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• Drivers on slip roads want vehicles on the target lane to decelerate. • Drivers in target lanes rate the behaviour of vehicles on slip roads ambiguously. • AVs are rated identically or even more positively than MVs with identical behaviour. • No different safety distance is kept from automated vehicles. • Results show that cross-border traffic between Germany and UK with AVs is feasible. • Intercultural aspects must still be considered in the development of AVs. To ensure safe and uninterrupted traffic flow, (semi-)automated vehicles must be capable of providing comprehensible and agreeable implicit communication cues to human drivers. This driving simulator study investigated the assessment of implicit communication at a motorway slip road through longitudinal driving dynamics (acceleration, deceleration, and maintaining speed). The second aim of the study was to determine whether expectations of automated vehicles are different from those of human drivers. And thirdly, we investigated whether these findings are country-specific or can be (partially) generalised to other countries. The perception of three means of communication in connection with the presence of a labelling as an automated vehicle (eHMI) was examined in two samples in Germany and England. 27 participants drove from a slip road onto the motorway and interacted with another vehicle. After a stretch on the motorway, they passed a second slip road on which there was a vehicle merging onto the participants lane. This was repeated six times to test all variables. After each situation, the perceived cooperativity and criticality was recorded, as well as the time headway (THW) to the other vehicle. This paper presents the findings from the UK sample and compares them with the German results, which were previously published. Results show, that when the cooperating vehicles are on the slip road, participants from both countries prefer this vehicle to decelerate. However, when participants themselves are on the slip road, expectations for vehicles on the target lane are ambiguous in the UK sample. Except for one aspect (perceived cooperativity of decelerating vehicles on the slip road), the perception of automated vehicles is similar to those of manual drivers. Also, UK participants do not maintain a different safety distance from these vehicles, while this is the case in the German sample. This paper contributes valuable insights into the cross-cultural evaluation of driving dynamics, shedding light on implications for the development and acceptance of automated vehicles. [ABSTRACT FROM AUTHOR]

• An experimental test track study explored the impact of three deceleration approaches and a non-driving activity on passenger comfort in diverse driving scenarios. • A linear deceleration profile was compared to two stepwise profiles derived from a trained chauffeur's driving data. • The linear deceleration was preferred for stops at Stop Signs, while smoother stepwise profiles were favoured overall. • Passenger engagement in a non-driving activity didn't affect comfort or profile preferences. • Participants reported perceiving a lower intensity of longitudinal vehicle movements when visually distracted during the drive. As automated vehicles advance and become more widespread, it is increasingly important to ensure optimal driving comfort for passengers. Recent research has focused on developing driving styles for automated vehicles that are perceived to be most comfortable. However, there is still little understanding of whether, and how, possible driving styles need to be adjusted for specific traffic scenarios. In this study, 36 participants experienced three different deceleration profiles (a linear deceleration profile 'One-Step', and two versions of stepwise deceleration profiles 'Two-Step V1 and V2') across different driving scenarios (deceleration before curves, approaching a speed-limit sign, and a stop sign). Deceleration profiles were rated by participants and the impact of non-driving related activities on driving comfort was investigated. Results showed a positive rating for all deceleration profiles in terms of comfort. For decelerations to a standstill at a Stop Sign, participants seemed to prefer the One-Step approach, in which there is a continuous, and constant deceleration. However, participants described the Two-Step V1 as a gentle and calmer approach and ranked it more frequently as a personal favourite than the One-Step profile or the Two-Step V2 profile. The visual distraction of the passenger through a non-driving activity had no impact on passenger comfort or profile preferences for the scenarios tested within this study. Nonetheless, participants reported perceiving a lower intensity of longitudinal vehicle movements when visually distracted during the drive. The results of the study provide insights into the design and implementation of comfortable deceleration profiles. [ABSTRACT FROM AUTHOR]

