Effects of an integrated collision warning system on risk compensation behavior: An examination under naturalistic driving conditions.

Collision warning systems can improve traffic safety, while their safety benefit may be lessened due to improper risk compensation or system misuse. There are limited studies of advanced safety systems increasing unexpected risky driving behavior, especially with adolescent drivers. This study is designed to address this research gap in two main areas: 1) it seeks to examine whether and how the introduction of advanced driver-assistance systems influences drivers' risk compensation behavior (e.g., increase of hard braking frequency), and 2) it investigates key factors (e.g., distraction) that contribute to changes in hard braking frequency during driving for both teen and adult drivers. Naturalistic driving data from two previous studies were analyzed in this study with two methods: a hierarchical logistic regression model was used to evaluate the effects of an integrated collision warning system on hard braking behavior, while a Random forests algorithm was applied to model hard braking behavior and to rank the contributing factors by calculating the importance scores. No statistical evidence was observed that the integrated collision warning system significantly changed the likelihood of hard braking for teen or adult drivers. Other factors like distraction, especially visual-manual distraction, had the largest impact on the hard braking behavior, followed by speeding and roadway segments (i.e., at intersections or not). Short time-headways and driving in high-density traffic significantly increased the likelihood of hard braking. Furthermore, the rate of hard braking behavior on surface roads was much higher than on highways, as expected. Compared with straight road segments, hard braking behavior was less likely to occur on curve roads. This study applied an analytical strategy by using both machine learning and statistical analysis methods to achieve high model accuracy and facilitate inference concerning the relationships among variables. Findings in this study can help to improve the design of integrated collision warning systems and the use of autonomous braking systems, and to apply appropriate analysis methods in understanding teen drivers' behavior changes with those safety systems.

The Influence of Hearing Impairment on Driving Avoidance Among a Large Cohort of Older Drivers.

As people age, some of the commonly experienced psychomotor, visual, and cognitive declines can interfere with the ability to safely drive, often leading to situational avoidance of challenging driving situations. The effect of hearing impairment on these avoidance behaviors has not been comprehensively studied. Data from the American Automobile Association (AAA) Longitudinal Research on Aging Drivers (LongROAD) study were used to assess the effect of hearing impairment on driving avoidance, using three measures of hearing. Results indicated that hearing loss plays a complex role in driving avoidance, and that an objective hearing measure was a stronger predictor than hearing aid use and self-rated hearing. Greater hearing impairment was related to less nighttime and freeway driving, more trips farther than 15 mi from home, and lower odds of avoiding peak driving times. The moderating influence of hearing on both vision and cognition is also discussed, along with study implications and future research.

The importance of cycle threshold values in interpreting molecular tests for SARS-CoV-2.

Using the Allplex™ 2019-nCoV assay (Seegene, South Korea), 285 samples were tested; 49 (17%) were positive for 3 genes, 4 (1.4%) samples were positive for 2 genes (all N gene and RdRP gene), 8 (3%) samples were positive for 1 gene (all N gene only), and 224 (78.5%) samples were negative.

Improving Safe Mobility: An Assessment of Vehicles and Technologies among a Large Cohort of Older Drivers.

Evidence suggests that older driver safety may be improved by good vehicle maintenance, in-vehicle advanced technologies, and proper vehicle adaptations. This study explored the prevalence of several measures of vehicle maintenance and damage among older drivers through inspection of their vehicles. We also investigated the prevalence of in-vehicle technologies and aftermarket adaptations. Vehicle inspections were conducted by trained research staff using an objective, standardized procedure. This procedure, developed by a multidisciplinary team of researchers, was based on a review of inspection checklists used by automobile dealerships and the project team's expertise. The study used baseline data from vehicles of 2988 participants in the multi-site Longitudinal Research on Aging Drivers (LongROAD) study. Among this cohort, vehicles were well maintained, had little damage, and contained a range of advanced technologies but few aftermarket adaptations. Implications of study findings for occupational therapy practice are discussed.

Using naturalistic driving data to better understand the driving exposure and patterns of older drivers.

