A Comprehensive Review of Autonomous Vehicle Architecture, Sensor Integration, and Communication Networks: Challenges and Performance Evaluation

Autonomous Vehicles (AVs) are poised to revolutionize transportation by integrating advanced sensor technologies, sophisticated control systems, and robust communication networks. This paper presents a comprehensive review of the current state of AV architectures, covering essential components such as perception, localization, path planning, and control. A detailed analysis of sensor technologies—including LiDAR, radar, cameras, and inertial navigation systems—highlights their individual roles, benefits, and limitations. Furthermore, the paper examines both intra-vehicle and inter-vehicle communication networks (e.g., CAN, LIN, FlexRay, MOST, and Ethernet), offering a quantitative performance evaluation through mathematical models and comparative analysis. Critical challenges, including cybersecurity threats, sensor reliability issues, data processing demands, and regulatory hurdles, are discussed alongside potential future directions. The insights provided aim to guide researchers and industry professionals in advancing AV technology while balancing performance, cost, and safety.