Driving on familiar roads: Automaticity and inattention blindness

This paper describes our research into the processes that govern driver attention and behavior in familiar, well-practiced situations. The experiment examined the effects of extended practice on inattention blindness and detection of changes to the driving environment in a high-fidelity driving simulator. Participants were paid to drive a simulated road regularly over 3 months of testing. A range of measures, including detection task performance and driving performance, were collected over the course of 20 sessions. Performance from a yoked Control Group who experienced the same road scenarios in a single session was also measured. The data showed changes in what drivers reported noticing indicative of inattention blindness, and declining ratings of mental demand suggesting that many participants were “driving without awareness”. Extended practice also resulted in increased sensitivity for detecting changes to road features associated with vehicle guidance and improved performance on an embedded vehicle detection task (detection of a specific vehicle type). The data provide new light on a “tandem model” of driver behavior that includes both explicit and implicit processes involved in driving performance. The findings also suggest reasons drivers are most likely to crash at locations very near their homes.     

The impact of navigation system display size and environmental illumination on young driver mental workload

Driver distraction is a major cause of road crashes and has a great influence on road safety. In vehicles, one of the common distracting sources is navigation systems (NSs). The navigation system (NS) can distract the driver due to following directions and reading the provided information through its display. These tasks take the driver’s attention from the primary task of driving and may cause poor driving performance, increasing the risk of crashes. In this paper, the effect of the environment (i.e., urban areas and rural areas), the navigation system display (NSD) size, environmental illumination, and gender on young drivers between the ages of 18 and 29 years mental workload was investigated using a simulated driving experiment. To evaluate each driving condition, the NASA-TLX (NASA Task Load Index) workload assessment tool, and a distraction evaluation element, were introduced and used to assess the overall workload, the workload subscales and the distraction by the NSD. The assessment showed a higher perceived overall workload for urban areas and night driving as compared to a rural areas and daytime driving. Moreover, the results showed a greater perceived distraction by the NSD in urban areas compared to driving in rural areas. The subjects also felt distracted when using the small NS compared to using the large NS. The study concluded that urban areas driving, and night driving creates higher perceived workload than rural areas and daytime driving. Furthermore, small NSD leads to more perceived distraction than large NSD while driving. The NSD designers may utilize this research findings to optimize NSD designs to improve driving safety, performance and comfort. Moreover, this study contributes to our understanding of the effect of the NSD size on driving workload and distraction.     

New parents and driver safety: What’s sleep got to do with it? A systematic review

Fatigue-related motor vehicle crashes are common worldwide and have been addressed by a range of road safety campaigns. These campaigns are typically directed towards at-risk groups (e.g., heavy vehicle drivers), who may be likely to experience fatigue resulting from reduced or disrupted sleep opportunities. Another population likely to experience sleep loss and disruption is new parents. The sleep of new parents is likely to be significantly disrupted by childcare responsibilities. As such, new parents may also be likely to experience fatigue while driving. A systematic review of five databases (PubMed, Cumulative Index to Nursing and Allied Health Literature, PsycINFO, EMBASE, and the Cochrane Central Register of Controlled Trials) was performed to identify what research is currently available on sleep, fatigue, and driving in new parents. A total of twelve documents were included in this review. A synthesis of findings suggests new parents are at risk of fatigued driving – though the amount and quality of evidence available is limited. A research agenda is proposed to address the limitations of this field of research.     

Differential effects of driver sleepiness and sleep inertia on driving behavior

ObjectivesDriver sleepiness is one of the major safety issues in conventional driving and sleep inertia emerges as a driver state in automated driving. The aim of the present study was to assess the differential impacts of sleepiness and sleep inertia on driving behavior.Method61 participants completed a 10-min manual driving task during an otherwise automated drive. They completed the task (a) under an alert state, (b) under a sleepy state, and (c) after EEG-confirmed sleep. Driving performance was assessed with the parameters lane-keeping, speed choice, and speed-keeping. The eye-blink-based sleepiness measure PERCLOS (the proportion of time with eyes closed) was compared for the three driver states.ResultsLane- and speed-keeping performance were impaired under the sleepy state and after sleep, relative to the alert state. After sleep, lane-keeping behavior recovered rapidly and speed-keeping recovered by trend. Under the sleepy state, performance deteriorated. After sleep, the mean speed was lower than in the sleepy state and in the alert state. PERCLOS was increased after sleep and under the sleepy state, relative to the alert state.ConclusionsAlthough sleep inertia had detrimental effects on driving parameters similar to sleepiness, this effect rapidly vanished. Hence, while brief naps might be suitable to restore alertness in general, the minimal time needed to regain full capacity after napping should be a focus of future research.     

