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20242026
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cs.RO2026

Beyond Scalar Rewards: Distributional Reinforcement Learning with Preordered Objectives for Safe and Reliable Autonomous Driving

Ahmed Abouelazm, Jonas Michel, Daniel Bogdoll +2

Autonomous driving involves multiple, often conflicting objectives such as safety, efficiency, and comfort. In reinforcement learning (RL), these objectives are typically combined…

cs.RO2025

Online Performance Assessment of Multi-Source-Localization for Autonomous Driving Systems Using Subjective Logic

Stefan Orf, Sven Ochs, Marc René Zofka +1

Autonomous driving (AD) relies heavily on high precision localization as a crucial part of all driving related software components. The precise positioning is necessary for the uti…

cs.RO2025

Functionality Assessment Framework for Autonomous Driving Systems using Subjective Networks

Stefan Orf, Sven Ochs, Valentin Marotta +3

In complex autonomous driving (AD) software systems, the functioning of each system part is crucial for safe operation. By measuring the current functionality or operability of ind…

cs.RO2025

Label-Free Model Failure Detection for Lidar-based Point Cloud Segmentation

Daniel Bogdoll, Finn Sartoris, Vincent Geppert +2

Autonomous vehicles drive millions of miles on the road each year. Under such circumstances, deployed machine learning models are prone to failure both in seemingly normal situatio…

cs.RO2024

Modular Fault Diagnosis Framework for Complex Autonomous Driving Systems

Stefan Orf, Sven Ochs, Jens Doll +4

Fault diagnosis is crucial for complex autonomous mobile systems, especially for modern-day autonomous driving (AD). Different actors, numerous use cases, and complex heterogeneous…

cs.RO2024

Empowering Autonomous Shuttles with Next-Generation Infrastructure

Sven Ochs, Melih Yazgan, Rupert Polley +9

As cities strive to address urban mobility challenges, combining autonomous transportation technologies with intelligent infrastructure presents an opportunity to transform how peo…