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Driver intention recognition: state-of-the-art review
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. Department of Complete Vehicle Data Science, R&D, Volvo Car Corporation, Gothenburg, Sweden. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0003-2135-6615
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0003-2949-4123
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0003-2973-3112
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0001-8884-2154
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2022 (English)In: IEEE Open Journal of Intelligent Transportation Systems, E-ISSN 2687-7813, Vol. 3, p. 602-616Article, review/survey (Refereed) Published
Abstract [en]

Every year worldwide more than one million people die and a further 50 million people are injured in traffic accidents. Therefore, the development of car safety features that actively support the driver in preventing accidents, is of utmost importance to reduce the number of injuries and fatalities. However, to establish this support it is necessary that the advanced driver assistance system (ADAS) understands the driver’s intended behavior in advance. The growing variety of sensors available for vehicles together with improved computer vision techniques, hence led to increased research directed towards inferring the driver’s intentions. This article reviews 64 driver intention recognition studies with regard to the maneuvers considered, the driving features included, the AI methods utilized, the achieved performance within the presented experiments, and the open challenges identified by the respected researchers. The article provides a high level analysis of the current technology readiness level of driver intention recognition technology to address the challenges to enable reliable driver intention recognition, such as the system architecture, implementation, and the purpose of the technology.

Place, publisher, year, edition, pages
IEEE, 2022. Vol. 3, p. 602-616
Keywords [en]
Driver intentions, intention recognition, driver behavior, driving maneuvers
National Category
Computer Systems
Research subject
Skövde Artificial Intelligence Lab (SAIL)
Identifiers
URN: urn:nbn:se:his:diva-21812DOI: 10.1109/ojits.2022.3197296ISI: 000853832800001Scopus ID: 2-s2.0-85147393634OAI: oai:DiVA.org:his-21812DiVA, id: diva2:1695099
Projects
Intention recognition for real-time automotive 3D situation awareness
Funder
Vinnova, 2018-05012
Note

CC BY-NC-ND 4.0

CORRESPONDING AUTHOR: K. VELLENGA (e-mail: koen.vellenga@volvocars.com)

This work was supported by the Intention Recognition in Real Time for Automotive 3D Situation Awareness (IRRA) Project (https://www.vinnova.se/p/intention-recognition-i-realtid-for-automotive-3d-situation-awareness-irra/).

Available from: 2022-09-12 Created: 2022-09-12 Last updated: 2023-02-16Bibliographically approved

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Vellenga, KoenSteinhauer, H. JoeKarlsson, AlexanderFalkman, Göran

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