Drivers’ Attention to Dash-Based Human-Machine Interfaces: The Effect of Partial Automation and Cognitive LoadA vehicle’s dash-based Human-Machine Interface (HMI) provides critical information to drivers. However, the location of these displays can take drivers' visual attention away from the forward view and compromise safety. As vehicle automation becomes increasingly common, its impact on drivers’ visual attention to dash-based HMI remains under-explored. Moreover, drivers tend to engage more frequently in non-driving-related tasks during automation, but how the cognitive load imposed by these tasks affects drivers’ inspection of HMI displays is unclear. This driving simulator study examined how partial automation and cognitive load (imposed by a 2-back task) influence drivers’ visual attention to dash-based HMI containing speed and automation status information (N=46). Results showed that increased levels of automation and cognitive load additively reduced drivers’ visual attention to the dash area. Drivers prioritized inspecting the speedometer over the automation status information across all conditions. Our findings provide important implications for HMI design in automated vehicles.2025HQHao Qin et al.Head-Up Display (HUD) & Advanced Driver Assistance Systems (ADAS)AutoUI
Measuring Driver Electrodermal Activity when Exposed to HMIs Conveying Uncertainty in Conditional Automated DrivingThe emergence of automated vehicles (AVs) introduces new challenges to human-vehicle interactions, especially in conditional automated driving. This study presents different head-up display designs as the human-machine interface (HMI) to convey uncertainty to AV users. It investigates the impact of such designs on drivers’ physiological responses–via electrodermal activity data–and subjective evaluations of cognitive workload during the automated drive. A between-subjects driving simulator experiment (N=187) was conducted to examine four conditions: baseline (no HMI), a progressive colour-based Guardian Angel display, a text-based interruption, and a combination approach. The results showed significant effects of the presence of the colour-based display interventions on physiological arousal, associated with cognitive workload. However, the subjective ratings showed no difference across conditions. These findings indicate that the designed displays can trigger physiological responses without affecting perceived workload. It offers insights into HMI design to balance driver awareness and cognitive demand in automated driving.2025JPJorge Pardo et al.Head-Up Display (HUD) & Advanced Driver Assistance Systems (ADAS)AutoUI
Changing Lanes Toward Open Science: Openness and Transparency in Automotive User ResearchWe review the state of open science and the perspectives on open data sharing within the automotive user research community. Openness and transparency are critical not only for judging the quality of empirical research, but also for accelerating scientific progress and promoting an inclusive scientific community. However, there is little documentation of these aspects within the automotive user research community. To address this, we report two studies that identify (1) community perspectives on motivators and barriers to data sharing, and (2) how openness and transparency have changed in papers published at AutomotiveUI over the past 5 years. We show that while open science is valued by the community and openness and transparency have improved, overall compliance is low. The most common barriers are legal constraints and confidentiality concerns. Although research published at AutomotiveUI relies more on quantitative methods than research published at CHI, openness and transparency are not as well established. Based on our findings, we provide suggestions for improving openness and transparency, arguing that the motivators for open science must outweigh the barriers. All supporting materials are freely available at: https://osf.io/zdpek/2024PEPatrick Ebel et al.Research Ethics & Open ScienceAutoUI
Do Drivers have Preconceived Ideas about an Automated Vehicle’s Driving Behaviour?This study investigated drivers' preconceived notions about manoeuvres of Automated Vehicles (AVs) compared to manually driven vehicles (MVs) using a pseudo-coupled driving simulator. The simulator displayed a message indicating the state of approaching vehicles (AV/MV) in a bottleneck scenario, while participants were informed that the MV was controlled by an experimenter using another simulator, despite all trials having the same preprogrammed behaviours. Results showed that the types of AV/MV did not impact participants’ subjective responses. Communication through kinematic cues of the AV/MV was effective, with higher perceived safety, comprehension, and trust reported for approaching vehicles that yielded with an offset away from participants. Perceived safety and trust of the AV were also higher for trials with a light-band external Human Machine Interface (eHMI). This study highlights the value of both explicit and implicit cues for the communication of AVs with other drivers.2023YLYang Li et al.Automated Driving Interface & Takeover DesignExternal HMI (eHMI) — Communication with Pedestrians & CyclistsAutoUI
Towards future pedestrian-vehicle interactions: Introducing theoretically-supported AR prototypesThe future urban environment may consist of mixed traffic in which pedestrians interact with automated vehicles (AVs). However, it is still unclear how AVs should communicate their intentions to pedestrians. Augmented reality (AR) technology could transform the future of interactions between pedestrians and AVs by offering targeted and individualized communication. This paper presents nine prototypes of AR concepts for pedestrian-AV interaction that are implemented and demonstrated in a real crossing environment. Each concept was based on expert perspectives and designed using theoretically-informed brainstorming sessions. Prototypes were implemented in Unity MARS and subsequently tested on an unmarked road using a standalone iPad Pro with LiDAR functionality. Despite the limitations of the technology, this paper offers an indication of how future AR systems may support future pedestrian-AV interactions.2021WTWilbert Tabone et al.External HMI (eHMI) — Communication with Pedestrians & CyclistsAR Navigation & Context AwarenessAutoUI
The Public Life of Data: Investigating Reactions to Visualizations on RedditThis research investigates how people engage with data visualizations when commenting on the social platform Reddit. There has been considerable research on collaborative sensemaking with visualizations and the personal relation of people with data. Yet, little is known about how public audiences without specific expertise and shared incentives openly express their thoughts, feelings, and insights in response to data visualizations. Motivated by the extensive social exchange around visualizations in online communities, this research examines characteristics and motivations of people’s reactions to posts featuring visualizations. Following a Grounded Theory approach, we study 475 reactions from the /r/dataisbeautiful community, identify ten distinguishable reaction types, and consider their contribution to the discourse. A follow-up survey with 168 Reddit users clarified their intentions to react. Our results help understand the role of personal perspectives on data and inform future interfaces that integrate audience reactions into visualizations to foster a public discourse about data.2021TKTobias Kauer et al.University of Edinburgh, Potsdam University of Applied SciencesInteractive Data VisualizationCommunity Collaboration & WikipediaCHI
Understanding The Messages Conveyed by Automated VehiclesEfficient and safe interactions between automated vehicles and other road users can be supported through external Human-Machine Interfaces (eHMI). The success of these interactions relies on the eHMI signals being adequately understood by other road users. A paired-comparison forced choice task (Task 1), and a 6-point rating task (Task 2) were used to assess the extent to which ten different eHMI signals conveyed three separate messages, ‘I am giving way’, ‘I am in automated mode’ and ‘I will start moving’. The different eHMI options consisted of variations of a 360° lightband, a single lamp, and an auditory signal. Results demonstrated that the same eHMI format could convey different messages equally well, suggesting a need to be cautious when designing eHMI, to avoid presenting misleading, potentially unsafe, information. Future research should investigate whether the use of an eHMI signal indicating a change in the AV’s behaviour is sufficient for conveying intention.2019YLYee Mun Lee et al.External HMI (eHMI) — Communication with Pedestrians & CyclistsAutoUI