###### Abstract  
Highly automated shuttle vehicles (SAE Level 4) have the potential to enhance public transport services by decreasing the demand for drivers, enabling more frequent and flexible ride options. However, at least in a transitionary phase, safety operators that supervise and support the shuttles with their driving tasks may be required on board the vehicle from a technical or legal point of view. A crucial component for executing supervisory and intervening tasks is the human-machine interface between an automated vehicle and its on-board operator. This research presents in-depth case studies from three heterogenous living laboratories in Germany that deployed highly automated shuttle vehicles with on-board operators on public roads. The living labs differed significantly regarding the on-board operators' tasks and the design of the human-machine interfaces. Originally considered a provisional solution until the vehicle automation is fully capable of running without human support, these interfaces were, in general, not designed in a user-centered way. However, since technological progress has been slower than expected, on-board operator interfaces are likely to persist in the mid-term at least. Hence, this research aims to assess the aptitude of interfaces that are in practical use for the on-board operators' tasks, in order to determine the user-centered design of future interfaces. Completing questionnaires and undergoing comprehensive, semi-structured interviews, nine on-board operators evaluated their human-machine interfaces in light of the respective tasks they complete regarding user variables such as work context, acceptance, system transparency, and trust. The results were highly diverse across laboratories and underlined that the concrete system setup, encompassing task and interface design, has a considerable impact on these variables. Ergonomics, physical demand, and system transparency were identified as the most significant deficits. These findings and derived recommendations may inform the design of on-board operator workspaces, and bear implications for remote operation workstations as well. highly automated vehicles; automated driving; on-board operators; human-machine interface; workplace analysis; living lab; shuttles; public transport +
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demand services [2]. Many cities consider this means of transport a substantial component of the targeted mobility shift. For instance, the city of Hamburg, Germany, plans to have at least 10,000 highly automated and electric shuttles by 2030 in order to meet sustainable mobility goals [3]. In order to test the feasibility of highly automated driving in a real-world environment, a large number of countries and cities have set up living laboratories with automated vehicles of different kinds. The funding scheme of the German Federal Ministry for Digital and Transport on Connected and Automated Driving (CAD) lists 79 programs that have received funding since 2018 [4]. As living labs, many of the CAD projects collect data on the deployment of automated vehicles in public spaces. Although reaching \"full driving automation\" (Level 5 [1]) is the ultimate goal of some of the CAD projects, this goal is at stake. The reason for this is the rather sluggish development of automated driving functions. Driving automation is not progressing as quickly as previously projected [5]. Fully automated driving lies far in the future or may never become fully feasible, at least not in all situations conceivable [6]. Even when limiting the operational context to certain road types, geographic areas, or weather conditions, i.e., running a vehicle with \"high driving automation\" (HAV, Level 4 [1]), situations remain that require human assistance. Some examples include ambiguous object detection and deadlock situations [7]. Thus, in order to test HAVs in specific use cases while fulfilling safety requirements, many projects that deploy HAVs in the real world include safety operators on board the HAVs.