Self-Monitored Clutter Rate Estimation for the Labeled Multi-Bernoulli Filter

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Scheible_2024_FUSION.pdf (529.15 KB)

Date

2024-10-11

Authors

Scheible, Alexander
Griebel, Thomas
Buchholz, Michael

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Beitrag zu einer Konferenz

DOI

https://doi.org/10.18725/OPARU-54077

Published in

2024 27th International Conference on Information Fusion (FUSION)

Abstract

Decision making in automated vehicles is based on the environment model, which is typically computed by a tracking module from information gathered by sensors. Thus, for safe and robust operation of the vehicle, the assessment of the current quality of the tracking module is crucial. This work makes a step towards this goal by providing a clutter rate estimation method with a self-monitored quality assessment for the labeled multi-Bernoulli filter. The significance of the proposed quality index is demonstrated by comparing it with the actual estimation error calculated with ground truth data. The simulation results show that the developed quality index is a meaningful value that can be computed online without the need for ground truth data. Moreover, it is competitive and closely related to the estimation error.

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

Other projects THU

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CC BY 4.0 International
https://creativecommons.org/licenses/by/4.0/

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DOI external

DOI external

https://doi.org/10.23919/FUSION59988.2024.10706463

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DFG Project THU

item.page.thu.projectEU

item.page.thu.projectOther

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Keywords

Self-Assessment, Zielverfolgung, Tracking (Engineering), DDC 620 / Engineering & allied operations