well as other traffic participants. Besides, random failures or malfunctions in its components might result in hazardous situation(s), further raising concerns regarding safety. The intensity of these hazards caused by the malfunctions depends upon the current state of the operational context in which they occur. Thus to guarantee safe behavior of the vehicle, one must be aware of its operational context in the first place. To this end, we propose to systematically model the operational context of an autonomous vehicle apropos its safety-relevant aspects. This paper puts forth our initial work for context-awareness aided safety, including our perspective towards context and its modeling, and its categorization based on relevance and goal. We also propose a context meta-model and its fundamental elements crucial for developing a safety-relevant context model.
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Haupt, N.B., Liggesmeyer, P. (2022). Towards Context-Awareness for Enhanced Safety of Autonomous Vehicles. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2021. Lecture Notes in Networks and Systems, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-82196-8_40
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DOI: https://doi.org/10.1007/978-3-030-82196-8_40
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