Self-Assessment for Multi-Object Tracking Based on Subjective Logic
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Date
2024-07-15
Authors
Griebel, Thomas
Dehler, Nikolas
Scheible, Alexander
Buchholz, Michael
Dietmayer, Klaus
Journal Title
Journal ISSN
Volume Title
Publication Type
Beitrag zu einer Konferenz
Published in
2024 IEEE Intelligent Vehicles Symposium (IV), 2024
Abstract
In automated driving, the safety and robustness of the overall system are among the most important key challenges today. To tackle these safety and robustness challenges, the monitoring and self-assessment of all modules in the automated system is necessary. Tracking surrounding objects as part of the environmental perception is a key module in automated systems. Thus, this work presents a novel overall concept and framework for self-assessment in multi-object tracking based on the subjective logic theory. The self-assessment concept is comprehensively discussed and evaluated by simulations and real-world data of the KITTI dataset, showing the relevance of this proposed method.
Description
Faculties
Fakultät für Ingenieurwissenschaften, Informatik und Psychologie
Institutions
Institut für Mess-, Regel- und Mikrotechnik
Citation
DFG Project uulm
EU Project THU
EVENTS / ReliablE in-Vehicle pErception and decisioN-making in complex environmenTal conditionS / EC / HE / 101069614
PoDIUM / PDI connectivity and cooperation enablers building trust and sustainability for CCAM / EC / HE / 101069547
PoDIUM / PDI connectivity and cooperation enablers building trust and sustainability for CCAM / EC / HE / 101069547
Other projects THU
License
CC BY 4.0 International
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DOI external
DOI external
10.1109/IV55156.2024.10588720
Institutions
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DFG Project THU
item.page.thu.projectEU
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Keywords
Self-assessment, Multi-object tracking, Monitoring, Subjective logic, Multi-sensor systems, Autonomes Fahrzeug, Objekterkennung, Multimodales System, Deep learning, Automated vehicles, Environmental monitoring, Optical data processing, Pattern recognition, Automobile driving; Automation, Deep learning, DDC 620 / Engineering & allied operations