Culture of distracted driving among intra-city commercial bus drivers in Ile-Ife,South-western Nigeria

This study investigated the culture of driving distractions among commercial bus drivers in Ile-Ife, Southwestern Nigeria. The aim was to identify the most prominent non-driving activity (N-DA) causing distraction to drivers. 16 independent research assistants were engaged in naturalistic recording of 128 commercial bus drivers in the study area. Among the variables selected for observation, passenger scouting (93%), fare collection (89.8%) and money counting (75%) were found to be the frequent N-DAs in their order of importance. These variables (passenger scouting, fare collection and money counting), however, have correlations with drivers having no conductor on-board. More so, relationships existed between certain N-DAs (call making, passenger scouting, fare collection sight-seeing and money counting) and loss of concentration by drivers on one hand; and between loss of concentration and the forms the loss of concentration took. It can be concluded from the findings that driving was disrupted and uncoordinated when combined with non-driving activities.     

Different level automation technology acceptance: Older adult driver opinion

The increase in the number of older adult drivers in developed countries has raised safety concerns due to the decline in their sensory, motor, perceptual, and cognitive abilities which can limit their driving capabilities. Their driving safety could be enhanced by the use of modern Automated Driver Assistance Systems (ADASs) and might totally resolved by full driving automation. However, the acceptance of these technologies by older adult drivers is not yet well understood. Thus, this study investigated older adult drivers’ intention to use six ADASs and full driving automation through two questionnaires with 115 and 132 participants respectively in Rhode Island, USA. A four-dimensional model referred to as the USEA model was used for exploring older adult drivers’ technology acceptance. The USEA model included perceived usefulness, perceived safety, perceived ease of use, and perceived anxiety. Path Analysis was applied to evaluate the proposed model. The results of this study identified the important factors in older adult drivers’ intention to use ADASs and full driving automation, which could assist stakeholders in improving technologies for use by older drivers.     

Distracted driving caused by voice message apps: A series of experimental studies

Hand-free voice message apps are frequently used by young people while driving. Previous studies have identified voice message apps as a common source of driving distraction. To quantitatively evaluate the factors contributing to driving distractions, three simulated driving experiments were designed using a dual-task experimental paradigm. In Experiment 1, participants completed several common tasks related to voice messages in WeChat with or without manual operations (perceptual-motor distraction). Experiments 2 and 3 further took into consideration the cognitive distraction level, measured by task difficulty and task frequency. The results showed that, in comparison with undistracted driving, the perceptual-motor distraction related to voice message app use significantly (ps < 0.05) weakened young drivers’ driving performance with respect to the standard deviation of lateral position (SDLP) between two cars (0.24 m), response time (0.21 s) and error rate (0.12) to turning lights, and collision percentage (0.54%), similar to the effects induced by non-voice-based apps. There were also significant differences (ps < 0.05) between driving with secondary tasks with and without continuous manual operations in the SDLP between two cars (0.19 m) and in the response time (0.18 s) and error rate (0.10) to turning lights, which indicates that the distracting effect produced by voice-message apps comes from the related manual operations. The effects of cognitive distraction on driving performance mainly depended on task difficulty level. High-difficulty secondary tasks via a voice message app significantly (ps < 0.05) weakened the driving performance in response time (by 0.13 s and 0.13 s compared to low-difficulty and baseline conditions, respectively) and error rate (by 0.07 and 0.07 compared to low-difficulty and baseline conditions, respectively) to turning lights and collision percentage (by 0.90% and 0.80% compared to low-difficulty and baseline conditions, respectively). The findings provide a theoretical reference for analysing the distracting components of voice messages and suggest that drivers should limit the use of these kinds of apps during driving.     

