Standard driver education in the United States focuses on basic skills and the knowledge needed to pass licensure examinations. Newly licensed teen drivers are at high risk of crashes and death. To ...date, few interventions have addressed advanced driving skills that are not taught in typical driver education programs. We investigated the effect of a single day advanced driver training course on crash-avoidance skills. We enrolled 785 teens in a controlled quasi-experimental trial of advanced driver training (ADT: “intervention group”) versus a waitlist comparison group. The ADT consisted of 2 h of classroom education and repeated execution, with instruction and feedback, of four driving skill drills on a controlled, closed course. The comparison group performed each drill once per assessment, with only basic instruction. We measured their ability to successfully execute the driving skill drills (i.e., slalom, wet braking and steering, emergency lane change, and spin avoidance) on the day of the ADT and 3 to 6 months after the baseline skills assessment. The intervention group improved more than the comparison group, particularly in the spin avoidance skills, including spin avoidance, keeping the car on the course, and maintaining an appropriate speed during the drill. Further exploration of the ADT concept as an improvement to driver education and safety is warranted.
Solar photovoltaic technology is one of the most important resources of renewable energy. However, the current solar photovoltaic systems have significant drawbacks, such as high costs compared to ...fossil fuel energy resources, low efficiency, and intermittency. Capturing maximum energy from the sun by using photovoltaic systems is challenging. Several factors that affect the energy output of such systems include the photovoltaic material, geographical location of solar irradiances, ambient temperature and weather, angle of sun incidence, and orientation of the panel. This study reviews the principles and mechanisms of photovoltaic tracking systems to determine the best panel orientation. The tracking techniques, efficiency, performance, advantages, and disadvantages of simple tracking systems are compared with those of state-of-the-art tracking systems. Diverse types of solar tracking systems based on their technologies and driving methods will be presented and categorized.The future trends of tracking systems are also highlighted.
•Learner and provisionally licensed drivers reported similar levels of risky driving behaviours.•Self-determination theory explained engagement in risky driving behaviours.•Self-regulatory processes ...used by Learners and provisionally licensed drivers differed.•Perceived pressure by novice drivers inhibited self-regulation for distractive behaviours.•Effort towards safe driving indicates self-regulation and reduced deliberate risky driving.
Risky driving behaviours are a known contributor to young drivers’ overrepresentation in road trauma, with self-regulation suggested as an important associated construct, but yet to be extensively explored. The aims of this study were to examine the utility of self-determination theory in explaining risky driving behaviours and to explore differences between young Learner and Provisional (P1)- licensed drivers in regard to their self-regulated safety orientation and engagement in risky driving behaviours. Learners (n = 1038) and P1(n = 589) drivers, aged 16–19 years, responded to a 91-item online survey, including self-regulated safety orientation items adapted from self-determination theory and inattentive and intentional risky driving behaviour items. Results showed that self-determination theory had good predictive power for the two types of risky driving behaviours for both licence groups. Learner and P1 drivers’ engagement in risky behaviours was similar, however, the relative importance of self-regulated safety orientation elements to reduced engagement in these behaviours differed. Learners’ engagement in intentional risky behaviours reflected greater perceived effort/importance and pressure/tension compared to P1 drivers. Greater effort/importance is an overarching indicator of internalised regulation concerning safe driving behaviours, which might be primed when first exposed to driving. However, greater perceived pressure/tension suggests that internalisation of self-regulatory processes is being suppressed during the Learner phase. This might stem from the required presence of driver trainers and supervisory drivers, as well as interactions with other road users. Whilst only tentative explanations in this first exploration, the findings suggest there is potential for greater efforts in Learner driver training and supervision to encompass the types of skills and learning that encourage the development of self-regulation to reduce risky driving behaviours during both the Learner and P1 stage. These findings contribute to the limited research regarding self-regulation by young novice drivers and informs a better understanding of the psychological influences of engagement in risky driving behaviours, including the first such examination among early independent licensed drivers.
•Young drivers are not homogenous and have different driving styles.•Young drivers were classified as either careful or careless drivers.•A training program was developed to improve young drivers’ ...cognitive skills.•Training improved the performance of only careful drivers, not careless drivers.
