As autonomous vehicles enter public spaces, external human–machine interfaces are proposed to support communication with external road users. A decade of research has produced hundreds of studies and reviews, yet it remains unclear whether the field is converging on shared principles or diverging across approaches. We present a multi-dimensional analysis of 620 publications, complemented by industry deployments and regulatory documents, to track research evolution and identify convergence. The analysis reveals several field-level patterns. First, convergence on a safety-first core: simple visual cues that clarify intent. Second, sustained divergence in necessity and implementation. Third, a progressive filtering funnel: broad exploration in research and concepts narrows in deployment and is codified by regulation into a minimal set of permitted signals. These insights point to a shift in emphasis for future work, from producing new prototypes toward consolidating evidence, clarifying points of contention, and developing frameworks that can adapt across contexts.

While visual augmentation dominates the augmented reality landscape, devices like Meta Ray-Ban audio smart glasses signal growing industry movement toward audio augmented reality (AAR). Hearing is a primary channel for sensing context, anticipating change, and navigating social space, yet AAR's everyday potential remains underexplored. We address this gap through a collaborative autoethnography (N=5, authoring) and an online survey (N=74). We identify ten roles for AAR, grouped into three categories: task- and utility-oriented, emotional and social, and perceptual collaborator. These roles are further layered with a rhythmic and embodied collaborator framing, mapping them onto micro-, meso-, and macro-rhythms of everyday life. Our analysis surfaces nuanced tensions, such as blocking distractions without erasing social presence, highlighting the need for context-aware design. This paper contributes a foundational and forward-looking framework for AAR in everyday life, providing design groundwork for systems attuned to daily routines, sensory engagement, and social expectations.

External Human-Machine Interfaces (eHMIs) have been proposed to enhance communication between automated vehicles (AVs) and pedestrians, with growing interest in multi-modal designs such as audio-visual eHMIs. Just as poor lighting can impair visual cues, a loud background noise may mask the auditory stimuli. However, its effects within these systems have not been examined, and little is known about how pedestrians — particularly Deaf and Hard-of-Hearing (DHH) people — perceive different types of auditory stimuli. We conducted a virtual reality study (Hearing N=25, DHH N=11) to examine the effects of background noise (quiet and loud) on auditory stimuli (baseline, bell, speech) within an audio-visual eHMI. Results revealed that: (1) Crossing experiences of DHH pedestrians significantly differ from Hearing pedestrians. (2) Loud background noise adversely affects pedestrians’ crossing experiences. (3) Providing an additional auditory eHMI (bell/speech) improves crossing experiences. We outlined four practical implications for future eHMI design and research.

As vehicle automation advances toward highly automated driving, takeover systems must address scenarios where users are entirely disengaged from the driving task. Although highly automated driving remains largely experimental, designing and researching robust takeover systems is essential for ensuring safe deployment, fostering user trust, and promoting system acceptance. Existing research has explored individual aspects of takeover design and interaction, but a comprehensive synthesis remains lacking. This paper presents a systematic review of 61 studies between 2015 and 2024, retrieved from the ACM Digital Library, Web of Science, ScienceDirect, and IEEE Xplore. The review is structured across three core dimensions: 1)takeover system design, including takeover budgets, modalities, and prompt information; 2)takeover scenarios, including driver characteristics, non-driving-related tasks, and traffic environments; and 3)takeover evaluation, including methods, measurement, and experimental apparatus. The analysis highlights inconsistencies in the definitions of automation levels and discusses their implications for comparability and validity in highly-automated driving research. It then identifies concrete research priorities: adaptive multimodal takeover systems, unified evaluation metrics, and ethical frameworks to guide human–system collaboration.

Uncertainty is an inherent aspect of autonomous vehicle (AV) decision-making, yet it is rarely communicated to pedestrians, which hinders transparency.This study investigates how AV uncertainty can be conveyed through two approaches: explicit communication (confidence percentage displays) and implicit communication (vehicle motion cues), across different confidence levels (high and low).Through a within-subject VR experiment (N=26), we evaluated these approaches in a crossing scenario, assessing interface qualities (visibility and intuitiveness), how well the information conveyed the vehicle's level of confidence, and their impact on participants' perceived safety, trust, and user experience.Our results show that explicit communication is more effective and preferred for conveying uncertainty, enhancing safety, trust, and user experience.Conversely, implicit communication introduces ambiguity, especially when AV confidence is low.This research provides empirical insights into how uncertainty communication shapes pedestrian interpretation of AV behaviour and offer design guidance for external interfaces that integrate uncertainty as a communicative element.

Autonomous mobility systems increasingly operate in environments shared with animals, from urban pets to wildlife.However, their design has largely focused on human interaction, with limited understanding of how non-human species perceive, respond to, or are affected by these systems.Motivated by research in Animal-Computer Interaction (ACI) and more-than-human design, this study investigates animal interactions with autonomous mobility through a multi-method approach combining a scoping review (45 articles), online ethnography (39 YouTube videos and 11 Reddit discussions), and expert interviews (8 participants).Our analysis surfaces five key areas of concern: Physical Impact (e.g., collisions, failures to detect), Behavioural Effects (e.g., avoidance, stress), Accessibility Concerns (particularly for service animals), Ethics and Regulations, and Urban Disturbance.We conclude with design and policy directions aimed at supporting multispecies coexistence in the age of autonomous systems.This work underscores the importance of incorporating non-human perspectives to ensure safer, more inclusive futures for all species.

