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Area of Science:

  • Road Safety
  • Human-Computer Interaction
  • Transportation Psychology

Background:

  • Mobile phone use while driving is a significant road safety concern.
  • Existing research often imposes uniform distraction levels, limiting understanding of driver self-regulation.
  • The nuances of how drivers manage secondary tasks (mobile phone use) and their impact on driving performance are not fully understood.

Purpose of the Study:

  • To investigate the relationship between self-regulatory secondary task performance and driving behavior.
  • To analyze how drivers manage mobile phone interactions (hands-free vs. visual-manual) when given control over task engagement.
  • To determine the influence of different road conditions on self-regulated distracted driving.

Main Methods:

  • A driving simulator experiment involving 35 young drivers (18-29 years) was conducted using the CARRS-Q advanced driving simulator.
  • Participants experienced three conditions: no phone use, hands-free phone interactions, and visual-manual phone interactions, with self-selected task timing.
  • Driving performance (longitudinal and lateral vehicle control) was analyzed across various road types and modeled using Generalized Estimation Equations (GEE).

Main Results:

  • The degree of engagement in secondary tasks significantly influenced both longitudinal and lateral vehicle control.
  • Drivers engaging in more hands-free interactions tended to select lower driving speeds.
  • Conversely, longer visual-manual interactions were associated with higher driving speeds among self-regulating drivers.
  • Self-regulated distracted drivers reduced speed more on s-curves compared to straight or motorway segments.

Conclusions:

  • Road traffic demands critically influence both secondary task management and overall driving performance.
  • Driver self-regulation of mobile phone use leads to varied driving behaviors depending on interaction type and road complexity.
  • A human-machine system approach is crucial for understanding the interplay between driver, technology, and environment in distracted driving scenarios.