Examining the effects of emotional valence and arousal on takeover performance in conditionally automated driving

In conditionally automated driving, drivers have difficulty in takeover transitions as they become increasingly decoupled from the operational level of driving. Factors influencing takeover performance, such as takeover lead time and the engagement of non-driving-related tasks, have been studied in the past. However, despite the important role emotions play in human-machine interaction and in manual driving, little is known about how emotions influence drivers’ takeover performance. This study, therefore, examined the effects of emotional valence and arousal on drivers’ takeover timeliness and quality in conditionally automated driving. We conducted a driving simulation experiment with 32 participants. Movie clips were played for emotion induction. Participants with different levels of emotional valence and arousal were required to take over control from automated driving, and their takeover time and quality were analyzed. Results indicate that positive valence led to better takeover quality in the form of a smaller maximum resulting acceleration and a smaller maximum resulting jerk. However, high arousal did not yield an advantage in takeover time. This study contributes to the literature by demonstrating how emotional valence and arousal affect takeover performance. The benefits of positive emotions carry over from manual driving to conditionally automated driving while the benefits of arousal do not

Predicting Driver Takeover Performance in Conditionally Automated Driving

http://deepblue.lib.umich.edu/bitstream/2027.42/156409/1/AAP_Predicting_takeover_performance.pdfSEL

Predicting Takeover Performance in Conditionally Automated Driving

In conditionally automated driving, drivers decoupled from operational control of the vehicle have difficulty taking over control when requested. To address this challenge, we conducted a human-in-the-loop experiment wherein the drivers needed to take over control from an automated vehicle. We collected drivers’ physiological data and data from the driving environment, and based on which developed random forest models for predicting drivers’ takeover performance in real time. Drivers’ subjective ratings of their takeover performance were treated as the ground truth. The best random forest model had an accuracy of 70.2% and an F1-score of 70.1%. We also discussed the implications on the design of an adaptive in-vehicle alert system.University of Michigan McityNational Science FoundationPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153789/1/Du et al. 2020.pdfDescription of Du et al. 2020.pdf : Main Fil

Evaluating Effects of Cognitive Load, Takeover Request Lead Time, and Traffic Density on Drivers’ Takeover Performance in Conditionally Automated Driving

The views expressed are those of the authors and do not reflect the official policy or position of State Farm®.In conditionally automated driving, drivers engaged in non-driving related tasks (NDRTs) have difficulty taking over control of the vehicle when requested. This study aimed to examine the relationships between takeover performance and drivers’ cognitive load, takeover request (TOR) lead time, and traffic density. We conducted a driving simulation experiment with 80 participants, where they experienced 8 takeover events. For each takeover event, drivers’ subjective ratings of takeover readiness, objective measures of takeover timing and quality, and NDRT performance were collected. Results showed that drivers had lower takeover readiness and worse performance when they were in high cognitive load, short TOR lead time, and heavy oncoming traffic density conditions. Interestingly, if drivers had low cognitive load, they paid more attention to driving environments and responded more quickly to takeover requests in high oncoming traffic conditions. The results have implications for the design of in-vehicle alert systems to help improve takeover performance.University of Michigan McityNational Science FoundationPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/156045/1/Du et al. 2020.pd

The effectiveness of a sustained nurse home visiting intervention for Aboriginal infants compared with non-Aboriginal infants and with Aboriginal infants receiving usual child health care : a quasi-experimental trial : the Bulundidi Gudaga study

Background: In Australia there is commitment to developing interventions that will 'Close the Gap' between the health and welfare of Indigenous and non-Indigenous Australians and recognition that early childhood interventions offer the greatest potential for long term change. Nurse led sustained home visiting programs are considered an effective way to deliver a health and parenting service, however there is little international or Australian evidence that demonstrates the effectiveness of these programs for Aboriginal infants. This protocol describes the Bulundidi Gudaga Study, a quasi-experimental design, comparing three cohorts of families from the Macarthur region in south western Sydney to explore the effectiveness of the Maternal Early Childhood Sustained Home-visiting (MECSH) program for Aboriginal families. Methods: Mothers were recruited when booking into the local hospital for perinatal care and families are followed up until child is age 4 years. Participants are from three distinct cohorts: Aboriginal MECSH intervention cohort (Group A), Non-Aboriginal MECSH intervention cohort (Group B) and Aboriginal non-intervention cohort (Group C). Eligible mothers were those identified as at risk during the Safe Start assessment conducted by antenatal clinic midwives. Mothers in Group A were eligible if they were pregnant with an Aboriginal infant. Mothers in Group B were eligible if they were pregnant with a non-Aboriginal infant. Mothers in Group C are part of the Gudaga descriptive cohort study and were recruited between October 2005 and May 2007. The difference in duration of breastfeeding, child body mass index, and child development outcomes at 18 months and 4 years of age will be measured as primary outcomes. We will also evaluate the intervention effect on secondary measures including: child dental health; the way the program is received; patterns of child health and illness; patterns of maternal health, health knowledge and behaviours; family and environmental conditions; and service usage for mothers and families. Discussion: Involving local Aboriginal research and intervention staff and investing in established relationships between the research team and the local Aboriginal community is enabling this study to generate evidence regarding the effectiveness of interventions that are feasible to implement and sustainable in the context of Aboriginal communities and local service systems. Trial registration: Australian New Zealand Clinical Trials Registry ACTRN12616001721493 Registered 14 Dec 2016. Retrospectively registered