OBJECTIVE: The aging of the population in the United States and elsewhere has brought increasing attention to the issue of safe driving and mobility among older adults. The overall objective of this research was to use naturalistic data collection to better understand driving exposure and driving patterns, 2 important contributors to crash risk. METHODS: Data came from a study conducted at the University of Michigan Transportation Research Institute as part of the Integrated Vehicle-Based Safety System (IVBSS) program. A total of 108 randomly sampled drivers took part, with the sample stratified by age and sex. The age groups examined were 20 to 30 (younger), 40 to 50 (middle-aged), and 60 to 70 years old (older). Sixteen late-model Honda Accords were used as research vehicles and were driven by participants as their personal vehicles over the study period. Roughly the first 2 weeks of vehicle use comprised the baseline driving period, during which the IVBSS technologies were turned off (i.e., no warnings were presented to the drivers) but all onboard data were collected. For this article, only data from the baseline period were analyzed to limit any confounding effects that the safety technology may have had on driving behavior. RESULTS: Results indicated that when looking at age independent of sex, older drivers (age 60-70) took fewer trips, drove fewer minutes, were less likely to drive at night, and had fewer high decelerations and speeding events than the youngest age group (20-30). They were also less likely to drive during peak morning traffic and on high-speed roads than their middle-age counterparts (40-50). Across all age groups, there were few differences by sex, with the exception that females drove fewer miles and fewer minutes and had fewer high decelerations than males. When both age and sex were taken into account, it was often the group of females age 60-70 that appeared to account for many of the age and sex differences found in driving exposure and patterns. CONCLUSIONS: Future research in this area would benefit from larger scale and longitudinal study designs so that changes in driving exposure and patterns over time among large samples of drivers could be examined.

Drought timing and local climate determine the sensitivity of eastern temperate forests to drought.

Projected changes in temperature and drought regime are likely to reduce carbon (C) storage in forests, thereby amplifying rates of climate change. While such reductions are often presumed to be greatest in semi-arid forests that experience widespread tree mortality, the consequences of drought may also be important in temperate mesic forests of Eastern North America (ENA) if tree growth is significantly curtailed by drought. Investigations of the environmental conditions that determine drought sensitivity are critically needed to accurately predict ecosystem feedbacks to climate change. We matched site factors with the growth responses to drought of 10,753 trees across mesic forests of ENA, representing 24 species and 346 stands, to determine the broad-scale drivers of drought sensitivity for the dominant trees in ENA. Here we show that two factors-the timing of drought, and the atmospheric demand for water (i.e., local potential evapotranspiration; PET)-are stronger drivers of drought sensitivity than soil and stand characteristics. Drought-induced reductions in tree growth were greatest when the droughts occurred during early-season peaks in radial growth, especially for trees growing in the warmest, driest regions (i.e., highest PET). Further, mean species trait values (rooting depth and ψ50 ) were poor predictors of drought sensitivity, as intraspecific variation in sensitivity was equal to or greater than interspecific variation in 17 of 24 species. From a general circulation model ensemble, we find that future increases in early-season PET may exacerbate these effects, and potentially offset gains in C uptake and storage in ENA owing to other global change factors.

Prevalence, attitudes, and knowledge of in-vehicle technologies and vehicle adaptations among older drivers.

The purpose of the present study was to gain a better understanding of the types of in-vehicle technologies being used by older drivers as well as older drivers' use, learning, and perceptions of safety related to these technologies among a large cohort of older drivers at multiple sites in the United States. A secondary purpose was to explore the prevalence of aftermarket vehicle adaptations and how older adults go about making adaptations and how they learn to use them. The study utilized baseline questionnaire data from 2990 participants from the Longitudinal Research on Aging Drivers (LongROAD) study. Fifteen in-vehicle technologies and 12 aftermarket vehicle adaptations were investigated. Overall, 57.2% of participants had at least one advanced technology in their primary vehicle. The number of technologies in a vehicle was significantly related to being male, having a higher income, and having a higher education level. The majority of respondents learned to use these technologies on their own, with "figured-it-out-myself" being reported by 25%-75% of respondents across the technologies. Overall, technologies were always used about 43% of the time, with wide variability among the technologies. Across all technologies, nearly 70% of respondents who had these technologies believed that they made them a safer driver. With regard to vehicle adaptations, less than 9% of respondents had at least one vehicle adaptation present, with the number of adaptations per vehicle ranging from 0 to 4. A large majority did not work with a professional to make or learn about the aftermarket vehicle adaptation.

