Driver distraction and inattention in the realm of automated driving

Cunningham, Mitchell L.; Regan, Michael

doi:10.1049/iet-its.2017.0232

Cited by 58 publications

(36 citation statements)

References 52 publications

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“…However, functional impairment may be influenced by mental illnesses and can change an individual's driving behavior, which might endanger other road users (26). According to the literature, the presence of mental illness symptoms such as anxiety and depression might decrease road safety (27). Furthermore, a study done in Australia targeting young drivers identified depression as a predictor of risky behavior (28).…”

Section: Discussionmentioning

confidence: 99%

Predictors of Seatbelt Use Among Saudi Adults: Results From the National Biobank Project

Alghnam

Alyabsi

Aburas

et al. 2020

Front. Public Health

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Introduction: Road traffic crashes (RTCs) are a leading cause of death and disabilities and impose a significant burden on the healthcare system and economy of Saudi Arabia. Around 20% of all hospital beds are occupied by victims of RTCs, which represent approximately 80% of trauma deaths occurring in these facilities. Using a seatbelt is an effective method to reduce traffic deaths and minimize the extent of associated injuries. However, little is currently known about the prevalence and predictors of seatbelt use in Saudi Arabia. More studies are needed to determine the trends of seatbelt use and study the relationship between individual factors and compliance with seatbelt use laws. The aim of the present study is to examine the prevalence and predictors of seatbelt use using the National Saudi Biobank dataset. Materials and Methods: This cross-sectional study was conducted using an in-person survey from the Saudi National Biobank (SNB). The participants were adults affiliated with the Ministry of National Guard Health Affairs in Riyadh who were examined between 2017 and 2019. Chi-squared and Wald tests were used to assess the association between the respondents' characteristics and their seatbelt use. In addition, logistic regression models were constructed to assess the univariate and multivariate associations between seatbelt use and potential predictors. All statistical tests were two-sided, and the findings were considered significant at P < 0.05. Results: A total of 5,790 adults participated in the survey. The majority of the participants (52.44%) were between 18 and 25 years old, half were males, and 58.80% were single. About 42.83% of the participants reported consistent seatbelt use as drivers or passengers. In the multivariable analysis, females were 86% less likely to wear seatbelts than males (OR = 0.136, 95%CI = 0.107-0.173). Individuals who rated their mental health as "weak" were 26% less likely to wear seatbelts than those who reported "excellent" mental health status. Conclusion: Seatbelt use remains low in the country and substantially lower than in developed countries. Young adults, females, and individuals reporting suboptimal mental health were less likely to fasten their seatbelts. Alghnam et al. Seatbelt Use Among Saudi Adults These findings are valuable for public health programs to target specific groups and raise awareness about the need to increase seatbelt compliance and reduce traffic injuries.

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Section: Discussionmentioning

confidence: 99%

Predictors of Seatbelt Use Among Saudi Adults: Results From the National Biobank Project

Alghnam

Alyabsi

Aburas

et al. 2020

Front. Public Health

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“…This monitoring task places little demand on the driver, and driver interventions with the vehicle are infrequent when automation is operating properly. The driver experiences a vigilance decrement during PAD because scenarios of monotonous PAD cause a state of cognitive underload in the driver (Körber et al, 2015a;Cabrall et al, 2016;Solís-Marcos et al, 2017;Cunningham and Regan, 2018).…”

Section: Vigilance Decrements and Cognitive Underloadmentioning

confidence: 99%

Underload on the Road: Measuring Vigilance Decrements During Partially Automated Driving

McWilliams

Ward

2021

Front. Psychol.

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Partially automated vehicle technology is increasingly common on-road. While this technology can provide safety benefits to drivers, it also introduces new concerns about driver attention. In particular, during partially automated driving (PAD), drivers are expected to stay vigilant so they can readily respond to important events in their environment. However, using partially automated vehicles on the highway places drivers in monotonous situations and requires them to do very little. This can place the driver in a state of cognitive underload in which they experience a very small amount of cognitive demand. In this situation, drivers can exhibit vigilance decrements which impact their ability to respond to on-road threats. This is of particular concern in situations when the partially automated vehicle fails to respond to a potentially critical situation and leaves all responsibility to safely navigate to the driver. This paper reviews situations that lead to vigilance decrements and characterizes the different methodologies of measuring driver vigilance during PAD, highlighting their advantages and limitations. Based on our reading of the literature, we summarize several factors future research on vigilance decrements in PAD should consider.

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“…An important influence on driver responses during planned takeovers and silent failures is the extent to which the driver is engaged in tasks that divert resources from supervising the AV [ 16 ]. In silent failure paradigms, reaction times have been reported to be slower when drivers were engaged in additional non-driving-related-tasks that added to the cognitive load [ 4 , 12 ], which then appeared to propagate through to other metrics of steering, such as increasing maximum steering wheel angles by ≈ 15% [ 12 ] and leading to more lane excursions [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Predicting takeover response to silent automated vehicle failures

et al. 2020

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Current and foreseeable automated vehicles are not able to respond appropriately in all circumstances and require human monitoring. An experimental examination of steering automation failure shows that response latency, variability and corrective manoeuvring systematically depend on failure severity and the cognitive load of the driver. The results are formalised into a probabilistic predictive model of response latencies that accounts for failure severity, cognitive load and variability within and between drivers. The model predicts high rates of unsafe outcomes in plausible automation failure scenarios. These findings underline that understanding variability in failure responses is crucial for understanding outcomes in automation failures.

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Driver distraction and inattention in the realm of automated driving

Cited by 58 publications

References 52 publications

Predictors of Seatbelt Use Among Saudi Adults: Results From the National Biobank Project

Predictors of Seatbelt Use Among Saudi Adults: Results From the National Biobank Project

Underload on the Road: Measuring Vigilance Decrements During Partially Automated Driving

Predicting takeover response to silent automated vehicle failures

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