Advanced driver assistance system (ADAS) based on sensor fusion

In many fields, including robotics, autonomous systems, and healthcare, sensor fusion ,the skill of merging data from many sensors to create a more complete and accurate representation of the environment has become an essential technology. This study examines the foundations, uses, and developments of sensor fusion methods. Modern vehicles now come standard with advanced driver assistance systems (ADAS), which considerably enhance driver experience and safety. The integration of various sensors, or sensor fusion, is essential to the efficiency of these systems. This study examines the implementation, advantages, and difficulties of an ADAS system that makes use of sensor fusion. In order to develop a comprehensive picture of the world around the vehicle, the ADAS system presented in this paper integrates a wide variety of sensors, including radar, LiDAR, cameras, ultrasonic sensors, and GPS. The system improves item detection, tracking, and environment perception accuracy by combining the data from these sensors. It can reliably detect diverse traffic conditions, obstructions, and collision hazards and react accordingly. Several safety-critical ADAS functions, like as collision avoidance, lane maintaining, traffic sign recognition, and parking assistance, demonstrate the practical implications of sensor fusion. The study also looks into how sensor fusion might be crucial in allowing autonomous driving and provides a roadmap for integrating ADAS into higher levels of automation.