Systematic Review: Anomaly Detection in Connected and Autonomous Vehicles

arXiv:2405.02731v1 Announce Type: new
Abstract: This systematic review focuses on anomaly detection for connected and autonomous vehicles. The initial database search identified 2160 articles, of which 203 were included in this review after rigorous screening and assessment. This study revealed that the most commonly used Artificial Intelligence (AI) algorithms employed in anomaly detection are neural networks like LSTM, CNN, and autoencoders, alongside one-class SVM. Most anomaly-based models were trained using real-world operational vehicle data, although anomalies, such as attacks and …

abstract algorithms anomaly anomaly detection articles artificial artificial intelligence arxiv assessment autonomous autonomous vehicles cs.lg database database search detection intelligence review screening search study type vehicles