TUdatalib : AR-CP: Uncertainty-Aware Perception in Adverse Conditions with Conformal Prediction and Augmented Reality For Assisted Driving

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dc.contributor.author	Doula, Achref
dc.contributor.author	Mühlhäuser, Max
dc.contributor.author	Sanchez Guinea, Alejandro
dc.date.accessioned	2024-04-30T16:10:57Z
dc.date.available	2024-04-30T16:10:57Z
dc.date.issued	2024-04-14
dc.identifier.uri	https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4219
dc.description	Deep learning models play a crucial role in improving driver assistance systems and environmental perception. However, their tendency toward overconfident predictions poses risks to driver safety, particularly in adverse conditions. To address this, we propose AR-CP, an uncertainty-aware framework integrating conformal prediction and augmented reality (AR). AR-CP starts with a conformal prediction step, generating an uncertainty-aware prediction set. Then, AR simplifies and clarifies the visualization of the closest common parent class, reducing misinformation. We present a rigorous formulation and theoretical analysis, evaluating AR-CP on the ROAD dataset. Results demonstrate superior performance compared to existing methods, ensuring safer driving experiences with reduced mental load and heightened situation awareness, as validated by an immersive user study involving 15 participants.	de_DE
dc.language.iso	en	de_DE
dc.rights	Open Data Commons Attribution License (ODC-By) v1.0
dc.rights.uri	https://opendatacommons.org/licenses/by/1.0/
dc.subject	Uncertainty Quantification	de_DE
dc.subject	Deep Learning	de_DE
dc.subject	Augmented Reality	de_DE
dc.subject	Urban Scene Understanding	de_DE
dc.subject.classification	4.43-04 Künstliche Intelligenz und Maschinelle Lernverfahren	de_DE
dc.subject.classification	4.43-05 Bild- und Sprachverarbeitung, Computergraphik und Visualisierung, Human Computer Interaction, Ubiquitous und Wearable Computing
dc.subject.ddc	004
dc.title	AR-CP: Uncertainty-Aware Perception in Adverse Conditions with Conformal Prediction and Augmented Reality For Assisted Driving	de_DE
dc.type	Software	de_DE
dc.description.version	0.1	de_DE
tud.unit	TUDa
tud.history.classification	Version=2016-2020;409-05 Interaktive und intelligente Systeme, Bild- und Sprachverarbeitung, Computergraphik und Visualisierung