@inproceedings{EderLoewHof2025, author = {Eder, Lukas and L{\"o}w, Jakob and Hof, Hans-Joachim}, title = {Charging Communication Sniffing and Man-in-the-Middle Attacks}, booktitle = {Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-1125-1}, doi = {ttps://doi.org/10.1145/3679240.3734648}, pages = {799 -- 804}, year = {2025}, abstract = {In recent years an increasing amount of electric vehicle fast charging stations have been built to meet the growing demand from rising electric vehicle numbers. The standard for fast charging communication in europe is ISO 15118. In theory the standard includes security controls for authentication and transport encryption. In reality difficulties with implementing those security controls as well as insecure design within the standard lead to multiple possible attack vectors compromising the confidentiality and authenticity of charging communication sessions. The goal of this research is to present different approaches towards performing sniffing and man-in-the-middle attacks against charging communication. We also provide a novel approach, which does not rely on race conditions and thus is more reliable than previous approaches.}, language = {en} } @article{MoralesTorricosBergFiggemeieretal.2025, author = {Morales Torricos, Pablo and Berg, Sascha and Figgemeier, Egbert and Endisch, Christian and Lewerenz, Meinert}, title = {The important role of lithiation-induced pressure change on apparent aging of lithium-ion batteries during accelerated cyclic aging tests}, volume = {2025}, pages = {117323}, journal = {Journal of Energy Storage}, number = {131, Part A}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2352-1538}, doi = {https://doi.org/10.1016/j.est.2025.117323}, year = {2025}, abstract = {In assessing the lifespan of lithium-ion batteries in laboratory conditions, the measured capacity declines during accelerated cyclic aging tests but increases when the cells are left idle. This recoverable capacity loss, known in literature as apparent aging, results from an inhomogeneous lithium distribution in the anode appearing in dV/dQ and capacity difference analysis. This study explores the origin of the apparent aging by correlating lithium distribution in the anode and recoverable capacity loss, with the lithiation induced pressure change and generated electrolyte motion during cycling. To this end, we compressed five commercial pouch lithium-ion cells (NMC/Gr) with holder stiffnesses ranging from 0.9 to 15.4 MPa/mm and offset pressure from 289 to 681 kPa and subjected them to continuous cyclic aging tests. While offset pressure had no significant impact, we observed, that holder stiffnesses over 3.3 MPa/mm induces an apparent capacity loss, which is recoverable by 35 \% during a resting phase. The root cause is the so-called electrolyte motion induced salt inhomogeneity (EMSI), driven by continuous high current cycling and electrolyte motion, which is intensified by higher holder stiffness but not by offset pressure. These insights are crucial for improving the accuracy of accelerated aging tests and enhancing battery lifespan predictions.}, language = {en} } @inproceedings{DevillersKurtenackerMembarthetal.2025, author = {Devillers, Hugo and Kurtenacker, Matthias and Membarth, Richard and Lemme, Stefan and Kenzel, Michael and Yazici, {\"O}mercan and Slusallek, Philipp}, title = {No More Shading Languages: Compiling C++ to Vulkan Shaders}, booktitle = {High-Performance Graphics - Symposium Papers}, editor = {Knoll, Aaron and Peters, Christoph}, publisher = {The Eurographics Association}, address = {Goslar}, isbn = {978-3-03868-291-2}, url = {https://diglib.eg.org/handle/10.2312/hpg20251167}, doi = {https://doi.org/10.2312/hpg.20251167}, year = {2025}, abstract = {Graphics APIs have traditionally relied on shading languages, however, these languages have a number of fundamental defects and limitations. By contrast, GPU compute platforms offer powerful, feature-rich languages suitable for heterogeneous compute. We propose reframing shading languages as embedded domain-specific languages, layered on top of a more general language like C++, doing away with traditional limitations on pointers, functions, and recursion, to the benefit of programmability. This represents a significant compilation challenge because the limitations of shaders are reflected in their lower-level representations. We present the Vcc compiler, which allows conventional C and C++ code to run as Vulkan shaders. Our compiler is complemented by a simple shading library and exposes GPU particulars as intrinsics and annotations. We evaluate the performance of our compiler using a selection of benchmarks, including a real-time path tracer, achieving competitive performance compared to their native CUDA counterparts.