Maternal super-obesity and perinatal outcomes in Australia: A national population-based cohort study

Background: Super-obesity is associated with significantly elevated rates of obstetric complications, adverse perinatal outcomes and interventions. The purpose of this study was to determine the prevalence, risk factors, management and perinatal outcomes of super-obese women giving birth in Australia. Methods: A national population-based cohort study. Super-obese pregnant women (body mass index (BMI) >50 kg/m2 or weight >140 kg) who gave birth between January 1 and October 31, 2010 and a comparison cohort were identified using the Australasian Maternity Outcomes Surveillance System (AMOSS). Outcomes included maternal and perinatal morbidity and mortality. Prevalence estimates calculated with 95 % confidence intervals (CIs). Adjusted odds ratios (ORs) were calculated using multivariable logistic regression. Results: 370 super-obese women with a median BMI of 52.8 kg/m2 (range 40.9–79.9 kg/m2) and prevalence of 2.1 per 1 000 women giving birth (95 % CI: 1.96–2.40). Super-obese women were significantly more likely to be public patients (96.2 %), smoke (23.8 %) and be socio-economically disadvantaged (36.2 %). Compared with other women, super-obese women had a significantly higher risk for obstetric (adjusted odds ratio (AOR) 2.42, 95 % CI: 1.77–3.29) and medical (AOR: 2.89, 95 % CI: 2.64–4.11) complications during pregnancy, birth by caesarean section (51.6 %) and admission to special care (HDU/ICU) (6.2 %). The 372 babies born to 365 super-obese women with outcomes known had significantly higher rates of birthweight ≥4500 g (AOR 19.94, 95 % CI: 6.81–58.36), hospital transfer (AOR 3.81, 95 % CI: 1.93–7.55) and admission to Neonatal Intensive Care Unit (NICU) (AOR 1.83, 95 % CI: 1.27–2.65) compared to babies of the comparison group, but not prematurity (10.5 % versus 9.2 %) or perinatal mortality (11.0 (95 % CI: 4.3–28.0) versus 6.6 (95 % CI: 2.6- 16.8) per 1 000 singleton births). Conclusions: Super-obesity in pregnancy in Australia is associated with increased rates of pregnancy and birth complications, and with social disadvantage. There is an urgent need to further address risk factors leading to super-obesity among pregnant women and for maternity services to better address pre-pregnancy and pregnancy care to reduce associated inequalities in perinatal outcomes. Keywords: Super-obesity, Obesity, Perinatal outcomes, Pregnancy, Maternal socio-economic disadvantage, Obstetric complication

Towards standardized metrics for measuring takeover performance in conditionally automated driving: A systematic review

A particular concern with SAE Level 3 automated vehicles is the takeover transition from the automated vehicle to the driver. Prior research has employed a wide range of metrics for measuring takeover performance. However, the lack of a set of standard metrics for measuring takeover performance makes it difficult to consolidate findings and summarize the influence of different factors. This article presents a review of the metrics employed in empirical literature examining takeover transitions in Level 3 automated driving and proposes a framework for standardizing the objective takeover performance metrics.University of Michigan McityNational Science FoundationPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/168148/1/Cao et al. 2021 (DeepBlue).pdfDescription of Cao et al. 2021 (DeepBlue).pdf : Main FileSEL

Rheumatic heart disease in pregnancy: strategies and lessons learnt implementing a population-based study in Australia

