Subjective awareness of sleepiness while driving in younger and older adults.

Understanding whether drivers can accurately assess sleepiness is essential for educational campaigns advising drivers to stop driving when feeling sleepy. However, few studies have examined this in real-world driving environments, particularly among older drivers who comprise a large proportion of all road users. To examine the accuracy of subjective sleepiness ratings in predicting subsequent driving impairment and physiological drowsiness, 16 younger (21-33 years) and 17 older (50-65 years) adults drove an instrumented vehicle for 2 h on closed loop under two conditions: well-rested and 29 h sleep deprivation. Sleepiness ratings (Karolinska Sleepiness Scale, Likelihood of Falling Asleep scale, Sleepiness Symptoms Questionnaire) were obtained every 15min, alongside lane deviations, near crash events, and ocular indices of drowsiness. All subjective sleepiness measures increased with sleep deprivation for both age groups (p < 0.013). While most subjective sleepiness ratings significantly predicted driving impairment and drowsiness in younger adults (OR: 1.7-15.6, p < 0.02), this was only apparent for KSS, likelihood of falling asleep, and "difficulty staying in the lane for the older adults" (OR: 2.76-2.86, p = 0.02). This may be due to an altered perception of sleepiness in older adults, or due to lowered objective signs of impairment in the older group. Our data suggest that (i) younger and older drivers are aware of sleepiness; (ii) the best subjective scale may differ across age groups; and (iii) future research should expand on the best subjective measures to inform of crash risk in older adults to inform tailored educational road safety campaigns on signs of sleepiness.

European NCAP Driver State Monitoring Protocols: Prevalence of Distraction in Naturalistic Driving.

OBJECTIVE: examine the prevalence of driver distraction in naturalistic driving when implementing European New Car Assessment Program (Euro NCAP)-defined distraction behaviours. BACKGROUND: The 2023 introduction of Occupant Status monitoring (OSM) into Euro NCAP will accelerate uptake of Driver State Monitoring (DSM). Euro NCAP outlines distraction behaviours that DSM must detect to earn maximum safety points. Distraction behaviour prevalence and driver alerting and intervention frequency have yet to be examined in naturalistic driving. METHOD: Twenty healthcare workers were provided with an instrumented vehicle for approximately two weeks. Data were continuously monitored with automotive grade DSM during daily work commutes, resulting in 168.8 hours of driver head, eye and gaze tracking. RESULTS: Single long distraction events were the most prevalent, with .89 events/hour. Implementing different thresholds for driving-related and driving-unrelated glance regions impacts alerting rates. Lizard glances (primarily gaze movement) occurred more frequently than owl glances (primarily head movement). Visual time-sharing events occurred at a rate of .21 events/hour. CONCLUSION: Euro NCAP-described driver distraction occurs naturalistically. Lizard glances, requiring gaze tracking, occurred in high frequency relative to owl glances, which only require head tracking, indicating that less sophisticated DSM will miss a substantial amount of distraction events. APPLICATION: This work informs OEMs, DSM manufacturers and regulators of the expected alerting rate of Euro NCAP defined distraction behaviours. Alerting rates will vary with protocol implementation, technology capability, and HMI strategies adopted by the OEMs, in turn impacting safety outcomes, user experience and acceptance of DSM technology.

Get Ready for Take-Overs: Using Head-Up Display for Drivers to Engage in Non-Driving-Related Tasks in Automated Vehicles.

OBJECTIVE: The study aims to investigate the potential of using HUD (head-up display) as an approach for drivers to engage in non-driving-related tasks (NDRTs) during automated driving, and examine the impacts on driver state and take-over performance in comparison to the traditional mobile phone. BACKGROUND: Advances in automated vehicle technology have the potential to relieve drivers from driving tasks so that they can engage in NDRTs freely. However, drivers will still need to take-over control under certain circumstances. METHOD: A driving simulation experiment was conducted using an Advanced Driving Simulator and real-world driving videos. Forty-six participants completed three drives in three display conditions, respectively (HUD, mobile phone and baseline without NDRT). The HUD was integrated with the vehicle in displaying NDRTs while the mobile phone was not. Drivers' visual (e.g. gaze, blink) and physiological (e.g. ECG, EDA) data were collected to measure driver state. Two take-over reaction times (hand and foot) were used to measure take-over performance. RESULTS: The HUD significantly shortened the take-over reaction times compared to the mobile phone condition. Compared to the baseline condition, drivers in the HUD condition also experienced lower cognitive workload and physiological arousal. Drivers' take-over reaction times were significantly correlated with their visual and electrodermal activities during automated driving prior to the take-over request. CONCLUSION: HUDs can improve driver performance and lower workload when used as an NDRT interface. APPLICATION: The study sheds light on a promising approach for drivers to engage in NDRTs in future AVs.

