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Timo Tokkonen

dblp:35/6817 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Ubiquitous computing and smart environments · 56% Usability and user experience research · 44%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Usability and user experience research › safety-critical interaction
driver distraction
0.812024
Effects of context-sensitive distraction warnings on drivers' smartphone use and acceptance: A long-term naturalistic field study · Int. J. Hum. Comput. Stud. 2024
Ubiquitous computing and smart environments › urban computing
intelligent transportation
0.812024
Effects of context-sensitive distraction warnings on drivers' smartphone use and acceptance: A long-term naturalistic field study · Int. J. Hum. Comput. Stud. 2024
Ubiquitous computing and smart environments › mobile computing
smartphone use
0.212024
Effects of context-sensitive distraction warnings on drivers' smartphone use and acceptance: A long-term naturalistic field study · Int. J. Hum. Comput. Stud. 2024

Methods — techniques the papers use, named apart from their topics

naturalistic field study · 0.8
YearPublicationVenuePosition
2024 Effects of context-sensitive distraction warnings on drivers' smartphone use and acceptance: A long-term naturalistic field study
abstract
Driver distraction by smartphone use is a major contributor in traffic accidents. Context-sensitive driver (in)attention monitoring and warning systems might mitigate the associated risks. However, few naturalistic studies are yet available on the effects of such systems. In this paper, utility of context-sensitivity in inattention monitoring was studied by a smartphone-based context-sensitive distraction warning system. The warnings were based on driver's phone use and the attentional demands of the upcoming traffic environment. The system's effects on 26 heavy smartphone users’ phone usage and acceptance were analyzed after a within-subject naturalistic study with 12 weeks of control (warnings off) and 12 weeks of interventions (warnings on). The system decreased odds that the drivers would touch their smartphones in reminder areas that were defined a priori as high demanding for attention. Against expectations, the system had no effect in urban road environments. The drivers reported that they had paid more attention to traffic because of the system and that the warnings were acceptable and useful, even if annoying. Similar systems’ safety effects should be further studied. No eye-tracking or driving performance measures were collected and thereby it is questionable if there was a true positive effect on participants’ attention. However, the findings suggest that (in)attention warning systems might benefit from adaptation of the warnings to the upcoming driving demands. The findings can be utilized for the development of proactive and context-sensitive (in)attention monitoring and distraction mitigation systems.
Tuomo Kujala, Hilkka Grahn, Jakke Mäkelä, Johanna M. Silvennoinen, Timo Tokkonen
Int. J. Hum. Comput. Stud.5