Uncertainty inherently exists in the autonomous decision-making process of robots. Involving humans in resolving this uncertainty not only helps robots mitigate it but is also crucial for improving human-robot interactions. However, in public urban spaces filled with unpredictability, robots often face heightened uncertainty without direct human collaborators. This study investigates how robots can engage bystanders for assistance in public spaces when encountering uncertainty and examines how these interactions impact bystanders' perceptions and attitudes towards robots. We designed and tested a speculative `peephole' concept that engages bystanders in resolving urban robot uncertainty. Our design is guided by considerations of non-intrusiveness and eliciting initiative in an implicit manner, considering bystanders' unique role as non-obligated participants in relation to urban robots. Drawing from field study findings, we highlight the potential of involving bystanders to mitigate urban robots' technological imperfections to both address operational challenges and foster public acceptance of urban robots. Furthermore, we offer design implications to encourage bystanders' involvement in mitigating the imperfections.

With growing investment in consumer augmented reality (AR) headsets and glasses, wearable AR is moving from niche applications to everyday use. However, current research primarily examines AR in controlled settings, offering limited insights into its use in real-world daily life. To address this gap, we adopt a digital ethnographic approach, analysing 27 hours of 112 YouTube videos featuring early adopters. These videos capture usage ranging from continuous periods of hours to intermittent use over weeks and months. Our analysis shows that currently, wearable AR is primarily used for media consumption and gaming. While productivity is a desired use case, frequent use is constrained by current hardware limitations and the nascent application ecosystem. Users seek continuity in their digital experience, desiring functionalities similar to those on smartphones, tablets, or computers. We propose implications for everyday AR development that promote adoption while ensuring safe, ethical, and socially-aware integration into daily life.

Virtual reality (VR) has been increasingly utilised as a simulation tool for human-robot interaction (HRI) studies due to its ability to facilitate fast and flexible prototyping. Despite efforts to achieve high validity in VR studies, haptic sensation, an essential sensory modality for perception and a critical factor in enhancing VR realism, is often absent from these experiments. Studying an interactive robot help-seeking scenario, we used a VR simulation with haptic gloves that provide highly realistic tactile and force feedback to examine the effects of haptic sensation on VR-based HRI. We compared participants’ sense of presence and their assessments of the robot to a traditional setup using hand controllers. Our results indicate that haptic sensation enhanced participants’ social and self-presence in VR and fostered more diverse and natural bodily engagement. Additionally, haptic sensations significantly influenced participants’ affective-related perceptions of the robot. Our study provides insights to guide HRI researchers in building VR-based simulations that better align with their study contexts and objectives.

Abstract Enhancing transparency in automated vehicle (AV) behaviour can help pedestrians understand how AVs work, which builds trust and ensures safer interactions. As AVs increasingly operate as part of a coordinated network, it is important to make their connectivity clear, helping pedestrians anticipate AV behaviour on the road. This study uses a qualitative design exploration to investigate visual methods for conveying AV connectivity. In the first phase, design concepts were generated using a biomimicry approach, drawing inspiration from nature, such as the harmonious chirping of crickets. In the second phase, focus groups with 16 participants were conducted to gather new concept ideas and evaluate the biomimicry-inspired designs. Our findings suggest that network symbols (e.g., Wi-Fi signals) or graphical elements resembling these symbols (e.g., ripple waves) are more effective in communicating connectivity than abstract methods, such as light patterns moving in a coordinated manner across vehicles. Highly visible connectivity cues may enhance pedestrians' perceived safety, a promising area for future research. This research contributes to ongoing efforts in designing intuitive visual communication strategies for AVs, moving beyond intent communication to include how AVs function as a network.

The advancement of automated driving technologies is fundamentally transforming the relationship between humans and vehicles, shifting from direct control to a more collaborative dynamic. Consequently, the design of in-vehicle Human-Machine Interfaces (iHMIs) is becoming increasingly intricate, focusing on aspects beyond mechanics and ergonomics towards enriched interaction and enhanced user experience. This shift has prompted research efforts to explore and advance iHMI concepts. Despite the iterative nature of design and its role in knowledge creation, our high-level understanding of the design processes utilised in iHMI development remains limited. To provide a comprehensive overview, this paper presents a scoping review of 324 papers (2013—2023) focused on the design underpinnings of iHMI development. Our review presents a categorisation of study goals and a detailed classification of five key stages within the design process. Based on these analyses, we discuss the influence of design and identify potential avenues for future research on iHMIs.

