Autonomous vehicles promise to revolutionize society and improve the daily life of many, making them a coveted aim for a vast research community. To enable complex reasoning in autonomous vehicles, researchers are exploring new methods beyond traditional engineering approaches, in particular the idea of drawing inspiration from the only existing being able to drive: the human. The mental processes behind the human ability to drive can inspire new approaches with the potential to bridge the gap between artificial drivers and human drivers. In this review, we categorize and evaluate existing work on autonomous driving influenced by cognitive science, neuroscience, and psychology. We propose a taxonomy of the various sources of inspiration and identify the potential advantages with respect to traditional approaches. Although these human-inspired methods have not yet reached widespread adoption, we believe they are critical to the future of fully autonomous vehicles.

Human-inspired autonomous driving: A survey / Plebe, Alice; Svensson, Henrik; Mahmoud, Sara; Da Lio, Mauro. - In: COGNITIVE SYSTEMS RESEARCH. - ISSN 1389-0417. - ELETTRONICO. - 83:(2024), p. 101169. [10.1016/j.cogsys.2023.101169]

Human-inspired autonomous driving: A survey

Plebe, Alice
Primo
;
Da Lio, Mauro
Ultimo
2024-01-01

Abstract

Autonomous vehicles promise to revolutionize society and improve the daily life of many, making them a coveted aim for a vast research community. To enable complex reasoning in autonomous vehicles, researchers are exploring new methods beyond traditional engineering approaches, in particular the idea of drawing inspiration from the only existing being able to drive: the human. The mental processes behind the human ability to drive can inspire new approaches with the potential to bridge the gap between artificial drivers and human drivers. In this review, we categorize and evaluate existing work on autonomous driving influenced by cognitive science, neuroscience, and psychology. We propose a taxonomy of the various sources of inspiration and identify the potential advantages with respect to traditional approaches. Although these human-inspired methods have not yet reached widespread adoption, we believe they are critical to the future of fully autonomous vehicles.
2024
Plebe, Alice; Svensson, Henrik; Mahmoud, Sara; Da Lio, Mauro
Human-inspired autonomous driving: A survey / Plebe, Alice; Svensson, Henrik; Mahmoud, Sara; Da Lio, Mauro. - In: COGNITIVE SYSTEMS RESEARCH. - ISSN 1389-0417. - ELETTRONICO. - 83:(2024), p. 101169. [10.1016/j.cogsys.2023.101169]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/399018
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