The development of automated vehicles (AVs) and their integration into traffic are seen by many vehicle manufacturers and stakeholders such as cities or transportation companies as a revolution in mobility. In future urban traffic, it is more likely that AVs will operate not in separated traffic spaces but in so-called mixed traffic environments where different types of traffic participants interact. Therefore, AVs must be able to communicate with other traffic participants, e.g., pedestrians as vulnerable road users (VRUs), to solve ambiguous traffic situations. To achieve well-working communication and thereby safe interaction between AVs and other traffic participants, the latest research discusses external human–machine interfaces (eHMIs) as promising communication tools. Therefore, this study examines the potential positive and negative effects of AVs equipped with static (only displaying the current vehicle automation status (VAS)) and dynamic (communicating an AV’s perception and intention) eHMIs on the interaction with pedestrians by taking subjective and objective measurements into account. In a Virtual Reality (VR) simulator study, 62 participants were instructed to cross a street while interacting with non-automated (without eHMI) and automated vehicles (equipped with static eHMI or dynamic eHMI). The results reveal that a static eHMI had no effect on pedestrians’ crossing decisions and behaviors compared to a non-automated vehicle without any eHMI. However, participants benefit from the additional information of a dynamic eHMI by making earlier decisions to cross the street and higher certainties regarding their decisions when interacting with an AV with a dynamic eHMI compared to an AV with a static eHMI or a non-automated vehicle. Implications for a holistic evaluation of eHMIs as AV communication tools and their safe introduction into traffic are discussed based on the results.
Future automated vehicles (AVs) of different sizes will share the same space with other road users, e. g., pedestrians. For a safe interaction, successful communication needs to be ensured, in particular, with vulnerable road users, such as pedestrians. Two possible communication means exist for AVs: vehicle kinematics for implicit communication and external human-machine interfaces (eHMIs) for explicit communication. However, the exact interplay is not sufficiently studied yet for pedestrians' interactions with AVs. Additionally, very few other studies focused on the interplay of vehicle kinematics and eHMI for pedestrians' interaction with differently sized AVs, although the precise coordination is decisive to support the communication with pedestrians. Therefore, this study focused on how the interplay of vehicle kinematics and eHMI affects pedestrians' willingness to cross, trust and perceived safety for the interaction with two differently sized AVs (smaller AV vs. larger AV). In this experimental online study (N = 149), the participants interacted with the AVs in a shared space. Both AVs were equipped with a 360° LED light-band eHMI attached to the outer vehicle body. Three eHMI statuses (no eHMI, static eHMI, and dynamic eHMI) were displayed. The vehicle kinematics were varied at two levels (non-yielding vs. yielding). Moreover, “non-matching” conditions were included for both AVs in which the dynamic eHMI falsely communicated a yielding intent although the vehicle did not yield. Overall, results showed that pedestrians' willingness to cross was significantly higher for the smaller AV compared to the larger AV. Regarding the interplay of vehicle kinematics and eHMI, results indicated that a dynamic eHMI increased pedestrians' perceived safety when the vehicle yielded. When the vehicle did not yield, pedestrians' perceived safety still increased for the dynamic eHMI compared to the static eHMI and no eHMI. The findings of this study demonstrated possible negative effects of eHMIs when they did not match the vehicle kinematics. Further implications for a holistic communication strategy for differently sized AVs will be discussed.
In future urban traffic, communication abilities of automated vehicles (AVs) are needed to enable a safe interaction with pedestrians as so-called vulnerable road users. Dynamic human-machine interfaces (dHMIs) and external human-machine interfaces (eHMIs) are designed to enable AVs to communicate implicitly, e.g., via vehicle dynamics, and explicitly, e.g., by light signals. To this point, it is neither sufficiently studied how the exact interplay of both communication tools should take place nor how this should be considered for an automated bus. This study aims to shed light on pedestrians' interaction with an automated bus by combining vehicle behavior (dHMI) and different eHMIs. The main focus was on the effect of contradictory communication messages on pedestrians' willingness to cross. Results showed that for non-yielding conditions, a dynamic eHMI that displayed an erroneous yielding intent lead to a significantly higher pedestrians' willingness to cross compared to static eHMI or no eHMI.
The successful integration of highly automated vehicles (HAV) in future mixed traffic environments will depend, among other things, on their seamless, safe, and accepted interaction with other road users. Therefore, appropriate combination of light signals, as external human-machine interface (eHMI), and driving behavior, as dynamic human-machine interface (dHMI), is required consistently in order to develop trust of following manual drivers in HAVs. Especially, in borderline traffic scenarios where HAVs are confronted with challenges, such as loss of connectivity, so-called minimal risk maneuvers (MRMs) are performed abruptly. Here, understanding communication via eHMI and dHMI is crucial for road safety, as drivers need to prepare for maneuvers themselves. Therefore, two consecutive, explorative online video studies were conducted. Firstly, the appropriate braking dynamics for an MRM were evaluated. Secondly, insights into the eHMI communication strategy of an HAV during an MRM were gained. The overall aim of this work is to present strategies for implicit and explicit communication channels of an HAV in order to promote learned trust during MRMs from the perspective of drivers who follow them. The results show that adding novel eHMI designs (e.g., warning sign, 360° LED light-band) to conventional light signals positively affects the user experience in a first contact interaction. The findings could have a positive impact on the development of trust in HAVs. In conclusion, specific eHMI communication strategies can be highly supportive for following manual drivers in MRM scenarios, which may lead to legislative considerations in the future.
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