Published Article

ABSTRACT

This study explored the core technologies powering autonomous vehicle systems, with a focus on how cameras, LiDAR, radar, and ultrasonic sensors work together to achieve 360-degree vision. It highlights how these sensors collectively enable vehicles to perceive their surroundings, detect objects, and make real-time driving decisions with minimal human intervention. Cameras provide detailed visual information for recognizing lanes, signs, and objects; LiDAR delivers precise three-dimensional mapping for accurate spatial awareness; radar ensures reliable detection of distance and speed even in poor weather conditions, while ultrasonic sensors handle short-range tasks such as parking and obstacle avoidance. The study emphasizes that no single sensor is sufficient on its own, making sensor fusion a critical approach for combining their strengths and minimizing limitations. In addition, the integration of artificial intelligence enhances the system’s ability to process large volumes of data, improving accuracy, efficiency, and decision-making in dynamic environments. The study concluded that the effectiveness of autonomous vehicle systems is fundamentally dependent on the integration of core sensing technologies that enable accurate 360-degree environmental perception. The study recommended that governments and industry stakeholders should establish clear standards for sensor performance, data interoperability, and safety validation in autonomous systems.