• The number and mean duration of glances away from the non-driving related tasks (NDRTs) increased significantly when the standard deviation (SD) of speed was high. • The mean speed had a significant effect on the mean glance duration, with longer glances away from NDRTs when mean speed was low, compared to that in high speed. • There was a significant effect of age on NDRT engagement, with older drivers less likely to engage in NDRTs, while female drivers were more engaged in NDRTs than males. Previous simulator and real-world studies with SAE Level 2 automated vehicles (AVs) have shown that, when compared to manual driving, drivers are more inattentive to the driving environment when automation is engaged, as reflected by fewer glances towards the forward roadway and side/rear view mirrors, and more focus on non-driving related tasks (NDRTs). Manual driving studies also suggest that drivers are more likely to engage in NDRTs during slow-moving or stationary traffic conditions. The aim of the current study was to understand whether NDRT engagement and visual attention patterns are impacted by the driving environment while drivers experienced a ride in a real-world SAE Level 3 AV. Forty-six video clips, from 32 drivers interacting with NDRTs during L3 motorway driving were analysed for this study. Due to the absence of externally facing cameras, the mean and standard deviation (SD) of driving speed were used as a proxy for assessing the surrounding traffic volume. The number of glances, and mean glance duration away from NDRTs per minute, were used as proxy measures for NDRT engagement. A generalised linear mixed model (GLMM) was used to investigate the effect of surrounding traffic on NDRT engagement. Results showed that the number and mean duration of glances away from the NDRT increased significantly when the SD of speed was high. The mean speed had a significant effect on the mean glance duration, with longer glances away from NDRTs when mean speed was low, compared to that in high speed. There was a significant effect of age on NDRT engagement, with older drivers less likely to engage in another task, while female drivers were more engaged in NDRTs than males. Overall, the results indicate that drivers' propensity to engage in NDRTs is impacted by the AV's speed, which is influenced by the volume of surrounding traffic. These results are useful for understanding the implications of surrounding traffic on drivers' self-regulated engagement in NDRTs in the real world during SAE Level 3 driving. [ABSTRACT FROM AUTHOR]

• An on-road study was conducted with prototype vehicles. • Participants experienced either a motorway or an urban automated driving function. • Impact of demographic and ADFs evaluation on their willingness to use was studied. • The higher feelings of ease and perceived usefulness, the higher willingness to use. • System monitoring requirements, information, expectations and age also predict WtU. To ensure the successful deployment of Automated Vehicles (AVs), it is important to understand users' acceptance and willingness to use. The majority of previous studies which have investigated Willingness to Use of automated functionalities in vehicles, have relied on users' imagination of system operational features, without any actual hands-on experience. To close this research gap, we conducted an extensive questionnaire study with participants who had experienced either a Motorway (N = 294) or an Urban (N = 144) Automated Driving Function (ADF) in an on-road study using prototype vehicles, conducted as part of the large-scale European L3Pilot project. We investigated the impact of participants' demographic characteristics, and their evaluation of the ADFs, on their Willingness to Use these ADFs again in the future. Findings revealed that age was a significant predictor but had a small effect, with younger users showing a higher Willingness to Use the Motorway ADF, but not the Urban ADF. Other user characteristics, such as safety drivers versus ordinary drivers, system familiarity, and gender, did not predict Willingness to Use, for either system. Factors related to users' Feelings of Ease (e.g., perceived safety, fun, comfort, trust) and Perceived Usefulness of the system, were the most important predictors, with more positive ratings for these factors leading to a higher Willingness to Use, for both systems. Other factors that showed an effect on Willingness to Use include System Monitoring Requirements (i.e., willingness to engage in other tasks instead of monitoring the system), System Information (i.e., wanting to know more about the system's limitations) and System Expectations being met. This study shows the importance of ensuring that users have a good experience and perceive the system as useful to increase their Willingness to Use the ADF. [ABSTRACT FROM AUTHOR]

