The quality of an advanced driver assistance system (ADAS) is limited by the quality of its interaction with the driver. For an efficient human-machine-interaction design, it is necessary to possess a thorough understanding of driver behavior and perception in relevant driving situations. While several previous studies have addressed the topic of driver behavior in regard to collision avoidance in general, this paper examines how situational parameters of a collision avoidance scenario relate to drivers' reactions and perceptions. A driving experiment with a cross traffic obstacle appearing at different speeds and different times-to-collision (TTC) was performed on a test track. While the TTC proved to be the most defining factor for the objective criticality of the situation, drivers' reactions and perceptions were impacted most severely by obstacle movement speed. The implications of these and further findings for ADAS research and development are discussed.

The presented work focuses on investigating the influence of different hand-over timing strategies on the fluency and efficiency of a human-robot team in an assembly task. To this aim, four different timing strategies were experimentally evaluated: (I) a fixed time interval between two handovers, (II) a reactive behavior, where the robot is triggered by the human, (III) fixed time intervals depending on the current component, and (IV) a predictive assembly duration estimation algorithm. During the experiment, the time-to-completion of the task and the waiting times for human and robot were measured as reciprocal indication for the efficiency and respectively the fluency of the team. The results indicate that the efficiency of the human-robot team is significantly increased using a predictive timing strategy, because it enables the robot to provide the needed component just-in-time. The decrease in waiting times for the human worker leads to improved fluency of the collaboration. In addition, the predictive strategy enables the robot to perform preliminary tasks if no assistance is needed. Therefore, a nearly full usage of both partners' capacities can be reached.

Lane-keeping assistance systems for vehicles may be more acceptable to users if the assistance was adaptive to the driver's state. To adapt systems in this way, a method for detection of driver distraction is needed. Thus, we propose a novel technique for online detection of driver's distraction, modeling the long-range temporal context of driving and head tracking data. We show that long short-term memory (LSTM) recurrent neural networks enable a reliable subject-independent detection of inattention with an accuracy of up to 96.6%. Thereby, our LSTM framework significantly outperforms conventional approaches such as support vector machines (SVMs).

Extravehicular activities (EVAs) are a hazardous and expensive procedural method to operate in outer space. A possible support or alternative for manned missions in terms of on-orbit servicing are telemanipulation-systems. Whether or not such systems can actually achieve the efficiency of suited astronauts remains a central issue in telemanipulation research. Both scenarios, extravehicular activities as well as telemanipulation-systems, are restricted by different environmental factors, especially in terms of tasks that require fine motor skills. For suited astronauts, different factors, such as restricted mobility and reduced tactile feedback through the gloves, as well as a restricted field of view, impair fine motor skills. On the other hand, time delay, limited degrees of freedom and restricted haptic and visual feedback are amongst the factors, which may cause impairment of performance during the work with telemanipulation-systems. In order to compare the efficiency of both scenarios, a testbed equipped with typical mounting tasks was developed. An experimental study showed that the testbed is a valid measure of fine motor skills. In two follow-up studies, the influence of some factors debilitating fine motor performance in telemanipulation-systems and simulated extra-vehicular activities was analysed and compared.

Telepresence-systems have the potential to take on an important role in on-orbit servicing scenarios. In comparison to manned missions, these systems offer a safer way to operate in outer space. One of the main goals of telepresence research is to learn whether immersive telepresence systems can achieve the efficiency of astronauts in typical mounting tasks, considering that astronauts' mobility is restricted by a range of factors including microgravity and space suits. In order to determine whether a telepresence system is more efficient in performing tasks compared to suited astronauts, an experimental study comparing both scenarios was accomplished.

The collaborative research center SFB453 (www.sfb453.de) aims to realize high-fidelity telepresence and teleaction systems. Telepresence and teleaction systems extend the human workspace to remote locations in order to overcome barriers like distance, scaling, danger or the human skin. Using a human-system interface the human operator controls a remotely located teleoperator. Multi-modal feedback in form of visual, auditory, and haptic data is used to increase the feeling of telepresence. Different application areas including minimally invasive surgery, on-orbit servicing, microassembly as well as tele-manufacturing and tele-maintenance are targeted.

The aim of the presented study was to measure physiological correlates of emotions that are of particular interest in the field of human-robot interaction (HRI). Therefore, we did not focus on self-induced basic emotions but rather evoked states that might occur naturally in this context. Our video shows how such states (namely stress, boredom, surprise, and perplexity) were elicited during a joint construction task with an industrial robot (see figure 1). Participants were asked to build different LEGO objects, while the robot arm was passing the bricks with predetermined velocity. States of stress and boredom were generated by varying the handover interval from 3 seconds (stress) to 5 seconds (normal working condition) up to 35 seconds (boredom). Surprise was induced by passing an unexpected component. At the end of the experiment, we additionally wanted to know how people react if the robot seems to tease them by repeatedly changing the handover position.

The video shows a rich multi-modal multi-user telepresence system, which was developed within the SFB453 funded by the German Research Foundation (www.sfb453.de). As a complex application scenario, the remote repairing of a broken pipe is presented in this paper. The system basically consists of two operator-teleoperator- pairs. While one of the operators interacts with a stationary human- system-interface, the other operator uses a mobile one. Both systems provide visual, auditory, and haptic feedback and enable to control the motion of head, arms, and grippers as well as the locomotion of the corresponding teleoperator.

Perception of compliant environments through a human system interface with visual and proprioceptive feedback is investigated. Participants had to explore the virtual environment by gripping with two fingers. Haptically, compliance was generated by an admittance control scheme. Perception of compliance under conflicting multimodal information was analyzed using an adaptive staircase method. Inter alia, experiments showed that conflicts could be detected when compliances by both modalities differ more than 55%.