Taming the eHMI jungle: A classification taxonomy to guide, compare, and assess the design principles of automated vehicles' external human-machine interfacesShow others and affiliations
2020 (English)In: Transportation Research Interdisciplinary Perspectives, E-ISSN 2590-1982, Vol. 7, article id 100174Article in journal (Refereed) Published
Abstract [en]
There is a growing body of research in the field of interaction between automated vehicles and other road users in their vicinity. To facilitate such interactions, researchers and designers have explored designs, and this line of work has yielded several concepts of external Human-Machine Interfaces (eHMI) for vehicles. Literature and media review reveals that the description of interfaces is often lacking in fidelity or details of their functionalities in specific situations, which makes it challenging to understand the originating concepts. There is also a lack of a universal understanding of the various dimensions of a communication interface, which has impeded a consistent and coherent addressal of the different aspects of the functionalities of such interface concepts. In this paper, we present a unified taxonomy that allows a systematic comparison of the eHMI across 18 dimensions, covering their physical characteristics and communication aspects from the perspective of human factors and human-machine interaction. We analyzed and coded 70 eHMI concepts according to this taxonomy to portray the state of the art and highlight the relative maturity of different contributions. The results point to a number of unexplored research areas that could inspire future work. Additionally, we believe that our proposed taxonomy can serve as a checklist for user interface designers and researchers when developing their interfaces. © 2020 The Authors
Place, publisher, year, edition, pages
Elsevier Ltd , 2020. Vol. 7, article id 100174
Keywords [en]
Automated vehicle, External human-machine interface, Human factors, Human-computer interaction, Pedestrian, Taxonomy, Vulnerable road user
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-46789DOI: 10.1016/j.trip.2020.100174Scopus ID: 2-s2.0-85089012884OAI: oai:DiVA.org:ri-46789DiVA, id: diva2:1460642
Note
Funding details: Ministerie van Economische Zaken, EZ, 14896; Funding details: Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO; Funding details: Fellowships Fund Incorporated, FFI; Funding details: Knowledge Foundation; Funding details: Bundesministerium für Bildung und Forschung, BMBF; Funding details: Bundesministerium für Bildung und Frauen, BMBF, 13FH7I01IA; Funding details: Bundesministerium für Verkehr und Digitale Infrastruktur, BMVI, 16AVF2145F; Funding text 1: The contribution of Debargha Dey is supported by the Dutch Domain Applied and Engineering Sciences, which is part of the Netherlands Organization for Scientific Research (NWO), and which is partly funded by the Ministry of Economic Affairs (project number 14896 ).; Funding text 2: The contribution of Azra Habibovic is supported the Knowledge Foundation (KK-stiftelsen) and the Strategic Vehicle Research and Innovation ( FFI ) via Scale-up project Nr. 2018-04999 .; Funding text 3: The contributions of Andreas Löcken , Philipp Wintersberger , and Andreas Riener are supported under the FH-Impuls program of the German Federal Ministry of Education and Research ( BMBF ), Grant Number 13FH7I01IA (SAFIR), and by the German Federal Ministry of Transport and Digital Infrastructure ( BMVI ) through the Automated and Connected Driving funding program under Grant No. 16AVF2145F (SAVe).
2020-08-242020-08-242025-09-23Bibliographically approved