This paper explores the design of expressive movements for service robots in fine-dining restaurants, using a performative approach to understand how robots can be integrated and accepted in complex real-world settings. Drawing on dramaturgical principles, we conducted three research and design activities-speculative enactments, scenario building, and extended reality (XR) simulations-to examine how specific movements of a restaurant service robot and the contexts in which they are performed influence the experiences of guests, serving staff, and managers. We propose that such robots can be conceptualized as “ensemblists,“ capable of adopting multiple roles and collaborating with humans in a larger choreography of service delivery. The study concludes by reflecting on the strengths and limitations of performative approaches in HRI, emphasizing the need to move beyond traditional one-on-one human-robot interaction models and, instead, to consider how robots perform their roles in complex, dynamic environments involving multiple actors.

Traffic jams occurring on highways cause increased travel time as well as increased fuel consumption and collisions. So-calledphantom traffic jamsare traffic jams that do not have a clear cause, such as a merging on-ramp or an accident. Phantom traffic jams make up 50% of all traffic jams and result from instabilities in the traffic flow that are caused by human driving behavior. Automating the longitudinal vehicle motion of only 5% of all cars in the flow can dissipate phantom traffic jams. However, driving automation introduces safety issues when human drivers need to take over the control from the automation. We investigated whether phantom traffic jams can be dissolved using haptic shared control. This keeps humans in the loop and thus bypasses the problem of humans' limited capacity to take over control, while benefiting from most advantages of automation. In an experiment with 24 participants in a driving simulator, we tested the effect of haptic shared control on the dynamics of traffic flow and compared it with manual control and full automation. We also investigated the effect of two control types on participants' behavior during simulated silent automation failures. Results show that haptic shared control can help dissipating phantom traffic jams better than fully manual control but worse than full automation. We also found that haptic shared control reduces the occurrence of unsafe situations caused by silent automation failures compared to full automation. Our results suggest that haptic shared control can dissipate phantom traffic jams while preventing safety risks associated with full automation.