Sensor systems for autonomous vehicles: functionality and reliability challenges in adverse environmental conditions

Abstract

Autonomous vehicles (AVs) have gained significant attention in recent years. AVs rely on a combination of advanced sensing technologies to accurately perceive their environments and make decisions to navigate safely. The integration of sensors into AVs applications across ground, aerial, and underwater environments is a challenging task. This review explores the need and role of the sensors, highlighting their importance in achieving safe, reliable, and full autonomy. It classifies AVs based on working medium (ground/surface, air, and underwater), control strategy and autonomy levels, offering insights into their functional hierarchy. A detailed discussion on different sensors employed in AVs, including cameras, Lidar, radar, ultrasonic sensors, GPS/GNSS, IMU/INS, odometry sensors, and acoustic systems, is presented along with their working principles, advantages, and limitations. Due to the limitations of individual sensors, the concept of fusion techniques is explored, emphasising its advantages in advancing the perception accuracy, redundancy, and robustness. Integrating multiple sensors is associated with several challenges in adverse climatic circumstances, impacting the performance in perception and navigation. With a comprehensive overview of sensing technologies, sensor fusion strategy, integration challenges, potential challenges in cybersecurity and safety, vulnerability in adverse climate conditions, this review aims to serve as a valuable reference for researchers, industry professionals, and engineers involved in the development of AVs.