Dynamic Safety Intelligence A Self-Adapting Systems Engineering Framework for AI-Driven Automotive Systems

Vasudha Srikumar; Piyush Jain

Dynamic Safety Intelligence A Self-Adapting Systems Engineering Framework for AI-Driven Automotive Systems

Authors: Vasudha Srikumar, Piyush Jain

Unique Paper ID: 167180
Volume: 11
Issue: 3
PageNo: 1780-1786

Keywords: Functional Safety Artificial Intelligence Automotive Systems Dynamic Safety Intelligence Real-Time Adaptability Continuous Learning Human-in-the-Loop Validation Adaptive Sensor Fusion Autonomous Vehicles.

Abstract:
The integration of Artificial Intelligence (AI) in auto-motive systems marks a transformative era, promising enhanced safety, efficiency, and autonomy. As AI as-sumes a pivotal role, ensuring the functional safety of these algorithms becomes a critical concern, particu-larly for autonomous vehicles. This paper addresses the evolving landscape of Functional Safety (FuSa) in AI-driven automotive systems, presenting a novel ap-proach—Dynamic Safety Intelligence (DSI). DSI transcends traditional safety paradigms by introducing real-time adaptability, continuous learning, and a col-laborative interface between AI and human drivers [1]. The foundational challenge lies in the interpretability of complex AI models, the limitations of training datasets, and the dynamic nature of real-world environments. This paper draws inspiration from advancements in formal verification [8], runtime monitoring, and multi-disciplinary collaboration to propose DSI as a pio-neering framework for overcoming these challenges [5]. The DSI framework emphasizes the integration of adaptive sensor fusion, dynamic risk assessment, and human-in-the-loop validation to create a robust safety mechanism [6]. Detailed case studies demonstrate the application and efficacy of DSI in enhancing the safety and reliability of autonomous driving systems [7]. This approach aims to bridge the gap between traditional systems engineering methodologies and the emerging demands of AI integration in automotive safety [2], [3], [4].

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 3
PageNo: 1780-1786

Dynamic Safety Intelligence A Self-Adapting Systems Engineering Framework for AI-Driven Automotive Systems

Available:https://ijirt.org/Article?manuscript=167180

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Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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