Impact of introduction of xpert flu assay for influenza PCR testing on obstetric patients: a quality improvement project.

OBJECTIVE: The aim of this project was to assess the implementation of a quality improvement project regarding the introduction of on-site influenza PCR testing in a stand-alone obstetric hospital. METHODS: As part of a quality improvement project on the management of influenza in obstetric patients, the Xpert Flu assay (Cepheid Inc., Sunnyvale, CA) was introduced on-site and it replaced the previous method of PCR testing which was off-site. The main outcome measures were duration of antimicrobials, rate of admission and administration of oseltamavir in the emergency department. RESULTS: Twenty-eight patients were included in the pre-intervention period and 45 patients were included in the post-intervention period. Following the introduction of the test, there was a statistically significant reduction seen in commencement of antimicrobials (76% pre- and 33% post-intervention), and also rate of admission (88% pre- and 45% post-intervention) while there was a statistically significant improvement in the commencement of oseltamavir in the emergency department (72% pre-and 95% post-intervention) (p < .01 for all outcomes). CONCLUSION: Introduction of on-site rapid influenza PCR testing can lead to a significant improvement in patient management and should be considered for introduction to other sites.

Longitudinal Research on Aging Drivers (LongROAD): study design and methods.

BACKGROUND: As an important indicator of mobility, driving confers a host of social and health benefits to older adults. Despite the importance of safe mobility as the population ages, longitudinal data are lacking about the natural history and determinants of driving safety in older adults. METHODS: The Longitudinal Research on Aging Drivers (LongROAD) project is a multisite prospective cohort study designed to generate empirical data for understanding the role of medical, behavioral, environmental and technological factors in driving safety during the process of aging. RESULTS: A total of 2990 active drivers aged 65-79 years at baseline have been recruited through primary care clinics or health care systems in five study sites located in California, Colorado, Maryland, Michigan, and New York. Consented participants were assessed at baseline with standardized research protocols and instruments, including vehicle inspection, functional performance tests, and "brown-bag review" of medications. The primary vehicle of each participant was instrumented with a small data collection device that records detailed driving data whenever the vehicle is operating and detects when a participant is driving. Annual follow-up is being conducted for up to three years with a telephone questionnaire at 12 and 36 months and in-person assessment at 24 months. Medical records are reviewed annually to collect information on clinical diagnoses and healthcare utilization. Driving records, including crashes and violations, are collected annually from state motor vehicle departments. Pilot testing was conducted on 56 volunteers during March-May 2015. Recruitment and enrollment were completed between July 2015 and March 2017. CONCLUSIONS: Results of the LongROAD project will generate much-needed evidence for formulating public policy and developing intervention programs to maintain safe mobility while ensuring well-being for older adults.

Screening for early-onset invasive group B Streptococcal disease in neonates in an Irish hospital (2001-2014): a retrospective audit.

Group B Streptococcus (GBS) is the most common cause of early-onset neonatal sepsis and meningitis. In babies with no clinical suspicion of infection, who are at risk of early-onset invasive disease based on maternal risk factors, blood cultures are taken to detect bacteraemia. In our institution, lumbar punctures are performed in infants with clinical signs of sepsis but not in infants who are well at the time of screening. Between 2001 and 2014, there were 112,361 live births weighing >500 g, of whom 13,959 (12.4%) infants had a blood culture taken on the first or second day of life, and 1971 (14.1%) of these infants had lumbar punctures on these first two days of life. Fifty-three cases of early-onset GBS disease were identified. Only three patients with invasive GBS disease had no clinical suspicion for sepsis at the time of testing. Thus, the number of blood cultures taken to detect one case of GBS bacteraemia in an infant who is well at the time of testing was 3996.

Accelerated Evaluation of Automated Vehicles Safety in Lane-Change Scenarios Based on Importance Sampling Techniques.

