Franziska Babel

Many of the challenges encountered in in-the-wild public deployments of robots remain undocumented despite sharing many common pitfalls. This creates a high barrier of entry and results in repetition of avoidable mistakes. To articulate the tacit knowledge in the HRI community, this paper presents a guideline in the form of a checklist to support researchers in preparing for robot deployments in public. Drawing on their own experience with public robot deployments, the research team collected essential topics to consider in public HRI research. These topics are represented as modular flip cards in a hierarchical table, structured into deployment phases and important domains. We interviewed six interdisciplinary researchers with expertise in public HRI and show how including community input refines the checklist. We further show the checklist in action in context of real public studies. Finally, we contribute the checklist as an open-source, customizable community resource that both collects joint expertise for continual evolution and is usable as a list, set of cards, and an interactive web tool.

As autonomous vehicles (AVs) emerge as new agents in traffic, it becomes imperative to understand how they can be introduced effectively and acceptably. AVs enter existing socio-technical systems, where members of various social communities are already present, including residents rushing to work, tourists strolling around, and workers cleaning the streets. This workshop seeks to explore the intricate dynamics of introducing AVs into established social systems within shared spaces. It aims to understand what the needs of pedestrians, cyclists, drivers, and passengers are, and how they interact with each other when AVs enter the social system. Through presentations and interactive activities, this workshop will provide a platform for researchers, practitioners, and other stakeholders to exchange insights, share experiences, and co-create strategies relevant to the integration of AVs into the social systems of shared spaces. The workshop aims to discuss the benefits, risks, and design challenges associated with integrating this emerging technology into our everyday lives.

Increasing encounters between people and autonomous service robots may lead to conflicts due to mismatches between human expectations and robot behaviour. This interactive online study (N = 335) investigated human-robot interactions at an elevator, focusing on the effect of communication and behavioural expectations on participants’ acceptance and compliance. Participants evaluated a humanoid delivery robot primed as either submissive or assertive. The robot either matched or violated these expectations by using a command or appeal to ask for priority and then entering either first or waiting for the next ride. The results highlight that robots are less accepted if they violate expectations by entering first or using a command. Interactions were more effective if participants expected an assertive robot which then asked politely for priority and entered first. The findings emphasize the importance of power expectations in human-robot conflicts for the robot’s evaluation and effectiveness in everyday situations.

Robots in our society are commonly perceived as subordinate servants with a lower social status than humans. This often leads to humans prioritizing themselves during conflict situations. This becomes problematic when robots start to directly represent humans as proxies if people do not think of the human operator behind them. This could be considered a cognitive bias of human representation in HRI. To explore the extent of this problem, we conducted a user study featuring several conflict situations. Participants granted more priority to the robot when the human representation was visible. This paper explores the societal consequences and emerging inequities such as potentially deprioritizing humans by deprioritizing a robot in certain situations. Possible strategies to address potential negative consequences are discussed on a design level while acknowledging that a societal change in how we perceive and treat robots that represent humans might be necessary.

A third of large truck crashes are associated with driver-related factors, especially speeding. This study aimed to examine the impact of behavior-based safety (BBS) programs on speeding. Speeding data were examined from a trucking fleet that had incorporated a BBS program using in-vehicle data recorders (IVDR) and post hoc feedback. Speeding events were examined over 37 weeks in two stages—an initial 4-week period (Stage 1), and the final 30 weeks (Stage 2). In Stage 1, data were collected without any feedback. In Stage 2, a subset of the drivers received feedback. A cluster analysis was performed based on the speeding event rate from Stage 1. The analysis yielded two clusters per group based on risk. The higher-risk cluster contained fewer drivers and showed a greater reduction in speeding with the BBS program, compared to the lower-risk cluster. Both clusters showed significant decreases in speeding across Stage 2. The BBS program was associated with reduced speeding, with a more pronounced reduction for the higher-risk drivers, highlighting the role of BBS programs in trucking and underscoring the importance of driver sub-groups. Targeted safety approaches may be more efficient and yield higher safety benefits than a one-size fits all approach.

As automated shuttle buses gradually become a part of urban traffic solutions, their interactions with vulnerable road users need careful consideration. However, the cyclists’ perspectives on autonomous shuttle buses have not been explored extensively. This research addresses this gap by surveying 50 cyclists who regularly encounter automated shuttle buses. The results show that, in general, cyclists exhibit a high level of trust in the safety of the buses. Nevertheless, approximately one-third of the cyclists expressed disapproval as the buses tend to drive on the bicycle lane, leading them to wish for infrastructural solutions to avoid forcing cyclists to divert to pedestrian walkways. Identifying potential conflicts like these is vital for the development of effective and acceptable human-agent interactions in road traffic environments.