Beyond gaze fixation: Modeling peripheral vision in relation to speed, Tesla Autopilot, cognitive load, and age in highway driving.

OBJECTIVE: The study aims to model driver perception across the visual field in dynamic, real-world highway driving. BACKGROUND: Peripheral vision acquires information across the visual field and guides a driver's information search. Studies in naturalistic settings are lacking however, with most research having been conducted in controlled simulation environments with limited eccentricities and driving dynamics. METHODS: We analyzed data from 24 participants who drove a Tesla Model S with Autopilot on the highway. While driving, participants completed the peripheral detection task (PDT) using LEDs and the N-back task to generate cognitive load. The I-DT (identification by dispersion threshold) algorithm sampled naturalistic gaze fixations during PDTs to cover a broader and continuous spectrum of eccentricity. A generalized Bayesian regression model predicted LED detection probability during the PDT-as a surrogate for peripheral vision-in relation to eccentricity, vehicle speed, driving mode, cognitive load, and age. RESULTS: The model predicted that LED detection probability was high and stable through near-peripheral vision but it declined rapidly beyond 20°-30° eccentricity, showing a narrower useful field over a broader visual field (maximum 70°) during highway driving. Reduced speed (while following another vehicle), cognitive load, and older age were the main factors that degraded the mid-peripheral vision (20°-50°), while using Autopilot had little effect. CONCLUSIONS: Drivers can reliably detect objects through near-peripheral vision, but their peripheral detection degrades gradually due to further eccentricity, foveal demand during low-speed vehicle following, cognitive load, and age. APPLICATIONS: The findings encourage the development of further multivariate computational models to estimate peripheral vision and assess driver situation awareness for crash prevention.

Evaluating Driver Features for Cognitive Distraction Detection and Validation in Manual and Level 2 Automated Driving.

OBJECTIVE: This study aimed to investigate the impacts of feature selection on driver cognitive distraction (CD) detection and validation in real-world nonautomated and Level 2 automated driving scenarios. BACKGROUND: Real-time driver state monitoring is critical to promote road user safety. METHOD: Twenty-four participants were recruited to drive a Tesla Model S in manual and Autopilot modes on the highway while engaging in the N-back task. In each driving mode, CD was classified by the random forest algorithm built on three "hand-crafted" glance features (i.e., percent road center [PRC], the standard deviation of gaze pitch, and yaw angles), or through a large number of features that were transformed from the output of a driver monitoring system (DMS) and other sensing systems. RESULTS: In manual driving, the small set of glance features was as effective as the large set of machine-generated features in terms of classification accuracy. Whereas in Level 2 automated driving, both glance and vehicle features were less sensitive to CD. The glance features also revealed that the misclassified driver state was the result of the dynamic fluctuations and individual differences of cognitive loads under CD. CONCLUSION: Glance metrics are critical for the detection and validation of CD in on-road driving. APPLICATIONS: The paper suggests the practical value of human factors domain knowledge in feature selection and ground truth validation for the development of driver monitoring technologies.

On-road driving impairment following sleep deprivation differs according to age.