Drivers aged 16–24 are overrepresented in fatal crashes compared to middle-aged, more experienced drivers. This age-related difference in crash rates partly arises from younger drivers’ poorer performance on three cognitive skills known to be related to crash involvement: hazard anticipation, hazard mitigation and attention maintenance. Training programs have been shown effective at improving these skills within a short period of time. However, young drivers are not homogenous and they have different driving styles. The driving styles can interact with driving skills by influencing both their acquisition and, once acquired, their execution. A study was undertaken on a driving simulator to determine whether the effectiveness of an already existing training program aimed at improving the three above mentioned skills is moderated by driving style. In particular, drivers were classified as either careful or careless drivers based both on their scores on measures designed to evaluate two general traits relevant to discriminating between careful and careless drivers (sensation seeking and aggressiveness) as well as on their scores designed to evaluate driving specific behaviors that discriminate between careful and careless drivers (aggressive driving behaviors and driving violations and errors). It was found that training improved the hazard anticipation and attention maintenance performance of only the careful drivers, not the careless drivers.
Objectives: Fatigue among truck drivers has been studied extensively; however, less is known regarding the fatigue experience of taxi drivers in heavily populated metropolitan areas. This study aimed ...to compare the differences and similarities between truck and taxi driver fatigue to provide implications for the fatigue management and education of professional drivers.
Methods: A sample of 274 truck drivers and 286 taxi drivers in Beijing was surveyed via a questionnaire, which included items regarding work characteristics, fatigue experience, accident information, attitude toward fatigue, and methods of counteracting fatigue.
Results: Driver fatigue was prevalent among professional drivers, and it was even more serious for taxi drivers. Taxi drivers reported more frequent fatigue experiences and were involved in more accidents. Among the contributing factors to fatigue, prolonged driving time was the most important factor identified by both driver groups. Importantly, the reason for the engagement in prolonged driving was neither due to the lack of awareness concerning the serious outcome of fatigue driving nor because of their poor detection of fatigue. The most probable reason was the optimism bias, as a result of which these professional drivers thought that fatigue was more serious for other drivers than for themselves, and they thought that they were effective in counteracting the effect of fatigue on their driving performance. Moreover, truck drivers tended to employ methods that require stopping to counteract fatigue, whereas taxi drivers preferred methods that were simultaneous with driving. Although both driver groups considered taking a nap as one of the most effective means to address fatigue, this method was not commonly used. Interestingly, these drivers were aware that the methods they frequently used were not the most effective means to counteract fatigue.
Conclusions: This study provides knowledge on truck and taxi drivers' characteristics in fatigue experience, fatigue attitude, and fatigue countermeasures, and these findings have practical implications for the fatigue management and education of professional drivers.
▶ Male and teen drivers reported more risky driving than female and adult drivers. ▶ Positive affect and perceived risk mediated the age and gender effects. ▶ Positive affect predicted risky driving ...more strongly for teen than adult drivers. ▶ Positive affect also predicted risky driving more strongly for male than female drivers. ▶ Future research should investigate how to reduce positive affect toward driving.
A phone survey of 504 teen (age 16–20) and 409 adult (age 25–45) drivers in the US state of Alabama was conducted to examine the relationships among risk perception, positive affect and risky driving. Male drivers reported engaging in risky driving behaviors more frequently than female drivers and teen drivers reported engaging in risky driving behaviors more frequently than adult drivers. Positive affect (liking for risky driving behaviors) and perceived risk mediated the relationships of age and gender with risky driving. Affect and risk perception were independent predictors of risky driving behavior. Interactions of positive affect and perceived risk with gender and age showed that positive affect more strongly predicted risky driving for teen and male drivers than for adult and female drivers. These findings are interpreted in the context of dual process models of behavioral decision making. Future research into interventions designed to moderate the positive affect surrounding driving may have promise for reducing risky driving behavior.
Distracted driving is one of the most significant human factor issues in transport safety. Mobile phone interactions while driving may involve a multitude of cognitive and physical resources that ...result in inferior driving performance and reduced safety margins. The current study investigates characteristics of usage, risk factors, compensatory strategies in use and characteristics of high-frequency offenders of mobile phone use while driving. A series of questions were administered to drivers in Queensland (Australia) using an on-line questionnaire. A total of 484 drivers (34.9% males and 49.8% aged 17-25) participated anonymously. At least one of every two motorists surveyed reported engaging in distracted driving. Drivers were unable to acknowledge the increased crash risk associated with answering and locating a ringing phone in contrast to other tasks such as texting/browsing. Attitudes towards mobile phone usage were more favourable for talking than texting or browsing. Lowering the driving speed and increasing the distance from the vehicle in front were the most popular task-management strategies for talking and texting/browsing while driving. On the other hand, keeping the mobile phone low (e.g. in the driver's lap or on the passenger seat) was the favourite strategy used by drivers to avoid police fines for both talking and texting/browsing. Logistic regression models were fitted to understand differences in risk factors for engaging in mobile phone conversations and browsing/texting while driving. For both tasks, exposure to driving, driving experience, driving history (offences and crashes), and attitudes were significant predictors. Future mobile phone prevention efforts would benefit from development of safe attitudes and increasing risk literacy. Enforcement of mobile phone distraction should be re-engineered, as the use of task-management strategies to evade police enforcement seems to dilute its effect on the prevention of this behaviour. Some countermeasures and suggestions were proposed in the design of public education campaigns and driver-mobile phone interaction.