Background The global burden of rheumatic heart disease (RHD) is two-to-four times higher in women, with a heightened risk in pregnancy. In Australia, RHD is found predominantly among Aboriginal and Torres Strait Islander peoples. Methods This paper reviews processes developed to identify pregnant Australian women with RHD during a 2-year population-based study using the Australasian Maternity Outcomes Surveillance System (AMOSS). It evaluates strategies developed to enhance reporting and discusses implications for patient care and public health. Results AMOSS maternity coordinators across 262 Australian sites reported cases. An extended network across cardiac, Aboriginal and primary healthcare strengthened surveillance and awareness. The network notified 495 potential cases, of which 192 were confirmed. Seventy-eight per cent were Aboriginal and/or Torres Strait Islander women, with a prevalence of 22 per 1000 in the Northern Territory. Discussion Effective surveillance was challenged by a lack of diagnostic certainty, incompatible health information systems and varying clinical awareness among health professionals. Optimal outcomes for pregnant women with RHD demand timely diagnosis and access to collaborative care. Conclusion The strategies employed by this study highlight gaps in reporting processes and the opportunity pregnancy provides for diagnosis and re/engagement with health services to support better continuity of care and promote improved outcomes.The authors gratefully acknowledge aid from the Australian National Health and Medical Research Council (NHMRC) project grant #1024206 and NHMRC Postgraduate Scholarship #11332944; University of Technology Sydney Chancellor’s Research Scholarship; and END RHD Centre of Research Excellence, Telethon Kids Institute, University of Western Australia

Maternal super-obesity and perinatal outcomes in Australia: A national population-based cohort study

© 2015 Sullivan et al. Background: Super-obesity is associated with significantly elevated rates of obstetric complications, adverse perinatal outcomes and interventions. The purpose of this study was to determine the prevalence, risk factors, management and perinatal outcomes of super-obese women giving birth in Australia. Methods: A national population-based cohort study. Super-obese pregnant women (body mass index (BMI) >50 kg/m2 or weight >140 kg) who gave birth between January 1 and October 31, 2010 and a comparison cohort were identified using the Australasian Maternity Outcomes Surveillance System (AMOSS). Outcomes included maternal and perinatal morbidity and mortality. Prevalence estimates calculated with 95 % confidence intervals (CIs). Adjusted odds ratios (ORs) were calculated using multivariable logistic regression. Results: 370 super-obese women with a median BMI of 52.8 kg/m2 (range 40.9-79.9 kg/m2) and prevalence of 2.1 per 1 000 women giving birth (95 % CI: 1.96-2.40). Super-obese women were significantly more likely to be public patients (96.2 %), smoke (23.8 %) and be socio-economically disadvantaged (36.2 %). Compared with other women, super-obese women had a significantly higher risk for obstetric (adjusted odds ratio (AOR) 2.42, 95 % CI: 1.77-3.29) and medical (AOR: 2.89, 95 % CI: 2.64-4.11) complications during pregnancy, birth by caesarean section (51.6 %) and admission to special care (HDU/ICU) (6.2 %). The 372 babies born to 365 super-obese women with outcomes known had significantly higher rates of birthweight ≥4500 g (AOR 19.94, 95 % CI: 6.81-58.36), hospital transfer (AOR 3.81, 95 % CI: 1.93-7.55) and admission to Neonatal Intensive Care Unit (NICU) (AOR 1.83, 95 % CI: 1.27-2.65) compared to babies of the comparison group, but not prematurity (10.5 % versus 9.2 %) or perinatal mortality (11.0 (95 % CI: 4.3-28.0) versus 6.6 (95 % CI: 2.6- 16.8) per 1 000 singleton births). Conclusions: Super-obesity in pregnancy in Australia is associated with increased rates of pregnancy and birth complications, and with social disadvantage. There is an urgent need to further address risk factors leading to super-obesity among pregnant women and for maternity services to better address pre-pregnancy and pregnancy care to reduce associated inequalities in perinatal outcomes

Giving Voice to the Voiceless: The Use of Digital Technologies by Marginalized Groups

This paper reports on a workshop hosted at the University of Massachusetts Amherst in September, 2018. The workshop, called “Giving Voice to the Voiceless: The Use of Digital Technologies by Marginalized Groups”, focused on discussing how marginalized groups use digital technologies to raise their voices. At the workshop, a diverse group of scholars and doctoral students presented research projects and perspectives on the role that digital technologies have in activist projects that represent marginalized groups that have gained momentum in the last few years. The studies and viewpoints presented shed light on four areas in which IS research can expand our understanding about how marginalized groups use digital technologies to address societal challenges: 1) the rise of cyberactivism, 2) resource mobilization for cyberactivism, 3) cyberactivism by and with marginalized groups, and 4) research methods for examining how marginalized groups use digital technologies