Impaired driving performance due to sleep loss is a major contributor to motor-vehicle crashes, fatalities, and serious injuries. As on-road, fully-instrumented studies of drowsy driving have largely focused on young drivers, we examined the impact of sleep loss on driving performance and physiological drowsiness in both younger and older drivers of working age. Sixteen 'younger' adults (M = 24.3 ± 3.1 years [21-33 years], 9 males) and seventeen 'older' adults (M = 57.3 ± 5.2, [50-65 years], 9 males) undertook two 2 h drives on a closed-loop track in an instrumented vehicle with a qualified instructor following (i) 8 h sleep opportunity the night prior (well-rested), and (ii) after 29-h of total sleep deprivation (TSD). Following TSD, both age groups displayed increased subjective sleepiness and lane departures (p < 0.05), with younger drivers exhibiting 7.37 × more lane departures, and 11 × greater risk of near crash events following sleep loss. While older drivers exhibited a 3.5 × more lane departures following sleep loss (p = 0.008), they did not have a significant increase in near-crash events (3/34 drives). Compared to older adults, younger adults had 3.1 × more lane departures (p = < 0.001), and more near crash events (79% versus 21%, p = 0.007). Ocular measures of drowsiness, including blink duration, number of long eye closures and PERCLOS increased following sleep loss for younger adults only (p < 0.05). These results suggest that for older working-aged adults, driving impairments observed following sleep loss may not be due to falling asleep. Future work should examine whether this is attributed to other consequences of sleep loss, such as inattention or distraction from the road.

The impact of 7-hour and 11-hour rest breaks between shifts on heavy vehicle truck drivers' sleep, alertness and naturalistic driving performance.

BACKGROUND: An inadequate rest break between shifts may contribute to driver sleepiness. This study assessed whether extending the major rest break between shifts from 7-hours (Australian industry standard) to 11-hours, improved drivers' sleep, alertness and naturalistic driving performance. METHODS: 17 heavy vehicle drivers (16 male) were recruited to complete two conditions. Each condition comprised two 13-hour shifts, separated by either a 7- or 11-hour rest break. The initial 13-hour shift was the drivers' regular work. The rest break and following 13-hour shift were simulated. The simulated shift included 5-hours of naturalistic driving with measures of subjective sleepiness, physiological alertness (ocular and electroencephalogram) and performance (steering and lane departures). RESULTS: 13 drivers provided useable data. Total sleep during the rest break was greater in the 11-hour than the 7-hour condition (median hours [25th to 75th percentile] 6.59 [6.23, 7.23] vs. 5.07 [4.46, 5.38], p = 0.008). During the simulated shift subjective sleepiness was marginally better for the 11-hour condition (mean Karolinska Sleepiness Scale [95th CI] = 4.52 [3.98, 5.07] vs. 5.12 [4.56, 5.68], p = 0.009). During the drive, ocular and vehicle metrics were improved for the 11-hour condition (p<0.05). Contrary to expectations, mean lane departures p/hour were increased during the 11-hour condition (1.34 [-0.38,3.07] vs. 0.63 [-0.2,1.47], p = 0.027). CONCLUSIONS: Extending the major rest between shifts substantially increases sleep duration and has a modest positive impact on driver alertness and performance. Future work should replicate the study in a larger sample size to improve generalisability and assess the impact of consecutive 7-hour major rest breaks.

The Impacts of Temporal Variation and Individual Differences in Driver Cognitive Workload on ECG-Based Detection.

OBJECTIVE: This paper aimed to investigate the robustness of driver cognitive workload detection based on electrocardiogram (ECG) when considering temporal variation and individual differences in cognitive workload. BACKGROUND: Cognitive workload is a critical component to be monitored for error prevention in human-machine systems. It may fluctuate instantaneously over time even in the same tasks and differ across individuals. METHOD: A driving simulation study was conducted to classify driver cognitive workload underlying four experimental conditions (baseline, N-back, texting, and N-back + texting distraction) in two repeated 1-hr blocks. Heart rate (HR) and heart rate variability (HRV) were compared among the experimental conditions and between the blocks. Random forests were built on HR and HRV to classify cognitive workload in different blocks and for different individuals. RESULTS: HR and HRV were significantly different between repeated blocks in the study, demonstrating the time-induced variation in cognitive workload. The performance of cognitive workload classification across blocks and across individuals was significantly improved after normalizing HR and HRV in each block by the corresponding baseline. CONCLUSION: The temporal variation and individual differences in cognitive workload affects ECG-based cognitive workload detection. But normalization approaches relying on the choice of appropriate baselines help compensate for the effects of temporal variation and individual differences. APPLICATION: The findings provide insight into the value and limitations of ECG-based driver cognitive workload monitoring during prolonged driving for individual drivers.

Effects of Distraction in On-Road Level 2 Automated Driving: Impacts on Glance Behavior and Takeover Performance.

