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.

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.

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.

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.

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.

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.

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.

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.

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.

When paradigms collide at the road rail interface: evaluation of a sociotechnical systems theory design toolkit for cognitive work analysis.

The Cognitive Work Analysis Design Toolkit (CWA-DT) is a recently developed approach that provides guidance and tools to assist in applying the outputs of CWA to design processes to incorporate the values and principles of sociotechnical systems theory. In this paper, the CWA-DT is evaluated based on an application to improve safety at rail level crossings. The evaluation considered the extent to which the CWA-DT met pre-defined methodological criteria and aligned with sociotechnical values and principles. Both process and outcome measures were taken based on the ratings of workshop participants and human factors experts. Overall, workshop participants were positive about the process and indicated that it met the methodological criteria and sociotechnical values. However, expert ratings suggested that the CWA-DT achieved only limited success in producing RLX designs that fully aligned with the sociotechnical approach. Discussion about the appropriateness of the sociotechnical approach in a public safety context is provided. Practitioner Summary: Human factors and ergonomics practitioners need evidence of the effectiveness of methods. A design toolkit for cognitive work analysis, incorporating values and principles from sociotechnical systems theory, was applied to create innovative designs for rail level crossings. Evaluation results based on the application are provided and discussed.

Variability in decision-making and critical cue use by different road users at rail level crossings.

Collisions at rail level crossings (RLXs) are typically high-severity and high-cost, often involving serious injuries, fatalities and major disruptions to the transport network. Most research examining behaviour at RLXs has focused exclusively on drivers and consequently there is little knowledge on how other road users make decisions at RLXs. We collected drivers', motorcyclists', bicyclists' and pedestrians' self-reported daily experiences at RLXs for two weeks, focusing on behaviour, decision-making and information use in the presence of a train and/or activated RLX signals. Both information use and behaviour differed between road users. Visual information (e.g. flashing lights) was more influential for motorists, whereas pedestrians and cyclists relied more on auditory information (e.g. bells). Pedestrians were also more likely to violate active RLX warnings and/or cross before an approaching train. These results emphasise the importance of adopting holistic RLX design approaches that support cognition and behaviour across for all road users. Practitioner Summary: This study explores how information use and decision-making at rail level crossings (RLXs) differ between road user groups, using a two-week self-report study. Most users make safe decisions, but pedestrians are most likely to violate RLX warnings. Information use (visual vs. auditory) also differs substantially between road user groups.

Designing sociotechnical systems with cognitive work analysis: putting theory back into practice.

Cognitive work analysis (CWA) is a framework of methods for analysing complex sociotechnical systems. However, the translation from the outputs of CWA to design is not straightforward. Sociotechnical systems theory provides values and principles for the design of sociotechnical systems which may offer a theoretically consistent basis for a design approach for use with CWA. This article explores the extent to which CWA and sociotechnical systems theory offer complementary perspectives and presents an abstraction hierarchy (AH), based on a review of literature, that describes an 'optimal' CWA and sociotechnical systems theory design system. The optimal AH is used to assess the extent to which current CWA-based design practices, uncovered through a survey of CWA practitioners, aligns with sociotechnical systems theory. Recommendations for a design approach that would support the integration of CWA and sociotechnical systems theory design values and principles are also derived.

Designing a ticket to ride with the Cognitive Work Analysis Design Toolkit.

Cognitive work analysis has been applied in the design of numerous sociotechnical systems. The process used to translate analysis outputs into design concepts, however, is not always clear. Moreover, structured processes for translating the outputs of ergonomics methods into concrete designs are lacking. This paper introduces the Cognitive Work Analysis Design Toolkit (CWA-DT), a design approach which has been developed specifically to provide a structured means of incorporating cognitive work analysis outputs in design using design principles and values derived from sociotechnical systems theory. This paper outlines the CWA-DT and describes its application in a public transport ticketing design case study. Qualitative and quantitative evaluations of the process provide promising early evidence that the toolkit fulfils the evaluation criteria identified for its success, with opportunities for improvement also highlighted. PRACTITIONER SUMMARY: The Cognitive Work Analysis Design Toolkit has been developed to provide ergonomics practitioners with a structured approach for translating the outputs of cognitive work analysis into design solutions. This paper demonstrates an application of the toolkit and provides evaluation findings.

Using the event analysis of systemic teamwork (EAST) to explore conflicts between different road user groups when making right hand turns at urban intersections.

Collisions between different types of road users at intersections form a substantial component of the road toll. This paper presents an analysis of driver, cyclist, motorcyclist and pedestrian behaviour at intersections that involved the application of an integrated suite of ergonomics methods, the Event Analysis of Systemic Teamwork (EAST) framework, to on-road study data. EAST was used to analyse behaviour at three intersections using data derived from an on-road study of driver, cyclist, motorcyclist and pedestrian behaviour. The analysis shows the differences in behaviour and cognition across the different road user groups and pinpoints instances where this may be creating conflicts between different road users. The role of intersection design in creating these differences in behaviour and resulting conflicts is discussed. It is concluded that currently intersections are not designed in a way that supports behaviour across the four forms of road user studied. Interventions designed to improve intersection safety are discussed. Practitioner Summary: Intersection safety currently represents a key road safety issue worldwide. This paper presents a novel application of a framework of ergonomics methods for studying differences in road user behaviour at intersections. The findings support development of interventions that consider all road users as opposed to one group in isolation.