Dual-task decrements in driving performance: The impact of task type,working memory,and the frequency of task performance

Driving while carrying out another (secondary) task interferes with performance, though the degree of interference may vary between tasks and individual drivers. In this study, we focused on two potentially interrelated individual difference variables that may play a role in determining dual-task interference: working memory capacity and the driver’s experience with the relevant secondary task. We used a driving simulator to measure interference, comparing single-task performance (driving alone) with driving performance during three secondary tasks: conversing on a handsfree cellphone, texting, and selecting a song on a touchscreen Mp3 player. Drivers also rated the difficulty of driving while carrying out each secondary task. For the individual difference variables, working memory was measured using the Operation Span test (OSPAN), and experience was assessed in terms of self-reported daily driving exposure and exposure to the relevant secondary tasks (frequency, duration). Overall, we found evidence of dual-task interference, though interference varied between tasks; the texting and Mp3 tasks produced significantly more interference than handsfree cellphone conversation. For the texting and Mp3 song selection tasks, interference was apparent in terms of increased steering variability, but for the Mp3 task there was also compensatory slowing, with drivers slowing down while carrying out the task. OSPAN performance and daily driving exposure were both covariates in predicting the amount of dual-task interference. However, our results suggest that in all but two cases, both involving the texting task, the effects of the OSPAN and the driving and secondary task exposure variables were independent rather than interrelated.     

App-based feedback on safety to novice drivers: Learning and monetary incentives

An over-proportionally large number of car crashes is caused by novice drivers. In a field experiment, we investigated whether and how car drivers who had recently obtained their driving license reacted to app-based feedback on their safety-relevant driving behavior (speeding, phone usage, cornering, acceleration and braking). Participants went through a pre-measurement phase during which they did not receive app-based feedback but driving behavior was recorded, a treatment phase during which they received app-based feedback, and a post-measurement phase during which they did not receive app-based feedback but driving behavior was recorded. Before the start of the treatment phase, we randomly assigned participants to two possible treatment groups. In addition to receiving app-based feedback, the participants of one group received monetary incentives to improve their safety-relevant driving behavior, while the participants of the other group did not. At the beginning and at the end of experiment, each participant had to fill out a questionnaire to elicit socio-economic and attitudinal information.We conducted regression analyses to identify socio-economic, attitudinal, and driving-behavior-related variables that explain safety-relevant driving behavior during the pre-measurement phase and the self-chosen intensity of app usage during the treatment phase. For the main objective of our study, we applied regression analyses to identify those variables that explain the potential effect of providing app-based feedback during the treatment phase on safety-relevant driving behavior. Last, we applied statistical tests of differences to identify self-selection and attrition biases in our field experiment.For a sample of 130 novice Austrian drivers, we found moderate improvements in safety-relevant driving skills due to app-based feedback. The improvements were more pronounced under the treatment with monetary incentives, and for participants choosing higher feedback intensities. Moreover, drivers who drove relatively safer before receiving app-based feedback used the app more intensely and, ceteris paribus, higher app use intensity led to improvements in safety-related driving skills. Last, we provide empirical evidence for both self-selection and attrition biases.     

Do aggressive driving and negative emotional driving mediate the link between impulsiveness and risky driving among young Italian drivers?

ABSTRACT

The present study examined the contribution of impulsiveness and aggressive and negative emotional driving to the prediction of traffic violations and accidents taking into account potential mediation effects. Three hundred and four young drivers completed self-report measures assessing impulsiveness, aggressive and negative emotional driving, driving violations, and accidents. Structural equation modeling was used to assess the direct and indirect effects of impulsiveness on violations and accidents among young drivers through aggressive and negative emotional driving. Impulsiveness only indirectly influenced drivers’ violations on the road via both the behavioral and emotional states of the driver. On the contrary, impulsiveness was neither directly nor indirectly associated with traffic accidents. Therefore, impulsiveness modulates young drivers’ behavioral and emotional states while driving, which in turn influences risky driving.     

Hazard perception performance and visual scanning behaviours: The effect of sleepiness

Driver sleepiness accounts for a substantial proportion of crashes in Australia and Worldwide. Young adults are overrepresented in sleep-related crashes and are more susceptible to sleepiness, resulting in impaired attention and driving performance. Visual scanning behaviour can affect the role between attention and information acquisition from the driver's environment. Thus, if attention is impaired, visual scanning behaviours are likely to show decrements as well. Overall, 32 young adults aged between 20 and 25 years completed a 60-minute hazard perception task to examine the effect of sleepiness and time-on-task on hazard perception performance, visual scanning behaviours, subjective sleepiness scores, and psychomotor vigilance test performance. The main outcomes include decrements in hazard perception performance and a restriction in horizontal and vertical eye scanning ranges across the 60-minute session, but with a more pronounced effect when sleep-restricted. These outcomes were consistent with increases in subjective sleepiness and behavioural metrics of sleepiness assessed via the PVT. Reductions in scanning range could limit opportunities to attend to hazards and other critical safety events. The current study outcomes provide an important contribution regarding the risks associated with sleepy driving performance.     