OBJECTIVE: The paper aimed to investigate glance behaviors under different levels of distraction in automated driving (AD) and understand the impact of distraction levels on driver takeover performance. BACKGROUND: Driver distraction detrimentally affects takeover performance. Glance-based distraction measurement could be a promising method to remind drivers to maintain enough attentiveness before the takeover request in partially AD. METHOD: Thirty-six participants were recruited to drive a Tesla Model S in manual and Autopilot modes on a test track while engaging in secondary tasks, including temperature-control, email-sorting, and music-selection, to impose low and high distractions. During the test drive, participants needed to quickly change the lane as if avoiding an immediate road hazard if they heard an unexpected takeover request (an auditory warning). Driver state and behavior over the test drive were recorded in real time by a driver monitoring system and several other sensors installed in the Tesla vehicle. RESULTS: The distribution of off-road glance duration was heavily skewed (with a long tail) by high distractions, with extreme glance duration more than 30 s. Moreover, being eyes-off-road before takeover could cause more delay in the urgent takeover reaction compared to being hands-off-wheel. CONCLUSION: The study measured off-road glance duration under different levels of distraction and demonstrated the impacts of being eyes-off-road and hands-off-wheel on the following takeover performance. APPLICATION: The findings provide new insights about engagement in Level 2 AD and are useful for the design of driver monitoring technologies for distraction management.

European NCAP Program Developments to Address Driver Distraction, Drowsiness and Sudden Sickness.

Driver distraction and drowsiness remain significant contributors to death and serious injury on our roads and are long standing issues in road safety strategies around the world. With developments in automotive technology, including driver monitoring, there are now more options available for automotive manufactures to mitigate risks associated with driver state. Such developments in Occupant Status Monitoring (OSM) are being incorporated into the European New Car Assessment Programme (Euro NCAP) Safety Assist protocols. The requirements for OSM technologies are discussed along two dimensions: detection difficulty and behavioral complexity. More capable solutions will be able to provide higher levels of system availability, being the proportion of time a system could provide protection to the driver, and will be able to capture a greater proportion of complex real-word driver behavior. The testing approach could initially propose testing using both a dossier of evidence provided by the Original Equipment Manufacturer (OEM) alongside selected use of track testing. More capable systems will not rely only on warning strategies but will also include intervention strategies when a driver is not attentive. The roadmap for future OSM protocol development could consider a range of known and emerging safety risks including driving while intoxicated by alcohol or drugs, cognitive distraction, and the driver engagement requirements for supervision and take-over performance with assisted and automated driving features.

Interaction-centred design: an end user evaluation of road intersection concepts developed using the cognitive work analysis design toolkit (CWA-DT).

Crashes at intersections represent an important road safety problem. Interactions between different road user types, such as between vehicles and vulnerable road users, are a particular concern. It has been suggested driver-centric road design plays a role in crashes. A multi-road user evaluation of three novel intersection designs is described. The designs were generated using the Cognitive Work Analysis Design Toolkit, underpinned by sociotechnical systems theory. The desktop evaluation involved drivers, motorcyclists, cyclists and pedestrians rating the design concepts against alignment with design goals, sociotechnical systems theory and usability, and providing feedback on the positive and negative aspects. Two concepts received more positive ratings and feedback in comparison to a concept that provided more user autonomy. The evaluation results also highlight clear differences in needs across road user groups. The design and evaluation process demonstrates how sociotechnical systems values and principles can be applied in the design of public spaces. Practitioner Summary: This study involved a participatory evaluation of novel road intersection designs, based on sociotechnical systems theory. The results identified important differences in needs and preferences across road user groups and demonstrate the value of sociotechnical systems theory and user participation in road transport design and evaluation processes. Abbreviations: CWA-DT: cognitive work analysis design toolkit; WDA: work domain analysis; SUS: system usability scale.

A pre-drive ocular assessment predicts alertness and driving impairment: A naturalistic driving study in shift workers.

