Knowing me, knowing you-A study on top-down requirements for compensatory scanning in drivers with homonymous visual field loss.

OBJECTIVE: It is currently still unknown why some drivers with visual field loss can compensate well for their visual impairment while others adopt ineffective strategies. This paper contributes to the methodological investigation of the associated top-down mechanisms and aims at validating a theoretical model on the requirements for successful compensation among drivers with homonymous visual field loss. METHODS: A driving simulator study was conducted with eight participants with homonymous visual field loss and eight participants with normal vision. Participants drove through an urban surrounding and experienced a baseline scenario and scenarios with visual precursors indicating increased likelihoods of crossing hazards. Novel measures for the assessment of the mental model of their visual abilities, the mental model of the driving scene and the perceived attention demand were developed and used to investigate the top-down mechanisms behind attention allocation and hazard avoidance. RESULTS: Participants with an overestimation of their visual field size tended to prioritize their seeing side over their blind side both in subjective and objective measures. The mental model of the driving scene showed close relations to the subjective and actual attention allocation. While participants with homonymous visual field loss were less anticipatory in their usage of the visual precursors and showed poorer performances compared to participants with normal vision, the results indicate a stronger reliance on top-down mechanism for drivers with visual impairments. A subjective focus on the seeing side or on near peripheries more frequently led to bad performances in terms of collisions with crossing cyclists. CONCLUSION: The study yielded promising indicators for the potential of novel measures to elucidate top-down mechanisms in drivers with homonymous visual field loss. Furthermore, the results largely support the model of requirements for successful compensatory scanning. The findings highlight the importance of individualized interventions and driver assistance systems tailored to address these mechanisms.

Exoskeletons: A challenge for development.

The development of exoskeletons is currently a lengthy process full of challenges. We are proposing a framework to accelerate the process and make the resulting exoskeletons more user-centered. The needed accomplishments in science are described in an effort to lay the foundation for future research projects. Since the early 2000s, exoskeletons have been discussed as an emerging technology in industrial, medical, or military applications. Those systems are designed to support people during manual tasks. At first, those systems lacked broad acceptance. Many models found their niches in ongoing developments and more diverse systems entering the market. There are still applications that are in dire need of such assistance. Due to the lack of experience with body-worn robotics, the development of such systems has been shaped by trial and error. The lack of legacy products results in longer development times. In this paper, a process to generate a framework is presented to display the required research to enable future exoskeleton designers. Owing to their proximity to the user's body, exoskeletons are highly complex systems that need sophisticated subsystems, such as kinematic, control, interaction design, or actuators, to be accepted by users. Due to the wide variety of fields and high user demands, a synchronized multidisciplinary effort is necessary. To achieve this, a process to develop a modular framework for exoskeleton design is proposed. It focuses on user- and use-case-centered solutions for matching kinematics, actuation, and control. To ensure the usefulness of the framework, an evaluation of the incorporated solutions is required.

Digital ergonomics and digital work planning in university education: experiences from Germany and Austria.

The publication presents an overview of the use of digital human models (DHM) in academic education at five exemplary universities in Germany and Austria. In addition to the presentation of different human models, the integration of them into the respective lectures is discussed. The teaching concepts of the individual courses of the universities, exercise examples and scenarios are presented. Experience shows that the active and independent use of digital ergonomics tools gives students pleasure and motivates them to deal intensively with complex tasks in terms of time and content. Feedback is consistently positive over all the involved lectures and universities. As a consequence of the recent Covid-19 pandemic, universities significantly increased online and blended learning. Based on the experience with the use of digital human models, the paper derives recommendations for future developments. Practical Relevance To sustain global value chains, companies are increasingly planning trans-regionally adapted products and production processes. Tools for digital ergonomics contribute to increasing competitiveness by using prospective working methods. Companies increasingly need experts with the corresponding know-how. Firmly anchoring the topic of digital ergonomics in relevant subjects of university teaching is therefore a prerequisite for this transfer of trained graduates.

