An Insight Review of Autonomous Vehicle Architecture, Sensors, and Challenges

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Abstract

Autonomous Vehicles (AVs) are revolutionizing transportation by integrating advanced sensors, artificial intelligence, and communication networks to enhance safety and efficiency. This review explores the architecture of AVs, focusing on perception, localization, path planning, and control. A detailed analysis of AV sensors, including LiDAR, radar, cameras, and inertial navigation systems, highlights their roles, advantages, and limitations. Additionally, the paper examines in-vehicle and inter-vehicle communication networks, such as CAN, LIN, FlexRay, and Ethernet, which facilitate real-time data exchange. The study also addresses the key challenges AVs face, including cybersecurity threats, data processing, legal policies, and ethical concerns. By synthesizing recent advancements and ongoing challenges, this paper provides a comprehensive understanding of the state of AV technologies and their future prospects.

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