Eye movements predict driver reaction time to takeover request in automated driving: A real-vehicle study

For automated driving at SAE level 3 or lower, driver performance in responding to takeover requests (TORs) is decisive in providing system safety. A driver state monitoring system that can predict a driver’s performance in a TOR event will facilitate a safer control transition from vehicle to driver. This experimental study investigated whether driver eye-movement measured before a TOR can predict driving performance in a subsequent TOR event. We recruited participants (N = 36) to obtain realistic results in a real-vehicle study. In the experiment, drivers rode in an automated vehicle on a test track for about 32 min, and a critical TOR event occurred at the end of the drive. Eye movements were measured by a camera-based driver monitoring system, and five measures were extracted from the last 2-min epoch prior to the TOR event. The correlations between each eye-movement measure and driver reaction time were examined, and a multiple regression model was built using a stepwise procedure. The results showed that longer reaction time could be significantly predicted by a smaller number of large saccades, a greater number of medium saccades, and lower saccadic velocity. The implications of these relationships are consistent with previous studies. The present real-vehicle study can provide insights to the automotive industry in the search for a safer and more flexible interface between the automated vehicle and the driver.     

Driver speeding typologies by roadway behaviours and beliefs: A latent class analysis with a multistate sample of U.S. adults

Speeding has consistently contributed to a high number of motor vehicle crashes and subsequent injuries and deaths in the U.S. Identifying types of drivers related to speeding behaviour may help target interventions to reduce speeding. Typology of U.S. driver speeders have examined very specifically speeding behaviours and speeding-related attitudes. This exploratory work used latent class analysis (LCA) to examine how other driving behaviours and attitudes cluster around speeding behaviours to determine speeder typologies, which may lend a more holistic perspective to speeder types. Predicted class assignments were evaluated for associations with demographic and personality factors. The LCA resulted in four driver typologies, which we labelled: Externally Motivated (40.7%), Non-Reactors (26.2%), Perceived Invulnerable (24.3%), and Perceived Vulnerable (8.9%). The Externally Motivated and Non-Reactors typologies had the highest probability of reporting extreme speeding. The Externally Motivated may be intervened upon with messaging about reducing risks crashes and injuring passengers, while the Perceived Vulnerable class already exhibit several risk-averse behaviours that self-limits their speeding behaviour. Class placement was associated with age, self-reported speeding frequency, receipt of speeding violations. The resulting U.S. driver typologies advances the literature by demonstrating that non-speeding driver behaviours and attitudes cluster with speeding behaviours, which altogether can inform more nuanced and effective anti-speeding campaigns.     

Higher order training supporting competence,autonomy, relatedness (HOT-CAR): A model to improve learner drivers' higher order skills

Approaches to teaching young Learners to drive on-road often lack a strong, overarching theoretical framework. This paper proposes a transtheoretical model to guide instruction of higher-order skills – that are associated with reduced crash risk in young drivers – including established teaching techniques for effective instruction. Learnings from Self-Determination Theory (SDT) and the Goals for Driver Education framework (widely identified as best-practice but not effectively translated into practice) were integrated into the Higher Order Training supporting Competence, Autonomy, Relatedness (HOT-CAR) model. The model was empirically informed from naturalistic observation of professional in-vehicle lessons (n = 110) and a survey of young adolescent drivers (n = 1627). The HOT-CAR model is presented as a three-component framework that recognises learning to drive occurs within a broader system beyond the Learner and the instructor. The foundation of the model identifies the nature of the relationship between the Learner and the instructor that underlies the success of all other elements. The core of the model is the higher-order driving instruction approach including teaching strategies informed by SDT’s needs-supportive model. The context for the model incorporates some of the immediate considerations relevant to instruction; for example, the graduated driver licensing system, automated vehicle features, and peer influence. An example of the application of the model is provided to reflect the immediate practicality of the HOT-CAR model to driver training. This contributes to the limited road safety literature providing a practical solution to Learner driver training that has potential to reduce the crash risk of young novice drivers. Importantly, the model has potential to be applied and adapted to education and other training environments where higher-order skills are a safety–critical component.     

What makes a good driver on public roads and race tracks? An interview study

Future vehicles may drive automatically in a human-like manner or contain systems that monitor human driving ability. Algorithms of these systems must have knowledge of criteria of good and safe driving behavior with regard to different driving styles. In the current study, interviews were conducted with 30 drivers, including driving instructors, engineers, and race drivers. The participants were asked to describe good driving on public roads and race tracks, and in some questions were supported with video material. The results were interpreted with the help of Endsley’s model of situation awareness. The interviews showed that there were clear differences between what was considered good driving on the race track and good driving on the public road, where for the former, the driver must touch the limit of the vehicle, whereas, for the latter, the limit should be avoided. However, in both cases, a good driver was characterized by self-confidence, lack of stress, and not being aggressive. Furthermore, it was mentioned that the driver’s posture and viewing behavior are essential components of good driving, which affect the driver’s prediction of events and execution of maneuvers. The implications of our findings for the development of automation technology are discussed. In particular, we see potential in driver posture estimation and argue that automated vehicles excel in perception but may have difficulty making predictions.     

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.     

