ARAD: Automated and Real-Time Anomaly Detection in Sensors of Autonomous Vehicles Through a Lightweight Supervised Learning Approach

In this paper, an automated and real-time anomaly detection approach for sensors of autonomous vehicles called ARAD is presented. Automated vehicles gather environmental information through their diverse built-in sensors thus the correctness of this data affects the system’s reliability, dire...

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Bibliographic Details

Main Authors:	Athena Abdi, Arash Ghasemi-Tabar
Format:	Artigo
Language:	Inglês
Published:	IEEE 2024-01-01
Series:	IEEE Access
Subjects:	Anomaly detection autonomous vehicles data-driven learning fault tolerance sensors
Online Access:	https://ieeexplore.ieee.org/document/10574834/
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