An online hazard perception training course reduces heavy braking,speeding, and over-revving rates during everyday driving

In essence, driver training involves learning the skills required to drive safely and avoid dangerous events. However, in traditional on-road driver instruction, drivers virtually never accrue experience of the most significant types of events that they are learning to avoid: crashes. One means of providing this experience safely is to present novice drivers with video clips of real crashes, as part of structured learning exercises. A six-week automated online hazard perception training course for drivers, incorporating evidence-based training methods and over a hundred crash clips, was previously found to improve novice drivers’ hazard perception skill, which is known to be an important attribute for avoiding crashes. However, since hazard perception was measured using computer-based methods, the possibility remained that the training effect might not transfer to actual driving. We report a randomized control trial in which novice drivers were recruited to assess everyday driving behaviour objectively, using g-force triggered dashcams and GPS trackers installed in their vehicles. On-road data were collected for a one-month baseline period, and for a further two months after half of the sample completed the hazard perception training course. Drivers who completed the course significantly reduced their rate of heavy-braking events, their speeding behaviour, and their rate of over-revving events. These findings support the proposal that a relatively inexpensive and highly scalable hazard perception training intervention can improve on-road driving behaviour, with the clear potential to impact real-world driver safety.     

Professional drivers’ fatigue as a problem of the modern era

ObjectiveAll around the world numerous studies have been carried out and indicated that 20–50% of commercial vehicle accidents occur because of fatigue. Professional drivers represent an important category of drivers who are present in traffic on a daily basis transporting passengers or goods and their responsibility is at a very high level. These drivers are most exposed to the impact of fatigue. The review of the literature has provided three main factors which can influence the onset of fatigue: sleep factors, work factors, health factors. The main aim of this study was to determine the influence of the three main factors of fatigue between bus and truck drivers in the Republic of Serbia.MethodsThe survey has been conducted among bus and truck drivers who are employed in transportation companies across the Republic of Serbia. The research consists of collecting and analyzing bus and truck drivers’ answers according to the above mentioned factors which influence the occurrence of fatigue.ResultsIn this study we have found that circadian rhythm, sleep and work factors have an impact on drivers’ fatigue. On the other side, time of going to sleep has no impact on the quality of sleep and on fatigue. The results show that if the drivers work over the legal limit, they are 3 times more likely to sleep less than 6 h in 24 h and if they sleep less than 6 h, it is likely that the poor quality of their sleep will be 8 times higher. The poor quality of sleep reduces driver performance, and therefore increases the risk of accidents.Conclusions2 of 3 investigated factors have an impact on the occurrence of fatigue. The third factor, health factor, should be examined in more detail, and other elements should be analysed in order to determine their influence on the fatigue.     

Driving manoeuvre during lane maintenance in older adults: Associations with neuropsychological scores

Older drivers experience difficulties in lane maintenance under challenging driving sections due to age-related cognitive declines, yet there is little comprehensive evidence on associations between cognitive functions and the lane maintenance in this population. In this study, fifty older drivers completed an on-road driving assessment and a battery of standard neuropsychological tests. Mean Lane Position (MLP), Standard Deviation of Lane Position (SDLP) and manoeuvre time calculated from precise vehicle movement trajectories were used as the lane maintenance parameters. The GNSS tracking vehicle movement presents comprehensive and reliable vehicle position data, which is more sensitive for detecting subtle variations of lane maintenance in older drivers. Statistical analysis results showed that lower visual attention (selective and divided attention) was associated with higher MLP and SDLP; MLP was also correlated to spatial abilities, executive function, and motor speed; manoeuvre time was negatively correlated with drivers’ risk-taking personality (all p < .01). Selective attention was found to be the best predictor of MLP in lane maintenance. A combined eight variables from three neuropsychological tests, UFOV 2 and 3, BD and BJLO, D-KEFS TMT 1, 2, 3, and 4, correctly classified 80.4% of participants with good versus low-performing lane maintenance.