Stop or Go? Let me Know!

Mirnig, Alexander G.; Gärtner, Magdalena; Wallner, Vivien; Gafert, Michael; Braun, Hanna; Fröhlich, Peter; Suette, Stefan; Sypniewski, Jakub; Meschtscherjakov, Alexander; Tscheligi, Manfred

doi:10.1145/3409118.3475131

Cited by 9 publications

(3 citation statements)

References 13 publications

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“…They also felt safer when the HAV was equipped with an eHMI indicating the vehicle's yielding intent compared to no eHMI or an eHMI only displaying the vehicle's automation status (Lau et al, 2022). Mirnig et al (2021) investigated the use of an intention-based light-band eHMI for a highly automated shuttle and showed that the eHMI supported a smooth interaction between the shuttle and the surrounding traffic. The authors stated that the eHMI helped other road users to better understand the vehicle's intention and, accordingly, to adapt their behavior to the shuttle's behavior.…”

Section: Visual External Communication Of Havs With Other Tra C Parti...mentioning

confidence: 99%

Promoting trust in HAVs of following manual drivers through implicit and explicit communication during minimal risk maneuvers

Hess

Lau

Wilbrink

et al. 2023

Front. Comput. Sci.

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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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Section: Visual External Communication Of Havs With Other Tra C Parti...mentioning

confidence: 99%

Promoting trust in HAVs of following manual drivers through implicit and explicit communication during minimal risk maneuvers

Hess

Lau

Wilbrink

et al. 2023

Front. Comput. Sci.

View full text Add to dashboard Cite

show abstract

“…Cyclists may interact with AVs in more dynamic situations, and may necessitate eHMIs that can be viewed from all sides (e.g., Vlakveld et al, 2020). Additionally, researchers have devised eHMIs that communicate to manual vehicles, such as in a bottleneck scenario (Rettenmaier et al, 2020) or to communicate yielding intention at junctions (e.g., Avsar et al, 2021;Mirnig et al, 2021;Papakostopoulos et al, 2021). These developments raise the question of whether eHMIs will have to be separately tailored to different road users (pedestrians, cyclists, manual vehicles) and scenarios.…”

Section: Argument 2 Against Ehmis: There Is a Lack Of Standardization...mentioning

confidence: 99%

“…There is a limited but growing number of eHMI studies conducted with real vehicles, but typically in simple settings such as parking lots (Ahn et al, 2021;Chen et al, 2020;Hensch et al, 2020;Liu et al, 2021), indoor environments (Burns et al, 2019;Reschke et al, 2018), test tracks (Faas et al, 2021;Fuest et al, 2020;Horn et al, 2021), or roads with otherwise restricted access (Barendse, 2019;Dey et al, 2021a;Habibovic et al, 2018;Joisten et al, 2019;Morales Alvarez et al, 2019;Mührmann, 2019;Papakostopoulos et al, 2021;Zadeh Darrehshourian, 2021). Research in real traffic is still relatively rare (Cefkin et al, 2019;Forke et al, 2021;Merat et al, 2018;Mirnig et al, 2021;Monzel et al, 2021), and some evidence concurs that eHMIs will have to compete with other visual cues in the environment. In particular, Cefkin et al (2019) found that, in real traffic, which can be busy and requires distributed visual attention, pedestrians often did not even notice the eHMI on the car.…”

Section: Argument 3 Against Ehmis: Ehmis Elicit Negative Effectsmentioning

confidence: 99%