What determines the take-over time? An integrated model approach of driver take-over after automated driving

In recent years the automation level of driver assistance systems has increased continuously. One of the major challenges for highly automated driving is to ensure a safe driver take-over of the vehicle guidance. This must be ensured especially when the driver is engaged in non-driving related secondary tasks. For this purpose it is essential to find indicators of the driver’s readiness to take over and to gain more knowledge about the take-over process in general.     

Traumatic brain injury,driver aggression and motor vehicle collisions in Canadian adults

ObjectiveThis study examines the associations between lifetime traumatic brain injury (TBI), driver aggression, and motor vehicle collisions among a population sample of adults who reside in the province of Ontario, Canada.MethodA cross-sectional sample of 3993 Ontario adults, aged 18–97 were surveyed by telephone in 2011 and 2012 as part of Center for Addiction and Mental Health’s ongoing representative survey of adult mental health and substance use in Canada. TBI was defined as trauma to the head that resulted in loss of consciousness for at least five minutes or overnight hospitalization.ResultsAn estimated 91% (95% CI: 90.0, 91.9) of individuals in this sample held a valid Ontario driver’s license at the time of testing. Among those, 16.7% reported a history of lifetime TBI and 83.3% reported no TBI. The prevalence of TBI was higher among men than women. Relative to licensed adults without TBI, adults with a history of TBI had significantly higher odds of engaging in serious driver aggression in the past 12 months, such as making threats to hurt another driver, passenger or their vehicle (AOR = 4.39). These individuals also reported significantly higher odds (AOR = 1.74) of being involved in a motor vehicle collision that resulted in hurting themselves, their passenger(s) or their vehicle.ConclusionThis is the first population-based study to demonstrate a relationship between a history of TBI and higher rates of serious driver aggression and collision involvement. Given the large proportion of adult drivers with a history of TBI, these individuals may account for a disproportion burden of all traffic safety problems. Whether the increased road safety risk of adults with a history of TBI is reflective of neurocognitive deficits or is merely evidence of a cluster of unsafe activities produced by a higher risk lifestyles requires further research attention.     

An observational study of driving distractions on urban roads in Spain

The present research investigated the prevalence of driver engagement in secondary tasks and whether there were any differences by age and gender, as well as day of the week and time of the day. Two independent researchers observed 6578 drivers at nine randomly selected urban locations in Girona, Spain. Nearly 20% of the drivers observed were engaged in some type of secondary task, with the most common being: conversing with a passenger (11.1%), smoking (3.7%) and talking on a handheld mobile phone (1.3%). Surprisingly there were no differences by gender, but there were age-related differences with younger drivers being more frequently observed engaged in a number of different types of secondary tasks while driving (i.e. drinking, talking on a handheld mobile phone, and texting or keying numbers). Logistic regression showed that younger drivers, and to a lesser extent middle-age drivers, were significantly more likely to be observed engaged in a technological distraction than older drivers. Conversely, non-technological distractions were significantly predicted by day of the week, time of the day and location. A substantial number of the drivers observed in this study were putting themselves at an increased risk of becoming involved in a crash by engaging in non-driving related tasks at the same time as driving. Furthermore, the higher crash rate among young drivers may be partially accounted for by their more frequent engagement in some types of secondary tasks while driving.     

Effects of fog,driver experience and gender on driving behavior on S-curved road segments

Driving on curved roads has been recognized as a significant safety issue for many years. However, driver behavior and the interactions among variables that affect driver performance on curves is complicated and not well understood. Previous studies have investigated various factors that influence driver performance on right- or left-turn curves, but have paid little attention to the effects of foggy weather, driver experience and gender on driver performance on complex curves. A driving simulator experiment was conducted in this study to evaluate the relationships between driving behavior on a continuous S-curve and foggy weather, driver experience and gender. The process of negotiating a curve was divided into three stages consisting of a straight segment, the transition from the straight segment to the S-curve and the S-curve. The experimental results indicated that drivers tended to drive more cautiously in heavy fog, but the driving risk was still increased, especially in the transition stage from the straight segment to the S-curve. The non-professional (NP) drivers were less sensitive to the impending change in the road geometry, and less skilled in both longitudinal and lateral vehicle control than the professional drivers. The NP female drivers in particular were found to be the most vulnerable group in S-curve driving.     

