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Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior
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Modelling discomfort: How do drivers feel when cyclists cross their path?

Christian-Nils Boda1, Marco Dozza1, Pablo Puente Guillen2

  • 1Chalmers University of Technology, Hörselgången 4, 417 56, Göteborg, Sweden.

Accident; Analysis and Prevention
|September 18, 2020
PubMed
Summary
This summary is machine-generated.

This study quantifies driver discomfort when cyclists cross their path. Incorporating driver discomfort into active safety systems can improve their acceptance by drivers.

Keywords:
AcceptabilityActive safety systemsComfortDriver behavior modelDriving simulatorTest track

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Area of Science:

  • Road safety
  • Human-computer interaction
  • Automotive engineering

Background:

  • Cyclist fatalities often occur at intersections when crossing vehicle paths.
  • Current active safety systems may lack driver acceptance due to suboptimal driver behavior models.
  • Estimating driver discomfort could enhance the acceptance of active safety systems.

Purpose of the Study:

  • To quantify the level of discomfort experienced by drivers when cyclists cross their path.
  • To investigate the influence of car speed, bicycle speed, and encroachment sequence on driver discomfort.
  • To assess the impact of time-to-arrival at the intersection (TTAvis) on driver discomfort.

Main Methods:

  • Experiments conducted in a fixed-base simulator and on a test track.
  • Controlled variables included car speed (30, 50 km/h), bicycle speed (10, 20 km/h), and encroachment sequence.
  • Driver discomfort was measured using a 7-point Likert scale, analyzed with cumulative link mixed models (CLMM).

Main Results:

  • Car speed, bicycle speed, and encroachment sequence significantly influenced driver discomfort.
  • A shorter time-to-arrival at the intersection (TTAvis) correlated with increased driver discomfort.
  • CLMM models showed moderate prediction accuracy for exact discomfort levels (40-50%) and good accuracy with one-step deviation (80-85%).

Conclusions:

  • A model quantifying driver discomfort was developed.
  • This model can be integrated into active safety systems to improve driver acceptance.
  • Tuning system activation based on predicted driver discomfort can prevent annoyance and enhance safety.