Non-driving related tasks' effects on takeover and manual driving behavior in a real driving setting: A differentiation approach based on task switching and modality shifting.

Many studies on effects of non-driving related tasks in the context of SAE Level3 automated driving have been conducted in driving simulator settings applying standardized tasks. Thereby internal validity is favored over external validity. To assess the influence of engagement in three natural non-driving related tasks on takeover behavior in the context of SAE Level3 automated driving, we conducted an experiment on a test track with a sample of naïve participants from the general public. We used a Wizard-of-Oz vehicle to simulate a SAE Level 3 traffic jam function in a real driving setting. To measure effects of compatibility between non-driving related tasks and driving task on subsequent takeover behavior and following manual driving behavior, participants played Tetris, watched a documentary film and read a text and typed a summary of it. After approx. 15 min, each non-driving related task was interrupted by a request to intervene. In the manual driving phase after the third takeover, participants encountered a balloon car positioned on their lane which they had to evade. Results show longer takeover times in the film and text condition compared to the Tetris condition. Implications on theory and practice are discussed.

A Compliance-Reactance Framework for Evaluating Human-Robot Interaction.

When do we follow requests and recommendations and which ones do we choose not to comply with? This publication combines definitions of compliance and reactance as behaviours and as affective processes in one model for application to human-robot interaction. The framework comprises three steps: human perception, comprehension, and selection of an action following a cue given by a robot. The paper outlines the application of the model in different study settings such as controlled experiments that allow for the assessment of cognition as well as observational field studies that lack this possibility. Guidance for defining and measuring compliance and reactance is outlined and strategies for improving robot behaviour are derived for each step in the process model. Design recommendations for each step are condensed into three principles on information economy, adequacy, and transparency. In summary, we suggest that in order to maximise the probability of compliance with a cue and to avoid reactance, interaction designers should aim for a high probability of perception, a high probability of comprehension and prevent negative affect. Finally, an example application is presented that uses existing data from a laboratory experiment in combination with data collected in an online survey to outline how the model can be applied to evaluate a new technology or interaction strategy using the concepts of compliance and reactance as behaviours and affective constructs.

How users of automated vehicles benefit from predictive ambient light displays.

With the introduction of Level 3 and 4 automated driving, the engagement in a variety of non-driving related activities (NDRAs) will become legal. Previous research has shown that users desire information about the remaining time in automated driving mode and system status information to plan and terminate their activity engagement. In past studies, however, the positive effect of this additional information was realized when it was integrated in or displayed close by the NDRA. As future activities and corresponding items will be diverse, a device-independent and non-interruptive way of communication is required to continuously keep the user informed, thus avoiding negative effects on driver comfort and safety. With a set of two driving simulator studies, we have investigated the effectiveness of ambient light display (ALD) concepts communicating remaining time and system status when engaged in visually distracting NDRAs. In the first study with 21 participants, a traffic light color-coded ALD concept (LED stripe positioned at the bottom of the windshield) was compared to a baseline concept in two subsequent drives. Subjects were asked to rate usability, workload, trust, and their use of travel time after each drive. Furthermore, gaze data and NDRA disengagement timing was analyzed. The ALD with three discrete time steps led to improved usability ratings and lower workload levels compared to the baseline interface without any ALD. No significant effects on trust, attention ratio, travel time evaluation, and NDRA continuation were found, but a vast majority favored the ALD. Due to this positive evaluation, the traffic light ALD concept was subsequently improved and compared to an elapsing concept in a subsequent study with 32 participants. In addition to the first study, the focus was on the intuitiveness of the developed concepts. In a similar setting, results revealed no significant differences between the ALD concepts in subjective ratings (workload, usability, trust, travel time ratings), but advantages of the traffic light concept can be found in terms of its intuitiveness and the level of support experienced.

Pedestrian Crossing Decisions in Virtual Environments: Behavioral Validity in CAVEs and Head-Mounted Displays.

