Exploring Human and Artificial Attention Mechanisms in Driving Scenarios

Martin Rechberger, Daniel Kraus, Peter Priller, Olga Saukh

Publikation: KonferenzbeitragPaperBegutachtung

Abstract

Understanding attention is crucial for improving safety in driving scenarios. Detected and classified objects, along with their observation by the driver, are used as a measure of attention. This paper investigates the differences between human and artificial attention in real-world and replay driving scenarios. By analyzing attention patterns from drivers and a vision-language model agent, we identify a number of differences. The results highlight the limitations of current AI attention models and suggest the way forward for developing more context-aware systems.
Originalspracheenglisch
Seitenumfang6
PublikationsstatusVeröffentlicht - 7 Dez. 2024
VeranstaltungInternational Workshop on Smart Moving (SMVG 2024): Co-located with ACM/IEEE Symposium on Edge Computing - Rome, Italy, Rome, Italien
Dauer: 7 Dez. 20249 Dez. 2024
https://acm-ieee-sec.org/2024/interact_moving.php

Workshop

WorkshopInternational Workshop on Smart Moving (SMVG 2024)
KurztitelSMVG 2024
Land/GebietItalien
OrtRome
Zeitraum7/12/249/12/24
Internetadresse

Fields of Expertise

  • Information, Communication & Computing

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