ArticleHuman factors2024
How Do Drivers Perceive Risks During Automated Driving Scenarios? An fNIRS Neuroimaging Study.
Article in Human factors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Longitudinal changes in frontopolar cortex activity during postural tasks in collegiate ice hockey athletes.Neurophotonics · 2025Article
- A Comprehensive Review of Unobtrusive Biosensing in Intelligent Vehicles: Sensors, Algorithms, and Integration Challenges.Bioengineering (Basel, Switzerland) · 2025Review
- Safety Decision-Making for Autonomous Vehicles Integrating Passenger Physiological States by fNIRS.Cyborg and bionic systems (Washington, D.C.) · 2025Article
- Adopting Stimulus Detection Tasks for Cognitive Workload Assessment: Some Considerations.Human factors · 2024Review
- An fNIRS dataset for driving risk cognition of passengers in highly automated driving scenarios.Scientific data · 2024Article
- From brain to worksite: the role of fNIRS in cognitive studies and worker safety.Frontiers in public health · 2023Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveUsing brain haemodynamic responses to measure perceived risk from traffic complexity during automated driving.
backgroundAlthough well-established during manual driving, the effects of driver risk perception during automated driving remain unknown. The use of fNIRS in this paper for assessing drivers' states posits it could become a novel method for measuring risk perception.
methodsTwenty-three volunteers participated in an empirical driving simulator experiment with automated driving capability. Driving conditions involved suburban and urban scenarios with varying levels of traffic complexity, culminating in an unexpected hazardous event. Perceived risk was measured via fNIRS within the prefrontal cortical haemoglobin oxygenation and from self-reports.
resultsPrefrontal cortical haemoglobin oxygenation levels significantly increased, following self-reported perceived risk and traffic complexity, particularly during the hazardous scenario.
conclusionThis paper has demonstrated that fNIRS is a valuable research tool for measuring variations in perceived risk from traffic complexity during highly automated driving. Even though the responsibility over the driving task is delegated to the automated system and dispositional trust is high, drivers perceive moderate risk when traffic complexity builds up gradually, reflected in a corresponding significant increase in blood oxygenation levels, with both subjective (self-reports) and objective (fNIRS) increasing further during the hazardous scenario. APPLICATION: Little is known regarding the effects of drivers' risk perception with automated driving. Building upon our experimental findings, future work can use fNIRS to investigate the mental processes for risk assessment and the effects of perceived risk on driving behaviours to promote the safe adoption of automated driving technology.
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