Dual-task Interference in a Simulated Driving Environment: Serial or Parallel Processing?

Abbaszadeh, Mojtaba; Gholam‐Ali Hossein‐Zadeh; Vaziri-Pashkam, Maryam · 2019 · OpenAlex-citations

DOI: 10.1101/853119

archive: archived pipeline: cataloged verified

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Summary

This study investigates the cognitive mechanisms underlying dual-task interference in a simulated driving environment, specifically addressing whether concurrent tasks are processed serially or in parallel. While previous research has established that performing secondary tasks while driving increases reaction times and reduces performance, the theoretical debate remains between the "bottleneck theory," which posits serial processing of decision stages, and the "central capacity sharing theory," which suggests parallel processing with shared resources. The authors aimed to extend these findings from artificial laboratory settings to a more naturalistic driving context and to determine how task order predictability influences these processes. The experiment involved twenty healthy adults performing a lane-change driving task and an image discrimination task (identifying faces versus scenes) on a desktop computer. The researchers systematically varied the Stimulus Onset Asynchrony (SOA)—the time difference between the onset of the two tasks—across eight intervals. The study included both predictable and unpredictable task order conditions, as well as single-task baseline conditions. Reaction times and accuracy were measured, and the data were analyzed using repeated-measures ANOVA. Crucially, the authors employed drift-diffusion modeling (DDM) to decompose reaction times into evidence accumulation rates (drift rate) and non-decision times, allowing for a precise test of serial versus parallel processing hypotheses. The results demonstrated significant dual-task interference, with reaction times in dual-task conditions exceeding those in single-task conditions. SOA significantly influenced reaction times for the second-presented task in both conditions and for the image task when presented first. Notably, when the image task was presented first, shorter SOAs led to faster reaction times, suggesting participants accelerated their response to minimize interference with the subsequent driving task. In the unpredictable condition, participants adjusted their response order based on task difficulty rather than presentation order, indicating the involvement of higher-order control mechanisms. The drift-diffusion modeling revealed that dual-task performance affected both the rate of evidence accumulation and the non-decision delays. This pattern contradicts the strict bottleneck model, which predicts constant drift rates with increased delays, and instead supports a partial-parallel processing model where resources are shared between tasks. These findings provide evidence that dual-task interference in naturalistic settings involves partial-parallel processing rather than strict serial bottlenecks. The study highlights that unpredictability in task order allows for strategic optimization of response sequences, reducing total reaction time. By validating capacity-sharing mechanisms in a driving simulation, the research deepens the understanding of cognitive limitations during complex, real-world tasks and offers implications for designing interventions to improve driving safety and reduce accidents caused by divided attention.

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Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• dual task performance
• dual task multitasking
• temporal
• auditory
• visual manual
• mental demand

Information type

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• Empirical Findings: behavioral performance data
• Theoretical Contribution: theory or model, computational model