ArticleHuman factors2024
Multitasking While Driving: Central Bottleneck or Problem State Interference?
Article in Human factors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Divided attention assessment: cross-cultural adaptation and psychometric properties of the Persian version of the Divided Attention Questionnaire (P-DAQ) among male older drivers.BMC psychology · 2026Article
- Parental broad autism phenotype traits and executive function in families of children with autism spectrum disorder.Frontiers in psychiatry · 2026Article
- Texting while driving is a visual problem influenced by phone viewing angle and working distance in young individuals.Heliyon · 2024Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
objectiveThe objective of this work was to investigate if visuospatial attention and working memory load interact at a central control resource or at a task-specific, information processing resource during driving.
backgroundIn previous multitasking driving experiments, interactions between different cognitive concepts (e.g., attention and working memory) have been found. These interactions have been attributed to a central bottleneck or to the so-called problem-state bottleneck, related to working memory usage.
methodWe developed two different cognitive models in the cognitive architecture ACT-R, which implement the central vs. problem-state bottleneck. The models performed a driving task, during which we varied visuospatial attention and working memory load. We evaluated the model by conducting an experiment with human participants and compared the behavioral data to the model's behavior.
resultsThe problem-state-bottleneck model could account for decreased driving performance due to working memory load as well as increased visuospatial attentional demands as compared to the central-bottleneck model, which could not account for effects of increased working memory load.
conclusionThe interaction between working memory and visuospatial attention in our dual tasking experiment can be best characterized by a bottleneck in the working memory. The model results suggest that as working memory load becomes higher, drivers manage to perform fewer control actions, which leads to decreasing driving performance. APPLICATION: Predictions about the effect of different mental loads can be used to quantify the contribution of each subtask allowing for precise assessments of the current overall mental load, which automated driving systems may adapt to.
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