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Open AccessArticle
Modeling Autonomous Vehicle Responses to Novel Observations Using Hierarchical Cognitive Representations Inspired Active Inference †
1
Department of Electrical, Electronic, Telecommunications Engineering and Naval Architecture, University of Genoa, 16126 Genoa, Italy
2
Department of Systems Engineering and Automation, University Carlos III of Madrid, 28903 Madrid, Spain
*
Author to whom correspondence should be addressed.
†
This paper is an extended version of our paper published in the 6th International Conference on System-Integrated Intelligence (SysInt 2022), 7–9 September 2022, Genova, Italy.
Computers 2024, 13(7), 161; https://doi.org/10.3390/computers13070161 (registering DOI)
Submission received: 24 November 2023
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Revised: 29 January 2024
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Accepted: 9 February 2024
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Published: 28 June 2024
Abstract
Equip** autonomous agents for dynamic interaction and navigation is a significant challenge in intelligent transportation systems. This study aims to address this by implementing a brain-inspired model for decision making in autonomous vehicles. We employ active inference, a Bayesian approach that models decision-making processes similar to the human brain, focusing on the agent’s preferences and the principle of free energy. This approach is combined with imitation learning to enhance the vehicle’s ability to adapt to new observations and make human-like decisions. The research involved develo** a multi-modal self-awareness architecture for autonomous driving systems and testing this model in driving scenarios, including abnormal observations. The results demonstrated the model’s effectiveness in enabling the vehicle to make safe decisions, particularly in unobserved or dynamic environments. The study concludes that the integration of active inference with imitation learning significantly improves the performance of autonomous vehicles, offering a promising direction for future developments in intelligent transportation systems.
Share and Cite
MDPI and ACS Style
Nozari, S.; Krayani, A.; Marin, P.; Marcenaro, L.; Gomez, D.M.; Regazzoni, C.
Modeling Autonomous Vehicle Responses to Novel Observations Using Hierarchical Cognitive Representations Inspired Active Inference. Computers 2024, 13, 161.
https://doi.org/10.3390/computers13070161
AMA Style
Nozari S, Krayani A, Marin P, Marcenaro L, Gomez DM, Regazzoni C.
Modeling Autonomous Vehicle Responses to Novel Observations Using Hierarchical Cognitive Representations Inspired Active Inference. Computers. 2024; 13(7):161.
https://doi.org/10.3390/computers13070161
Chicago/Turabian Style
Nozari, Sheida, Ali Krayani, Pablo Marin, Lucio Marcenaro, David Martin Gomez, and Carlo Regazzoni.
2024. "Modeling Autonomous Vehicle Responses to Novel Observations Using Hierarchical Cognitive Representations Inspired Active Inference" Computers 13, no. 7: 161.
https://doi.org/10.3390/computers13070161
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