Improving Driver Emotions with Affective Strategies

Braun, Michael; Schubert, Jonas; Pfleging, Bastian; Alt, Florian

doi:10.3390/mti3010021

Cited by 69 publications

(39 citation statements)

References 53 publications

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“…Zhu et al [65] and Fakhrhosseini et al [16] investigated the use of music to relieve anger situations while driving. Braun et al explored the viability of ambient light, visual feedback, voice interaction, and an empathic voice assistant as strategies to regulate sadness and anger while driving [6]. Nass et al investigated mirroring voice with driver emotions and found that when drivers' emotions matched the car's voice emotion, they had fewer accidents, focused more on the road and spoke more to the car [41].…”

Section: In-car Responses To Regulate and Influence Emotionsmentioning

confidence: 99%

“…doors open, car locked), or as reading lights (for example, BMW Moodlight 5 ). Outside the car, ambient lighting is also used in other road environments such as tunnels 6 . This familiarity makes it a useful and suitable modality to augment the car's interior with further information that can easily be perceived by the driver.…”

Section: Emotion Feedback: In-car Ambient Lightmentioning

confidence: 99%

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Detecting and Influencing Driver Emotions Using Psycho-Physiological Sensors and Ambient Light

Hassib

Braun

Pfleging

et al. 2019

Lecture Notes in Computer Science

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DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

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Section: In-car Responses To Regulate and Influence Emotionsmentioning

confidence: 99%

Section: Emotion Feedback: In-car Ambient Lightmentioning

confidence: 99%

Detecting and Influencing Driver Emotions Using Psycho-Physiological Sensors and Ambient Light

Hassib

Braun

Pfleging

et al. 2019

Lecture Notes in Computer Science

Self Cite

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“…This approach has the advantages of being adaptive to various driving situations, drivers' propensities and coping strategies, and the uncertainty of traffic behaviors [62]. Recent findings suggest that, in addition to matching vehicle voice to driver's affect, vehicle voice showing empathy via a voice assistant led to the largest improvement of negative emotions and was also positively perceived by angry and sad drivers [63].…”

Section: Measuring Affect To Improve Driver-vehicle Interactionsmentioning

confidence: 99%

A Review on Measuring Affect with Practical Sensors to Monitor Driver Behavior

Welch

Harnett

Lee

2019

Safety

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Using sensors to monitor signals produced by drivers is a way to help better understand how emotions contribute to unsafe driving habits. The need for intuitive machines that can interpret intentional and unintentional signals is imperative for our modern world. However, in complex human-machine work environments, many sensors will not work due to compatibility issues, noise, or practical constraints. This review focuses on practical sensors that have the potential to provide reliable monitoring and meaningful feedback to vehicle operators-such as drivers, train operators, pilots, astronauts-as well as being feasible for implementation and integration with existing work infrastructure. Such an affect-sensitive intelligent vehicle might sound an alarm if signals indicate the driver has become angry or stressed, take control of the vehicle if needed, and collaborate with other vehicles to build a stress map that improves roadway safety. Toward such vehicles, this paper provides a review of emerging sensor technologies for driver monitoring. In our research, we look at sensors used in affect detection. This insight is especially helpful for anyone challenged with accurately understanding affective information, like the autistic population. This paper also includes material on sensors and feedback for drivers from populations that may have special needs.Safety 2019, 5, 72 2 of 18 would be challenging to apply in vehicles because of noise sensitivity and data-processing requirements. Beyond engineering considerations, it would be unrealistic to expect daily drivers to apply the EEG sensor before each trip because it would be a new behavior and a time-consuming departure from the driver's routine in a world where it is already difficult to get people to wear seatbelts. Wearable sensing devices such as watches and eyeglasses that fit into a driver's established routine are more practical. Video cameras, reviewed in 2016 by Fernández et al. [1], are practical in the sense that users do not need to activate or touch them, but cameras and microphones also introduce privacy concerns and produce high bandwidth data that requires processing. New soft and textile-embedded sensor formats are promising because they can be fitted to vehicle interiors, and because they can detect safety-relevant activity using body contact data that is not as personally identifiable as video and audio streams. Figure 1 illustrates a pressure sensor for tracking a driver's grip pressure in (a) a body-worn format, and (b) a vehicle surface format. Wearable sensors such as the glove in (a) are more practical for daily use than, for example, blood sampling to measure glucose [2] or cortisol levels, or neural implants to detect brain activity in animal studies. Such invasive sampling can validate conclusions drawn from proxy signals available at the body surface, but a sensor glove is better for daily wear from the user's viewpoint. However, for this grip-tracking application, the driver would have to modify their behavior to put gloves on, would need ...

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“…The first article [16] investigates the characteristics of in-vehicle voice agents to increase technology acceptance and improve upon the perceived ease of use of automated vehicle technology. The next article [17] addresses the issue of driver emotions that may have a negative influence on road safety, and the authors suggest employing affective computing for emotional state detection and parametrization of empathic digital assistants to improve driver emotions and, as a consequence, enable safer driving. The authors of the third article [18] focus (again) on the effect of feedback on the perceived ease of use when interacting with automated driving systems at lower levels of automation (Society of Automotive Engineers (SAE) Levels 0-3) and conclude that the perceived ease of use can be used as a diagnostic measure in interaction with automated vehicles.…”

Section: Summary Of Contributionsmentioning

confidence: 99%

“…The basic assumption of the authors in "Improving Driver Emotions with Affective Strategies" [17] is that sad or angry drivers are prone to perform worse at driving which, in turn, decreases overall road safety. To counteract, Braun et al suggest using affective computing tools and methods for the detection of drivers' (negative) emotional states.…”

Section: Summary Of Contributionsmentioning

confidence: 99%