Literature DB >> 30509537

An experimental study to investigate design and assessment criteria: What is important for communication between pedestrians and automated vehicles?

Claudia Ackermann1, Matthias Beggiato2, Sarah Schubert2, Josef F Krems2.   

Abstract

In the near future, more vehicles will have automated functions. The traffic system will be a shared space of automated and manually driven vehicles. In our study we focused on the perspective of vulnerable road users, namely pedestrians, in cooperative situations with automated vehicles. Established communication methods, such as eye-contact between pedestrians and drivers, may no longer work when automated vehicles represent the interaction partner. Therefore, we evaluated several human-machine-interfaces (HMI) in order to implement smooth and comfortable communication. We conducted a two-stage study consisting of an explorative focus group discussion with naïve pedestrians (n = 6), followed by an experimental video simulation study (n = 25) based on the results of the focus group discussion. From the focus group we sought member opinion about various HMI, upon presentation of acoustic and visual communication systems such as projections, displays and LED light strips, in addition to portable communication systems, specifically smart watches. On the basis of the focus group discussion, an evaluation criteria was derived. For the video simulation study, HMI designs were created with variations in position, type and coding of the message, and technology. These were assessed by 25 subjects according to the focus discussion derived evaluation criteria: recognizability, unambiguousness, interaction comfort and intuitive comprehensibility. The results show that direct instructions to cross the street are preferred over status information of the vehicle and that large-scale text-based messages from the vehicle to the pedestrian, deliver better results. Design recommendations for HMIs for communication between automated vehicles are derived, and the extent external HMIs may supplement informal communication strategies such as vehicle movement or braking maneuvers, is discussed.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Automated vehicles; HMI design recommendations; HMI evaluation; Pedestrian-automation-interaction

Mesh:

Year:  2018        PMID: 30509537     DOI: 10.1016/j.apergo.2018.11.002

Source DB:  PubMed          Journal:  Appl Ergon        ISSN: 0003-6870            Impact factor:   3.661


  11 in total

1.  External Human-Machine Interfaces for Autonomous Vehicles from Pedestrians' Perspective: A Survey Study.

Authors:  Jiawen Guo; Quan Yuan; Jingrui Yu; Xizheng Chen; Wenlin Yu; Qian Cheng; Wuhong Wang; Wenhui Luo; Xiaobei Jiang
Journal:  Sensors (Basel)       Date:  2022-04-27       Impact factor: 3.847

2.  The Application of Artificial Intelligence Technology in Art Teaching Taking Architectural Painting as an Example.

Authors:  Jing Li; Bingyu Zhang
Journal:  Comput Intell Neurosci       Date:  2022-05-17

Review 3.  eHMI: Review and Guidelines for Deployment on Autonomous Vehicles.

Authors:  Juan Carmona; Carlos Guindel; Fernando Garcia; Arturo de la Escalera
Journal:  Sensors (Basel)       Date:  2021-04-21       Impact factor: 3.576

Review 4.  External Human-Machine Interfaces for Autonomous Vehicle-to-Pedestrian Communication: A Review of Empirical Work.

Authors:  Alexandros Rouchitsas; Håkan Alm
Journal:  Front Psychol       Date:  2019-12-10

5.  Pedestrians' Understanding of a Fully Autonomous Vehicle's Intent to Stop: A Learning Effect Over Time.

Authors:  Michal Hochman; Yisrael Parmet; Tal Oron-Gilad
Journal:  Front Psychol       Date:  2020-12-03

6.  The Effect of eHMI Malfunctions on Younger and Elderly Pedestrians' Trust and Acceptance of Automated Vehicle Communication Signals.

Authors:  Ann-Christin Hensch; Isabel Kreißig; Matthias Beggiato; Josef F Krems
Journal:  Front Psychol       Date:  2022-05-03

7.  The Application of RBF Neural Network Model Based on Deep Learning for Flower Pattern Design in Art Teaching.

Authors:  Lijun Xiao; Yan Luo
Journal:  Comput Intell Neurosci       Date:  2022-06-13

8.  Analysing the effect of gender on the human-machine interaction in level 3 automated vehicles.

Authors:  Shuo Li; Phil Blythe; Yanghanzi Zhang; Simon Edwards; Weihong Guo; Yanjie Ji; Paul Goodman; Graeme Hill; Anil Namdeo
Journal:  Sci Rep       Date:  2022-07-08       Impact factor: 4.996

9.  Toward a Holistic Communication Approach to an Automated Vehicle's Communication With Pedestrians: Combining Vehicle Kinematics With External Human-Machine Interfaces for Differently Sized Automated Vehicles.

Authors:  Merle Lau; Meike Jipp; Michael Oehl
Journal:  Front Psychol       Date:  2022-07-28

10.  Corrigendum: External Human-Machine Interfaces for Autonomous Vehicle-to-Pedestrian Communication: A Review of Empirical Work.

Authors:  Alexandros Rouchitsas; Håkan Alm
Journal:  Front Psychol       Date:  2020-10-16
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