Print Email Facebook Twitter Bio-inspired intent communication for automated vehicles Title Bio-inspired intent communication for automated vehicles Author Oudshoorn, Max (Student TU Delft) de Winter, J.C.F. (TU Delft Human-Robot Interaction) Bazilinskyy, P. (TU Delft Human-Robot Interaction) Dodou, D. (TU Delft Medical Instruments & Bio-Inspired Technology) Date 2021 Abstract Various external human-machine interfaces (eHMIs) have been proposed that communicate the intent of automated vehicles (AVs) to vulnerable road users. However, there is no consensus on which eHMI concept is most suitable for intent communication. In nature, animals have evolved the ability to communicate intent via visual signals. Inspired by intent communication in nature, this paper investigated three novel and potentially intuitive eHMI designs that rely on posture, gesture, and colouration, respectively. In an online crowdsourcing study, 1141 participants viewed videos featuring a yielding or non-yielding AV with one of the three bio-inspired eHMIs, as well as a green/red lightbar eHMI, a walk/don't walk text-based eHMI, and a baseline condition (i.e., no eHMI). Participants were asked to press and hold a key when they felt safe to cross and to answer rating questions. Together, these measures were used to determine the intuitiveness of the tested eHMIs. Results showed that the lightbar eHMI and text-based eHMI were more intuitive than the three bio-inspired eHMIs, which, in turn, were more intuitive than the baseline condition. An exception was the bio-inspired colouration eHMI, which produced a performance score that was equivalent to the text-based eHMI when communicating ‘non-yielding’. Further research is necessary to examine whether these observations hold in more complex traffic situations. Additionally, we recommend combining features from different eHMIs, such as the full-body communication of the bio-inspired colouration eHMI with the colours of the lightbar eHMI. Subject Automated vehiclesBio-inspiredCrowdsourcingExternal human-machine interfaceIntent communication To reference this document use: http://resolver.tudelft.nl/uuid:e56d8125-27c0-4467-bcf2-bb255402cf90 DOI https://doi.org/10.1016/j.trf.2021.03.021 ISSN 1369-8478 Source Transportation Research. Part F: Traffic Psychology and Behaviour, 80, 127-140 Part of collection Institutional Repository Document type journal article Rights © 2021 Max Oudshoorn, J.C.F. de Winter, P. Bazilinskyy, D. Dodou Files PDF 1_s2.0_S1369847821000759_main.pdf 3.61 MB Close viewer /islandora/object/uuid:e56d8125-27c0-4467-bcf2-bb255402cf90/datastream/OBJ/view