Younger drivers executive functioning and the relationship with experiencing signs of sleepiness

Young drivers are more likely to continue driving when experiencing signs of sleepiness and are over-represented in sleep-related crashes. Adolescence and early adulthood are characterised by comparatively poor executive functioning, and while previous research has demonstrated a link between poor executive functions and several risky driving behaviours, the relationship with sleepy driving is not well understood. Accordingly, the first aim of the current study was to examine the association between executive functions and experiencing the signs of driver sleepiness in a sample of young adult drivers. Additionally, young drivers who have less experience with driving while sleepy, may attribute less importance to the signs of sleepiness as an indicator of underlying sleepiness level. To test this assumption (aim two), the impact of experiencing signs of sleepiness on perceptions of the importance of those signs was examined. Participants included 118 young adults aged between 17 and 25 years, who completed an online survey measuring experiences with the signs of sleepiness while driving, executive functions, and demographic characteristics. This sample of young adults reported having considerable experience with several signs of sleepiness (i.e., yawning, mind wandering, and difficulty keeping eyes while driving). A linear regression analysis found that the demographic variables of age and hours driven per week, as well as the executive function constructs of organization, strategic planning, and impulse control were associated with experiencing signs or sleepiness. Moreover, having experienced more signs of sleepiness was associated with an increased likelihood in rating those signs as important indicators of sleepiness. The current findings suggest both that several high-level cognitive processes as well as levels of experience with driving when experiencing signs of sleepiness contribute to young peoples’ sleepy driving.     

Contributory factors to sleepiness amongst London bus drivers

Driver sleepiness contributes to a substantial proportion of all road crashes. Despite all that is known about driver sleepiness, bus drivers are often overlooked. What is certain is that bus drivers have the potential to suffer from sleepiness as they are shift workers. The current research used a large online survey to investigate sleepiness amongst London bus drivers. There were two aims; to quantify the prevalence of sleepiness amongst London bus drivers, and to determine the factors which contributed to sleepiness. Overall, 20.8% of respondents indicated that they had to fight sleepiness at least 2–3 times a week, and 36.6% of respondents stated that they had experienced a close call due to sleepiness in the past year. There were several potential causes of sleepiness including work, sleep, and personal factors such as obtaining less than 11 h rest between shifts, working 6 or more days without a rest day, and poor self-reported health. These findings show that sleepiness is common amongst London bus drivers and is caused by a combination of factors. The combination of contributory factors suggests that a multifaceted approach should be taken to reduce bus driver sleepiness.     

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.     

Mapping visual attention with change blindness: new directions for a new method

Change blindness provides a new technique for mapping visual attention with unprecedented spatial and temporal resolution. Change blindness can occur when a brief full-field blank interferes with the detection of changes in a scene that occur during the blank. This interference can be overcome by attending to the location of a change. Because changes are detected at attended locations, but not at unattended locations, detection accuracy provides an indirect measure of the distribution of visual attention. The likelihood of detecting a new element in a scene provides a measure of the occurrence of attention at that element’s location. Potential new directions, advantages, and problems with this method are considered.     

Identifying behavioural change among drivers using Long Short-Term Memory recurrent neural networks

Globally, motor vehicle crashes account for over 1.2 million fatalities per year and are the leading cause of death for people aged 15–29 years. The majority of road crashes are caused by human error, with risk heightened among young and novice drivers learning to negotiate the complexities of the road environment. Direct feedback has been shown to have a positive impact on driving behaviour. Methods that could detect behavioural changes and therefore, positively reinforce safer driving during the early stages of driver licensing could have considerable road safety benefit. A new methodology is presented combining in-vehicle telematics technology, providing measurements forming a personalised driver profile, with neural networks to identify changes in driving behaviour. Using Long Short-Term Memory (LSTM) recurrent neural networks, individual drivers are identified based on their pattern of acceleration, deceleration and exceeding the speed limit. After model calibration, new, real-time data of the driver is supplied to the LSTM and, by monitoring prediction performance, one can assess whether a (positive or negative) change in driving behaviour is occurring over time. The paper highlights that the approach is robust to different neural network structures, data selections, calibration settings, and methodologies to select benchmarks for safe and unsafe driving. Presented case studies show additional model applications for investigating changes in driving behaviour among individuals following or during specific events (e.g., receipt of insurance renewal letters) and time periods (e.g., driving during holiday periods). The application of the presented methodology shows potential to form the basis of timely provision of direct feedback to drivers by telematics-based insurers. Such feedback may prevent internalisation of new, risky driving habits contributing to crash risk, potentially reducing deaths and injuries among young drivers as a result.     

