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Applications of brain imaging methods in driving behaviour research
Milad Haghani1, Michiel C J Bliemer2, Bilal Farooq3
1Institute of Transport and Logistics Studies, The University of Sydney Business School, The University of Sydney, NSW, Australia; Centre for Spatial Data Infrastructure and Land Administration (CSDILA), School of Electrical, Mechanical and Infrastructure Engineering, The University of Melbourne, Australia.
Neuroimaging methods like EEG and fMRI offer insights into driver cognition, aiding research in fatigue detection and distracted driving. While fMRI is invasive, EEG and fNIRS show promise for real-world driving studies.
Area of Science:
- Neuroscience
- Cognitive Science
- Human Factors Engineering
Background:
- Neuroimaging methods provide critical insights into the neuro-cognitive processes underlying human driving behavior.
- Understanding driver brain activity is essential for enhancing road safety and developing advanced driver assistance systems.
Purpose of the Study:
- To comprehensively review the application of neuroimaging techniques in driving behavior research.
- To identify key themes, methodologies, and findings within this research domain.
- To explore future research directions and practical considerations for neuroimaging in driving studies.
Main Methods:
- Bibliometric analysis of neuroimaging driving studies.
- Systematic review and synthesis of findings across different neuroimaging methods.
- Analysis of macro-scale (bibliometric) and micro-scale (thematic) aspects of the literature.
Main Results:
- Functional Magnetic Resonance Imaging (fMRI) and Electroencephalography (EEG) are the most common methods, with fMRI used for studying intoxication and distraction, and EEG for fatigue detection.
- Functional Near-Infrared Spectroscopy (fNIRS) and Magnetoencephalography (MEG) have also been applied, with EEG and fNIRS showing greater practical applicability in field studies.
- Research on driver brain activity in semi-automated settings and in individuals with neurological conditions is limited.
Conclusions:
- Neuroimaging offers valuable tools for understanding driver cognition, with EEG and fNIRS demonstrating particular potential for practical application in real-world driving scenarios.
- Future research should explore under-investigated areas such as semi-automated driving and special populations.
- The review highlights the advantages and limitations of various neuroimaging techniques, guiding future research design in driving behavior studies.