OBJECTIVE: To contribute to the validation of virtual reality (VR) as a tool for analyzing pedestrian behavior, we compared two types of high-fidelity pedestrian simulators to a test track. BACKGROUND: While VR has become a popular tool in pedestrian research, it is uncertain to what extent simulator studies evoke the same behavior as nonvirtual environments. METHOD: An identical experimental procedure was replicated in a CAVE automatic virtual environment (CAVE), a head-mounted display (HMD), and on a test track. In each group, 30 participants were instructed to step forward whenever they felt the gap between two approaching vehicles was adequate for crossing. RESULTS: Our analyses revealed distinct effects for the three environments. Overall acceptance was highest on the test track. In both simulators, crossings were initiated later, but a relationship between gap size and crossing initiation was apparent only in the CAVE. In contrast to the test track, vehicle speed significantly affected acceptance rates and safety margins in both simulators. CONCLUSION: For a common decision task, the results obtained in virtual environments deviate from those in a nonvirtual test bed. The consistency of differences indicates that restrictions apply when predicting real-world behavior based on VR studies. In particular, the higher susceptibility to speed effects warrants further investigation, since it implies that differences in perceptual processing alter experimental outcomes. APPLICATION: Our observations should inform the conclusions drawn from future research in pedestrian simulators, for example by accounting for a higher sensitivity to speed variations and a greater uncertainty associated with crossing decisions.

Investigating Differences in Behavior and Brain in Human-Human and Human-Autonomous Vehicle Interactions in Time-Critical Situations.

Some studies provide evidence that humans could actively exploit the alleged technological advantages of autonomous vehicles (AVs). This implies that humans may tend to interact differently with AVs as compared to human driven vehicles (HVs) with the knowledge that AVs are programmed to be risk-averse. Hence, it is important to investigate how humans interact with AVs in complex traffic situations. Here, we investigated whether participants would value interactions with AVs differently compared to HVs, and if these differences can be characterized on the behavioral and brain-level. We presented participants with a cover story while recording whole-head brain activity using fNIRS that they were driving under time pressure through urban traffic in the presence of other HVs and AVs. Moreover, the AVs were programmed defensively to avoid collisions and had faster braking reaction times than HVs. Participants would receive a monetary reward if they managed to finish the driving block within a given time-limit without risky driving maneuvers. During the drive, participants were repeatedly confronted with left-lane turning situations at unsignalized intersections. They had to stop and find a gap to turn in front of an oncoming stream of vehicles consisting of HVs and AVs. While the behavioral results did not show any significant difference between the safety margin used during the turning maneuvers with respect to AVs or HVs, participants tended to be more certain in their decision-making process while turning in front of AVs as reflected by the smaller variance in the gap size acceptance as compared to HVs. Importantly, using a multivariate logistic regression approach, we were able to predict whether the participants decided to turn in front of HVs or AVs from whole-head fNIRS in the decision-making phase for every participant (mean accuracy = 67.2%, SD = 5%). Channel-wise univariate fNIRS analysis revealed increased brain activation differences for turning in front of AVs compared to HVs in brain areas that represent the valuation of actions taken during decision-making. The insights provided here may be useful for the development of control systems to assess interactions in future mixed traffic environments involving AVs and HVs.

Opportunities and Limitations of a Gaze-Contingent Display to Simulate Visual Field Loss in Driving Simulator Studies.

