Evaluating Visual Communication Interfaces Between Pedestrians and Autonomous Vehicles Using Virtual Reality Experiments

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F24%3A00381145" target="_blank" >RIV/68407700:21260/24:00381145 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21730/24:00381145

Result on the web

<a href="https://doi.org/10.14311/NNW.2024.34.015" target="_blank" >https://doi.org/10.14311/NNW.2024.34.015</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.14311/NNW.2024.34.015" target="_blank" >10.14311/NNW.2024.34.015</a>

Result language

angličtina

Original language name

Evaluating Visual Communication Interfaces Between Pedestrians and Autonomous Vehicles Using Virtual Reality Experiments

Original language description

This study explores the development and evaluation of external human-machine interfaces (eHMI) for communication between autonomous vehicles (AVs) and pedestrians. By employing advanced virtual reality (VR) simulations and leveraging behavioral data from 600 survey respondents, the research examines the intelligibility and effectiveness of seven eHMI prototypes. The experiments utilized eye-tracking and spatial analysis to measure pedestrian response to AV signals in realistic virtual environments. The findings emphasize the potential of LED strip-based communication interfaces, demonstrating their superiority in terms of visibility, clarity, and implementation cost. This research contributes to the broader field of artificial intelligence applications in transportation, with a focus on ensuring safety and trust in autonomous systems interacting with vulnerable road users.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Neural Network World

ISSN

1210-0552

e-ISSN

2336-4335

Volume of the periodical

34

Issue of the periodical within the volume

5

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

13

Pages from-to

279-291

UT code for WoS article

001419837000001

EID of the result in the Scopus database

2-s2.0-105000140139