Absorbed in sleep: Dissociative absorption as a predictor of sleepiness following sleep deprivation in two high-functioning samples

In recent years, a labile sleep-wake cycle has been implicated as a cause for dissociative experiences, and studies show that dissociation is elevated following sleep deprivation. Dissociative individuals may find it harder to regulate sleepiness in the face of sleep disruption. Although there is significant variability in reactions to sleep deprivation, research on trait predictors is scarce. The present study examined the ability of trait dissociation to prospectively predict sleepiness following sleep loss and recovery sleep. Two high-functioning samples, namely, Remotely Piloted Aircraft officers (N = 29) and Air Force jet pilots (N = 57) completed state and trait questionnaires assessing sleep and dissociation before and after full or partial sleep loss. Dissociative absorption was a consistent predictor of an increase in sleepiness following sleep loss and following recovery sleep, controlling for baseline sleepiness levels. We discuss the findings in light of a difficulty to regulate and monitor consciousness states.     

A fuzzy-based driver assistance system using human cognitive parameters and driving style information

Reducing the number of traffic accidents due to human errors is an urgent need in several countries around the world. In this scenario, the use of human-robot interaction (HRI) strategies has recently shown to be a feasible solution to compensate human limitations while driving. In this work we propose a HRI system which uses the driver’s cognitive factors and driving style information to improve safety. To achieve this, deep neural networks based approaches are used to detect human cognitive parameters such as sleepiness, driver’s age and head posture. Additionally, driving style information is also obtained through speed analysis and external traffic information. Finally, a fuzzy-based decision-making stage is proposed to manage both human cognitive information and driving style, and then limit the maximum allowed speed of a vehicle. The results showed that we were able to detect human cognitive parameters such as sleepiness –63% to 88% accuracy–, driver’s age –80% accuracy– and head posture –90.42% to 97.86% accuracy– as well as driving style –87.8% average accuracy. Based on such results, the fuzzy-based architecture was able to limit the maximum allowed speed for different scenarios, reducing it from 50 km/h to 17 km/h. Moreover, the fuzzy-based method showed to be more sensitive with respect to inputs changes than a previous published weighted-based inference method.     

Pigeons (<Emphasis Type="Italic">Columba livia</Emphasis>) show change blindness in a color-change detection task

Change blindness is a phenomenon whereby changes to a stimulus are more likely go unnoticed under certain circumstances. Pigeons learned a change detection task, in which they observed sequential stimulus displays consisting of individual colors back-projected onto three response keys. The color of one response key changed during each sequence and pecks to the key that displayed the change were reinforced. Pigeons showed a change blindness effect, in that change detection accuracy was worse when there was an inter-stimulus interval interrupting the transition between consecutive stimulus displays. Birds successfully transferred to stimulus displays involving novel colors, indicating that pigeons learned a general change detection rule. Furthermore, analysis of responses to specific color combinations showed that pigeons could detect changes involving both spectral and non-spectral colors and that accuracy was better for changes involving greater differences in wavelength. These results build upon previous investigations of change blindness in both humans and pigeons and suggest that change blindness may be a general consequence of selective visual attention relevant to multiple species and stimulus dimensions.     