Sleepiness is a major contributor to motor vehicle crashes and shift workers are particularly vulnerable. There is currently no validated objective field-based measure of sleep-related impairment prior to driving. Ocular parameters are promising markers of continuous driver alertness in laboratory and track studies, however their ability to determine fitness-to-drive in naturalistic driving is unknown. This study assessed the efficacy of a pre-drive ocular assessment for predicting sleep-related impairment in naturalistic driving, in rotating shift workers. Fifteen healthcare workers drove an instrumented vehicle for 2 weeks, while working a combination of day, evening and night shifts. The vehicle monitored lane departures and behavioural microsleeps (blinks >500 ms) during the drive. Immediately prior to driving, ocular parameters were assessed with a 4-min test. Lane departures and behavioural microsleeps occurred on 17.5 % and 10 % of drives that had pre-drive assessments, respectively. Pre-drive blink duration significantly predicted behavioural microsleeps and showed promise for predicting lane departures (AUC = 0.79 and 0.74). Pre-drive percentage of time with eyes closed had high accuracy for predicting lane departures and behavioural microsleeps (AUC = 0.73 and 0.96), although was not statistically significant. Pre-drive psychomotor vigilance task variables were not statistically significant predictors of lane departures. Self-reported sleep-related and hazardous driving events were significantly predicted by mean blink duration (AUC = 0.65 and 0.69). Measurement of ocular parameters pre-drive predict drowsy driving during naturalistic driving, demonstrating potential for fitness-to-drive assessment in operational environments.

Evaluation of alternative intersection treatments at rural crossroads using simulation software.

OBJECTIVE: Rural roads are characterized by hazardous roadsides and suboptimal geometry yet allow for high travel speeds and unfavorable impact angles. In Victoria, 25% of persons seriously injured and 52% of fatalities occur on rural roads, with 30% occurring at intersections. In the United States, almost twice the number of traffic fatalities occur in rural areas than in urban areas, while accounting for less than half of all vehicle miles traveled and 21% of the population. The choice of safety countermeasure is therefore paramount. Simulation software provides a cost-effective means of analyzing alternative intersection treatments with a view to identifying their effectiveness in mitigating crashes. The aim of this research was to assess the safety benefits of 4 alternative intersection treatments using in-depth crash data with an advanced crash reconstruction process. METHOD: Using a single serious injury real-world crash from the Monash University Accident Research Centre Enhanced Crash Investigation Study and crash reconstruction software, an exemplar rural crash was reconstructed and validated against real-world data. The crash involved a passenger vehicle (European New Car Assessment Programme 5-star) approaching from a minor road and failing to yield at a give-way sign; the posted speed limit was 80 km/h. The vehicle was struck on the right/driver side by a rigid truck (B-vehicle; 1990) traveling on the major approach (100 km/h). The driver of the case vehicle was seriously injured. Four alternative intersection treatments appropriate for the crash site were constructed in computer-aided design software (Rhinoceros Ver. 5): roundabout; rumble strips; a reduced speed limit; and the combination of lower speed limit and rumbles to determine the reduction in crash forces in the presence of the countermeasures. RESULTS: The hypothetical scenarios demonstrate substantial reductions in impact force and different points of impact, resulting in a significantly lower injury severity for the struck driver. Speed limit reduction to 80 km/h on the main approach (from 100 km/h) in combination with rumble strips on both intersection approaches had the most favorable outcome with the crash avoided entirely, assuming speed compliance. DISCUSSION: The findings have implications for understanding the role of speed in crashes and hence the design of effective countermeasures. Simulation software, validated using real-world data, provides a cost-effective means of evaluating alternative intersection treatments for rural intersections. Scaled up, implementing these treatments would have significant safety benefits and reduce the road trauma currently associated with rural roads.

The impact of texting on driver behaviour at rail level crossings.

A driver text messaging in the vicinity of a rail level crossing represents the merging of a high-risk, high-workload driving environment with a highly distracting secondary task. In this simulator study, we examined how texting impacts driver behaviour on approach to actively controlled urban rail level crossings. Twenty-eight participants drove a series of simulated urban routes containing rail level crossings, while sending text messages and while driving without performing a secondary task. At half of the crossings, drivers were required to respond to the crossing warnings as a train approached. Results revealed that texting on approach to rail level crossings had a detrimental impact on a range of driver behaviour measures. Specifically, texting more than doubled the amount of time spent with eyes off the forward roadway, resulting in drivers spending more than half of their approach time to rail level crossings looking away from the road. This lack of visual attention to the roadway was associated with a range of decrements in driving that may be indicative of a loss of situation awareness, including increased brake reaction time to the crossing warnings and a reduction in lateral position control. The findings have safety implications, not only for urban level crossings, but also for passive level crossings where no warnings are present to re-orient the distracted driver's attention toward an approaching train.

