Self-Monitored Detection Probability Estimation for the Labeled Multi-Bernoulli Filter
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Date
2025-03-20
Authors
Scheible, Alexander
Griebel, Thomas
Buchholz, Michael
Journal Title
Journal ISSN
Volume Title
Publication Type
Beitrag zu einer Konferenz
Published in
2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), 2024
Abstract
Automated vehicles rely on their environment
model, usually generated by a tracking module using sensor data,
to make decisions. Therefore, estimating the accuracy of the
tracking module is vital for the safe and reliable operation of the
vehicle. This work makes a step towards this goal by providing
a detection probability estimation method with a self-monitored
quality assessment for the labeled multi-Bernoulli filter. We
demonstrate the significance of the proposed quality index by
comparing it with the actual estimation error calculated with
ground truth data. This shows that the developed index is a
meaningful value that can be computed online without ground
truth data.
Description
Faculties
Fakultät für Ingenieurwissenschaften, Informatik und Psychologie
Institutions
Institut für Mess-, Regel- und Mikrotechnik
Citation
DFG Project uulm
EU Project THU
PoDIUM / PDI connectivity and cooperation enablers building trust and sustainability for CCAM / EC / HE / 101069547
EVENTS / ReliablE in-Vehicle pErception and decisioN-making in complex environmenTal conditionS / EC / HE / 101069614
EVENTS / ReliablE in-Vehicle pErception and decisioN-making in complex environmenTal conditionS / EC / HE / 101069614
Other projects THU
License
CC BY 4.0 International
Is version of
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Part of
DOI external
DOI external
10.1109/ITSC58415.2024.10920041
Institutions
Periodical
Degree Program
DFG Project THU
item.page.thu.projectEU
item.page.thu.projectOther
Series
Keywords
Self-Assessment, Objektverfolgung, Tracking (Engineering), DDC 620 / Engineering & allied operations