Background: Research on task performance under visual field loss is often limited due to small and heterogenous samples. Simulations of visual impairments hold the potential to account for many of those challenges. Digitally altered pictures, glasses, and contact lenses with partial occlusions have been used in the past. One of the most promising methods is the use of a gaze-contingent display that occludes parts of the visual field according to the current gaze position. In this study, the gaze-contingent paradigm was implemented in a static driving simulator to simulate visual field loss and to evaluate parallels in the resulting driving and gaze behavior in comparison to patients. Methods: The sample comprised 15 participants without visual impairment. All the subjects performed three drives: with full vision, simulated left-sided homonymous hemianopia, and simulated right-sided homonymous hemianopia, respectively. During each drive, the participants drove through an urban environment where they had to maneuver through intersections by crossing straight ahead, turning left, and turning right. Results: The subjects reported reduced safety and increased workload levels during simulated visual field loss, which was reflected in reduced lane position stability and greater absence of large gaze movements. Initial compensatory strategies could be found concerning a dislocated gaze position and a distorted fixation ratio toward the blind side, which was more pronounced for right-sided visual field loss. During left-sided visual field loss, the participants showed a smaller horizontal range of gaze positions, longer fixation durations, and smaller saccadic amplitudes compared to right-sided homonymous hemianopia and, more distinctively, compared to normal vision. Conclusion: The results largely mirror reports from driving and visual search tasks under simulated and pathological homonymous hemianopia concerning driving and scanning challenges, initially adopted compensatory strategies, and driving safety. This supports the notion that gaze-contingent displays can be a useful addendum to driving simulator research with visual impairments if the results are interpreted considering methodological limitations and inherent differences to the pathological impairment.

[Work design measures and solutions for dealing with the COVID-19 pandemic: A systematic analysis of work in the primary, secondary, and tertiary sectors in Germany]. / Maßnahmen und Lösungen zur Arbeitsgestaltung für den Umgang mit der COVID-19 Pandemie: Eine systematische Analyse der Arbeit im Primär­, Sekundär- und Tertiärsektor in Deutschland.

The demand to adapt the work processes to hygiene- and contact reduction requirements in order to curtail the spread of the COVID-19 pandemic in Germany has led to short-term and sometimes radical changes in companies and organizations. Based on 52 expert interviews with company and organization representatives, this research project analyzed which pandemic-related changes in the context of work occur on a supraregional and cross-sectoral level, how they are to be evaluated, and which new ways of working might also prove beneficial to companies after the pandemic. In line with existing studies, an increasing flexibilization of work location and working hours, an acceleration of the digitalization of work processes, and effects on leadership culture were identified. Other key experiences relate to the adaptation of internal and external communication processes and the operational handling of crisis-related challenges. Based on the results, good practices were derived in form of normative-narrative use-case based scenarios.Practical Relevance: Dealing with the COVID-19 pandemic has been the central challenge for many companies over the past year and a half. The presented results show measures that have been successfully implemented in practice to overcome the challenges posed by the crisis, as well as approaches for the future development of forms of work. The measures are contextualized by outlining necessary framework conditions and success factors, thus promoting transfer to other companies and sectors of the economy.

Communication via motion - Suitability of automated vehicle movements to negotiate the right of way in road bottleneck scenarios.

The introduction of automated vehicles (AVs) into urban areas initially leads to mixed traffic, consisting of AVs, human drivers, and vulnerable road users. Since the AV's passenger is no longer actively involved in the driving task, there may be changes in the interaction between AVs and surrounding human road users. Therefore, it is essential for an AV to behave in a comprehensible manner in order to maintain or even enhance traffic efficiency and traffic safety. This work investigates the interaction of an AV and a simultaneously oncoming human driver at road bottlenecks due to double-parked vehicles on both sides of the road. Based on findings derived from AV-pedestrian interaction, comfort limits in terms of driving dynamics, and traffic observations, we designed nine AV movements to either yield the right of way or to insist on it by varying the AV's speed (maintain speed, one-step deceleration, two-step deceleration) and its lateral offset (no offset, close offset, distant offset). The different vehicle movements were evaluated with 34 participants in a driving simulator study. The results show participants' shorter passing times, fewer crashes, and significantly higher ratings of the AV's communication if the AV movement contained a lateral offset. In addition to the regular encounters, we analyzed the controllability of an automation failure and its aftereffect on participants' trust in AVs. The experience of the automation failure reduced the trust rating significantly. From the results we conclude that the AV should communicate the right of way not only via speed adjustments but also via the performance of a lateral offset to enhance traffic efficiency and safety. Moreover, a change in the AV's maneuver due to an automation failure must be avoided since it is not controllable by the human driver.