Automated vehicles (AVs) must be thoroughly evaluated before their release and deployment. A widely used evaluation approach is the Naturalistic-Field Operational Test (N-FOT), which tests prototype vehicles directly on the public roads. Due to the low exposure to safety-critical scenarios, N-FOTs are time consuming and expensive to conduct. In this paper, we propose an accelerated evaluation approach for AVs. The results can be used to generate motions of the other primary vehicles to accelerate the verification of AVs in simulations and controlled experiments. Frontal collision due to unsafe cut-ins is the target crash type of this paper. Human-controlled vehicles making unsafe lane changes are modeled as the primary disturbance to AVs based on data collected by the University of Michigan Safety Pilot Model Deployment Program. The cut-in scenarios are generated based on skewed statistics of collected human driver behaviors, which generate risky testing scenarios while preserving the statistical information so that the safety benefits of AVs in nonaccelerated cases can be accurately estimated. The cross-entropy method is used to recursively search for the optimal skewing parameters. The frequencies of the occurrences of conflicts, crashes, and injuries are estimated for a modeled AV, and the achieved accelerated rate is around 2000 to 20 000. In other words, in the accelerated simulations, driving for 1000 miles will expose the AV with challenging scenarios that will take about 2 to 20 million miles of real-world driving to encounter. This technique thus has the potential to greatly reduce the development and validation time for AVs.

Gap Acceptance During Lane Changes by Large-Truck Drivers-An Image-Based Analysis.

This paper presents an analysis of rearward gap acceptance characteristics of drivers of large trucks in highway lane change scenarios. The range between the vehicles was inferred from camera images using the estimated lane width obtained from the lane tracking camera as the reference. Six-hundred lane change events were acquired from a large-scale naturalistic driving data set. The kinematic variables from the image-based gap analysis were filtered by the weighted linear least squares in order to extrapolate them at the lane change time. In addition, the time-to-collision and required deceleration were computed, and potential safety threshold values are provided. The resulting range and range rate distributions showed directional discrepancies, i.e., in left lane changes, large trucks are often slower than other vehicles in the target lane, whereas they are usually faster in right lane changes. Video observations have confirmed that major motivations for changing lanes are different depending on the direction of move, i.e., moving to the left (faster) lane occurs due to a slower vehicle ahead or a merging vehicle on the right-hand side, whereas right lane changes are frequently made to return to the original lane after passing.

Optimization of an in vitro human blood-brain barrier model: Application to blood monocyte transmigration assays.

The blood-brain barrier (BBB) is a selectively permeable barrier that separates the circulating blood from the extracellular fluid of the brain and is an essential component in brain homeostasis. In vitro BBB models are valuable supporting tools that can precede and complement animal and human studies of the development and progression of the central nervous system diseases. At present, mono-, co-, and tri-culture models that use porcine, murine, or human cells have been developed. We have optimized a two-dimensional model of the human BBB using primary human brain microvascular endothelial cells and normal human astrocytes. We have validated the effectiveness of our model with transmigration assays of human blood monocytes toward CCL19, a natural ligand of the chemokine receptor CCR7. This model offers the following advantages:•It is simple, convenient, and requires small quantities of material, reagents, and primary cells.•It can be used to monitor cell migration through the BBB.•It can be used to assess brain capillary permeability in the presence of xenobiotic, pro-inflammatory, or other substances.

Understanding and Reducing Inconsistency in Seatbelt-Use Decisions: Findings from a Cardinal Decision Issue Perspective.

This article has two aims. The first is to present results that partly explain why some automobile drivers choose to use their seatbelts only part time, thereby exposing themselves to unnecessary risk. The second is to offer and illustrate the "cardinal decision issue perspective"((1)) as a tool for guiding research and development efforts that focus on complex real-life decision behaviors that can entail wide varieties of risk, including but not limited to inconsistent seatbelt use. Each of 24 young male participants drove an instrumented vehicle equipped to record continuously seatbelt use as well as other driving data. After all trips were finished, each participant completed an interview designed to reconstruct how he made randomly selected seatbelt-use decisions under specified conditions. The interview also examined whether and how drivers established "decision policies" regarding seatbelt use. Such policies were good predictors of inconsistent seatbelt use. Drivers who had previously adopted policies calling for consistent seatbelt use were significantly more likely than others to actually drive belted. Meta-decisions about seatbelt policy adoption appeared to rest on factors such as whether the driver had ever been asked to consider selecting a policy. Whether a driver made an ad hoc, on-the-spot seatbelt-use decision was associated with a perceived need to make such a decision. Finally, participants with full-time policies were especially likely to deploy their seatbelts by default, without recognizing the need to decide about belt use on a trip-by-trip basis. We end with recommendations for reducing inconsistencies in seatbelt use in actual practice.

