Projects per year
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.
| Original language | English |
|---|---|
| Number of pages | 6 |
| Publication status | Published - 7 Dec 2024 |
| Event | International Workshop on Smart Moving (SMVG 2024): Co-located with ACM/IEEE Symposium on Edge Computing - Rome, Italy, Rome, Italy Duration: 7 Dec 2024 → 9 Dec 2024 https://acm-ieee-sec.org/2024/interact_moving.php |
Workshop
| Workshop | International Workshop on Smart Moving (SMVG 2024) |
|---|---|
| Abbreviated title | SMVG 2024 |
| Country/Territory | Italy |
| City | Rome |
| Period | 7/12/24 → 9/12/24 |
| Internet address |
Keywords
- driving safety, attention, VLM agent, perception
Fields of Expertise
- Information, Communication & Computing
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Dive into the research topics of 'Exploring Human and Artificial Attention Mechanisms in Driving Scenarios'. Together they form a unique fingerprint.Projects
- 1 Active
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CORVETTE - Cognitive sensing for vehicle fleet driven data services
Saukh, O. (Co-Investigator (CoI)), Römer, K. U. (Co-Investigator (CoI)), Krisper, M. (Co-Investigator (CoI)) & Papst, F. (Co-Investigator (CoI))
1/05/21 → 31/03/25
Project: Research project