The electric vehicle: A new driving experience involving specific skills and rules

The arrival of the electric vehicle (EV) on the market is one consequence of government measures to improve air quality and reduce CO² emissions. However, the EV has specific properties of use associated with its limited range and relative silence compared to normal vehicles, influencing the mobility behaviours of drivers and requiring them to develop some new driving abilities. This paper examines the behavioural modifications brought about by daily use of an electric vehicle at three different levels of driving activity: strategic, tactical and operational. The study collected and analyzed the self-reported behaviours (via questionnaires and travels dairies) of 36 Parisian private drivers, each of whom drove for six months an electric MINI E prototype. The results of the study show that driving an EV requires a learning phase to acquire the skills and knowledge necessary to operate the vehicle. At the strategic level of driving, drivers take into account the restricted range of the EV, implement a daily charge process, and develop new behaviours related to trip planning. The study also examines driver behaviour at the tactical level, in terms of driver interactions with other road users to deal with the silent nature of the EV, and at the operational level of driving, in terms of braking behaviour to master the regenerative braking function of the EV. The paper discusses the interactions between these three levels of driving activity.     

Can traffic violations be traced to gender-role,sensation seeking,demographics and driving exposure?

BackgroundTraffic safety is often expressed as the ‘inverse of accidents’. However, it is more than the mere absence of accidents. Past studies often looked for associations between accidents and self-reports like the Driver Behaviour Questionnaire (DBQ; Reason, Manstead, Stradling, Baxter, & Campbell, 1990). The focus in this study changed from counting accidents to quantifying unsafe acts as violations. The objective was to show that drivers' specific violations can be traced to personal characteristics such as sensation seeking (SSS-V; Zuckerman, 1994), gender role (BSRI; Bem sex role inventory, Bem, 1974), demographics, and driving exposure.MethodA web-based questionnaire was distributed, integrating several known questionnaires. Five hundred and twenty-seven questionnaires were completed and analyzed.ResultsSensation seeking, gender role, experience, and age predicted respondents’ score on the DBQ, as well as the interaction of sensation seeking with gender and gender role. Gender role was a more valid predictor of driver behavior than gender.ConclusionsThe effect of gender role on drivers’ self-reported violation tendency is the most interesting and the most intriguing finding of this survey and indicates the need to further examine gender role affects in driving.     

Mothering under political violence: Post-traumatic symptoms,observed maternal parenting practices and child externalising behaviour

Using the family stress model as our conceptual framework, we explored whether observed maternal parenting practices (positive and coercive) account for the associations between mothers' post-traumatic stress symptoms and children's externalising behaviours. Mothers' self-reported post-traumatic stress symptoms, observed maternal practices, and reports of children's externalising behaviour were collected from 123 Israeli mothers and their children, who were exposed to ongoing rocket attacks in southern Israel. A structural equation model revealed that mothers' post-traumatic stress symptoms were linked with greater maternal coercive parenting practices, which in turn were associated with more externalising behaviours in children. The study highlights the crucial role of maternal distress and mothers' parenting skills in the development of externalising behaviours in children exposed to chronic political violence. These results suggest that prevention interventions designed to promote parenting skills for mothers exposed to political violence may be beneficial for children's healthy development.     

Proposal of a driver profile classification in relation to risk level in overtaking maneuvers

Traffic crashes are a worldwide problem, and records have indicated frontal collisions have resulted in the most significant number of fatalities. Such a type of crash is frequently caused by improper overtaking of vehicles, which highlights the interference of human factors. Therefore, investigations on driver's risk perception are necessary. This study proposes a classification of driver's risk level through a decision tree using the Classification and Regression Tree (CART) algorithm from data collected from the overtaking maneuvers in a driving simulator. The model obtained by CART algorithm indicated young male drivers are more likely to take risks in overtaking maneuvers. The results were correlated with governmental records and similar studies. In addition, the results showed the potential of the tool for used as a risk level classifier, as well as the validation of the driving simulator in studies associated with human factor behaviours, accident analysis and investigation.     

The impact of auditory continual feedback on take-overs in Level 3 automated vehicles

ObjectiveTo implement auditory continual feedback into the interface design of a Level 3 automated vehicle and to test whether gaze behavior and reaction times of drivers improved in take-over situations.BackgroundWhen required to assume manual control in take-over situations, drivers of Level 3 automated vehicles are less likely than conventional drivers to spot potential hazards, and their reaction time is longer. Therefore, it is crucial that the interface of Level 3 automated vehicles will be designed to improve drivers’ performance in take-over situations.MethodIn two experiments, participants drove a simulated route in a Level 3 automated vehicle for 35 min with one imminent take-over event. Participants’ gaze behavior and performance in an imminent take-over event were monitored under one of three auditory interface designs: (1) Continual feedback. A system that provides verbal driving-related feedback; (2) Persistent feedback. A system that provides verbal driving-related feedback and a persistent beep; and (3) Chatter feedback. A system that provides verbal non-driving-related feedback. Also, there was a control group without feedback.ResultsUnder all three auditory feedback designs, the number of drivers' on-road glances increased compared to no feedback, but none of the designs shortened reaction time to the imminent event.ConclusionIncreasing the number of on-road glances during automated driving does not necessarily improve drivers’ attention to the road and their reaction times during take-overs.ApplicationPossible implications for the effectiveness of auditory continual feedback should be considered when designing interfaces for Level 3 automated vehicles.