In this paper, we investigate the effect of an external human-machine interface (eHMI) and a conspicuous external vehicle appearance due to visible sensors on pedestrian interactions with automated vehicles (AVs). Recent research shows that AVs may need to explicitly communicate with the environment due to the absence of a driver. Furthermore, in interaction situations, an AV that looks different and conspicuous owing to an extensive sensor system may potentially lead to hesitation stemming from mistrust in automation. Thus, we evaluated in a virtual reality study how pedestrian attitude, the presence/absence of an eHMI, and a conspicuous sensor system affect their willingness to cross the road. Results recommend the use of an eHMI. A conspicuous appearance of automated-driving capability had no effect for the sample as a whole, although it led to more efficient crossing decisions for those with a more negative attitude towards AVs. Our findings contribute towards the effective design of future AV interfaces.
People with vision impairments (VIP) are among the most vulnerable road users in traffic. Autonomous vehicles are believed to reduce accidents but still demand some form of external communication signaling relevant information to pedestrians. Recent research on the design of vehicle-pedestrian communication (VPC) focuses strongly on concepts for a non-disabled population. Our work presents an inclusive user-centered design for VPC, beneficial for both vision impaired and seeing pedestrians. We conducted a workshop with VIP (N=6), discussing current issues in road traffic and comparing communication concepts proposed by literature. A thematic analysis unveiled two important themes: number of communicating vehicles and content (affecting duration). Subsequently, we investigated these in a second user study in virtual reality (N=33, 8 VIP) comparing the VPC between groups of abilities. We found that trust and understanding is enhanced and cognitive load reduced when all relevant vehicles communicate; high content messages also reduce cognitive load.
In this paper, we report user preferences regarding color and animation patterns to support the interaction between Automated Vehicles (AVs) and pedestrians through an external Human-Machine-Interface (eHMI). Existing concepts of eHMI differ -- among other things -- in their use of colors or animations to express an AV's yielding intention. In the absence of empirical research, there is a knowledge gap regarding which color and animation leads to highest usability and preferences in traffic negotiation situations. We conducted an online survey (N=400) to investigate the comprehensibility of a light band eHMI with a combination of 5 color and 3 animation patterns for a yielding AV. Results show that cyan is considered a neutral color for communicating a yielding intention. Additionally, a uniformly flashing or pulsing animation is preferred compared to any pattern that animates sideways. These insights can contribute in the future design and standardization of eHMIs.
Autonomous vehicle (AV) systems are developing at a rapid pace, not only in technological capabilities, but also in human-centered directions. Despite this development, we lack a nuanced understanding of driver preference in decision scenarios that semi-AVs will face, and of possible misalignment between semi-AV decisions and user preference. Using an online survey, we explore how participants would like semi-AVs to act and alert them of the vehicles' decisions in various scenarios. Participants reported varying levels of comfort with autonomy, desire to takeover control, and desire for AV informing. Individual differences, including level of experience with autonomy and situation awareness, affected perceptions of the vehicle. Our results highlight the importance of considering driver preference in AV decision-making, and we present an influence diagram that situates this factor among others. We also derive five design principles, including that a previous positive AV experience can lead to more harmful consequences for AVs when not aligned with driver preference.
Autonomous vehicle system performance is limited by uncertainties inherent in the driving environment and challenges in processing sensor data. Engineers thus face the design decision of biasing systems toward lower sensitivity to potential threats (more misses) or higher sensitivity (more false alarms). We explored this problem for Automatic Emergency Braking systems in Level 3 autonomous vehicles, where the driver is required to monitor the system for failures. Participants (N=48) drove through a simulated suburban environment and experienced detection misses, perfect performance, or false alarms. We found that driver vigilance was greater for less-sensitive braking systems, resulting in improved performance during a potentially fatal failure. In addition, regardless of system bias, greater levels of autonomy resulted in significantly worse driver performance. Our results demonstrate that accounting for the effects of system bias on driver vigilance and performance will be critical design considerations as vehicle autonomy levels increase.