}, language = {en} } @inproceedings{WildgrubeEhrettTrojahnetal.2025, author = {Wildgrube, Fabian and Ehrett, Pete and Trojahn, Paul and Membarth, Richard and Beckmann, Bradford and Baumeister, Dominik and Chajdas, Matth{\"a}us}, title = {GPUs All Grown-Up: Fully Device-Driven SpMV Using GPU Work Graphs}, booktitle = {ISCA ´25: Proceedings of the 52nd Annual International Symposium on Computer Architecture}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-1261-6}, doi = {https://doi.org/10.1145/3695053.3731060}, pages = {1777 -- 1791}, year = {2025}, abstract = {Sparse matrix-vector multiplication (SpMV) is a key operation across high-performance computing, graph analytics, and many more applications. In these applications, the matrix characteristics, notably non-zero elements per row, can vary widely and impact which algorithm performs best. Thus, Graphics Processing Unit (GPU) SpMV algorithms often rely on costly preprocessing to determine what per-row algorithm to select to achieve high performance. In this work we combine SpMV preprocessing and the subsequent per-row processing on the GPU by leveraging the novel "Work Graphs" GPU programming model—initially designed for graphics applications—for dynamic on-device self-scheduling. Work Graphs allow for fine-grain dataflow execution of individual workgroups using emerging hardware and firmware support. As soon as preprocessing has generated sufficient work, workgroups of individual processing kernels are self-scheduled and executed, interleaved with those of other kernels. This improves cache locality and eliminates host interaction altogether. Across a suite of 59 sparse matrices, the best of various novel Work Graphs SpMV implementations outperforms state-of-the-art rocSPARSE "LRB" for a single SpMV by up to 7.19 × (mean: 3.35 ×, SD: 1.89). Furthermore, it achieves much more stable performance across various sparsity patterns than the rocSPARSE CSR-General algorithm, and even beats the advanced rocSPARSE CSR-Adaptive algorithm for up to 92 consecutive SpMV calculations. In addition, compared to rocSPARSE LRB, it reduces code complexity by 75\%. Its memory footprint for supporting data structures is a fixed ∼ 25 MiB independent of matrix size, compared to rocSPARSE LRB's data structures that scale with matrix size to hundreds of megabytes. Overall, this work showcases the performance potential of emerging dynamic on-device scheduling techniques for GPU compute applications.}, language = {en} } @article{GaedickeHauboldKlagesetal.2025, author = {Gaedicke, Sonja and Haubold, Rebekka and Klages, Anna-Lisa and Rhein, Christian and Schwertel, Tamara and Tietje, Olaf}, title = {Conference Report: Mapping Situational Analysis—An International Conference}, volume = {26}, pages = {20}, journal = {Forum Qualitative Sozialforschung / Forum: Qualitative Social Research (FQS)}, number = {2}, publisher = {Freie Universit{\"a}t Berlin}, address = {Berlin}, issn = {1438-5627}, doi = {https://doi.org/10.17169/fqs-26.2.4424}, year = {2025}, abstract = {In this conference report we provide insights into some of the key topics presented at the first international conference on situational analysis in Germany, held in November 2024 in Magdeburg. Central issues discussed include collaborations and feminist perspectives in practice for power-sensitive knowledge production, nonhumans and how they can be included in situational analysis through all types of mappings as well as methodical and methodological questions regarding mapping processes, interdisciplinary mapping, and the conceptualization of space in and through situational analysis. Adele CLARKE and her work were honored and celebrated at the conference.