• This experiment investigated whether gaze entropy metrics could estimate mental workload during hands-off Level 2 automation. • Previous research placed too much emphasis on average differences, despite human responses being inherently variable. • A Bayesian distributional multilevel modelling approach was used to quantify variability in gaze behaviours. • Variability was sufficient such that null effects and reversals of main effects were observed in a number of participants. As the level of vehicle automation increases, drivers are more likely to engage in non-driving related tasks which take their hands, eyes, and/or mind away from the driving task. Consequently, there has been increased interest in creating Driver Monitoring Systems (DMS) that are valid and reliable for detecting elements of driver state. Workload is one element of driver state that has remained elusive within the literature. Whilst there has been promising work in estimating mental workload using gaze-based metrics, the literature has placed too much emphasis on point estimate differences. Whilst these are useful for establishing whether effects exist, they ignore the inherent variability within individuals and between different drivers. The current work builds on this by using a Bayesian distributional modelling approach to quantify the within and between participants variability in Information Theoretical gaze metrics. Drivers (N = 38) undertook two experimental drives in hands-off Level 2 automation with their hands and feet away from operational controls. During both drives, their priority was to monitor the road before a critical takeover. During one drive participants had to complete a secondary cognitive task (2-back) during the hands-off Level 2 automation. Changes in Stationary Gaze Entropy and Gaze Transition Entropy were assessed for conditions with and without the 2-back to investigate whether consistent differences between workload conditions could be found across the sample. Stationary Gaze Entropy proved a reliable indicator of mental workload; 92 % of the population were predicted to show a decrease when completing 2-back during hands-off Level 2 automated driving. Conversely, Gaze Transition Entropy showed substantial heterogeneity; only 66 % of the population were predicted to have similar decreases. Furthermore, age was a strong predictor of the heterogeneity of the average causal effect that high mental workload had on eye movements. These results indicate that, whilst certain elements of Information Theoretic metrics can be used to estimate mental workload by DMS, future research needs to focus on the heterogeneity of these processes. Understanding this heterogeneity has important implications toward the design of future DMS and thus the safety of drivers using automated vehicle functions. It must be ensured that metrics used to detect mental workload are valid (accurately detecting a particular driver state) as well as reliable (consistently detecting this driver state across a population). [ABSTRACT FROM AUTHOR]

• Drivers' responses to silent automation failures were examined. • All drivers responded to all automation failures, despite no take-over requests. • NDRT engagement during automation resulted worse take-over behaviour. • More lane excursions, longer take-overs, and different distributions of visual attention. • Driver monitoring can detect drivers' attention to the driving task in automation. The aim of this study was to understand driver responses to "silent" failures in automated driving, where automation failed during a simulator drive, without a take-over warning. The effect of a visual non-driving related task (NDRT) and a road-based vigilance task presented drivers' take-over response and visual attention was also investigated. Currently, automated driving systems face a number of limitations that require control to be handed back to the driver. Much of the research to date has focused on explicit take-over requests (ToRs) and shows that drivers struggle to resume control safely, exacerbated by disengagement from the driving task, for instance, due to the presence of NDRTs. However, little is known about whether, and how, drivers will respond to more subtle automation failures that come without a warning, and how this is affected by NDRT engagement. Thirty participants drove a simulated automated drive in two conditions, which had 6 silent automation failures each (3 on a Curve, 3 in a Straight), with no ToRs. In one condition, drivers were required to constantly monitor the road, which was enforced by a road-based vigilance task (VMS Only). In the other, drivers performed an additional visual NDRT, requiring them to divide their attention (VMS + Arrows). Results showed that, in both conditions, all drivers eventually detected and responded to all silent automation failures. However, engaging in an additional NDRT during automation resulted in significantly more lane excursions and longer take-over times. Adding a visual NDRT not only changed the distribution of drivers' visual attention before and after the failure but also how they divided their attention between information on the road environment and the human–machine interface, which provided information on automation status. These results provide support for how driver monitoring systems may be used to detect drivers' visual attention to the driving task and surroundings, and used as a tool for encouraging driver intervention, when required. [ABSTRACT FROM AUTHOR]

