The last decade has seen a surge of driving simulator research on automation-to-manual take-overs. In this commentary, we argue that most research within the take-over paradigm bears little resemblance to real automated driving. Furthermore, we claim that results within this paradigm could already be known based on published research from the previous century. It is concluded that take-over studies have characteristics of a self-sustaining convenience. We end with recommendations for out-of-the-box take-over research that may contribute to the development of safer automated vehicles.

Objective: Research has shown that perceived risk is a vital variable in the understanding of road traffic safety. Having experience in a particular traffic environment can be expected to affect perceived risk. More specifically, drivers may readily recognize traffic hazards when driving in their own world region, resulting in high perceived risk (the expertise hypothesis). Oppositely, drivers may be desensitized to traffic hazards that are common in their own world region, resulting in low perceived risk (the desensitization hypothesis). This study investigated whether participants experienced higher or lower perceived risk for traffic situations from their region compared to traffic situations from other regions. Methods: In a crowdsourcing experiment, participants viewed dashcam videos from four regions: India, Venezuela, United States, and Western Europe. Participants had to press a key when they felt the situation was risky. Results: Data were obtained from 800 participants, with 52 participants from India, 75 from Venezuela, 79 from the United States, 32 from Western Europe, and 562 from other countries. The results provide support for the desensitization hypothesis. For example, participants from India perceived low risk for hazards (e.g., a stationary car on the highway) that were perceived as risky by participants from other regions. At the same time, support for the expertise hypothesis was obtained, as participants in some cases detected hazards that were specific to their own region (e.g., participants from Venezuela detected inconspicuous roadworks in a Venezuelan city better than did participants from other regions). Conclusion: We found support for the desensitization hypothesis and the expertise hypothesis. These findings have implications for cross-cultural hazard perception research.

Objective: We review the sampling models described in John Senders’s doctoral thesis on “visual sampling processes” via a ready and accessible exposition. Background: John Senders left a significant imprint on human factors/ergonomics (HF/E). Here, we focus on one preeminent aspect of his career, namely visual attention. Methods: We present, clarify, and expand the models in his thesis through computer simulation and associated visual illustrations. Results: One of the key findings of Senders’s work on visual sampling concerns the linear relationship between signal bandwidth and visual sampling rate. The models that are used to describe this relationship are the periodic sampling model (PSM), the random constrained sampling model (RCM), and the conditional sampling model (CSM). A recent replication study that used results from modern eye-tracking equipment showed that Senders’s original findings are manifestly replicable. Conclusions: Senders’s insights and findings withstand the test of time and his models continue to be both relevant and useful to the present and promise continued impact in the future. Application: The present paper is directed to stimulate a broad spectrum of researchers and practitioners in HF/E and beyond to use these important and insightful models.

Objective: The aim of the study was to investigate the effect of augmented feedback on participants’ workload, performance, and distribution of visual attention. Background: An important question in human–machine interface design is whether the operator should be provided with direct solutions. We focused on the solution space diagram (SSD), a type of augmented feedback that shows directly whether two aircraft are on conflicting trajectories. Method: One group of novices (n = 13) completed conflict detection tasks with SSD, whereas a second group (n = 11) performed the same tasks without SSD. Eye-tracking was used to measure visual attention distribution. Results: The mean self-reported task difficulty was substantially lower for the SSD group compared to the No-SSD group. The SSD group had a better conflict detection rate than the No-SSD group, whereas false-positive rates were equivalent. High false-positive rates for some scenarios were attributed to participants who misunderstood the SSD. Compared to the No-SSD group, the SSD group spent a large proportion of their time looking at the SSD aircraft while looking less at other areas of interest. Conclusion: Augmented feedback makes the task subjectively easier but has side effects related to visual tunneling and misunderstanding. Application: Caution should be exercised when human operators are expected to reproduce task solutions that are provided by augmented visual feedback.

