Impact of the driver’s visual engagement on situation awareness and takeover quality

During automated driving (SAE Level 3), drivers can delegate control of the vehicle and monitoring of the road to an automated system. They may then devote themselves to tasks other than driving and gradually lose situational awareness (SA). This could result in difficulty in regaining control of the vehicle when the automated system requires it. In this simulator study, the level of SA was manipulated through the time spent performing a non-driving task (NDRT), which alternated with phases where the driver could monitor the driving scene, prior to a critical takeover request (TOR). The SA at the time of TOR, the visual behaviour after TOR, and the takeover quality were analysed. The results showed that monitoring the road just before the TOR allowed the development of limited perception of the driving situation, which only partially compensated for the lack of a consolidated mental model of the situation. The quality of the recovery, assessed through the number of collisions, was consistent with the level of development of SA. The analysis of visual behaviour showed that engagement in the non-driving task at the time of TOR induced a form of perseverance in consulting the interface where the task was displayed, to the detriment of checking the mirrors. These results underline the importance of helping the driver to restore good SA well in advance of a TOR.     

Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style

The emergence of highly automated driving technology provides safe and convenient travel while also causing user inadaptation. Therefore, based on human factors engineering, it is necessary to study highly automated vehicles (HAVs) that meet different user needs. Thus, this study aims to investigate the relationships between state anxiety, situational awareness, trust, and role adaptation. The adaptation model is constructed to conduct a study on the adaptation of HAVs with different automated styles when user roles change from driver to passenger. Simulated riding was conducted in the HAV experiment (N = 117), collecting scale data after each participant had experienced each automated driving style. A structural equation modeling approach was applied to analyze the adaptation model based on scale data. The results showed that there was a significant correlation between state anxiety, situational awareness, trust, and role adaptation. State anxiety has a significant negative predictive effect on trust, situational awareness, and role adaptation. In addition to its direct impact on role adaptation, state anxiety also has an indirect effect on role adaptation through situational awareness and trust. Furthermore, the automated driving style has been confirmed to have a moderating role in the relationship between the direct and indirect effects of state anxiety and role adaptation. Our findings contribute to multiple streams of the literature and have important implications for designing personalized automated driving to improve user acceptance.     

The effect of the dominance of an in-vehicle agent’s voice on driver situation awareness,emotion regulation,and trust: A simulated lab study of manual and automated driving

As in-vehicle voice agents increase in popularity, related research is extending to how voice messages can affect the driver’s cognitive and emotional states. Accordingly, we investigated how in-vehicle agent (IVA) voice dominance and driving automation can affect the driver’s situation awareness (SA), emotion regulation (ER), and trust. To this end, a lab-based experiment was conducted with a medium-fidelity driving simulator using actor-recorded voice agents. Twenty-two female and nineteen male driver-licensed participants were recruited to drive simulated vehicles with voice agents and evaluated. The results demonstrated that compared with the dominant voice, the agent with a submissive voice significantly increased ER in both manual and automated driving. Furthermore, the submissive voice significantly increased trust in automated driving compared with the dominant agent. Cross and synergistic interaction effects exist between voice dominance and driving automation in SA and ER, respectively. This study revealed that both the content of the messages of the IVAs and their voice characteristics are essential for modulating the driver’s SA, ER, and trust in driving. It is expected that larger-scale future studies with simulation or on a real road would increase the validity of this study.     

Feedback and driver situation awareness (SA): A comparison of SA measures and contexts

The dominant technological trajectory in vehicle design brings with it similarly dominant driver performance issues in regard to vehicle feedback and driver situational awareness (SA). Three experiments are reported in this paper that describe not only the effects on driver SA of manipulations of vehicle feedback but also illuminate issues concerned with SA measurement methods and contexts. The findings suggest that current trends in vehicle design may contribute little towards a driver’s SA and, in fact, may actually show a generalized trend towards decreasing it. The efficacy of verbal protocol and probe recall SA measurement techniques is noted in terms of observing this effect. On the other hand, a concerning dissociation occurred with findings from a self-report measure of SA. Drivers appear to show a concerning lack of self-awareness of their SA and, indeed, any shortfall in it.     

Controllability of Partially Automated Driving functions – Does it matter whether drivers are allowed to take their hands off the steering wheel?

Different motor vehicle manufacturers have recently introduced assistance systems that are capable of both longitudinal and lateral vehicle control, while the driver still has to be able to take over the vehicle control at all times (so-called Partial Automation). While these systems usually allow hands-free driving only for short time periods (e.g., 10 s), there has been little research whether allowing longer time periods of hands-off driving actually has a negative impact on driving safety in situations that the automation cannot handle alone. Altogether, two partially automated assistance systems, differing in the permitted hands-off intervals (Hands-off system vs. Hands-on system, n = 20 participants per assistance condition, age 25–70 years) were implemented in the driving simulation with a realistic take-over concept. The Hands-off system is defined by having a permitted hands-off interval of 120 s, while the Hands-on system is defined by a permitted hands-off interval of 10 s. Drivers’ reactions at a functional system limit were tested under conditions of high ecological validity: while driving in a traffic jam, participants unexpectedly encountered a time-critical situation, consisting of a vehicle at standstill that appeared suddenly and required immediate action. A visual-auditory take-over request was issued to the drivers. Regardless of the hands-off interval, all participants brought the vehicle to a safe stop. In spite of a stronger brake reaction with the Hands-on system, no significant differences between assistance levels were found in brake reaction times and the criticality of the situation. The reason for this may be that most of the drivers kept contact with the steering wheel, even in the Hands-off condition. Neither age nor prior experience with ACC was found to impact the results. The study thus demonstrates that permitting longer periods of hands-off driving does not necessarily lead to performance deficits of the driver in the case of take-over situations, if a comprehensive take-over concept is implemented.