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Where to from here?: On the future development of autonomous vehicles from a cognitive systems perspective
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Interaction Lab (ILAB))ORCID iD: 0000-0003-0093-3655
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Interaction Lab (ILAB))ORCID iD: 0000-0002-6568-9342
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Interaction Lab (ILAB))ORCID iD: 0000-0003-3129-4892
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, Netherlands. (Interaction Lab (ILAB))ORCID iD: 0000-0003-1177-4119
2022 (English)In: Cognitive Systems Research, ISSN 2214-4366, E-ISSN 1389-0417, Vol. 76, p. 63-77Article in journal (Refereed) Published
Abstract [en]

Self-driving cars not only solve the problem of navigating safely from location A to location B; they also have to deal with an abundance of (sometimes unpredictable) factors, such as traffic rules, weather conditions, and interactions with humans. Over the last decades, different approaches have been proposed to design intelligent driving systems for self-driving cars that can deal with an uncontrolled environment. Some of them are derived from computationalist paradigms, formulating mathematical models that define the driving agent, while other approaches take inspiration from biological cognition. However, despite the extensive work in the field of self-driving cars, many open questions remain. Here, we discuss the different approaches for implementing driving systems for self-driving cars, as well as the computational paradigms from which they originate. In doing so, we highlight two key messages: First, further progress in the field might depend on adapting new paradigms as opposed to pushing technical innovations in those currently used. Specifically, we discuss how paradigms from cognitive systems research can be a source of inspiration for further development in modeling driving systems, highlighting emergent approaches as a possible starting point. Second, self-driving cars can themselves be considered cognitive systems in a meaningful sense, and are therefore a relevant, yet underutilised resource in the study of cognitive mechanisms. Overall, we argue for a stronger synergy between the fields of cognitive systems and self-driving vehicles.

Place, publisher, year, edition, pages
Elsevier, 2022. Vol. 76, p. 63-77
National Category
Robotics Computer Systems Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Interaction Lab (ILAB)
Identifiers
URN: urn:nbn:se:his:diva-21894DOI: 10.1016/j.cogsys.2022.09.005ISI: 000883846400001Scopus ID: 2-s2.0-85140001741OAI: oai:DiVA.org:his-21894DiVA, id: diva2:1700573
Note

CC BY 4.0

Available online 1 October 2022

Corresponding author: E-mail address: sara.mahmoud@his.se (S. Mahmoud).

Available from: 2022-10-03 Created: 2022-10-03 Last updated: 2023-01-16Bibliographically approved

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Mahmoud, SaraBilling, ErikSvensson, HenrikThill, Serge

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