2026
2025
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X. Dong, et al., "Why autonomous vehicles are not ready yet: A multi‐disciplinary review of problems, attempted solutions, and future directions", Journal of Field Robotics [PAPER]
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A. Cherubini, et al., "Bootstrapped neural models for predicting self-driving vehicle collisions with quantified confidence: Offline and online applications", IEEE Transactions on Intelligent Vehicles [PAPER]
- T. Dorigo, et al., "Artificial intelligence in science and society: The vision of USERN", IEEE Access [PAPER]
2024
2023
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M. Da Lio, et al., "Complex self-driving behaviors emerging from affordance competition in layered control architectures", Cognitive Systems Research [PAPER] [VIDEO]
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A. Cherubini, et al., "Energy costs of safe speed policies in a pedestrian-crossing scenario", 35th IEEE Intelligent Vehicles Symposium (IV) [PAPER]
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A. Plebe and M. Da Lio, "Bio-inspired circular latent spaces to estimate objects' rotations", Frontiers in Computational Neuroscience [PAPER] [CODE]
2022
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M. Da Lio, et al., "The biasing of action selection produces emergent human-robot interactions in autonomous driving", IEEE Robotics and Automation Letters [PAPER] [VIDEO]
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A. Plebe, et al., "Distributed cognition for collaboration between human drivers and self-driving cars", Frontiers in Artificial Intelligence [PAPER]
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S. Mahmoud and A. Plebe, "A critical look into cognitively-inspired artificial intelligence", 8th International Workshop on Artificial Intelligence and Cognition (AIC) [PAPER]
2021
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G. P. Rosati Papini, et al., "A reinforcement learning approach for enacting cautious behaviours in autonomous driving system: Safe speed choice in the interaction with distracted pedestrians", IEEE Transactions on Intelligent Transportation Systems [PAPER] [CODE] [VIDEO]
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A. Plebe, et al., "Occupancy grid mapping with cognitive plausibility for autonomous driving applications", Workshop on Autonomous Vehicle Vision at the IEEE/CVF International Conference on Computer Vision (ICCV) [PAPER] [CODE]
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A. Plebe and M. Da Lio, "Neurocognitive-inspired approach for visual perception in autonomous driving", Smart Cities, Green Technologies and Intelligent Transport Systems [PAPER]
2020
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A. Plebe, et al., "On reliable neural network sensorimotor control in autonomous vehicles", IEEE Transactions on Intelligent Transportation Systems [PAPER]
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A. Plebe and M. Da Lio, "On the road with 16 neurons: Towards interpretable and manipulable latent representations for visual predictions in driving scenarios", IEEE Access [PAPER] [CODE]
2019
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A. Plebe and M. Da Lio, "Visual perception for autonomous driving inspired by convergence–divergence zones", 11th International Symposium on Image and Signal Processing and Analysis (ISPA) [PAPER]
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A. Plebe and M. Da Lio, "Variational autoencoder inspired by brain's convergence-divergence zones for autonomous driving application", 20th International Conference on Image Analysis and Processing (ICIAP) [PAPER]
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A. Plebe, et al., "Mental imagery for intelligent vehicles", 5th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS) [PAPER] [CODE]
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A. Plebe, et al., "Dreaming mechanism for training bio-inspired driving agents", 2nd International Conference on Intelligent Human Systems Integration (IHSI) [PAPER]
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A. Plebe, et al., "Optimizing costs and quality of interior lighting by genetic algorithm", Studies in Computational Intelligence [PAPER]
2018
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A. Plebe and G. Grasso, "Conceptual integrity without concepts", International Journal of Software Engineering and Knowledge Engineering [PAPER]
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M. Da Lio, et al., "Autonomous vehicle architecture inspired by the neurocognition of human driving", 4th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS) [PAPER]
2017
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A. Plebe, et al., "Evolving illumination design following genetic strategies", 9th International Joint Conference on Computational Intelligence (IJCCI) [PAPER]
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A. Plebe and M. Pavone, "Multi-objective genetic algorithm for interior lighting design", 3rd International Workshop on Machine learning, Optimization, and Big Data (MOD) [PAPER]
2016
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A. Plebe and G. Grasso, "Particle physics and polyedra proximity calculation for hazard simulations in large-scale industrial plants", 12th International Conference of Computational Methods in Sciences and Engineering (ICCMSE) [PAPER]