Literature DB >> 20380918

Monitoring drivers' mental workload in driving simulators using physiological measures.

Karel A Brookhuis1, Dick de Waard.   

Abstract

Many traffic accidents are caused by, or at least related to, inadequate mental workload, when it is either too low (vigilance) or too high (stress). Creating variations in mental workload and accident-prone driving for research purposes is difficult in the real world. In driving simulators the measurement of driver mental workload is relatively easily conducted by means of physiological measures, although good research skills are required and it is time-consuming. The fact that modern driving simulator environments are laboratory-equivalent nowadays allows full control with respect to environmental conditions, scenarios and stimuli, and enables physiological measurement of parameters of mental workload such as heart rate and brain activity. Several examples are presented to illustrate the potential of modern high-standard driving simulator environments regarding the monitoring of drivers' mental workload during task performance. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2010        PMID: 20380918     DOI: 10.1016/j.aap.2009.06.001

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


  14 in total

1.  Dynamics of Driver Distraction: The process of engaging and disengaging.

Authors:  John D Lee
Journal:  Ann Adv Automot Med       Date:  2014

Review 2.  Commonly Used Assessment Method to Evaluate Mental Workload for Multiple Driving Distractions: A Systematic Review.

Authors:  Nurainaa Kabilmiharbi; Nor Kamaliana Khamis; Nor Azila Noh
Journal:  Iran J Public Health       Date:  2022-03       Impact factor: 1.479

Review 3.  Mental workload and driving.

Authors:  Julie Paxion; Edith Galy; Catherine Berthelon
Journal:  Front Psychol       Date:  2014-12-02

4.  Driver's Cognitive Workload and Driving Performance under Traffic Sign Information Exposure in Complex Environments: A Case Study of the Highways in China.

Authors:  Nengchao Lyu; Lian Xie; Chaozhong Wu; Qiang Fu; Chao Deng
Journal:  Int J Environ Res Public Health       Date:  2017-02-17       Impact factor: 3.390

5.  Age-Related Differences in Pro-active Driving Behavior Revealed by EEG Measures.

Authors:  Stephan Getzmann; Stefan Arnau; Melanie Karthaus; Julian Elias Reiser; Edmund Wascher
Journal:  Front Hum Neurosci       Date:  2018-08-07       Impact factor: 3.169

6.  Editorial: Psychophysiological Contributions to Traffic Safety.

Authors:  Guido P H Band; Gianluca Borghini; Karel Brookhuis; Bruce Mehler
Journal:  Front Hum Neurosci       Date:  2019-11-19       Impact factor: 3.169

7.  Classifying visuomotor workload in a driving simulator using subject specific spatial brain patterns.

Authors:  Chris Dijksterhuis; Dick de Waard; Karel A Brookhuis; Ben L J M Mulder; Ritske de Jong
Journal:  Front Neurosci       Date:  2013-08-21       Impact factor: 4.677

8.  Influence of Mental Workload on the Performance of Anesthesiologists during Induction of General Anesthesia: A Patient Simulator Study.

Authors:  Hitoshi Sato; Tetsuya Miyashita; Hiromasa Kawakami; Yusuke Nagamine; Shunsuke Takaki; Takahisa Goto
Journal:  Biomed Res Int       Date:  2016-04-11       Impact factor: 3.411

9.  Measuring Mental Workload With Low-Cost and Wearable Sensors: Insights Into the Accuracy, Obtrusiveness, and Research Usability of Three Instruments.

Authors:  Julia C Lo; Emdzad Sehic; Sebastiaan A Meijer
Journal:  J Cogn Eng Decis Mak       Date:  2017-07-10

10.  Exploring the Participant-Related Determinants of Simulator Sickness in a Physical Motion Car Rollover Simulation as Measured by the Simulator Sickness Questionnaire.

Authors:  Piotr Rzeźniczek; Agnieszka Lipiak; Bartosz Bilski; Ida Laudańska-Krzemińska; Marcin Cybulski; Ewelina Chawłowska
Journal:  Int J Environ Res Public Health       Date:  2020-09-26       Impact factor: 3.390

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