Exploring schema-driven differences in situation awareness between road users: an on-road study of driver, cyclist and motorcyclist situation awareness.

Collisions between different road users make a substantial contribution to road trauma. Although evidence suggests that different road users interpret the same road situations differently, it is not clear how road users' situation awareness differs, nor is it clear which differences might lead to conflicts. This article presents the findings from an on-road study conducted to examine driver, motorcyclist and cyclist situation awareness in different road environments. The findings suggest that, in addition to minor differences in the structure of different road users' situation awareness (i.e. amount of information and how it is integrated), the actual content of situation awareness in terms of road user schemata, the resulting interaction with the world and the information underpinning situation awareness is markedly different. Further examination indicates that the differences are likely to be compatible along arterial roads, shopping strips and at roundabouts, but that they may create conflicts between different road users at intersections. Interventions designed to support compatible situation awareness and behaviour between different road users are discussed.

Objective and subjective measures of sleepiness, and their associations with on-road driving events in shift workers.

To assess the relationships between sleepiness and the incidence of adverse driving events in nurses commuting to and from night and rotating shifts, 27 rotating and permanent night shift-working nurses were asked to complete daily sleep and duty logs, and wear wrist-activity monitors for 2 weeks (369 driving sessions). During all commutes, ocular measures of drowsiness, including the Johns Drowsiness Scale score, were assessed using the Optalert™ system. Participants self-reported their subjective sleepiness at the beginning and end of each drive, and any events that occurred during the drive. Rotating shift nurses reported higher levels of sleepiness compared with permanent night shift nurses. In both shift-working groups, self-reported sleepiness, drowsiness and drive events were significantly higher during commutes following night shifts compared with commutes before night shifts. Strong associations were found between objective drowsiness and increased odds of driving events during commutes following night shifts. Maximum total blink duration (mean = 7.96 s) during the drive and pre-drive Karolinska Sleepiness Scale (mean = 5.0) were associated with greater incidence of sleep-related events [OR, 5.35 (95% CI, 1.32, 21.60), OR, 1.69 (95% CI, 1.04, 2.73), respectively]. Inattention was strongly associated with a Johns Drowsiness Scale score equal to or above 4.5 [OR, 4.58 (95% CI, 1.26-16.69)]. Hazardous driving events were more likely to occur when drivers had been awake for 16 h or more [OR, 4.50 (95% CI, 1.81, 11.16)]. Under real-world driving conditions, shift-working nurses experience high levels of drowsiness as indicated by ocular measures, which are associated with impaired driving performance following night shift work.

Population based case-control study of serious non-fatal motorcycle crashes.

BACKGROUND: Motorcycle sales, registration and use are increasing in many countries. The epidemiological literature on risk factors for motorcycle injury is becoming outdated, due to changes in rider demography, licensing regulations, traffic mix and density, road environments, and motorcycle designs and technologies. Further, the potential contribution of road infrastructure and travel speed has not yet been examined. METHODS/DESIGN: A population based case-control study together with a nested case-crossover study is planned. Cases will be motorcycle riders who are injured but not killed in a motorcycle crash on a public road within 150 km radius of Melbourne, Australia, and admitted to one of the study hospitals. Controls will be motorcycle riders who ride through the crash site on the same type of day (weekday or weekend) within an hour of the crash time. Data on rider, bike, and trip characteristics will be collected from the participants by questionnaire. Data on crash site characteristics will be collected in a structured site inspection, and travel speed for the cases will be estimated from these data. Travel speed for the controls will be measured prior to recruitment with a radar traffic detection device as they ride through the crash site. Control sites for the case-crossover study will be selected 1 km upstream from the crash site and matched on either intersection status or road curvature (either straight or cornered). If the initial site selected does not match the case site on these characteristics, then the closest matching site on the case route will be selected. Conditional multivariate logistic regression models will be used to compare risk between the matched case and control riders and to examine associations between road infrastructure and road environment characteristics and crash occurrence. Interactions between type of site and speed will be tested to determine if site type is an effect modifier of the relationship between speed and crash risk. The relationship between rider factors and travel speed generally will be assessed by multivariate regression methods. DISCUSSION: In the context of the changing motorcycling environment, this study will provide evidence on contemporary risk factors for serious non-fatal motorcycle crashes.

The impact of on-road motion on BMS touch screen device operation.

This study investigates the effect of vehicle motion on performance, usability and workload for a touch screen in-vehicle Battle Management System (BMS). Participants performed a series of battle management tasks while a vehicle was driven over sealed (characteristic of 'normal' vehicle motion) and unsealed (characteristic of 'high' vehicle motion) roads. The results indicate that unsealed road conditions impair the performance of information input tasks (tasks that require the user to enter information, e.g. text entry) but not information extraction tasks (tasks that require the user to retrieve information from the system, e.g. reading coordinates). Participants rated workload as higher and the system as less usable on the unsealed road. In closing, the implications for in-vehicle touch screen design and use in both military and civilian driving contexts are discussed. Practitioner Summary: The effect of motion on interacting with in-vehicle touch screen devices remains largely unexplored. This study examines the effect of different levels of vehicle motion on the use of a BMS. Using the system under off-road conditions had a detrimental impact on workload, performance and usability.

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.

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.