The impacts of perceptual load and driving duration on mind wandering in driving

Geden, Michael; Staicu, Ana‐Maria; Feng, Jing

doi:10.1016/j.trf.2017.07.004

Cited by 35 publications

(20 citation statements)

References 43 publications

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“…In the video, which ran for approximately 21 minutes, the car moves along the highway at night, at a slow speed with very few other cars. Even though long drives may last more than 21 minutes, Geden et al [16] shows drivers' minds start wandering after the first few minutes of starting to drive, giving support to our experimental design. Participants were instructed to annotate whether a road-sign appears to the left or to the right side of the road.…”

Section: Boredom Inducing Task Designsupporting

confidence: 60%

Mitigating Boredom Using An Empathetic Conversational Agent

Samrose

Anbarasu²,

Joshi

et al. 2020

Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents

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In spite of their ubiquity, our interactions with contemporary conversational agents (CA), such as Alexa, are still transactional in nature and lack the expressiveness of human-human communication. Conversational agents equipped with the ability to detect and address users' emotional and cognitive states could make our interactions with them more human. In this work, we investigate whether an empathetic CA can help mitigate boredom. We design a protocol in order to first elicit boredom in users, and explore strategies that attempt to mitigate their boredom with the help of two conversational agents, an empathetic agent and a non-empathetic agent, administered in a Wizard-of-Oz setting. We quantify their efficacy by measuring the effects on user mood and task performance. Our user study with 34 participants shows that the empathetic CA outperforms the non-empathetic CA with respect to modulating users' mood and performance. CCS CONCEPTS • Human-centered computing → User studies; Natural language interfaces.

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Section: Boredom Inducing Task Designsupporting

confidence: 60%

Mitigating Boredom Using An Empathetic Conversational Agent

Samrose

Anbarasu²,

Joshi

et al. 2020

Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents

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“…Few studies have analysed adaptations in driver behaviour capturing the impact of several explanatory factors and interdependencies between repeated observations over time for the same subject. For this purpose, recent studies have proposed linear mixed-effects models for repeated measures, which can accommodate both fixed and random effects capturing complex error structures (Peng, Boyle, and Lee 2014;Peng and Boyle 2015;Oviedo-Trespalacios et al 2017;Wang et al 2017;Geden, Staicu, and Feng 2018;Saad, Abdel-Aty, and Lee 2018;Albert 2019). Linear mixed-effects models allow to define explicitly a hierarchical structure (e.g.…”

Section: Statistical Analysis Methods For Adaptations In Driver Behavmentioning

confidence: 99%

Adaptations in driver behaviour characteristics during control transitions from full-range Adaptive Cruise Control to manual driving: an on-road study

Varotto

Farah

Bogenberger

et al. 2020

Transportmetrica A: Transport Science

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Adaptive Cruise Control (ACC) can reduce traffic congestion and accidents. In dense traffic flow conditions and when changing lanes, drivers prefer to deactivate the ACC. These control transitions between automation and manual driving could impact driver behaviour characteristics. However, few studies have analysed the magnitude and duration of these adaptations. This research aims at quantifying the adaptations in speed, acceleration, distance headway and relative speed when drivers resume manual control. We collected driver behaviour data in an on-road experiment with fullrange ACC during peak hours in Munich. We analysed these data using linear mixed-effects models to identify statistically significant changes in driver behaviour characteristics after drivers resumed manual control (transition period). The results reveal that the speed decreased significantly after the system was deactivated and it increased significantly after the system was overruled by pressing the gas pedal. These adaptations might have a substantial impact on traffic efficiency and safety.

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“…The ERPs utilized for resource reconstruction were acquired throughout the whole driving process, therefore, the effect of driving duration could not be detected using our current schema, which is another limitation of this study. Generally, driving duration had a close relationship with driving behaviors (Otmani et al, 2005; Geden et al, 2018) and EEG features (Puspasari et al, 2017). The influence of driving duration on personality, EEG and driving behaviors warrants further research.…”

Section: Discussionmentioning

confidence: 92%

Correlation Among Behavior, Personality, and Electroencephalography Revealed by a Simulated Driving Experiment

et al. 2019

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Drivers play the most important role in the human-vehicle-environment system and driving behaviors are significantly influenced by the cognitive state of the driver and his/her personality. In this paper, we aimed to explore the correlation among driving behaviors, personality and electroencephalography (EEG) using a simulated driving experiment. A total of 36 healthy subjects participated in the study. The 64-channel EEG data and the driving data, including the real-time position of the vehicle, the rotation angle of the steering wheel and the speed were acquired simultaneously during driving. The Cattell 16 Personality Factor Questionnaire (16PF) was utilized to evaluate the personalities of subjects. Through hierarchical clustering of the 16PF personality traits, the subjects were divided into four groups, i.e., the Inapprehension group, Insensitivity group, Apprehension group and the Unreasoning group, named after their representative personality trait. Their driving performance and turning behaviors were compared and EEG preprocessing, source reconstruction and the comparisons among the four groups were performed using Statistical Parameter Mapping (SPM). The turning process of the subjects can be formulated into two steps, rotating the steering wheel toward the turning direction and entering the turn, and then rotating the steering wheel back and leaving the turn. The bilateral frontal gyrus was found to be activated when turning left and right, which might be associated with its function in attention, decision-making and executive control functions in visual-spatial and visual-motor processes. The Unreasoning group had the worst driving performance with highest rates of car collision and the most intensive driving action, which was related to a higher load of visual spatial attention and decision making, when the occipital and superior frontal areas played a very important role. Apprehension (O) and Tension (Q4) had a positive correlation, and Reasoning (B) had a negative correlation with dangerous driving behaviors. Our results demonstrated the close correlation among driving behaviors, personality and EEG and may be taken as a reference for the prediction and precaution of dangerous driving behaviors in people with specific personality traits.

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The impacts of perceptual load and driving duration on mind wandering in driving

Cited by 35 publications

References 43 publications

Mitigating Boredom Using An Empathetic Conversational Agent

Mitigating Boredom Using An Empathetic Conversational Agent

Adaptations in driver behaviour characteristics during control transitions from full-range Adaptive Cruise Control to manual driving: an on-road study

Correlation Among Behavior, Personality, and Electroencephalography Revealed by a Simulated Driving Experiment

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