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• W2904039327 abstract "For the last few decades, a lot of attention has been given to intelligent vehicle systems, and in particular to automated safety and collision avoidance solutions. In this paper, we present a literature review and analysis of threat-assessment methods used for collision avoidance. We will cover algorithms that are based on single-behavior threat metrics, optimization methods, formal methods, probabilistic frameworks, and data driven approaches, i.e., machine learning. The different theoretical algorithms are finally discussed in terms of computational complexity, robustness, and most suited applications." @default.
• W2904039327 created "2018-12-22" @default.
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• W2904039327 date "2019-03-01" @default.
• W2904039327 modified "2023-10-05" @default.
• W2904039327 title "Collision Avoidance: A Literature Review on Threat-Assessment Techniques" @default.
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• W2904039327 doi "https://doi.org/10.1109/tiv.2018.2886682" @default.
• W2904039327 hasPublicationYear "2019" @default.
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