Exploring Relationship Between Driver’s Behavior and Cognitive Measures Observed by fNIRS in a Driving Simulator

İzzetoğlu, Meltem; Park, Sehhoon

doi:10.1007/978-3-030-78114-9_18

Cited by 2 publications

(3 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is important to overcome its functional deficiencies using the brain-computer interface technology by studying the relationship between passengers' mental activity and driving scenario risk and implementing the cognition of the most advanced senor-human being into safe driving. The characteristics of functional near-infrared spectroscopy (fNIRS) technology, such as non-invasiveness, safety, and lowcost characteristics, make fNIRS own potential as an ideal candidate for monitoring the brain activity [4][5][6][7][8][9][10][11][12] . Some researches have been done for looking into the mental activity of drivers on driving simulators or highways for different driving tasks [13][14][15][16][17][18][19] .…”

Section: Driving Risk Cognition Of Passengers In Highly Automated Dri...mentioning

confidence: 99%

“…The relationship between cortical activity and the levels of smartphone distraction was explored 14 , and it has found that the prefrontal cortical activities of drivers are sensitive to mental workload changes and the levels of smartphone distraction. The cognitive processes related to driving were explored, and it was noted that additional neural resources are needed in the prefrontal cortex during high-speed driving conditions compared to the lower-speed cases during dual task driving 8 . A study on the relationship between the prefrontal cortex activation and the changes in mental workload during simulated driving showed that the increases in the subjective ratings of mental workload are associated with increases in the concentration of oxygenated hemoglobin in the prefrontal cortex 19 .…”

Section: Driving Risk Cognition Of Passengers In Highly Automated Dri...mentioning

confidence: 99%

“…A study on the relationship between the prefrontal cortex activation and the changes in mental workload during simulated driving showed that the increases in the subjective ratings of mental workload are associated with increases in the concentration of oxygenated hemoglobin in the prefrontal cortex 19 . As stated above, the prefrontal cortices are related to driving tasks and mental workload, thus prefrontal cortices are the regions of interest for our study 8,14,19,20 . Gauvain Huve 21 presented a brain-computer interface system, and this system may analyze the brain activity of a user in real time and deduce the current driving mode of the car.…”

Section: Driving Risk Cognition Of Passengers In Highly Automated Dri...mentioning

confidence: 99%

See 2 more Smart Citations

Driving risk cognition of passengers in highly automated driving based on the prefrontal cortex activity via fNIRS

Wang,

Zhang,

et al. 2023

Sci Rep

View full text Add to dashboard Cite

For high-level automated vehicles, the human being acts as the passenger instead of the driver and does not need to operate vehicles, it makes the brain–computer interface system of high-level automated vehicles depend on the brain state of passengers rather than that of drivers. Particularly when confronting challenging driving situations, how to implement the mental states of passengers into safe driving is a vital choice in the future. Quantifying the cognition of the driving risk of the passenger is a basic step in achieving this goal. In this paper, the passengers’ mental activities in low-risk episode and high-risk episode were compared, the influences on passengers’ mental activities caused by driving scenario risk was first explored via fNIRS. The results showed that the mental activities of passengers caused by driving scenario risk in the Brodmann area 10 are very active, which was verified by examining the real-driving data collected in corresponding challenging experiments, and there is a positive correlation between the cerebral oxygen and the driving risk field. This initial finding provides a possible solution to design a human-centred intelligent system to promise safe driving for high-level automated vehicles using passengers’ driving risk cognition.

show abstract

Section: Driving Risk Cognition Of Passengers In Highly Automated Dri...mentioning

confidence: 99%

Section: Driving Risk Cognition Of Passengers In Highly Automated Dri...mentioning

confidence: 99%

Section: Driving Risk Cognition Of Passengers In Highly Automated Dri...mentioning

confidence: 99%

See 1 more Smart Citation

Driving risk cognition of passengers in highly automated driving based on the prefrontal cortex activity via fNIRS

Wang,

Zhang,

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

Prefrontal Correlates of Passengers’ Mental Activity Based on fNIRS for High-Level Automated Vehicles

Zhang,

Li,

et al. 2024

Automot. Innov.

View full text Add to dashboard Cite

With the spread adoption of artificial intelligence, the great challenges confronted by the intelligent safety concern-safety of the intended functionality has become the biggest roadblock to the mass production of high-level automated vehicles, notably arising from perception algorithm deficiencies. This paper focuses a cut-in scenario, dividing this scenario into low-risk and high-risk segments predicated on the kinetic energy field, and the mental activities of passengers on prefrontal cortex, are analyzed within these delineated segments. Two experiments are then conducted, leveraging driving simulators and real-world vehicles, respectively. Experiment results indicate that high risk may result in the passengers’ mental activity on prefrontal cortex change. This revelation posits a potential avenue for augmenting the intended functionality of automated vehicle by using passengers’ physiological state.

show abstract

Exploring Relationship Between Driver’s Behavior and Cognitive Measures Observed by fNIRS in a Driving Simulator

Cited by 2 publications

References 22 publications

Driving risk cognition of passengers in highly automated driving based on the prefrontal cortex activity via fNIRS

Driving risk cognition of passengers in highly automated driving based on the prefrontal cortex activity via fNIRS

Prefrontal Correlates of Passengers’ Mental Activity Based on fNIRS for High-Level Automated Vehicles

Contact Info

Product

Resources

About