Design of a hesitant movement gesture for mobile robots.

In previous experiments, a back-off movement was introduced as a motion strategy of robots to facilitate the order of passage at bottlenecks in human-robot spatial interaction. In this article we take a closer look at the appropriate application of motion parameters that make the backward movement legible. Related works in distance perception, size-speed illusions, and viewpoint-based legibility considerations suggest a relationship between the size of the robot and the observer's perspective on the expected execution of this movement. We performed a participant experiment (N = 50) in a virtual reality environment where participants adjusted the minimum required back-off length and preferred back-off speed as a result of the robot size, and the viewpoint of the back-off movement. We target a model-based approach on how appropriate back-off design translates to different sized robots and observer's viewpoints. Thus, we allow the application of back-off in a variety of autonomous moving systems. The results show a significant correlation between the increasingly expected back-off lengths with increasing robot size, but only weak effects of the viewpoint on the requirements of this movement. An exploratory analysis suggests that execution time might be a promising parameter to consider for the design of legible motion.

Analysis of Street-Crossing Behavior: Comparing a CAVE Simulator and a Head-Mounted Display among Younger and Older Adults.

Interactive pedestrian simulators have become a valuable research tool for investigating street-crossing behavior and developing solutions for improving pedestrian safety. There are two main kinds of pedestrian simulators: one uses a technology based on rear-projection screens (Cave Automatic Virtual Environment, or CAVE), the other a head-mounted display (HMD). These devices are used indiscriminately, regardless of the research objective, and it is not yet known whether they are equally effective for studying street crossing. The present study was aimed at comparing the street crossing behavior and subjective evaluations of younger and older adult pedestrians when they are using a CAVE-like or HMD-based (HTC Vive Pro) pedestrian simulator. Thirty younger adults and 25 older adults performed 36 street-crossing trials (combining different speeds, two-way traffic conditions, and gap sizes) on each of the two types of simulators. The results indicated that participants in the HMD condition crossed the street significantly more often (58.6 %) than in the CAVE condition (42.44%) and had shorter safety margins. The most striking difference pertained to crossing initiation, which occurred considerably earlier (1.78 s) in the HMD condition than in the CAVE condition. Synchronization of crossing initiation with oncoming traffic was not as good in the CAVE condition because visual information in front of the pedestrian was missing due to the absence of ground projection. In both simulators, older adults caused more collisions than did younger ones, had shorter safety margins, and a slower crossing speed. Hence, the HMD reproduced classical age-related differences in most street-crossing behaviors already found on the CAVE. Usually observed speed effects were also found for both simulators. Neither cybersickness nor any adverse effects on stereoacuity or postural balance were found for either simulator. The HMD produced a higher level of presence and preference than the CAVE did. These findings provide evidence that HMDs have a clear potential for studying pedestrian behaviour.

Measuring egocentric distance perception in virtual reality: Influence of methodologies, locomotion and translation gains.

Virtual reality has become a popular means to study human behavior in a wide range of settings, including the role of pedestrians in traffic research. To understand distance perception in virtual environments is thereby crucial to the interpretation of results, as reactions to complex and dynamic traffic scenarios depend on perceptual processes allowing for the correct anticipation of future events. A number of approaches have been suggested to quantify perceived distances. While previous studies imply that the selected method influences the estimates' accuracy, it is unclear how the respective estimates depend on depth information provided by different perceptual modalities. In the present study, six methodological approaches were compared in a virtual city scenery. The respective influence of visual and non-visual cues was investigated by manipulating the ratio between visually perceived and physically walked distances. In a repeated measures design with 30 participants, significant differences between methods were observed, with the smallest error occurring for visually guided walking and verbal estimates. A linear relation emerged between the visual-to-physical ratio and the extent of underestimation, indicating that non-visual cues during walking affected distance estimates. This relationship was mainly evident for methods building on actual or imagined walking movements and verbal estimates.

