In conditionally automated vehicles, drivers can engage in secondary activities while traveling to their destination. However, drivers are required to appropriately respond, in a limited amount of time, to a take-over request when the system reaches its functional boundaries. Interacting with the car in the proper way from the first ride is crucial for car and road safety in general. For this reason, it is necessary to train drivers in a risk-free environment by providing them the best practice to use these complex systems. In this context, Virtual Reality (VR) systems represent a promising training and learning tool to properly familiarize drivers with the automated vehicle and allow them to interact with the novel equipment involved. In addition, Head-Mounted Display (HMD)-based VR (light VR) would allow for the easy deployment of such training systems in driving schools or car dealerships. In this study, the effectiveness of a light Virtual Reality training program for acquiring interaction skills in automated cars was investigated. The effectiveness of this training was compared to a user manual and a fixed-base simulator with respect to both objective and self-reported measures. Sixty subjects were randomly assigned to one of the systems in which they went through a training phase followed by a test drive in a high-end driving simulator. Results show that the training system affects the take-over performances. Moreover, self-reported measures indicate that the light VR training is preferred with respect to the other systems. Finally, another important outcome of this research is the evidence that VR plays a strategic role in the definition of the set of metrics for profiling proper driver interaction with the automated vehicle.

Robots are becoming more and more present in our everyday life: they are already used for domestic tasks, for companionship activities, and soon they will be used to assist humans and collaborate with them in their work. Human-robot collaboration has already been studied in the industry, for ergonomics and efficiency purposes, but more from a safety than from an acceptability point of view. In this work, we focused on how people perceive robots in a collaboration task and we proposed to use virtual reality as a simulation environment to test different parameters, by making users collaborate with virtual robots. A simple use case was implemented to compare different robot appearances and different robot movements. Questionnaires and physiological measures were used to assess the acceptability level of each condition with a user study. The results showed that the perception of robot movements depended on robot appearance and that a more anthropomorphic robot, both in its appearance and movements, was not necessarily better accepted by the users in a collaboration task. Finally, this preliminary use case was also the opportunity to guarantee the relevance of using such a methodology -based on virtual reality, questionnaires and physiological measures -for future studies.

This paper focuses on the acceptability of humanrobot collaboration in industrial environments. A use case was designed in which an operator and a robot had to work sideby-side on automotive assembly lines, with different levels of co-presence. This use case was implemented both in a physical and in a virtual situation using virtual reality. A user study was conducted with operators from the automotive industry. The operators were asked to assess the acceptability to work side-by-side with the robot through questionnaires, and physiological measures (heart rate and skin conductance) were taken during the user study. The results showed that working close to the robot imposed more constraints on the operators and required them to adapt to the robot. Moreover, an increase in skin conductance level was observed after working close to the robot. Although no significant difference was found in the questionnaires results between the physical and virtual situations, the increase in physiological measures was significant only in the physical situation. This suggests that virtual reality may be a good tool to assess the acceptability of human-robot collaboration and draw preliminary results through questionnaires, but that physical experiments are still necessary to a complete study, especially when dealing with physiological measures.

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