The influence of driver distraction on driving performance is not yet well understood, but it can have detrimental effects on road safety. In this study, we examined the effects of visual and non-visual distractions during driving, using a high-fidelity driving simulator. The visual task was presented either at an offset angle on an in-vehicle screen, or on the back of a moving lead vehicle. Similar to results from previous studies in this area, non-visual (cognitive) distraction resulted in improved lane keeping performance and increased gaze concentration towards the centre of the road, compared to baseline driving, and further examination of the steering control metrics indicated an increase in steering wheel reversal rates, steering wheel acceleration, and steering entropy. We show, for the first time, that when the visual task is presented centrally, drivers’ lane deviation reduces (similar to non-visual distraction), whilst measures of steering control, overall, indicated more steering activity, compared to baseline. When using a visual task that required the diversion of gaze to an in-vehicle display, but without a manual element, lane keeping performance was similar to baseline driving. Steering wheel reversal rates were found to adequately tease apart the effects of non-visual distraction (increase of 0.5° reversals) and visual distraction with offset gaze direction (increase of 2.5° reversals). These findings are discussed in terms of steering control during different types of in-vehicle distraction, and the possible role of manual interference by distracting secondary tasks. [ABSTRACT FROM AUTHOR]

• The difference between visual-manual and auditory-cognitive distractions is investigated. • The effects of time pressure and distractions on pedestrian crossing behaviour are compared. • The impacts of these secondary tasks on pedestrian crossing behaviour and safety are evaluated. • A novel traffic flow impact on pedestrian is found. Distractions have been recognised as one important factor associated with pedestrian injuries, as the increasing use of cell phones and personal devices. However, the situation is less clear regarding the differences in the effects of visual-manual and auditory-cognitive distractions. Here, we investigated distracted pedestrians in a one-lane road with continuous traffic using an immersive CAVE-based simulator. Sixty participants were recruited to complete a crossing task and perform one of two distractions, a visual-manual task and an auditory-cognitive task. Moreover, normal and time pressure crossing conditions were included as a baseline and comparison. For the first time, this study directly compared the impacts of visual-manual, auditory-cognitive distractions, and time pressure on pedestrian crossing behaviour and safety in a controlled environment. The results indicated that although pedestrian safety was compromised under both types of distraction, the effects of the applied distractions were different. When engaged in the visual-manual distraction, participants crossed the road slowly, but there was no significant difference in gap acceptance or initiation time compared to baseline. In contrast, participants walked slowly, crossed earlier, and accepted smaller gaps when performing the auditory-cognitive distraction. This has interesting parallels to existing findings on how these two types of distractions affect driver performance. Moreover, the effects of the visual-manual distraction were found to be dynamic, as these effects were affected by the gap size. Finally, compared to baseline, time pressure resulted in participants accepting smaller time gaps with shorter initiation times and crossing durations, leading to an increase in unsafe decisions and a decrease in near-collisions. These results provide new evidence that two types of distraction and time pressure impair pedestrian safety, but in different ways. Our findings may provide insights for further studies involving pedestrians with different distraction components. [ABSTRACT FROM AUTHOR]

Driving around bends at high speeds is a task performed by many on a daily basis but the underlying mechanisms of steering control remain largely unknown. Previous research has shown that when steering, gaze direction can be a critical component of success. However, with increased use of in-vehicle information systems (IVIS), there is growing competition over the same resources that are needed to steer (gaze as well as associated attentional resources). Although it can be argued that locomotor steering is an automatic task that can be performed without recourse to conscious “cognitive” control, much simpler locomotor-related tasks, such as judging one’s heading, have been shown to be affected by concurrent attentional tasks (Wann, Swapp, & Rushton, 2000). Here we examined whether an attentional task placed at an offset fixation point influenced concurrent steering performance along a computer simulated road. The experiments either used gaze-fixation points that had similar properties to real-world road signs (i.e. moved relative to the vehicle) or were more akin to IVIS (i.e. fixed to the vehicle). Results showed that gaze fixation eccentric to future path caused systematic steering biases. The degree or type of cognitive load did not change the degree of steering bias, but there was some evidence of decreased lane variability when viewing the IVIS-type displays. No differences in steering performance were found between the different types of cognitive task. We conclude that where you look is critical for safe driving, and IVIS-type displays might make drivers more susceptible to cognitive interference. [ABSTRACT FROM AUTHOR]