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🔲 EXPLAINABLE AI FOR SAFE AND TRUSTWORTHY AUTONOMOUS DRIVING. REVIEW. THE SOLUTION IS SAFE X.

👉 Artificial Intelligence (AI) has useful applications in the perception and planning tasks in autonomous driving (AD), offering better performance than traditional methods. However, complex AI systems raise safety concerns for AD. To address this, explainable AI (XAI) techniques are suggested.

👉 This text reviews existing literature on XAI for safe AD and analyzes the necessary requirements in three areas: data, model, and agency. It highlights five key contributions of XAI for safe AD

-interpretable design

-interpretable surrogate models

-interpretable monitoring

-auxiliary explanations

-interpretable validation.

and proposes a framework called SafeX for integrating these methods.

Authors: Anton Kuznietsov Balint Gyevnar Cheng Wang Steven Peters
Stefano Albrecht
Institute of Automotive Engineering, Technical University (TU) of Darmstadt
University of Edinburgh, Edinburgh, U.K.
IEEE Transactions on Intelligent Transportation Systems (Volume: 25, Issue: 12, December 2024)

source: Authors/globalnetwork
#AI #autonomousdriving #ADAS #trustworthy #IAE #TUDarmstadt #UniversityofEdinburgh #safex

9 months ago (edited) | [YT] | 0