Abstract
Life-saving advanced driver-assistance systems (ADASs) and autonomous vehicles (AVs) are the fastest growing technology segment in the automotive market. Artificial intelligence (AI) is one of the most critical components in ADAS and AV. Machine learning (ML), deep Learning (DL), simulators, cloud computing, and embedded hardware platforms are entering the equation of ADAS and AV innovation, especially at level four and level five automation, where the classic rule-based ADAS functions reach their limits. This chapter reviews the basic concepts and recent applications of AI in ADAS and AV, including supervised learning, unsupervised learning, reinforcement learning, DL architectures in AVs, mostly used DL algorithms, edge cases and safety, training datasets, simulators, and infrastructures.
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