2021
DOI: 10.48550/arxiv.2112.14710
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Parallelized and Randomized Adversarial Imitation Learning for Safety-Critical Self-Driving Vehicles

Abstract: Self-driving cars and autonomous driving research has been receiving considerable attention as major promising prospects in modern artificial intelligence applications. According to the evolution of advanced driver assistance system (ADAS), the design of self-driving vehicle and autonomous driving systems becomes complicated and safety-critical. In general, the intelligent system simultaneously and efficiently activates ADAS functions. Therefore, it is essential to consider reliable ADAS function coordination … Show more

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