Combining Vehicle Braking Behavior with an External Human-Machine Interface towards a Holistic Communication Strategy for Automated Buses

Background. Future automated vehicles (AVs) of different sizes will share the same space with other traffic participants (TPs), e.g., manually-driven vehicles, cyclists or pedestrians. For a safe interaction, communication needs to be ensured, in particular, with vulnerable road users, e.g., pedestrians. This study focuses on two important research aspects of the future interaction between vehicle and pedestrians: firstly, the design of different communication strategies for the interaction between pedestrian and automated vehicle and, secondly, the concrete novel application to an automated bus. Current research shows that in today’s interaction, pedestrians use mostly implicit communication signals, i.e., vehicle dynamics, for their road-crossing decision. Moreover, they use explicit communication in low distance and low speed to negotiate or to clarify ambiguous traffic situations. Both communication means (implicit and explicit) are highly relevant for a safe interaction between pedestrians and vehicles and need to be considered in the design of future AVs. An external Human-Machine Interface (eHMIs) presents a possible communication tool to transmit explicit communication signals to other TPs. So far, research showed that the use of an eHMI increases pedestrians’ perceived safety and is seen as helpful for pedestrians’ road-crossing decisions. Nevertheless, implicit communication signals are described as primary indicator for the road-crossing decision. As communication tool, dynamic Human-Machine Interfaces (dHMIs) are able to transmit implicit communication signals, e.g., vehicle dynamics. Nevertheless, it is not sufficiently studied how the exact interplay between both communication means, i.e., dHMi and eHMI, should take place. Therefore, the interplay of explicit and implicit communication signals stands in focus of this study. Besides the question of how to communicate, it also needs to be addressed who communicates. This study focuses on the interaction between pedestrian and a public bus as an example for a larger vehicle type. Research has shown that pedestrians’ crossing behavior can be influenced by the interacting vehicle type. For smaller vehicles, pedestrians described a higher perceived chance to get out of the way and, therefore, felt safer with smaller vehicles compared to larger. This is also supported by research showing that larger vehicles are perceived to arrive earlier than smaller. In light of the aforementioned relevance of vehicle appearance, it is surprising that little research has focused on the design of a holistic communication strategy for different sized automated vehicles so far. Aim: This experimental online study aims to shed light on the interplay between implicit and explicit communication for an automated vehicle. Concurrently, this study focuses on the practical novel implementation to an automated bus. Method: In short video sequences, participants interacted with a highly automated bus equipped with a 360° LED light-band eHMI which was attached on the outer vehicle body. Three eHMI communication strategies were shown reflecting different information richness levels. The condition “no eHMI” was used as baseline and did not show any information. In the condition “status eHMI”, a continuously enlighted eHMI was shown which displayed the vehicle’s automation status. The condition “status + intention eHMI” included the status eHMI and further explicit information about the vehicle’s intention which was shown by the pulsation of the eHMI. Furthermore, the vehicle braking behavior was varied (no braking vs. braking) and combined with the different eHMI communication strategies. After the video sequences had stopped at a predefined point, participants were asked to state their willingness to cross. We hypothesize that pedestrians are more willing to cross the road when the bus presents a status + intention eHMI. Results: As this study is work-in-progress, the data collection is still on-going. Preliminary results indicated that the proposed eHMI communication strategies can contribute to a safe interaction between public bus and pedestrians. Conclusion: This study addresses how automated buses can safely and efficiently interact with pedestrians in future traffic using explicit and implicit communication. Further implications towards a holistic communication strategy for automated buses will be discussed