442 citations · 902 across the 47 of their papers we have counts for
51 papers
QoS-Aware Federated Learning for Multimodal In-Cabin Interaction in Smart Vehicles
Baran Can Gül, Mert Nakıp, Nasser Jazdi +1
Modern smart vehicles leverage multimodal sensors, ranging from high-bandwidth vision systems to low-rate physiological monitors, to provide personalized in-cabin services. However…
Situation Awareness for Intelligent Data Distribution in Connected Vehicles
Falk Dettinger, Akshay Narla, Michael Weyrich
The limitations of on-board sensors and blind spots caused by occlusion cause the reduction of perception quality in autonomous vehicles. In such cases, cooperative perception prov…
SecureDrive-FL: Joint Differential Privacy and Gradient-Aware Selective Homomorphic Encryption for Federated Driver Monitoring
Baran Can Gül, Hanuma Siddhartha Tunuguntla, Anjana Arvind Naik +3
Federated Learning (FL) enables privacy-aware distributed training, yet gradient updates remain exploitable: Man-in-the-Middle (MitM) interception exposes updates in transit, while…
LLM Agents Perform Controlled Experiments Using Simulation Models
Yuchen Xia, Michael Weyrich, Nasser Jazdi +6
Large language models (LLMs) have shown strong capabilities in reasoning, planning, and tool use, but many scientific and engineering tasks require more than plausible text and cod…
Self-Adaptive Anomaly Detection with Reinforcement Learning and Human Feedback in Connected Vehicles
Matthias Weiß, Athreya Hosahalli Prakash, Maurice Artelt +3
Connected vehicles are autonomous cyber-physical systems whose behavior must be continuously monitored during operation to detect deviations from normal operation before they propa…
Evaluating Hardware Abstraction Layer Concepts for Software Defined Vehicles: Insights into Applicability and Effectiveness
Akshay Narla, Johannes Stümpfle, Souvik Saha +2
The emergence of Software-Defined Vehicles represents a fundamental shift in automotive design, prioritizing software-centric architectures over traditional hardware-driven models.…
SDVDiag: Multimodal Causal Discovery for Online Diagnosis in Software-defined Vehicles
Matthias Weiß, Athreya Hosahalli Prakash, Falk Dettinger +2
The transition toward software-defined vehicles concentrates an increasing share of vehicle functionality into distributed software services, where failures propagate through servi…
Towards Intelligent Computation Offloading in Dynamic Vehicular Networks: A Scalable Multilayer Pipeline
Falk Dettinger, Matthias Weiß, Baran Can Gül +3
Software Defined Vehicles face an increasing computational gap as advanced algorithms and frequent software updates demand more processing power while onboard hardware remains stat…
SDVDiag: Using Context-Aware Causality Mining for the Diagnosis of Connected Vehicle Functions
Matthias Weiß, Falk Dettinger, Elias Detrois +2
Real-world implementations of connected vehicle functions are spreading steadily, yet operating these functions reliably remains challenging due to their distributed nature and the…
Advanced Strategies for Uncertainty-Guided Live Measurement Sequencing in Fast, Robust SAR ADC Linearity Testing
Thorben Schey, Khaled Karoonlatifi, Michael Weyrich +1
This paper builds on our Uncertainty-Guided Live Measurement Sequencing (UGLMS) method. UGLMS is a closed-loop test strategy that adaptively selects SAR ADC code edges based on mod…
Uncertainty-Guided Live Measurement Sequencing for Fast SAR ADC Linearity Testing
Thorben Schey, Khaled Karoonlatifi, Michael Weyrich +1
This paper introduces a novel closed-loop testing methodology for efficient linearity testing of high-resolution Successive Approximation Register (SAR) Analog-to-Digital Converter…
Directives for Function Offloading in 5G Networks Based on a Performance Characteristics Analysis
Falk Dettinger, Matthias Weiß, Daniel Baumann +2
Cloud-based offloading helps address energy consumption and performance challenges in executing resource-intensive vehicle algorithms. Utilizing 5G, with its low latency and high b…
An OpenSource CI/CD Pipeline for Variant-Rich Software-Defined Vehicles
Matthias Weiß, Anish Navalgund, Johannes Stümpfle +2
Software-defined vehicles (SDVs) offer a wide range of connected functionalities, including enhanced driving behavior and fleet management. These features are continuously updated…
SDVDiag: A Modular Platform for the Diagnosis of Connected Vehicle Functions
Matthias Weiß, Falk Dettinger, Michael Weyrich
Connected and software-defined vehicles promise to offer a broad range of services and advanced functions to customers, aiming to increase passenger comfort and support autonomous…
FedMultiEmo: Real-Time Emotion Recognition via Multimodal Federated Learning
Baran Can Gül, Suraksha Nadig, Stefanos Tziampazis +2
In-vehicle emotion recognition underpins adaptive driver-assistance systems and, ultimately, occupant safety. However, practical deployment is hindered by (i) modality fragility -…
Model-Based Control for Power-to-X Platforms: Knowledge Integration for Digital Twins
Daniel Dittler, Peter Frank, Gary Hildebrandt +3
Offshore Power-to-X platforms enable flexible conversion of renewable energy, but place high demands on adaptive process control due to volatile operating conditions. To face this…
A Concept for Autonomous Problem-Solving in Intralogistics Scenarios
Johannes Sigel, Daniel Dittler, Nasser Jazdi +1
Achieving greater autonomy in automation systems is crucial for handling unforeseen situations effectively. However, this remains challenging due to technological limitations and t…
Communication Architecture for Autonomous Power-to-X Platforms: Enhancing Inspection and Operation With Legged Robots and 5G
Peter Frank, Falk Dettinger, Daniel Dittler +4
Inspection and maintenance of offshore platforms are associated with high costs, primarily due to the significant personnel requirements and challenging operational conditions. Thi…
An Expert Survey on Models and Digital Twins
Jonathan Reif, Daniel Dittler, Milapji Singh Gill +5
Digital Twins (DTs) are becoming increasingly vital for future industrial applications, enhancing monitoring, control, and optimization of physical assets. This enhancement is made…
SyncFed: Time-Aware Federated Learning through Explicit Timestamping and Synchronization
Baran Can Gül, Stefanos Tziampazis, Nasser Jazdi +1
As Federated Learning (FL) expands to larger and more distributed environments, consistency in training is challenged by network-induced delays, clock unsynchronicity, and variabil…
Efficient Creation of Behavior Models with Variable Modeling Depths Used in Digital Twins
Valentin Stegmaier, Walter Schaaf, Nasser Jazdi +1
Behavior models form an integral component of Digital Twins. The specific characteristics of these models may vary depending on the use case. One of these key characteristics is th…
A Survey on Performance, Current and Future Usage of Vehicle-To-Everything Communication Standards
Falk Dettinger, Matthias Weiß, Daniel Dittler +3
Wireless communication between road users is essential for environmental perception, reasoning, and mission planning to enable fully autonomous vehicles, and thus improve road safe…
Control Industrial Automation System with Large Language Model Agents
Yuchen Xia, Nasser Jazdi, Jize Zhang +2
Traditional industrial automation systems require specialized expertise to operate and complex reprogramming to adapt to new processes. Large language models offer the intelligence…
Incorporating Large Language Models into Production Systems for Enhanced Task Automation and Flexibility
Yuchen Xia, Jize Zhang, Nasser Jazdi +1
This paper introduces a novel approach to integrating large language model (LLM) agents into automated production systems, aimed at enhancing task automation and flexibility. We or…