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Dr. D. Deepa is an Assistant Professor in the Department of Computer Science and Engineering at Sathyabama Institute of Science and Technology, Chennai, India. Her academic background is in computer science and engineering. Her contribution focuses on deep learning applications in autonomous vehicles and road safety.
Self-driving vehicles are revolutionising contemporary transit through the incorporation of artificial intelligence, sophisticated sensing technology, and astute decision-making frameworks. Deep learning has become a pivotal technique for allowing autonomous vehicles to sense their environment, identify road participants, analyse traffic situations, foresee possible dangers, and execute secure driving choices. This section explores the core tenets of deep learning in the context of self-driving vehicles, the amalgamation of perceptual and decision-making frameworks, and the use of advanced models for enhancing road safety. It also examines databases, assessment metrics, simulation frameworks, safety verification, ethical implications, and nascent research trajectories. The section presents an extensive framework that integrates multimodal sensor fusion, deep learning-driven risk assessment, and safety-conscious decision-making to enhance the dependability of autonomous vehicles. The discourse emphasises the significance of comprehensive model creation, methodical validation, and human-centric safety protocols for achieving safer and more intelligent transportation systems.