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Latest advancements and innovations in perception technologies for autonomous vehicles

artificial-intelligence
autonomous-systems
data-mining-and-machine-learning
emerging-technologies
internet-of-things

Abstract

Advanced driving assistance systems (ADAS) are crucial for enhancing automotive safety in modern vehicles. Although these systems are prevalent in commercial vehicles, their functionality remains evolving, with several features currently undergoing research and testing. ADAS relies significantly on onboard sensors that provide critical data regarding the vehicle's status and its surrounding environment. Hence, the selection and arrangement of these sensors are critical in optimizing performance. This study attempts to achieve improved safety via innovative technical developments by reviewing recent research and advancements in ADAS perception technologies. It elucidates the functionalities of these systems and highlights how ongoing improvements can yield smarter, more efficient safety mechanisms for drivers and passengers. Furthermore, we discuss the various technologies employed in ADAS perception tasks, providing a historical perspective on the field's evolution. Ultimately, our study focuses on sensory technologies, addressing the challenges and future directions in advancing ADAS perception capabilities.
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