Effects of Task-Induced Fatigue in Prolonged Conditional Automated Driving.

OBJECTIVE: The aim of this study was to investigate the effects of task-induced fatigue in prolonged conditional automated driving on takeover performance. BACKGROUND: In conditional automated driving, the driver can engage in non-driving related tasks (NDRTs) and does not have to monitor the system and the driving environment. In the event that the system hits its limits, the human driver must regain control of the car. To ensure safety, adequate driver fallback performance is necessary. Effects of the drivers' state and the engagement in NDRTs need to be investigated. METHOD: Seventy-three participants experienced prolonged conditional automated rides and simultaneously had to engage in either an activating quiz or a fatiguing monitoring task (between subjects). After 50 minutes, a takeover situation occurred, and participants had to regain control of the car. RESULTS: Prolonged conditional automated driving and simultaneously engaging in NDRTs affected the driver's state and the takeover performance of the participants. Takeover performance was impaired when participants had to deal with monotonous NDRTs. CONCLUSION: An engagement in monotonous monitoring tasks in conditional automated driving affects the driver's state and takeover performance when it comes to takeover situations. Especially in prolonged automated driving, an adequate driver state seems to be necessary for safety reasons. APPLICATION: The results of this study demonstrate that engagement in monotonous NDRTs while driving conditionally automated may negatively affect takeover performance. A monitoring of the driver state and adapted assistance in a takeover situation seems to be a good opportunity to ensure safety.

Influence of Size-Weight Illusion on Usability in Haptic Human-Robot Collaboration.

Collaborative power amplifying robots are accepted as one solution to overcome flexibility and ergonomic issues in future work and life scenarios. The handling of various sized and weighted objects in heterogeneous environments pose a particular challenge to the often applied admittance control. Haptic illusions, especially the Size-Weight Illusion (SWI), where the smaller of two equally weighted objects is perceived to be heavier, can have malicious, disturbing, or to some extent useful influence on system stability and usability. A within-subjects experiment was conducted with 40 participants and three within-factors (size, weight, and movement type), to investigate the occurrence and influence of SWI in bimanual fast-imprecise and slow-precise planar manipulation tasks. The illusion was replicated and an influence on usability was found. Further, different control strategies according to object size and mass (static, compensatory, and mismatch) were analyzed and did not show significant effects on task performance. It appears that either no change in assistance or a change according to object size is advisable.

Why Do I Have to Drive Now? Post Hoc Explanations of Takeover Requests.

OBJECTIVE: It was investigated whether providing an explanation for a takeover request in automated driving influences trust in automation and acceptance. BACKGROUND: Takeover requests will be recurring events in conditionally automated driving that could undermine trust as well as acceptance and, therefore, the successful introduction of automated vehicles. METHOD: Forty participants were equally assigned to either an experimental group provided with an explanation of the reason for a takeover request or a control group without explanations. In a simulator drive, both groups experienced three takeover scenarios that varied in the obviousness of their causation. Participants rated their acceptance before and after the drive and rated their trust before and after each takeover situation. RESULTS: All participants rated acceptance on the same high level before and after the drive, independent of the condition. The control group's trust ratings remained unchanged by takeover requests in all situations, but the experimental group showed decreased trust after experiencing a takeover caused by roadwork. Participants provided with explanation felt more strongly that they had understood the system and the reasons for the takeovers. CONCLUSION: A takeover request did not lower trust or acceptance. Providing an explanation for a takeover request had no impact on trust or acceptance but increased the perceived understanding of the system. APPLICATION: The results provide insights into users' perception of automated vehicles, takeover situations, and a fundament for future interface design for automated vehicles.

Modeling take-over performance in level 3 conditionally automated vehicles.

