The consequences of unexpected emotional sounds on driving behaviour in risky situations

Stasi, Leandro L. Di; Contreras, David; Cañas, José J.; Cândido, Antônio; Maldonado, Antonio; Catena, Andrés

doi:10.1016/j.ssci.2010.07.006

Cited by 44 publications

(25 citation statements)

References 23 publications

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“…In Pêcher et al (2009), happy music reduced driving speeds and impaired lateral control more than sad and neutral music. In Di Stasi et al (2010), emotional sounds (e.g., a scream or laugh) decreased alertness in drivers compared to a neutral beep. All these results demonstrate that emotional music and sounds can influence driving performance.…”

Section: Emotional Distractionmentioning

confidence: 94%

Emotion matters: Implications for distracted driving

Chan

Singhal

2015

Safety Science

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Section: Emotional Distractionmentioning

confidence: 94%

Emotion matters: Implications for distracted driving

Chan

Singhal

2015

Safety Science

View full text Add to dashboard Cite

“…Control parameters are initialized and groups number = 100, threshold = 0.01, crossover rate = 0.8, and mutation rate = 0.01. After repeated computing, the final optimization result is 4 , namely, driver's operation reaction time. Control parameters are initialized and groups number = 100, threshold = 0.01, crossover rate = 0.8, and mutation rate = 0.01.…”

Section: Feature Selectionmentioning

confidence: 99%

“…Sad music influenced drivers in a different way, as they drove slowly and kept their vehicle in its lane. Di Stasi et al [4] aimed to uncover whether emotional auditory stimuli could affect risky behaviour in hazardous situations. These results suggested that auditory warning systems for vehicles should avoid using emotionladen sounds, as their affective content might diminish their utility to increase driving alertness.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Feature Extraction Method of Driver's Propensity under Complicated Vehicle Group

Wang

Zhang

Ban

et al. 2013

Advances in Mechanical Engineering

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The effect of driver's physiological and psychological characteristics on traffic safety is represented mainly as driver's propensity. Previous researches focus mostly on psychology test and its influence on traffic safety from relative static and macroscopic perspective. However, in the field of vehicle active safety, there are few studies on driver's affective measurement and computing from microcosmic and dynamic perspective, and previous researchers did not consider the influence of environment. The emphasis is about situation factors which directly influence driver's affection in all environment factors under two-lane condition. Various experiments are designed to collect driver's microdynamic information, and characteristics of driver's propensity toward different environments are extracted using genetic simulated annealing algorithm. Results show that the method can provide a basis to establish dynamic recognition model of driver's propensity further which is adapted to multilane environment.

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“…Campagne et al [3] studied the relationship of driver's age difference to traffic accidence numbers using EEG recorder, and the result showed that driver's vigilance would decrease and the number of operation mistakes would grow as the age increases. Brundell-Freij and Ericsson [4], Leng et al [5], Pêcher [6], Di Stasi [7], Taubman-Ben-Ari [8], Cai and Lin [9], Parker et al [10], Trick et al [11], Lansdown [12], Daffy [13], Wang et al [14][15][16], Weng and Meng [17], Verschuur and Hurts [18], Zhang et al [19], Gosselin et al [20], and Hu et al [21], Danciu et al [22] have studied driver behavior characteristics from different angles. However, in the field of vehicle active safety, there are few researches on driver's affective characteristics from microcosmic and dynamic perspective.…”

Section: Forewordmentioning

confidence: 99%

Prediction Method of Driver's Propensity Adapted to Driver's Dynamic Feature Extraction of Affection

Zhang

Wang

Ban

et al. 2013

Advances in Mechanical Engineering

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Driver's propensity is a dynamic measurement of driver's characteristics, such as affection and preference. In the vehicle driverassistance system, especially its collision warning subsystem, it is also an important parameter of computing driver's intention. The prediction of driver's propensity from relative static and macroscopic perspective is an essential precondition for further researching and extracting dynamic characteristics. Physiology and psychology tests are designed to measure driver's character and calculate physiological rhythm. Changing data of driver's psychology and emotion during driving are obtained by real vehicle test. Then driver's propensity values of different types are calculated by weighting method according to the contribution rate of standard features. Results show that this method is better than the traditional psychology test, and it provides a basis for further studying dynamic characteristics of driver's affection.

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The consequences of unexpected emotional sounds on driving behaviour in risky situations

Cited by 44 publications

References 23 publications

Emotion matters: Implications for distracted driving

Emotion matters: Implications for distracted driving

Dynamic Feature Extraction Method of Driver's Propensity under Complicated Vehicle Group

Prediction Method of Driver's Propensity Adapted to Driver's Dynamic Feature Extraction of Affection

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