}, language = {en} } @inproceedings{RauscherStenzelEndisch2025, author = {Rauscher, Andreas and Stenzel, Peer and Endisch, Christian}, title = {Investigation of Factors Influencing the End-of-Line Partial Discharge Testing of Electrical Machines}, booktitle = {2025 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD)}, publisher = {IEEE}, address = {Piscataway}, doi = {https://doi.org/10.1109/WEMDCD61816.2025.11014117}, year = {2025}, language = {en} } @inproceedings{SequeiraInderstXhikuetal.2025, author = {Sequeira, Gerald Joy and Inderst, Maximilian and Xhiku, Redjon and Lugner, Robert and Brandmeier, Thomas}, title = {Sigmoid-Based Method for Longitudinal Crash Pulse Prediction in Intelligent Vehicles}, booktitle = {2024 IEEE International Conference on Vehicular Electronics and Safety (ICVES)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-8727-8}, doi = {https://doi.org/10.1109/ICVES61986.2024.10927899}, year = {2025}, language = {en} } @inproceedings{LoboFestagFacchi2025, author = {Lobo, Silas and Festag, Andreas and Facchi, Christian}, title = {Adaptive Message Prioritization: How to Prioritize VRU Awareness Messages in a Congested V2X Network}, booktitle = {2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3315-0592-9}, doi = {https://doi.org/10.1109/ITSC58415.2024.10919704}, pages = {423 -- 430}, year = {2025}, language = {en} } @inproceedings{WachtelGranadoTasabatRothmeieretal.2025, author = {Wachtel Granado, Diogo and Tasabat, Sinan and Rothmeier, Thomas and Crist{\´o}foli Duarte Silva, Let{\´i}cia and Huber, Werner}, title = {Exploring Synthetic Radar Data and Deep Learning for Road User Classification in Autonomous Vehicles}, booktitle = {2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3315-0592-9}, doi = {https://doi.org/10.1109/ITSC58415.2024.10919565}, pages = {2021 -- 2026}, year = {2025}, language = {en} } @inproceedings{WachtelGranadoTrevisolRothmeieretal.2025, author = {Wachtel Granado, Diogo and Trevisol, Heitor Derder and Rothmeier, Thomas and Nassu, Bogdan Tomoyuki and Huber, Werner}, title = {Navigating on Adverse Weather: Enhancing LiDAR-Based Detection with the DBSPRY Dataset}, booktitle = {2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3315-0592-9}, doi = {https://doi.org/10.1109/ITSC58415.2024.10920224}, pages = {4034 -- 4039}, year = {2025}, language = {en} } @inproceedings{BruehlShanmuganathanEweckeretal.2025, author = {Br{\"u}hl, Tim and Shanmuganathan, Aravind Kumar and Ewecker, Lukas and Schwager, Robin and Sohn, Tin Stribor and Vaculin, Ondrej and Hohmann, S{\"o}ren}, title = {Consideration of Safety Aspects in a Camera-Aided, Radar-Based Free Space Detection}, booktitle = {2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3315-0592-9}, doi = {https://doi.org/10.1109/ITSC58415.2024.10920194}, pages = {3997 -- 4004}, year = {2025}, language = {en} } @inproceedings{RothmeierDalVescoHogerNassuetal.2025, author = {Rothmeier, Thomas and Dal Vesco Hoger, Mayara and Nassu, Bogdan Tomoyuki and Huber, Werner and Knoll, Alois}, title = {Out of the Box: Weather Augmentation for Enhanced Detection in Bad Visibility Conditions}, booktitle = {2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3315-0592-9}, doi = {https://doi.org/10.1109/ITSC58415.2024.10919529}, pages = {1410 -- 1417}, year = {2025}, language = {en} } @article{BilalPodishettiGrossmannetal.2025, author = {Bilal, M{\"u}henad and Podishetti, Ranadheer and Großmann, Daniel and Bregulla, Markus}, title = {Benchmarking CNN Architectures for Tool Classification: Evaluating CNN Performance on a Unique Dataset Generated by Novel Image Acquisition System}, volume = {13}, journal = {IEEE Access}, publisher = {IEEE}, address = {New York}, issn = {2169-3536}, doi = {https://doi.org/10.1109/ACCESS.2025.3574785}, pages = {96400 -- 96422}, year = {2025}, abstract = {In this study, we introduce the ToolSurface-144 dataset, which is presented here for the first time. It comprises four subsets - Full R, Full S, Top R, and Top S - each containing 144 tool classes captured under varying illumination conditions and fields of view. A newly developed, patented imaging approach was employed to acquire the data. It is compared with conventional diffuse ring illumination to assess its effectiveness in evaluating state-of-the-art convolutional neural networks. This enabled a more targeted investigation of the role of global shape characteristics such as silhouettes versus localized features like