The impact of childhood symptoms of conduct disorder on driver aggression in adulthood

Background

Despite limited empirical investigation, existing scientific literature suggests that individuals with a history or current diagnosis of conduct disorder (CD) may be more likely to demonstrate reckless and aggressive driving. Much of the limited research in this field examines the impact of childhood CD on driver behaviour and collision risk in young adults. Few if any, studies assess the impact of this disorder on driver behaviour beyond age 21 years. The current research is a population-based study of the impact of CD symptoms during childhood on the risk of engaging in driver aggression during adulthood.

Methods

Data are based on telephone interviews with 5230 respondents who reported having driven in the past year. Data are derived from the 2011–2013 cycles of the CAMH Monitor, an ongoing cross-sectional survey of adults in Ontario, Canada aged 18 years and older. A binary logistic regression analysis of self-reported driver aggression in the previous 12 months was conducted, consisting of measures of demographic characteristics, driving exposure, problem substance use, alcohol- and drug-impaired driving, symptoms of attention deficit hyperactivity disorder, and childhood (before age 15) symptoms of CD.

Results

When entered with demographic characteristics, driving exposure, and other potential confounders, childhood symptoms of CD increased the odds of reporting driver aggression more than two-fold (adjusted OR = 2.12). Exploratory analyses of the interaction between childhood symptoms of CD and age was not a significant predictor of driver aggression.

Conclusions

Results suggest that symptoms of CD during childhood are associated with significantly increased odds of self-reported driver aggression during adulthood. Limitations and future directions of the research are discussed.     

On-road experiment to assess drivers’ detection of roadside targets as a function of headlight system,target placement,and target reflectance

Adaptive headlights swivel with steering input to keep the beams on the roadway as drivers negotiate curves. To assess the effects of this feature on driver’s visual performance, a field experiment was conducted at night on a rural, unlit, and unlined two-lane road during which 20 adult participant drivers searched a set of 60 targets. High- (n = 30) and low- (n = 30) reflectance targets were evenly distributed on straight road sections and on the inside or outside of curves. Participants completed three target detection trials: once with adaptive high-intensity discharge (HID) headlights, once with fixed HID headlights, and once with fixed halogen headlights. Results indicated the adaptive HID headlights helped drivers detect targets that were most difficult to see (low reflectance) at the points in curves found by other researchers to be most crucial for successful navigation (inside apex). For targets placed on straight stretches of road or on the outside of curves, the adaptive feature provided no significant improvement in target detection. However, the pattern of results indicate that HID lamps whether fixed or adaptive improved target detection somewhat, suggesting that part of the real world crash reduction measured for this adaptive system (Highway Loss Data Institute (HLDI), 2012a) may be due to the differences in the light source (HID vs. halogen). Depending on the scenario, the estimated benefits to driver response time associated with the tested adaptive (swiveling HID) headlights ranged from 200 to 380 ms compared with the fixed headlight systems tested.     

Real-time driver drowsiness feedback improves driver alertness and self-reported driving performance

Driver drowsiness has been implicated as a major causal factor in road accidents. Tools that allow remote monitoring and management of driver fatigue are used in the mining and road transport industries. Increasing drivers’ own awareness of their drowsiness levels using such tools may also reduce risk of accidents. The study examined the effects of real-time blink-velocity-derived drowsiness feedback on driver performance and levels of alertness in a military setting. A sample of 15 Army Reserve personnel (1 female) aged 21–59 (M = 41.3, SD = 11.1) volunteered to being monitored by an infra-red oculography-based Optalert Alertness Monitoring System (OAMS) while they performed their regular driving tasks, including on-duty tasks and commuting to and from duty, for a continuous period of 4–8 weeks. For approximately half that period, blink-velocity-derived Johns Drowsiness Scale (JDS) scores were fed back to the driver in a counterbalanced repeated-measures design, resulting in a total of 419 driving periods under “feedback” and 385 periods under “no-feedback” condition. Overall, the provision of real-time feedback resulted in reduced drowsiness (lower JDS scores) and improved alertness and driving performance ratings. The effect was small and varied across the 24-h circadian cycle but it remained robust after controlling for time of day and driving task duration. Both the number of JDS peaks counted for each trip and their duration declined in the presence of drowsiness feedback, indicating a dynamic pattern that is consistent with a genuine, entropy-reducing feedback mechanism (as distinct from random re-alerting) behind the observed effect. Its mechanisms and practical utility have yet to be fully explored. Direct examination of the alternative, random re-alerting explanation of this feedback effect is an important step for future research.     

