Literature DB >> 30245477

Modelling driver acceptance of driver support systems.

Md Mahmudur Rahman1, Lesley Strawderman2, Mary F Lesch3, William J Horrey4, Kari Babski-Reeves2, Teena Garrison5.   

Abstract

Driver support systems are intended to enhance driver performance and improve transportation safety. Even though these systems afford safety advantages, they challenge the traditional role of drivers in operating vehicles. Driver acceptance, therefore, is essential for the adoption of new in-vehicle technologies into the transportation system. In this study, a model of driver acceptance of driver support systems was developed. A conceptual driver acceptance model, including several components, was proposed based on a review of current literature. An empirical study was subsequently carried out using an online survey approach. The study collected data on participants' perceptions of two driver support systems (a fatigue monitoring system and an adaptive cruise control system combined with a lane-keeping system) in terms of attitude, perceived usefulness, and other components of driver acceptance. Results identified five components of driver acceptance (attitude, perceived usefulness, endorsement, compatibility, and affordability). The results also confirmed several mediating effects. The developed model was able to explain 85% of the variability in driver acceptance. The model provides an improved understanding how driver acceptance is formed, including which factors affect driver acceptance and how they affect it. The model can also help automakers and researchers to assess the design and estimate the potential use of a driver support system. The model could also be highly beneficial in developing a questionnaire to assess driver acceptance.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Advanced driver assistance systems; Driver acceptability; Intelligent transport technology; Vehicle automation

Mesh:

Year:  2018        PMID: 30245477     DOI: 10.1016/j.aap.2018.08.028

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  4 in total

1.  Preferred Sources of Information, Knowledge, and Acceptance of Automated Vehicle Systems: Effects of Gender and Age.

Authors:  Pamela M Greenwood; Carryl L Baldwin
Journal:  Front Psychol       Date:  2022-05-23

2.  Autonomous delivery vehicles to fight the spread of Covid-19 - How do men and women differ in their acceptance?

Authors:  Sebastian Kapser; Mahmoud Abdelrahman; Tobias Bernecker
Journal:  Transp Res Part A Policy Pract       Date:  2021-03-24       Impact factor: 5.594

3.  The Predictive Factors of New Technology Adoption, Workers' Well-Being and Absenteeism: The Case of a Public Maritime Company in Venice.

Authors:  Chiara Panari; Giorgio Lorenzi; Marco Giovanni Mariani
Journal:  Int J Environ Res Public Health       Date:  2021-11-24       Impact factor: 3.390

4.  Driving Performance and Technology Acceptance Evaluation in Real Traffic of a Smartphone-Based Driver Assistance System.

Authors:  Gheorghe-Daniel Voinea; Cristian Cezar Postelnicu; Mihai Duguleana; Gheorghe-Leonte Mogan; Radu Socianu
Journal:  Int J Environ Res Public Health       Date:  2020-09-28       Impact factor: 3.390

  4 in total

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