Testing the psychophysical characteristics of professional drivers – Can we identify unsafe drivers?

Vujanic, Milan P.; Antić, Boris; Pešić, Dalibor; Savićević, M

doi:10.1016/j.trf.2016.07.003

Cited by 9 publications

(5 citation statements)

References 40 publications

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“…Although some PVT measures (i.e., a reliable and objective measure of sleepiness, sensible to circadian and homeostatic factors [12,90,101]) showed a moderate effect size, the results of the ANOVAs did not reach statistical significance. Finally, young subjects accept higher levels of risk at the wheel (WRB-TV) than older adults, consistently with the studies that report greater impulsiveness while driving by young people [102][103][104][105].…”

Section: Discussionsupporting

confidence: 83%

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The Influence of Sleep Quality, Vigilance, and Sleepiness on Driving-Related Cognitive Abilities: A Comparison between Young and Older Adults

et al. 2020

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Background: Driving performance is strongly vulnerable to drowsiness and vigilance fluctuations. Excessive sleepiness may alter concentration, alertness, and reaction times. As people age, sleep undergoes some changes, becoming fragmented and less deep. However, the effects of these modifications on daily life have not been sufficiently investigated. Recently, the assessment of sleepiness became mandatory in Europe for people at risk who need the driving license release. Moreover, considering the expectation that people around the world are rapidly aging, it is necessary to investigate the relationships between senescence sleep changes, vigilance levels, and driving-related cognitive skills. Method: 80 healthy subjects (40 young adults and 40 elders) participated in the study. Sleep quality, sleepiness, and vigilance levels were assessed through the Pittsburgh Sleep Quality Index, the Karolinska Sleepiness Scale, the Epworth Sleepiness Scale, and the Psychomotor Vigilance Task (PVT). Driving-related cognitive abilities were assessed through Vienna Test System TRAFFIC, investigating selective attention, tachistoscopic perception, and risk assumption. Results: 2 × 2 between-subject ANOVAs showed less habitual sleep efficiency and worse performances in PVT in the older group. Unexpectedly, younger subjects show higher self-rated sleepiness. Moreover, older adults have lower performance in attention and perception tests, but they appear to be more cautious in situations involving traffic. Finally, the multiple regressions show age to be the only robust predictor of cognitive driving-related abilities. Conclusions: This is the first study that investigates the relationships among sleepiness/vigilance and specific driving-related cognitive skills on a sufficiently large sample. Nevertheless, the study should be considered preliminary and does not allow us to understand how specific changes in sleep architecture impact performances in the elders’ everyday life and, specifically, on driving skills.

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Section: Discussionsupporting

confidence: 83%

“…After considering the differences between the two groups, it is not surprising that the multiple regression approach confirms that age is the best predictor of poor driving performance, confirming the validity of the Vienna Test System TRAFFIC in discriminating subjects' performances based on age [97][98][99][100][101][102]106].…”

Section: Discussionmentioning

confidence: 88%

The Influence of Sleep Quality, Vigilance, and Sleepiness on Driving-Related Cognitive Abilities: A Comparison between Young and Older Adults

et al. 2020

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“…Traffic accidents were used as a dependent variable in examining the validity of traffic psychological assessment systems in a few studies. In relation to traffic accidents, there were only differences for complex reaction time and reasoning based on cognitive‐psychomotor abilities in one study (Amado et al, 2004), but no difference was reported in other studies (Hergovich et al, 2008; Vujanić et al, 2016).…”

Section: Discussionmentioning

confidence: 89%

How well do the traffic psychological assessment systems predict on‐road driving behaviour?

Kaça

Izmitligil

Koyuncu

et al. 2021

Applied Cognitive Psychology

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This study aims to investigate the predictive validities of three different traffic psychological assessment systems used in Turkey (ART 2020, TRAFIKENT and Vienna Test System) by using systematic observation of driving behaviour in natural traffic settings. For this purpose, 176 drivers were evaluated by observers and then tested in three different traffic psychological assessment systems. Drivers participated in a 45 km (approx. 80 min) driving session consisting of diverse road types. Observers filled systematic observation forms comprising 35 errors/violations on 10 road segments. Furthermore, observers evaluated participants regarding cognitive and psychomotor abilities measured with the psychological assessment system. Consequently, although the systems' power to predict on‐road behaviour was similar, the tests/abilities that contributed to the models differed in each system except for the reasoning test. It was recommended to increase the weight of these predictive tests in deciding safe driving for each system.

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“…5, anger intensity increases along with the increase of educated level of the subjects, which may have a deviation with our common sense. Vujanic et al [29] found that drivers with high educated level, have better psychophysical characteristics including general intelligence, concentration level and stress tolerance, with regard to driving safety. Note that the investigated subjects presenting anger states, especially medium and high anger were born in the 1980s or 1990s, which means that they generally received a comparably good education due to economic development of China during their growth.…”

Section: ) Gendermentioning

confidence: 99%

Sensitivity Analysis of Incentive Situations and Personal Attributes to Driving Anger Based on MNL Model: A Naturalistic Experimental Study

Park

Yan

2021

Teh. vjesn.

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Driving anger, called "road rage", has gradually become universal phenomenon nowadays, which has been a concern to traffic management authorities. It is necessary to figure out impacting degree of the influencing factors on driving anger for taking the corresponding intervening measures. Forty drivers were enrolled to conduct naturalistic experiments on a busy route in Wuhan, China, where drivers' anger can be induced by various incentive situations including jaywalking, weaving/cutting in line, traffic congestion and red light with extra paid if completing the experiment ahead of reference time. According to behavioral theory and disaggregation theory, the influencing factors including the incentive situations and personal attributes (i.e. gender, age, temperament) were determined for proposing driving anger prediction model based on MNL (multinomial logit). Then, the sensitivity of each influencing factor on driving anger was analyzed by elasticity theory on the basis of the proposed model. The result indicates that age, temperament and illegal behaviors from surrounding people are decisive influencing factors to driving anger sates with different intensity because their average elasticity values for none anger (neutral), low anger, medium anger, high anger are 1.254, 2.713, 2.914, respectively, which are all bigger than 1. Moreover, the accuracy of the proposed model is 78.30%. The results can provide theoretical support for developing key monitoring or targeted intervention to deal with the decisive influencing factors for traffic management authorities.

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Testing the psychophysical characteristics of professional drivers – Can we identify unsafe drivers?

Cited by 9 publications

References 40 publications

The Influence of Sleep Quality, Vigilance, and Sleepiness on Driving-Related Cognitive Abilities: A Comparison between Young and Older Adults

The Influence of Sleep Quality, Vigilance, and Sleepiness on Driving-Related Cognitive Abilities: A Comparison between Young and Older Adults

How well do the traffic psychological assessment systems predict on‐road driving behaviour?

Sensitivity Analysis of Incentive Situations and Personal Attributes to Driving Anger Based on MNL Model: A Naturalistic Experimental Study

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