Identifying Underrepresented Driving Scenarios in Training Datasets with SafeML Robustness Monitoring for Autonomous Driving Vehicles

This study investigates the evaluation of the representativeness of datasets in autonomous driving systems using statistical distance metrics. Eight different datasets, created in the Carla simulation environment, cover various driving conditions, including normal and impaired lighting scenarios, al...

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Vydané v:	2024 8th International Conference on System Reliability and Safety (ICSRS) s. 245 - 253
Hlavní autori:	Matthias, Bergler, Ramin, Tavakoli-Kolagari, Kristina, Lundqvist
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 20.11.2024
Predmet:	Autonomous Driving Autonomous vehicles Lighting Monitoring Power measurement Power system reliability Real-time systems Ro-bustness Robustness SafeML Safety Simulation Time measurement Training
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