•Performance on response inhibition tasks improved with training.•Training refined in a series of two studies in order to promote transfer.•Very little evidence of less risky simulated driving after ...training.•Weak and inconsistent relationships between behavioural and self-report measures of impulse control.
There is growing interest in young driver training that addresses age-related factors, including incompletely developed impulse control. Two studies investigated whether training of response inhibition can reduce risky simulated driving in young drivers (aged 16–24 years). Each study manipulated aspects of response inhibition training then assessed transfer of training using simulated driving measures including speeding, risky passing, and compliance with traffic controls. Study 1 (n = 65) used a Go/No-go task, Stop Signal Task and a Collision Detection Task. Designed to promote engagement, learning, and transfer, training tasks were driving-relevant and adaptive (i.e. difficulty increased as performance improved), included performance feedback, and were distributed over five days. Control participants completed matching “filler” tasks. Performance on trained tasks improved with training, but there was no significant improvement in simulated driving. Study 2 enhanced response inhibition training using Go/No-go and SST tasks, with clearer performance feedback, and 10 days of training. Control participants completed testing only, in order to avoid any possibility of training response inhibition in the filler tasks. Again performance on trained tasks improved, but there was no evidence of transfer of training to simulated driving. These findings suggest that although training of sufficient interest and duration can improve response inhibition task performance, a training schedule that is likely to be acceptable to the public does not result in improvements in simulated driving. Further research is needed to investigate whether response inhibition training can improve risky driving in the context of real-world motivations for risky driving.
Driving can be dangerous, especially for young and inexperienced drivers. To help address the issue of inexperience, a gamified logbook smartphone application was designed and developed for learner ...drivers in Queensland, Australia. The application aims to make it easy for learner drivers to record their mandatory practice sessions while the added gamification aims to encourage learners to undertake a wider range of practice. Previous research reported on a lab-based study of a gamified version and a non-gamified version of this application. This paper presents an updated design of the application and investigates the effect of the application when tested in the field. Results are provided from a within-groups field study undertaken with 25 learner drivers over a four-week period, during which the effect of the gamification on behavior change, perceived motivation and user experience was studied. Although results suggest that the gamified logbook was perceived as more enjoyable and motivating than the non-gamified version, no significant change in behavior was found. This encourages discussion on the effectiveness of gamification to encourage behavior change and the feasibility of using gamification in this particular context.
•A gamified learner logbook app was compared to a non-gamified version in the field.•User enjoyment and perceived motivation was higher when using the gamified version.•There was no increase in behavior when using the gamified version.
•We demonstrate the use of multilevel modeling to examine variability in driving behaviors.•Distracted driving varied within and between drivers in a naturalistic driving study.•Cell phone use and ...reaching behaviors varied more across trips than across people.•Simulated daily sleep demonstrates how predictors of driving can vary within a person.
Current methods of analyzing data from naturalistic driving studies provide important insights into real-world safety-related driving behaviors, but are limited in the depth of information they currently offer. Driving measures are frequently collapsed to summary levels across the study period, excluding more fine-grained differences such as changes that occur from trip to trip. By retaining trip-specific data, it is possible to quantify how much a driver differs from trip to trip (within-person variability) in addition to how he or she differs from other drivers (between-person variability). To the authors’ knowledge, the current study is the first to use multilevel modeling to quantify variability in distracted driving behavior in a naturalistic dataset of older drivers. The current study demonstrates the utility of examining within-person variability in a naturalistic driving dataset of 68 older drivers across two weeks. First, multilevel models were conducted for three distracted driving behaviors to distinguish within-person variability from between-person variability in these behaviors. A high percentage of variation in distracted driving behaviors was attributable to within-person differences, indicating that drivers’ behaviors varied more across their own driving trips than from other drivers (ICCs = .93). Then, to demonstrate the utility of personal characteristics in predicting daily driving behavior, a hypothetical model is presented using simulated daily sleep duration from the previous night to predict distracted driving behavior the following day. The current study demonstrates substantial variability in driving behaviors within an older adult sample and the promise of individual characteristics to provide better prediction of driving behaviors relevant to safety, which can be applied in investigations of current naturalistic driving datasets and in designing future studies.
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