Heavy-truck drivers' following behavior with intervention of an integrated, in-vehicle crash warning system: a field evaluation.

OBJECTIVE: This study is designed to evaluate heavy-truck drivers' following behavior and how a crash warning system influences their headway maintenance. BACKGROUND: Rear-end crashes are one of the major crash types involving heavy trucks and are more likely than other crash types to result in fatalities. Previous studies have observed positive effects of in-vehicle crash warning systems in passenger car drivers. Although heavy-truck drivers are generally more experienced, driver-related errors are still the leading factors contributing to heavy-truck-related rear-end crashes. METHOD: Data from a 10-month naturalistic driving study were used. Participants were 18 professional heavy-truck drivers who received warnings during the last 8 months of the study (treatment period) but not during the first 2 months (baseline period). Time headway and driver's brake reaction time were extracted and compared with condition variables, including one between-subjects variable (driver shift) and five within-subjects variables (treatment condition, roadway types, traffic density, wiper state, and trailer configuration). RESULTS: The presence of warnings resulted in a 0.28-s increase of mean time headway with dense on-road traffic and a 0.20-s increase with wipers on. Drivers also responded to the forward conflicts significantly faster (by 0.26 s, a 15% enhancement) in the treatment condition compared with responses in the baseline condition. CONCLUSION: Positive effects on heavy-truck drivers' following performance were observed with the warning system. APPLICATION: The installation of such in-vehicle crash warning systems can help heavy-truck drivers keep longer headway distances in challenging situations and respond quicker to potential traffic conflicts, therefore possibly increasing heavy-truck longitudinal driving safety.

Driving behaviors in early stage dementia: a study using in-vehicle technology.

According to the Alzheimer's Association (2011), (1) in 8 people age 65 and older, and about one-half of people age 85 and older, have Alzheimer's disease in the United States (US). There is evidence that drivers with Alzheimer's disease and related dementias are at an increased risk for unsafe driving. Recent advances in sensor, computer, and telecommunication technologies provide a method for automatically collecting detailed, objective information about the driving performance of drivers, including those with early stage dementia. The objective of this project was to use in-vehicle technology to describe a set of driving behaviors that may be common in individuals with early stage dementia (i.e., a diagnosis of memory loss) and compare these behaviors to a group of drivers without cognitive impairment. Seventeen drivers with a diagnosis of early stage dementia, who had completed a comprehensive driving assessment and were cleared to drive, participated in the study. Participants had their vehicles instrumented with a suite of sensors and a data acquisition system, and drove 1-2 months as they would under normal circumstances. Data from the in-vehicle instrumentation were reduced and analyzed, using a set of algorithms/heuristics developed by the research team. Data from the early stage dementia group were compared to similar data from an existing dataset of 26 older drivers without dementia. The early stage dementia group was found to have significantly restricted driving space relative to the comparison group. At the same time, the early stage dementia group (which had been previously cleared by an occupational therapist as safe to drive) drove as safely as the comparison group. Few safety-related behavioral errors were found for either group. Wayfinding problems were rare among both groups, but the early stage dementia group was significantly more likely to get lost.

Developing an inverse time-to-collision crash alert timing approach based on drivers' last-second braking and steering judgments.

Drivers were asked to execute last-second braking and steering maneuvers while approaching a surrogate target lead vehicle. This surrogate target was designed to allow safely placing naive drivers in controlled, realistic rear-end crash scenarios under test track conditions. Maneuver intensity instructions were varied so that drivers' perceptions of normal and non-normal braking envelopes could be properly identified and modeled for forward collision warning timing purposes. The database modeled includes 3536 last-second braking judgment trials. A promising inverse time-to-collision model was developed, which assumes that the driver deceleration response in response to a crash alert is based on an inverse time-to-collision threshold that decreases linearly with driver speed.