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.

External Human-Machine Interfaces (eHMIs) are expected to bridge the communication gap between an automated vehicle (AV) and pedestrians to replace the missing driver-pedestrian interaction. However, the relative impact of movement-based implicit communication and explicit communication with the aid of eHMIs on pedestrians has not been studied and empirically evaluated. In this study, we pit messages from an eHMI against different driving behaviors of an AV that yields to a pedestrian to understand whether pedestrians tend to pay more attention to the motion dynamics of the car or the eHMI in making road-crossing decisions. Our contributions are twofold: we investigate (1) whether the presence of eHMIs has any objective effect on pedestrians’ understanding of the vehicle’s intent, and (2) how the movement dynamics of the vehicle affect the perception of the vehicle intent and interact with the impact of an eHMI. Results show that (1) eHMIs help in convincing pedestrians of the vehicle’s yielding intention, particularly when the speed of the vehicle is slow enough to not be an obvious threat, but still fast enough to raise a doubt about a vehicle’s stopping intention, and (2) pedestrians do not blindly trust the eHMI: when the eHMI message and the vehicle’s movement pattern contradict, pedestrians fall back to movement-based cues. Our results imply that when explicit communication (eHMI) and implicit communication (motion-dynamics and kinematics) are in alignment and work in tandem, communication of the AV’s yielding intention can be facilitated most effectively. This insight can be useful in designing the optimal interaction between AVs and pedestrians from a user-centered design perspective when driver-centric communication is not available.

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.