Driver Distraction through Conversation Measured with Pupillometry

Dlugosch, Carsten; Conti, Antonia S.; Bengler, Klaus

doi:10.17077/drivingassessment.1488

Cited by 7 publications

(4 citation statements)

References 18 publications

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“…In an early study, Nunnally, Knott, Duchnowski, and Parker (1967) showed that increasingly louder tones were associated with larger pupil sizes (see also Antikainen & Niemi, 1983;Jones, Loeb, & Cohen, 1977), especially for sound levels above 90 dB (Nunnally et al, 1967). Furthermore, Nunnally et al already indicated the strong order effect on the pupil response (see Jones et al, 1977;Nunnally et al, 1967 3 Unpredictable/infrequent events are associated with larger pupil size/PDR Damsma & Van Rijn, 2017;Friedman et al, 1973;Gilzenrat et al, 2010;Hoffing & Seitz, 2015;Knapen et al, 2016;Korn & Bach, 2016;Marois et al, 2018;Preuschoff et al, 2011;Qiyuan et al, 1985 b ;Steiner & Barry, 2011;Steinhauer & Zubin, 1982;Wetzel et Dlugosch et al, 2013;Fletcher et al, 2016 a ;Kahneman & Beatty, 1967;Kramer et al, 2012;Kun et al, 2013;Liao et al, 2016;Palinko et al, 2010;Recarte & Nunes, 2003;Schlemmer et al, 200510 Ambler et al, 1976Einhäuser et al, 2008;Hoeks & Levelt, 1993;Lisi et al, 2015 4 Increased degradation level is associated with larger pupil size/PDR (up till resource overload) Koelewijn et al, 2012aKoelewijn et al, , 2012bKoelewijn et al, , 2014aKoelewijn et al, , 2014bKoelewijn et al, , 2015…”

Section: Automatic Attention and The Task-evoked Pupil Dilation Responsementioning

confidence: 99%

“…More complex designs have been used to assess the effort associated with having a conversation while driving. In general, having a conversation while driving increases the index of cognitive activity, which is based on a wavelet analysis of the pupil signal that quantifies the high-frequency detail in the pupil signal (Demberg, 2013;Dlugosch, Conti, & Bengler, 2013). Kun, Palinko, Medenica, and Heeman (2013) measured the pupil dilation response during an actual live conversation between two participants who played a game.…”

Section: Intentional Attention and The Task-evoked Pupil Dilation Responsementioning

confidence: 99%

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The Pupil Dilation Response to Auditory Stimuli: Current State of Knowledge

2018

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The measurement of cognitive resource allocation during listening, or listening effort, provides valuable insight in the factors influencing auditory processing. In recent years, many studies inside and outside the field of hearing science have measured the pupil response evoked by auditory stimuli. The aim of the current review was to provide an exhaustive overview of these studies. The 146 studies included in this review originated from multiple domains, including hearing science and linguistics, but the review also covers research into motivation, memory, and emotion. The present review provides a unique overview of these studies and is organized according to the components of the Framework for Understanding Effortful Listening. A summary table presents the sample characteristics, an outline of the study design, stimuli, the pupil parameters analyzed, and the main findings of each study. The results indicate that the pupil response is sensitive to various task manipulations as well as interindividual differences. Many of the findings have been replicated. Frequent interactions between the independent factors affecting the pupil response have been reported, which indicates complex processes underlying cognitive resource allocation. This complexity should be taken into account in future studies that should focus more on interindividual differences, also including older participants. This review facilitates the careful design of new studies by indicating the factors that should be controlled for. In conclusion, measuring the pupil dilation response to auditory stimuli has been demonstrated to be sensitive method applicable to numerous research questions. The sensitivity of the measure calls for carefully designed stimuli.

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Section: Automatic Attention and The Task-evoked Pupil Dilation Responsementioning

confidence: 99%

Section: Intentional Attention and The Task-evoked Pupil Dilation Responsementioning

confidence: 99%

The Pupil Dilation Response to Auditory Stimuli: Current State of Knowledge

2018

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“…Additional visual and visual-manual tasks in addition to pupil metrics were also tested in this experiment, though not presented here (for pupil metrics, see Dlugosch, Conti, & Bengler, 2013). The HDRT was used in this experiment due to its more consistent performance (Conti et al, 2012).…”

Section: Tasks and Equipmentmentioning

confidence: 99%

Driving and Speaking: Revelations by the Head-Mounted Detection Response Task

Conti

Dlugosch

Schwarz

et al. 2013

Proceedings of the 7th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design : Dr

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Summary:The cognitive workload of speech-related activity needs to be examined in an economic and simple way. This is especially important as invehicle technology is becoming more cognitive with, for example, the use of speech-interaction and industry will need a way to keep pace with new technologies. One proposed way to measure cognitive workload is the detection response task (DRT) method. In this study, the DRT was used to assess different speech-related cognitive tasks. Three conversation tasks and the n-back task were performed together with a simulated driving task and a head-mounted DRT (HDRT). The aim was to evaluate the conversation and n-back tasks with the HDRT and to quantify the respective cognitive workload. Results show an increase in HDRT reaction times when additional cognitive tasks are performed relative to baseline measurements. In line with other research methods, the HDRT provided a reliable measurement of additional workload.

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“…In addition to studies conducted at the AgeLab, the task has been used extensively internationally as a method of inducing graded levels of cognitive workload with studies such as [1,2,4,5,6,7,13,21,23,24,26,30] being conducted utilizing the English version of the task or translations into French, German, Chinese, Japanese, Swedish, Korean, and Polish. Various translations of materials provided by international research teams can be found at http://agelab.mit.edu/study-tools.…”

Section: Introductionmentioning

confidence: 99%

The MIT AgeLab n-back

Reimer

Gulash²,

Foley³

et al. 2014

Adjunct Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

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This paper briefly describes the background of the MIT AgeLab implementation of a delayed digit recall or nback task, and the capabilities of an android application developed to implement a multi-modal version. The MIT AgeLab n-back task is a well-established methodology for inducing graded levels of cognitive workload. It has been adopted for broad use as a multimodal surrogate demand and calibration task, and recently introduced as a driver and pedestrian distraction education tool.

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Driver Distraction through Conversation Measured with Pupillometry

Cited by 7 publications

References 18 publications

The Pupil Dilation Response to Auditory Stimuli: Current State of Knowledge

The Pupil Dilation Response to Auditory Stimuli: Current State of Knowledge

Driving and Speaking: Revelations by the Head-Mounted Detection Response Task

The MIT AgeLab n-back

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