the tool face, cutting edges, and delicate geometrical structures under different training strategies. In this study, we evaluate six state-of-the-art convolutional neural networks—AlexNet, DenseNet161, EfficientNet-B0, ResNet152, ResNet50, and VGG16—using three training strategies: fine-tuning, freezing of pre-trained layers, and training from scratch. The results show that EfficientNet-B0 consistently achieved the highest classification accuracy in nearly all experiments and data sets. Especially using the fine-tuning training strategy, the model achieved 99\% accuracy in tool classification. ResNet50 benefited greatly from fine-tuning and freezing, achieving a significant increase in performance compared to training from scratch. In contrast, ResNet152, AlexNet, and VGG16 consistently showed poor classification performance, indicating difficulties regarding learning and generalisation. The results show that diffuse illumination and complete tool views provide the best classification conditions, while restricted image sections with homogeneous illumination negatively affect model performance. Among the evaluated training strategies, fine-tuning proved the most efficient training method for developing CNN models for tool classification.}, language = {en} } @article{SchreiberLinSommeretal.2025, author = {Schreiber, Markus and Lin, Yilei and Sommer, Alessandro and Wassiliadis, Nikolaos and Morales Torricos, Pablo and Rogge, Marcel and Lewerenz, Meinert and Grosu, Cristina and Endisch, Christian and Jossen, Andreas and Lienkamp, Markus}, title = {Apparent vs. true battery aging: Impact of various load characteristics on accelerated aging tests}, volume = {2025}, pages = {116924}, journal = {Journal of Energy Storage}, number = {127}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2352-1538}, doi = {https://doi.org/10.1016/j.est.2025.116924}, year = {2025}, abstract = {Vehicle applications involve highly dynamic and variable operating conditions. These result from changing driving profiles and diverse driving behaviors. To accelerate battery aging tests, experiments are often based on constant load cycles. While efficient, this approach distorts the natural degradation behavior of the cells. This study compares cell aging under real-world and laboratory load conditions. For this purpose, we compare realistic driving profiles measured in a test vehicle in the field with synthetic constant power cycles. Average discharge power and charging sequences are kept identical for comparability. Results show that constant power cycles cause stronger cell aging than dynamic loads. Differential voltage analysis indicates more lithium inventory loss and active material loss at the negative electrode under static loads. Static loading also leads to strong inhomogeneity in the negative electrode and altered charge transfer and diffusion kinetics, as shown by impedance data. After 15 months of rest, the cells recovered up to 52 of lost capacity and 66 of the resistance increase. Impedance assessment and differential voltage analysis confirm the recovery and rehomogenization of the negative electrode. These findings show that conventional accelerated tests are strongly influenced by relaxation and load dynamics. As a result, their applicability to specific use cases, such as automotive applications, is strongly limited . Therefore, andraditional test strategies require reconsideration and redesign.}, language = {en} } @unpublished{HanKefferpuetzBeyerer2025, author = {Han, Longfei and Kefferp{\"u}tz, Klaus and Beyerer, J{\"u}rgen}, title = {Decentralized Fusion of 3D Extended Object Tracking based on a B-Spline Shape Model}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2504.18708}, year = {2025}, abstract = {Extended Object Tracking (EOT) exploits the high resolution of modern sensors for detailed environmental perception. Combined with decentralized fusion, it contributes to a more scalable and robust perception system. This paper investigates the decentralized fusion of 3D EOT using a B-spline curve based model. The spline curve is used to represent the side-view profile, which is then extruded with a width to form a 3D shape. We use covariance intersection (CI) for the decentralized fusion and discuss the challenge of applying it to EOT. We further evaluate the tracking result of the decentralized fusion with simulated and real datasets of traffic scenarios. We show that the CI-based fusion can significantly improve the tracking performance for sensors with unfavorable perspective.