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Modelling driver acceptance of driver support systems.

Md Mahmudur Rahman1, Lesley Strawderman1, Mary F Lesch2

  • 1Department of Industrial and Systems Engineering, Mississippi State University, PO Box 9542, Mississippi State, MS 39762, USA.

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|September 25, 2018
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Summary
This summary is machine-generated.

Driver acceptance of new vehicle technologies is key for safety. A new model identifies five factors influencing driver acceptance of driver support systems, explaining 85% of variability.

Keywords:
Advanced driver assistance systemsDriver acceptabilityIntelligent transport technologyVehicle automation

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Area of Science:

  • Transportation Engineering
  • Human-Computer Interaction
  • Automotive Safety

Background:

  • Driver support systems (DSS) aim to improve driver performance and transportation safety.
  • However, these systems alter the traditional driver's role, making driver acceptance crucial for technology adoption.
  • Understanding the factors influencing driver acceptance is vital for effective DSS implementation.

Purpose of the Study:

  • To develop and validate a comprehensive model of driver acceptance for driver support systems.
  • To identify key components influencing user perception and adoption of in-vehicle technologies.
  • To provide a framework for assessing and predicting the success of new automotive safety features.

Main Methods:

  • A literature review was conducted to establish a conceptual model of driver acceptance.
  • An empirical study utilized an online survey to collect data on user perceptions.
  • Participants evaluated fatigue monitoring systems and combined adaptive cruise control/lane-keeping systems.

Main Results:

  • Five key components of driver acceptance were identified: attitude, perceived usefulness, endorsement, compatibility, and affordability.
  • Several mediating effects between these components were confirmed.
  • The developed model successfully explained 85% of the variability in driver acceptance.

Conclusions:

  • The study provides a robust model for understanding the formation of driver acceptance.
  • The model offers insights into factors affecting driver acceptance and their interrelationships.
  • This framework can aid automakers and researchers in DSS design, assessment, and questionnaire development.