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Connected and automated vehicles (CAVs) are a transformative technology expected to change and improve the safety and efficiency of mobile vehicles. As the main functional components of CAVs, advanced sensing technologies and control algorithms, which gather environmental information, process data, and control vehicle motion, are of great importance. The development of novel sensing technologies for CAVs has become a research hot spot in recent years. Thanks to improved sensing technologies, CAVs can interpret sensory information to detect obstacles, localize their positions, navigate, and interact with vehicles in the surrounding dynamic environment. Further, by leveraging computer vision and other sensing methods, these vehicles can recognize in-cabin human body activities, facial emotions, and mental states.
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