The self-reported causes of sleepiness in shift-working tram and truck drivers

Identifying the causes of sleepiness in various safety-critical work environments is necessary for implementing more efficient fatigue management strategies. In transportation, little is known about drivers’ own perceptions of these causes. Therefore, we instructed shift-working tram (n = 23) and long-haul truck drivers (n = 52) to report at the end of their shifts what made them sleepy if they felt so. These self-reports, measured on-duty sleepiness, and sleep amounts were recorded on every shift over a period of 2–3 weeks per driver. The causes of sleepiness were queried with smartphone applications and sleep logs. Sleepiness was measured with the Karolinska Sleepiness Scale (KSS) and sleep with wrist-worn actigraphs. Data were analyzed using generalized estimating equations. Sleep loss and insufficient rest breaks were commonly reported as causing sleepiness among the tram drivers, whereas time of day and sleep loss were the leading causes among the truck drivers. Other causes, such as traffic or cabin conditions, were not frequently mentioned. During morning, day, and evening shifts, the truck drivers were less likely to report insufficient rest breaks as causing sleepiness than the tram drivers. Similarly, during morning shifts, the truck drivers were less likely to attribute their sleepiness to sleep loss. In shifts with drives reporting severe sleepiness (KSS ≥ 7 at least once, 18–21% of shifts), sleep loss was significantly reported as causing sleepiness among both groups. Reporting insufficient rest breaks was associated with severe sleepiness among the tram drivers, whereas time of day showed the same among the truck drivers. The results highlight the need for addressing sleep-related fatigue in transportation and provide directions for future research with regard to secondary causes of sleepiness.     

Intraindividual variability in driving simulator parameters of healthy drivers of different ages

Intraindividual variability is a fundamental behavioural characteristic of aging but has been examined to a very limited extent in driving. This study investigated intraindividual variability in driving simulator measures in healthy drivers of different ages using the coefficient of variation (COV) as a variability measure. Participants were healthy volunteers who were regular drivers, who were divided into a “young” group, a “middle-aged” group, and an “old” group. They drove in two environments (rural, 72 drivers; urban, 60 drivers), under conditions of moderate and high traffic load, without and with distraction (conversation). Significant differences in COV were observed in the rural condition for headway distance and lateral position as a function of traffic load, with high traffic (without and with distraction) resulting in increased COV of headway and decreased COV of lateral position. Significant differences in COV were observed in the urban condition for headway distance only, with high traffic (without and with distraction) resulting in increased COV of headway. No age effects were found for any of the driving conditions. The results indicate that traffic load affected headway distance and lateral position in opposite directions in all three age groups: high traffic resulted in increased variability of headway in both rural and urban conditions but in decreased variability of lateral position in the rural conditions compared to moderate traffic irrespective of distraction. The study indicates that driving conditions affect the intraindividual variability of driving measures in selective ways, which may be linked to the extent of automatization of the driving variables and to adaptive changes to traffic condition challenges.     

Failure to detect changes to people during a real-world interaction

Recent research on change detection has documented surprising failures to detect visual changes occurring between views of a scene, suggesting the possibility that visual representations contain few details. Although these studies convincingly demonstrate change blindness for objects in still images and motion pictures, they may not adequately assess the capacity to represent objects in the real world. Here we examine and reject the possibility that change blindness in previous studies resulted from passive viewing of 2-D displays. In one experiment, an experimenter initiated a conversation with a pedestrian, and during the interaction, he was surreptitiously replaced by a different experimenter. Only half of the pedestrians detected the change. Furthermore, successful detection depended on social group membership; pedestrians from the same social group as the experimenters detected the change but those from a different social group did not. A second experiment further examined the importance of this effect of social group. Provided that the meaning of the scene is unchanged, changes to attended objects can escape detection even when they occur during a natural, real-world interaction. The discussion provides a set of guidelines and suggestions for future research on change blindness.     

A sleep physiologist's view of the drowsy driver

Drowsy driving is dangerous because of the impairment of driving skills that it causes. Unfortunately, the conceptual basis that underlies much of the multi-disciplinary research on this topic is muddled. The same poorly defined terms, such as fatigue and sleepiness, are used differently by different disciplines and researchers. Some new definitions and concepts are proposed here which may be helpful, as least as a stimulus for discussion by others. Drowsiness, sleepiness and fatigue are distinguished. A new conceptual model of sleepiness is outlined, based on a mutually inhibitory interaction between a putative sleep drive and a wake drive. Sleepiness, defined as sleep propensity, is a function of the relative strengths, not the absolute strengths, of the sleep and wake drives. The measurement of sleepiness requires some new variables such as instantaneous sleep propensity, to be distinguished from either the situational or the average sleep propensity. A subject's instantaneous sleep propensity depends on many variables including his average sleep propensity in daily life, the time of day, the duration of prior wakefulness, the subject's posture, physical and mental activity at the time, and individual differences based on psychophysiological traits. The relationship between dozing at the wheel while driving and crashing the vehicle may not be as straightforward as it appears at first.     