Objective: To investigate pedestrians’ misuse of an automated vehicle (AV) equipped with an external human–machine interface (eHMI). Misuse occurs when a pedestrian enters the road because of uncritically following the eHMI’s message. Background: Human factors research indicates that automation misuse is a concern. However, there is no consensus regarding misuse of eHMIs. Methods: Sixty participants each experienced 50 crossing trials in a Cave Automatic Virtual Environment (CAVE) simulator. The three independent variables were as follows: (1) behavior of the approaching AV (within-subject: yielding at 33 or 43 m distance, no yielding), (2) eHMI presence (within-subject: eHMI on upon yielding, off), and (3) eHMI onset timing (between-subjects: eHMI turned on 1 s before or 1 s after the vehicle started to decelerate). Two failure trials were included where the eHMI turned on, yet the AV did not yield. Dependent measures were the moment of entering the road and perceived risk, comprehension, and trust. Results: Trust was higher with eHMI than without, and the −1 Group crossed earlier than the +1 Group. In the failure trials, perceived risk increased to high levels, whereas trust and comprehension decreased. Thirty-five percent of the participants in the −1 and +1 Groups walked onto the road when the eHMI failed for the first time, but there were no significant differences between the two groups. Conclusion: eHMIs that provide anticipatory information stimulate early crossing. eHMIs may cause people to over-rely on the eHMI and under-rely on the vehicle-intrinsic cues. Application: eHMI have adverse consequences, and education of eHMI capability is required.

The topic of situation awareness has received continuing interest over the last decades. Freeze-probe methods, such as the Situation Awareness Global Assessment Technique (SAGAT), are commonly employed for measuring situation awareness. The aim of this paper was to review validity issues of the SAGAT and examine whether eye movements are a promising alternative for measuring situation awareness. First, we outlined six problems of freeze-probe methods, such as the fact that freeze-probe methods rely on what the operator has been able to remember and then explicitly recall. We propose an operationalization of situation awareness based on the eye movements of the person in relation to their task environment to circumvent shortfalls of memory mediation and task interruption. Next, we analyzed experimental data in which participants (N = 86) were tasked to observe a display of six dials for about 10 min, and press the space bar if a dial pointer crossed a threshold value. Every 90 s, the screen was blanked and participants had to report the state of the dials on a paper sheet. We assessed correlations of participants’ task performance (% of threshold crossing detected) with visual sampling scores (% of dials glanced at during threshold crossings) and freeze-probe scores. Results showed that the visual-sampling score correlated with task performance at the threshold-crossing level (r = 0.31) and at the individual level (r = 0.78). Freeze-probe scores were low and showed weak associations with task performance. We conclude that the outlined limitations of the SAGAT impede measurement of situation awareness, which can be computed more effectively from eye movement measurements in relation to the state of the task environment. The present findings have practical value, as advances in eye-tracking cameras and ubiquitous computing lessen the need for interruptive tests such as SAGAT. Eye-based situation awareness is a predictor of performance, with the advantage that it is applicable through real-time feedback technologies.

In pioneering work, Senders (1983) tasked five participants to watch a bank of six dials, and found that glance rates and times glanced at dials increase linearly as a function of the frequency bandwidth of the dial's pointer. Senders did not record the angle of the pointers synchronously with eye movements, and so could not assess participants’ visual sampling behavior in regard to the pointer state. Because the study of Senders has been influential but never repeated, we replicated and extended it by assessing the relationship between visual sampling and pointer state, using modern eye-tracking equipment. Eye tracking was performed with 86 participants who watched seven 90-second videos, each video showing six dials with moving pointers. Participants had to press the spacebar when any of the six pointers crossed a threshold. Our results showed a close resemblance to Senders’ original results. Additionally, we found that participants did not behave in accordance with a periodic sampling model, but rather were conditional samplers, in that the probability of looking at a dial was contingent on pointer angle and velocity. Finally, we found that participants sampled more in agreement with Nyquist sampling when the high bandwidth dials were placed in the middle of the bank rather than at its outer edges. We observed results consistent with the saliency, effort, expectancy, and value model and conclude that human sampling of multidegree of freedom systems should not only be modeled in terms of bandwidth but also in terms of saliency and effort.