Taking over vehicle control from a Level 3 conditionally automated vehicle can be a demanding task for a driver. The take-over determines the controllability of automated vehicle functions and thereby also traffic safety. This paper presents models predicting the main take-over performance variables take-over time, minimum time-to-collision, brake application and crash probability. These variables are considered in relation to the situational and driver-related factors time-budget, traffic density, non-driving-related task, repetition, the current lane and driver's age. Regression models were developed using 753 take-over situations recorded in a series of driving simulator experiments. The models were validated with data from five other driving simulator experiments of mostly unrelated authors with another 729 take-over situations. The models accurately captured take-over time, time-to-collision and crash probability, and moderately predicted the brake application. Especially the time-budget, traffic density and the repetition strongly influenced the take-over performance, while the non-driving-related tasks, the lane and drivers' age explained a minor portion of the variance in the take-over performances.

Introduction matters: Manipulating trust in automation and reliance in automated driving.

Trust in automation is a key determinant for the adoption of automated systems and their appropriate use. Therefore, it constitutes an essential research area for the introduction of automated vehicles to road traffic. In this study, we investigated the influence of trust promoting (Trust promoted group) and trust lowering (Trust lowered group) introductory information on reported trust, reliance behavior and take-over performance. Forty participants encountered three situations in a 17-min highway drive in a conditionally automated vehicle (SAE Level 3). Situation 1 and Situation 3 were non-critical situations where a take-over was optional. Situation 2 represented a critical situation where a take-over was necessary to avoid a collision. A non-driving-related task (NDRT) was presented between the situations to record the allocation of visual attention. Participants reporting a higher trust level spent less time looking at the road or instrument cluster and more time looking at the NDRT. The manipulation of introductory information resulted in medium differences in reported trust and influenced participants' reliance behavior. Participants of the Trust promoted group looked less at the road or instrument cluster and more at the NDRT. The odds of participants of the Trust promoted group to overrule the automated driving system in the non-critical situations were 3.65 times (Situation 1) to 5 times (Situation 3) higher. In Situation 2, the Trust promoted group's mean take-over time was extended by 1154 ms and the mean minimum time-to-collision was 933 ms shorter. Six participants from the Trust promoted group compared to no participant of the Trust lowered group collided with the obstacle. The results demonstrate that the individual trust level influences how much drivers monitor the environment while performing an NDRT. Introductory information influences this trust level, reliance on an automated driving system, and if a critical take-over situation can be successfully solved.

Take-over performance in evasive manoeuvres.

We investigated after effects of automation in take-over scenarios in a high-end moving-base driving simulator. Drivers performed evasive manoeuvres encountering a blocked lane in highway driving. We compared the performance of drivers 1) during manual driving, 2) after automated driving with eyes on the road while performing the cognitively demanding n-back task, and 3) after automated driving with eyes off the road performing the visually demanding SuRT task. Both minimum time to collision (TTC) and minimum clearance towards the obstacle disclosed a substantial number of near miss events and are regarded as valuable surrogate safety metrics in evasive manoeuvres. TTC proved highly sensitive to the applied definition of colliding paths, and we prefer robust solutions using lane position while disregarding heading. The extended time to collision (ETTC) which takes into account acceleration was close to the more robust conventional TTC. In line with other publications, the initial steering or braking intervention was delayed after using automation compared to manual driving. This resulted in lower TTC values and stronger steering and braking actions. Using automation, effects of cognitive distraction were similar to visual distraction for the intervention time with effects on the surrogate safety metric TTC being larger with visual distraction. However the precision of the evasive manoeuvres was hardly affected with a similar clearance towards the obstacle, similar overshoots and similar excursions to the hard shoulder. Further research is needed to validate and complement the current simulator based results with human behaviour in real world driving conditions. Experiments with real vehicles can disclose possible systematic differences in behaviour, and naturalistic data can serve to validate surrogate safety measures like TTC and obstacle clearance in evasive manoeuvres.