Walking the talk: Comparing pedestrian 'activity as imagined' with 'activity as done'.

The safety of vulnerable road users, including pedestrians, is an important issue worldwide. In line with the shift towards systems thinking in transport safety, the aim of this study was to compare the normal performance of pedestrians as they navigate the road system with that imagined by road system managers to gain insights into how safety management can be improved for this vulnerable road user group. The Event Analysis of Systemic Teamwork framework was used to compare pedestrian activity 'as imagined' and 'as done' at signalised road intersections and railway level crossings. Data regarding 'activity as imagined' was derived from documentation review, and data on 'activity as done' was derived from a semi-naturalistic study of ten participants. It is concluded that in both environments pedestrians exhibited more diversity and variability than anticipated by system managers. Insights for improving the design of the road environment for pedestrians are provided. Further, it is argued that wider changes to the processes used in the design and management of road systems are needed.

Ending on a positive: Examining the role of safety leadership decisions, behaviours and actions in a safety critical situation.

Safety leadership is an important factor in supporting safe performance in the workplace. The present case study examined the role of safety leadership during the Bingham Canyon Mine high-wall failure, a significant mining incident in which no fatalities or injuries were incurred. The Critical Decision Method (CDM) was used in conjunction with a self-reporting approach to examine safety leadership in terms of decisions, behaviours and actions that contributed to the incidents' safe outcome. Mapping the analysis onto Rasmussen's Risk Management Framework (Rasmussen, 1997), the findings demonstrate clear links between safety leadership decisions, and emergent behaviours and actions across the work system. Communication and engagement based decisions featured most prominently, and were linked to different leadership practices across the work system. Further, a core sub-set of CDM decision elements were linked to the open flow and exchange of information across the work system, which was critical to supporting the safe outcome. The findings provide practical implications for the development of safety leadership capability to support safety within the mining industry.

Distributed improvisation: a systems perspective of improvisation 'epics' by led outdoor activity leaders.

Improvisation represents the spontaneous and real-time conception and execution of a novel response to an unanticipated situation. In order to benefit from the positive safety potential of this phenomenon, it is necessary to understand what influences its appropriateness and effectiveness. This study has applied the system-based methodology Impromaps to analysing accounts of improvisation aimed at mitigating adverse safety outcomes. These accounts were obtained from led outdoor activity (LOA) leaders through critical decision method interviews. Influencing factors and interactions have been identified across all system levels. The factors most influential to leaders' ability to improvise are 'Policy, procedures and rules', 'Organisation culture', 'Training', 'Role responsibilities', 'Communication/instruction/demonstration', 'Situation awareness', 'Leader experience', 'Mental simulation', 'Equipment, clothing & PPE' and 'Terrain/physical environment'. To enhance the likelihood of effective, appropriate improvisation, LOA providers are recommended to focus on higher level factors over which they are able to exert greater control. Practitioner Summary: To enhance resilience in safety-critical situations, organisations need to understand what influences appropriate, effective improvisation. To elucidate this, the Impromaps methodology is applied to in-depth interview data. The Impromap affords a graphical depiction of the influencing factors and interactions across the system, providing a basis for the development of interventions.

To stop or not to stop: Contrasting compliant and non-compliant driver behaviour at rural rail level crossings.

