Self-awareness in intelligent vehicles: Feature based dynamic Bayesian models for abnormality detection

no code implementations • 29 Oct 2020 • Divya Thekke Kanapram, Pablo Marin-Plaza, Lucio Marcenaro, David Martin, Arturo de la Escalera, Carlo Regazzoni

In this paper, datasets from real experiments of autonomous vehicles performing various tasks used to learn and test a set of switching DBN models.

Anomaly Detection Autonomous Vehicles +2

Self-awareness in Intelligent Vehicles: Experience Based Abnormality Detection

no code implementations • 28 Oct 2020 • Divya Kanapram, Pablo Marin-Plaza, Lucio Marcenaro, David Martin, Arturo de la Escalera, Carlo Regazzoni

The evolution of Intelligent Transportation System in recent times necessitates the development of self-driving agents: the self-awareness consciousness.

Anomaly Detection Semantic Segmentation

Collective Awareness for Abnormality Detection in Connected Autonomous Vehicles

no code implementations • 28 Oct 2020 • Divya Thekke Kanapram, Fabio Patrone, Pablo Marin-Plaza, Mario Marchese, Eliane L. Bodanese, Lucio Marcenaro, David Martín Gómez, Carlo Regazzoni

A growing neural gas (GNG) algorithm is used to learn the node variables and conditional probabilities linking nodes in the DBN models; a Markov jump particle filter (MJPF) is employed for state estimation and abnormality detection in each agent using learned DBNs as filter parameters.

Anomaly Detection Autonomous Vehicles +1