Use of change blindness to measure different abilities to detect relevant changes in natural driving scenes

Drivers have to focus their attention on a danger to become aware of it. Change blindness paradigms are therefore relevant to studying the ability to detect danger. However, research has not yet focused on the role of two essential factors in guiding drivers’ attention: driving experience and the specific needs for performing a manoeuvre. Based on a previous analysis of real accident situations, we used a one-shot paradigm with static scenes to test observers’ ability to detect various changes as a function of their driving experience, the manoeuvre envisaged and the environmental context. The results showed that change detection depends greatly on driving experience when planning to cross a junction or to turn left, while it depends more on the environmental setting and task complexity when seeking a direction. The results were not conclusive, however, in explaining how drivers failed to notice that the vehicle ahead of them was turning when they considered an overtaking manoeuvre. We discuss the contributions of our research in relation to the possibilities of using change blindness as a measurement tool in studies on automobile driving.     

Profile of urban vs rural drivers detected drink driving via Roadside Breath Testing (RBT) in Queensland,Australia, between 2000 and 2011

ProblemIn Australia, as in many other countries, a disproportionate number of drink driving crashes occur on rural roads.Aims and methodThe study used Queensland Police Random Breath Testing (RBT) data from 2000–2011 to (a) comparing drink driving rates and RBT efficacy in areas of increasing remoteness (b) compare drink driver factors and the circumstances of apprehensions in rural and urban areas.ResultsGenerally, rural areas had a higher detection rate per RBT intercepts and a greater number of apprehensions per licensed drivers than the state average. Main effects showed that rural drivers were more likely to be male and to be a reoffender but less likely to be apprehended between midnight and 5.59 am and after visiting a licensed venue. Urban drivers were more likely to be aged 17–49 years and to be apprehended with a BAC < 0.15%.ConclusionDifferences in RBT effectiveness and drink driving factors and circumstances exist between rural and urban areas.Practical applicationThe greater number of drink drivers in rural areas signal a need for targeted interventions in these areas. To increase the effectiveness of such interventions, further research should examine the mechanisms responsible for these observed differences between rural and urban drink driver.     

The effect of display timing on change blindness in pigeons (Columba livia)

Change blindness is a phenomenon in which even obvious changes in a visual scene may go unnoticed. Recent research has indicated that this phenomenon may not be exclusive to humans. Two experiments investigated change blindness in pigeons, using a variant of the widely‐used flicker task to investigate the influence of display timing on change blindness. Results indicate that the duration of time during which a stimulus display is visible influences change detection accuracy, with the effect due to additional search time. The results are discussed in relation to the value of comparative cognition and cross‐species investigations of behavior.     

Exploration of the effects of task-related fatigue on eye-motion features and its value in improving driver fatigue-related technology

Mental fatigue has been lacked attention in developing eye-tracking fatigue detection system for drivers. However, it has great influence on eye movement which could account for the poor validity of current fatigue detectors only focusing on sleep-related fatigue. This work sought to investigate the influence of two types of task-related mental fatigue on eye movement by examining 8 saccade-based, 3 blink-based, and 1 pupil-based metrics. We propose that two types of task-related fatigue caused by cognitive overload and prolonged underload will induce different physiological responses to eye-motion features. Twenty participants completed a vigilance task before and after a 1-h driving with a secondary task in a virtual simulation environment, while forty participants, divided equally into two groups, finished the same task before and after a 1-h and 1.5-h monotonous driving. T-test was applied to analyse the eye-motion, subjective and vigilance data during vigilance task. We found that overload driving made drivers vigilance ability decrease. The eye metrics showed different changes in underload and overload scenario. The blink duration, the mean velocity of saccade and saccade duration increased after 1-h overload driving, while the pupil diameter decreased. However, none of those changes were observed in 1.5-h underload driving, but saccade duration had a significant increase. The fatigue response to heavy demands over short periods of driving is different from the lighter demands over long periods in terms of eye-motion metrics. Considering mental fatigue in designing an eye-tracking fatigue detection system could possibly improve its accuracy.