Many rail level crossings (RLXs) have only passive protection, such as static signs instructing road users to stop, yield, or look for trains. Stop signs have been suggested as a low-cost option to improve safety at passive RLXs, as requiring drivers to stop should encourage safe behaviour. However, field observations have noted high rates of non-compliance at stop-controlled RLXs. To explore this further, we conducted an on-road study to identify factors that influence compliance at stop-controlled RLXs. Twenty-two drivers drove a 30.5km route in rural Australia, encompassing three stop-controlled RLXs. In over half of all cases (59%) drivers stopped completely at the RLX; on 27% of crossings drivers executed a rolling stop, and on 14% of crossings drivers violated the stop controls. Rolling stops were defined as a continuous deceleration to <10km/h, but remaining above 0km/h, before accelerating to >10km/h. Behavioural patterns, including visual checks and decision-making, were similar when comparing drivers who made complete versus rolling stops. Non-compliant drivers did not differ from compliant drivers in approach speeds, but spent less time visually checking for trains. Post-drive interviews revealed some drivers wilfully disregarded the stop sign, whereas others did not notice the stop sign. Those who intentionally violated noted trains were infrequent and suggested sight distance was good enough (even though all crossings had been formally assessed as having inadequate sight distance). Overall the results suggest most drivers exhibit safe behaviour at passive RLXs, but a notable minority disregard or fail to notice signs. Potential avenues for redesigning passive RLXs to improve safety are discussed.

Safety leadership and systems thinking: application and evaluation of a Risk Management Framework in the mining industry.

Safety leadership is an important factor in supporting safety in high-risk industries. This article contends that applying systems-thinking methods to examine safety leadership can support improved learning from incidents. A case study analysis was undertaken of a large-scale mining landslide incident in which no injuries or fatalities were incurred. A multi-method approach was adopted, in which the Critical Decision Method, Rasmussen's Risk Management Framework and Accimap method were applied to examine the safety leadership decisions and actions which enabled the safe outcome. The approach enabled Rasmussen's predictions regarding safety and performance to be examined in the safety leadership context, with findings demonstrating the distribution of safety leadership across leader and system levels, and the presence of vertical integration as key to supporting the successful safety outcome. In doing so, the findings also demonstrate the usefulness of applying systems-thinking methods to examine and learn from incidents in terms of what 'went right'. The implications, including future research directions, are discussed. Practitioner Summary: This paper presents a case study analysis, in which systems-thinking methods are applied to the examination of safety leadership decisions and actions during a large-scale mining landslide incident. The findings establish safety leadership as a systems phenomenon, and furthermore, demonstrate the usefulness of applying systems-thinking methods to learn from incidents in terms of what 'went right'. Implications, including future research directions, are discussed.

The relative importance of real-time in-cab and external feedback in managing fatigue in real-world commercial transport operations.

OBJECTIVE: Real-time driver monitoring systems represent a solution to address key behavioral risks as they occur, particularly distraction and fatigue. The efficacy of these systems in real-world settings is largely unknown. This article has three objectives: (1) to document the incidence and duration of fatigue in real-world commercial truck-driving operations, (2) to determine the reduction, if any, in the incidence of fatigue episodes associated with providing feedback, and (3) to tease apart the relative contribution of in-cab warnings from 24/7 monitoring and feedback to employers. METHODS: Data collected from a commercially available in-vehicle camera-based driver monitoring system installed in a commercial truck fleet operating in Australia were analyzed. The real-time driver monitoring system makes continuous assessments of driver drowsiness based on eyelid position and other factors. Data were collected in a baseline period where no feedback was provided to drivers. Real-time feedback to drivers then occurred via in-cab auditory and haptic warnings, which were further enhanced by direct feedback by company management when fatigue events were detected by external 24/7 monitors. Fatigue incidence rates and their timing of occurrence across the three time periods were compared. RESULTS: Relative to no feedback being provided to drivers when fatigue events were detected, in-cab warnings resulted in a 66% reduction in fatigue events, with a 95% reduction achieved by the real-time provision of direct feedback in addition to in-cab warnings (p < 0.01). With feedback, fatigue events were shorter in duration a d occurred later in the trip, and fewer drivers had more than one verified fatigue event per trip. CONCLUSIONS: That the provision of feedback to the company on driver fatigue events in real time provides greater benefit than feedback to the driver alone has implications for companies seeking to mitigate risks associated with fatigue. Having fewer fatigue events is likely a reflection of the device itself and the accompanying safety culture of the company in terms of how the information is used. Data were analysed on a per-truck trip basis, and the findings are indicative of fatigue events in a large-scale commercial transport fleet. Future research ought to account for individual driver performance, which was not possible with the available data in this retrospective analysis. Evidence that real-time driver monitoring feedback is effective in reducing fatigue events is invaluable in the development of fleet safety policies, and of future national policy and vehicle safety regulations. Implications for automotive driver monitoring are discussed.