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Driver Distraction Detection Using Artificial Intelligence and Smart Devices
RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems.ORCID iD: 0000-0002-5157-8131
Tietoevry, Sweden.
Virtual Vehicle Research GmbH, Austria.
RISE Research Institutes of Sweden, Digital Systems, Prototyping Society.
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2024 (English)In: Intelligent secure tgrustable things, Springer Science and Business Media Deutschland GmbH , 2024, Vol. 1147, p. 285-308Chapter in book (Refereed)
Abstract [en]

Distracted driving is known to be one of the leading causes of vehicle accidents. With the increase in the number of sensors available within vehicles, there exists an abundance of data for monitoring driver behaviour, which, however, has so far only been comparable across vehicle manufacturers to a limited extent due to proprietary solutions. A special role in distraction is played by smart devices, usually used while driving, such as smartphones and smartwatches. They are repeatedly a source of distraction for drivers through calls, messages, notifications and apps usage. However, such devices can also be used for driver behaviour monitoring (like driver distraction detection), as current developments show. As vehicle manufacturer-independent devices, which are usually equipped with adequate sensor technology, they can provide significant advantages and opportunities. This work illustrates the opportunities in using smartphones and wearables to detect driver distraction. The overall architecture description of the concept, called Smart Devices Distracted Driving Detection, is presented together with a series of initial experiments of a proof-of-concept. Artificial Intelligence and more especially Machine Learning is used to assess driving distractions using smart devices in a comprehensive manner. 

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH , 2024. Vol. 1147, p. 285-308
Series
Studies in Computational Intelligence ((SCI,volume 1147))
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:ri:diva-74763DOI: 10.1007/978-3-031-54049-3_16Scopus ID: 2-s2.0-85200456319OAI: oai:DiVA.org:ri-74763DiVA, id: diva2:1890359
Note

All Open Access, Hybrid Gold Open Access

Available from: 2024-08-19 Created: 2024-08-19 Last updated: 2025-09-23Bibliographically approved

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Papatheocharous, Efi

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CiteExportLink to record
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  • apa
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