Physiological Effects of Adaptive Cruise Control Behaviour in Real Driving

Brouwer, A.; Snelting, Anne; Jaswa, Matthew; Flascher, Oded; Krol, Laurens R.; Zander, Thorsten O.

doi:10.1145/3038439.3038441

Cited by 10 publications

(10 citation statements)

References 15 publications

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“…At the same time, ongoing methodological developments are resulting in more efficient systems, improved signal-to-noise ratio, and improved signal-processing methods, all of which culminate in rapidly improving the reliability and validity of acquisition across these multiple methodologies. Some attempts to assess cognitive states using multiple methods have been integrated in non-driving domains (ElKomy et al, 2017; Ko et al, 2017; Moghaddam and Lowe, 2019) and multi-method work in real-world driving contexts are already underway (Fu et al, 2016; Brouwer et al, 2017; Zander et al, 2017; Aricò et al, 2018; Belakhdar et al, 2018; Haouij et al, 2018; Paredes et al, 2018; Rastgoo et al, 2018).…”

Section: Research Applicability In Real-world Settingsmentioning

confidence: 99%

“…Extensive work has focused on electrophysiological indicators of under-arousal via EEG. A substantial number of papers have implicated changes in alpha amplitude during fatigued driving (e.g., Schier, 2000 ; Jensen and Mazaheri, 2010 ; Simon et al, 2011 ; Zhao et al, 2012 ; Borghini et al, 2014 ; Jagannath and Balasubramanian, 2014 ; Arnau et al, 2017 ; Brouwer et al, 2017 ), such that fatigued driving is associated with increased alpha activity. However, other work has challenged these alpha power links with fatigue and claim that alpha power changes may be due to the decreases in task-demands and visual input during monotonous driving tasks and not due to decline in cognitive processing abilities (Wascher et al, 2014 ).…”

Section: Psychophysiological Measures To Assess Cognitive Statesmentioning

confidence: 99%

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A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving

Lohani

Payne

Strayer

2019

Front. Hum. Neurosci.

242

181

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As driving functions become increasingly automated, motorists run the risk of becoming cognitively removed from the driving process. Psychophysiological measures may provide added value not captured through behavioral or self-report measures alone. This paper provides a selective review of the psychophysiological measures that can be utilized to assess cognitive states in real-world driving environments. First, the importance of psychophysiological measures within the context of traffic safety is discussed. Next, the most commonly used physiology-based indices of cognitive states are considered as potential candidates relevant for driving research. These include: electroencephalography and event-related potentials, optical imaging, heart rate and heart rate variability, blood pressure, skin conductance, electromyography, thermal imaging, and pupillometry. For each of these measures, an overview is provided, followed by a discussion of the methods for measuring it in a driving context. Drawing from recent empirical driving and psychophysiology research, the relative strengths and limitations of each measure are discussed to highlight each measures' unique value. Challenges and recommendations for valid and reliable quantification from lab to (less predictable) real-world driving settings are considered. Finally, we discuss measures that may be better candidates for a near real-time assessment of motorists' cognitive states that can be utilized in applied settings outside the lab. This review synthesizes the literature on in-vehicle psychophysiological measures to advance the development of effective human-machine driving interfaces and driver support systems.

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Section: Research Applicability In Real-world Settingsmentioning

confidence: 99%

Section: Psychophysiological Measures To Assess Cognitive Statesmentioning

confidence: 99%

A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving

Lohani

Payne

Strayer

2019

Front. Hum. Neurosci.

242

181

View full text Add to dashboard Cite

show abstract

“…Recently, various studies have been recorded in classrooms, cars or realistic tugboat simulators (Blankertz et al, 2010;Brouwer et al, 2017;Ko et al, 2017;Miklody et al, 2017). Mobile BCIs even allow participants to move freely during the recording (Lotte et al, 2009;Castermans et al, 2011;De Vos et al, 2014;Wriessnegger et al, 2017;von Lühmann et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Motor Imagery Under Distraction— An Open Access BCI Dataset

Brandl

Blankertz

2020

Front. Neurosci.

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“…If established parameters like the event-related P300 component can be replicated in real driving scenarios, EEG-data can be used to improve our understanding of how drivers process information while controlling a vehicle in a realistic environment. Providing direct access to the driver's neuronal responses during different driving process phases, EEG might serve the development and evaluation of user centered designs for technical assistance systems in the safety-critical driving environment (e.g., Brouwer et al, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

Investigating Established EEG Parameter During Real-World Driving

Protzak

Gramann

2018

Front. Psychol.

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In real life, behavior is influenced by dynamically changing contextual factors and is rarely limited to simple tasks and binary choices. For a meaningful interpretation of brain dynamics underlying more natural cognitive processing in active humans, ecologically valid test scenarios are essential. To understand whether brain dynamics in restricted artificial lab settings reflect the neural activity in complex natural environments, we systematically tested the auditory event-related P300 in both settings. We developed an integrative approach comprising an initial P300-study in a highly controlled laboratory set-up and a subsequent validation within a realistic driving scenario. Using a simulated dialog with a speech-based input system, increased P300 amplitudes reflected processing of infrequent and incorrect auditory feedback events in both the laboratory setting and the real world setup. Environmental noise and movement-related activity in the car driving scenario led to higher data rejection rates but revealed comparable theta and alpha frequency band pattern. Our results demonstrate the possibility to investigate cognitive functions like context updating in highly artifact prone driving scenarios and encourage the consideration of more realistic task settings in prospective brain imaging approaches.

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Physiological Effects of Adaptive Cruise Control Behaviour in Real Driving

Cited by 10 publications

References 15 publications

A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving

A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving

Motor Imagery Under Distraction— An Open Access BCI Dataset

Investigating Established EEG Parameter During Real-World Driving

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