A Unified Self-Assessment Framework for Autonomous Driving Stacks Using Subjective Logic
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Date
2025-03
Authors
Wodtko, Thomas
Griebel, Thomas
Buchholz, Michael
Dietmayer, Klaus
Journal Title
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Publication Type
Beitrag zu einer Konferenz
Published in
16. Uni-DAS e.V. Workshop Fahrerassistenz und automatisiertes Fahren (FAS- Workshop 2025)
Abstract
Self-assessment plays a critical and important role toward safe and robust autonomous driving. Current self-assessment approaches in this area focus on individual modules at specific positions within the autonomous driving stack. The literature lacks a unifying framework to combine various self-assessment information. Hence, this work provides a comprehensive self-assessment framework for autonomous driving stacks, combining and unifying existing self-assessment methods. For this framework, we propose using subjective logic as an interface to standardize the output of self-assessment modules. This allows the combination of different modules and their use in subsequent processing modules. Our approach can be deployed to existing autonomous vehicle software stacks without imposing any requirements on their functional parts, enabling easy integration. With this framework, we are aiming to contribute to the improvement of safety and reliability in autonomous driving.
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
Other projects THU
U-Shift II / U-Shift II (Demonstrator) / WM Baden-Württemberg / AZ 3-433.62-DLR/60
License
CC BY 4.0 International
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DOI external
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Keywords
Autonomous driving, Self-assessment, Subjective logic, Subjective networks, Autonomes Fahrzeug, Automated vehicles, DDC 620 / Engineering & allied operations