Policymakers advocate for the use of external Human-Machine Interfaces (eHMIs) to allow autonomous vehicles (AVs) to communicate their intentions or status. Nonetheless, scalability concerns in complex traffic scenarios arise, such as potentially increasing pedestrian cognitive load or conveying contradictory signals. Building upon precursory works, our study explores ‘interconnected eHMIs,’ where multiple AV interfaces are interconnected to provide pedestrians with clear and unified information. In a virtual reality study (N=32), we assessed the effectiveness of this concept in improving pedestrian safety and their crossing experience. We compared these results against two conditions: no eHMIs and unconnected eHMIs. Results indicated interconnected eHMIs enhanced safety feelings and encouraged cautious crossings. However, certain design elements, such as the use of the colour red, led to confusion and discomfort. Prior knowledge slightly influenced perceptions of interconnected eHMIs, underscoring the need for refined user education. We conclude with practical implications and future eHMI design research directions.

The deployment of autonomous delivery robots in urban environments presents unique challenges in navigating complex traffic conditions and interacting with diverse road and sidewalk users. Effective communication between robots and road and sidewalk users is crucial to address these challenges. This study investigates real-world encounter scenarios where delivery robots and road and sidewalk users interact, seeking to understand the essential role of communication in ensuring seamless encounters. Following an online ethnography approach, we collected 117 user-generated videos from TikTok and their associated 2,067 comments. Our systematic analysis revealed several design opportunities to augment communication between delivery robots and road and sidewalk users, which include facilitating multi-party path negotiation, managing unexpected robot behaviour via transparency information, and expressing robot limitations to request human assistance. Moreover, the triangulation of video and comments analysis provides a set of design considerations to realise these opportunities. The findings contribute to understanding the operational context of delivery robots and offer insights for designing interactions with road and sidewalk users, facilitating their integration into urban spaces.

Autonomous vehicles (AVs) may use external interfaces, such as LED light bands, to communicate with pedestrians safely and intuitively. While previous research has demonstrated the effectiveness of these interfaces in simple traffic scenarios involving one pedestrian and one vehicle, their performance in more complex scenarios with multiple road users remains unclear. The scalability of AV external communication has therefore attracted increasing attention, prompting the need for further investigation. This scoping review synthesises information from 54 papers to identify seven key scalability issues in multi-vehicle and multi-pedestrian environments, with Clarity of Recipients, Information Overload, and Multi-Lane Safety emerging as the most pressing concerns. To guide future research in scalable AV-pedestrian interactions, we propose high-level design directions focused on three communication loci: vehicle, infrastructure, and pedestrian. Our work contributes the groundwork and a roadmap for designing simplified, coordinated, and targeted external AV communication, ultimately improving safety and efficiency in complex traffic scenarios.

Wearable Augmented Reality (AR) has attracted considerable attention in recent years, as evidenced by the growing number of research publications and industry investments. With swift advancements and a multitude of interdisciplinary research areas within wearable AR, a comprehensive review is crucial for integrating the current state of the field. In this paper, we present a review of 389 research papers on wearable AR, published between 2018 and 2022 in three major venues: ISMAR, TVCG, and CHI. Drawing inspiration from previous works by Zhou et al. and Kim et al., which summarized AR research at ISMAR over the past two decades (1998-2017), we categorize the papers into different topics and identify prevailing trends. One notable finding is that wearable AR research is increasingly geared towards enabling broader consumer adoption. From our analysis, we highlight key observations related to potential future research areas essential for capitalizing on this trend and achieving widespread adoption. These include addressing challenges in Display, Tracking, Interaction, and Applications, and exploring emerging frontiers in Ethics, Accessibility, Avatar and Embodiment, and Intelligent Virtual Agents.

The rise of autonomous systems in cities, such as automated vehicles (AVs), requires new approaches for prototyping and evaluating how people interact with those systems through context-based user interfaces, such as external human-machine interfaces (eHMIs). In this paper, we present a comparative study of three prototype representations (real-world VR, computer-generated VR, real-world video) of an eHMI in a mixed-methods study with 42 participants. Quantitative results show that while the real-world VR representation results in higher sense of presence, no significant differences in user experience and trust towards the AV itself were found. However, interview data shows that participants focused on different experiential and perceptual aspects in each of the prototype representations. These differences are linked to spatial awareness and perceived realism of the AV behaviour and its context, affecting in turn how participants assess trust and the eHMI. The paper offers guidelines for prototyping and evaluating context-based interfaces through simulations.

An increasing number of studies employ virtual reality (VR) to evaluate interactions between autonomous vehicles (AVs) and pedestrians. VR simulators are valued for their cost-effectiveness, flexibility in developing various traffic scenarios, safe conduct of user studies, and acceptable ecological validity. Reviewing the literature between 2010 and 2020, we found 31 empirical studies using VR as a testing apparatus for both implicit and explicit communication. By performing a systematic analysis, we identified current coverage of critical use cases, obtained a comprehensive account of factors influencing pedestrian behavior in simulated traffic scenarios, and assessed evaluation measures. Based on the findings, we present a set of recommendations for implementing VR pedestrian simulators and propose directions for future research.