Measuring errors and violations on the road: A bifactor modeling approach to the Driver Behavior Questionnaire

The Driver Behavior Questionnaire (DBQ) is a self-report measure of driving behavior that has been widely used over more than 20 years. Despite this wealth of evidence a number of questions remain, including understanding the correlation between its violations and errors sub-components, identifying how these components are related to crash involvement, and testing whether a DBQ based on a reduced number of items can be effective. We address these issues using a bifactor modeling approach to data drawn from the UK Cohort II longitudinal study of novice drivers. This dataset provides observations on 12,012 drivers with DBQ data collected at .5, 1, 2 and 3 years after passing their test. A bifactor model, including a general factor onto which all items loaded, and specific factors for ordinary violations, aggressive violations, slips and errors fitted the data better than correlated factors and second-order factor structures. A model based on only 12 items replicated this structure and produced factor scores that were highly correlated with the full model. The ordinary violations and general factor were significant independent predictors of crash involvement at 6 months after starting independent driving. The discussion considers the role of the general and specific factors in crash involvement.     

An experimental study of factors associated with driver frustration and overtaking intentions

This study examined directly the impact of various factors associated with driving on ‘A-class’ roads in the United Kingdom (specifically length of platoon, proportion of heavy goods vehicles (HGVs), speed and opportunities for overtaking) on self-reported frustration and overtaking intentions. The impact of situational variables (being under time pressure, and time behind a slower moving platoon) were also examined, as was the association between frustration and self-reported overtaking intentions. 183 members of the public from the areas around Perth and Inverness, Scotland took part in the study. Participants viewed simulated ‘driver’s viewpoint’ clips representing all the combinations of the experimental variables (except time pressure, which was a between-groups variable, and time behind platoon, which was examined separately in four specific clips). After each clip, participants responded on a paper questionnaire as to the level of frustration they would feel for a given clip, and the likelihood that at some point during the clip they would have attempted an overtake manoeuvre. The findings show that the links between traffic variables such as speed and platoon length, and behaviourally-relevant variables such as frustration and overtaking intentions, are not simple. Although there are broad and predictable effects of speed and platoon length (lower speeds and longer platoons leading to greater frustration) these are mediated by other variables, and it is not always the case that more frustration leads to more intention to overtake. Analysis of driver attitudes identified three clusters (low, medium and high risk drivers) and suggests that higher risk drivers’ levels of frustration are more affected by situational changes than those of lower risk drivers.     

Validation of the Driver Behaviour Questionnaire in a representative sample of drivers in Australia

The Driver Behaviour Questionnaire (DBQ) is a widely used measure of driving behaviours that may increase a driver's risk of crash involvement. However, there are several different versions of the DBQ varying in terms of number of items and factor structure. The aim of the current research was to assess the construct validity of the popular 28-item four-factor DBQ solution in a representative sample of drivers in Australia. A further aim was to test the factorial invariance of the measure across gender, age and also between fleet and non-fleet drivers using multigroup confirmatory factor analyses. Data on a range of attitudes towards road safety were collected using an online survey. A stratified sampling procedure was undertaken to ensure the age, gender and location distributions of participants were representative of the Australian population. A total of 2771 responses were obtained from fully licensed motor vehicle drivers (male: 46%). Confirmatory factor analysis supported the 28-item four-factor DBQ in the Australian sample. The DBQ was also found to be gender-invariant and strong partial measurement invariance was found for drivers aged from 26 to 64, but not for younger (17–25) or older (65–75) drivers. Modifications to the DBQ suggest how the DBQ can be improved for use in these two age groups.