SENSOR FUSION: THE BACKBONE OF MODERN ADAS SYSTEMS
Keywords:
Sensor Fusion, Advanced Driver Assistance Systems, Environmental Perception, Autonomous Vehicles, Real-time ProcessingAbstract
This article presents a comprehensive analysis of sensor fusion technology in Advanced Driver Assistance Systems (ADAS), examining its fundamental principles, technical challenges, architectural considerations, and real-world applications. The article explores how the integration of multiple sensor modalities, including cameras, LiDAR, radar, and ultrasonic sensors, creates a robust environmental perception system for autonomous vehicles. The article investigates the evolution of sensor fusion technologies, addressing critical aspects such as temporal and spatial alignment, noise reduction, and system architecture choices between data-level and decision-level fusion approaches. The article also evaluates the impact of advanced sensor fusion on vehicle safety, emergency response capabilities, and obstacle avoidance while discussing future directions in deep learning-based algorithms, edge computing architectures, and sensor technology advancements.
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