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Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research
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Modeling take-over performance in level 3 conditionally automated vehicles.

Christian Gold1, Riender Happee2, Klaus Bengler1

  • 1Chair of Ergonomics, Technical University of Munich, Munich, Germany.

Accident; Analysis and Prevention
|December 3, 2017
PubMed
Summary
This summary is machine-generated.

Drivers face challenges when resuming control of Level 3 automated vehicles. This study models key take-over performance factors like time-to-collision and crash probability, identifying time-budget and traffic density as crucial influences.

Keywords:
Automated drivingDriver performanceHuman factorsModelingRegressionTake-Over

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Area of Science:

  • Human-Computer Interaction
  • Automotive Engineering
  • Traffic Safety

Background:

  • Resuming control of Level 3 conditionally automated vehicles presents significant challenges for drivers.
  • Driver take-over performance is critical for the safe operation of automated vehicle functions and overall traffic safety.

Purpose of the Study:

  • To develop and validate predictive models for key driver take-over performance variables.
  • To investigate the influence of situational and driver-related factors on take-over performance.

Main Methods:

  • Development of regression models using 753 take-over situations from driving simulator experiments.
  • Validation of models with an additional 729 take-over situations from five independent driving simulator studies.

Main Results:

  • Models accurately predicted take-over time, minimum time-to-collision, and crash probability.
  • Brake application was moderately predicted; time-budget, traffic density, and repetition significantly influenced performance.
  • Driver age and non-driving-related tasks had a minor impact on take-over performance.

Conclusions:

  • Predictive models offer valuable insights into driver behavior during automated vehicle take-overs.
  • Situational factors like time-budget and traffic density are primary determinants of take-over performance.
  • Understanding these factors is essential for enhancing the safety and usability of automated driving systems.