Feedforward Mutual-Information Anomaly Detection: Application to Autonomous Vehicles
Sasha M. McKee,
Osama S. Haddadin,
Kam K. Leang
Abstract:This paper describes a mutual-information-based approach that exploits a dynamics model to quantify and detect anomalies for applications such as autonomous vehicles. First, mutual information (MI) is utilized to quantify the level of uncertainty associated with the behaviors of the vehicle. The MI approach handles novel anomalies without the need for data-intensive training; and the metric readily applies to multivariate datasets for improved robustness, compared to for example, measures such as vehicle track… Show more
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