}, language = {en} } @unpublished{WanZhaoWiedholzetal.2025, author = {Wan, Lei and Zhao, Jianxin and Wiedholz, Andreas and Bied, Manuel and Martinez de Lucena, Mateus and Jagtap, Abhishek Dinkar and Festag, Andreas and Fr{\"o}hlich, Ant{\^o}nio and Keen, Hannan Ejaz and Vinel, Alexey}, title = {A Systematic Literature Review on Vehicular Collaborative Perception - A Computer Vision Perspective}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2504.04631}, year = {2025}, language = {en} } @unpublished{KalyanasundaramChandraSekaranStaeuberetal.2025, author = {Kalyanasundaram, Abinav and Chandra Sekaran, Karthikeyan and St{\"a}uber, Philipp and Lange, Michael and Utschick, Wolfgang and Botsch, Michael}, title = {Uncertainty-Aware Hybrid Machine Learning in Virtual Sensors for Vehicle Sideslip Angle Estimation}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2504.06105}, year = {2025}, abstract = {Precise vehicle state estimation is crucial for safe and reliable autonomous driving. The number of measurable states and their precision offered by the onboard vehicle sensor system are often constrained by cost. For instance, measuring critical quantities such as the Vehicle Sideslip Angle (VSA) poses significant commercial challenges using current optical sensors. This paper addresses these limitations by focusing on the development of high-performance virtual sensors to enhance vehicle state estimation for active safety. The proposed Uncertainty-Aware Hybrid Learning (UAHL) architecture integrates a machine learning model with vehicle motion models to estimate VSA directly from onboard sensor data. A key aspect of the UAHL architecture is its focus on uncertainty quantification for individual model estimates and hybrid fusion. These mechanisms enable the dynamic weighting of uncertainty-aware predictions from machine learning and vehicle motion models to produce accurate and reliable hybrid VSA estimates. This work also presents a novel dataset named Real-world Vehicle State Estimation Dataset (ReV-StED), comprising synchronized measurements from advanced vehicle dynamic sensors. The experimental results demonstrate the superior performance of the proposed method for VSA estimation, highlighting UAHL as a promising architecture for advancing virtual sensors and enhancing active safety in autonomous vehicles.}, language = {en} } @article{HimmelsBuchnerSchmitzetal.2025, author = {Himmels, Chantal and Buchner, Claudia and Schmitz, Jan and Parduzi, Arben and Riener, Andreas}, title = {Validity of Driver Assistance Systems in Driving Simulators: A Comparative Study of Real-World Driving and Two Simulator Environments}, volume = {41}, journal = {International Journal of Human-Computer Interaction}, number = {23}, publisher = {Taylor \& Francis}, address = {London}, issn = {1044-7318}, doi = {https://doi.org/10.1080/10447318.2025.2495120}, pages = {15197 -- 15214}, year = {2025}, language = {en} } @article{KnollmeyerCaymazerGrossmann2025, author = {Knollmeyer, Simon and Caymazer, Oğuz and Großmann, Daniel}, title = {Document GraphRAG: Knowledge Graph Enhanced Retrieval Augmented Generation for Document Question Answering Within the Manufacturing Domain}, volume = {14}, pages = {2102}, journal = {Electronics}, number = {11}, publisher = {MDPI}, address = {Basel}, issn = {2079-9292}, doi = {https://doi.org/10.3390/electronics14112102}, year = {2025}, abstract = {Retrieval-Augmented Generation (RAG) systems have shown significant potential for domain-specific Question Answering (QA) tasks, although persistent challenges in retrieval precision and context selection continue to hinder their effectiveness. This study introduces Document Graph RAG (GraphRAG), a novel framework that bolsters retrieval robustness and enhances answer generation by incorporating Knowledge Graphs (KGs) built upon a document's intrinsic structure into the RAG pipeline. Through the application of the Design Science Research methodology, we systematically design, implement, and evaluate GraphRAG, leveraging graph-based document structuring and a keyword-based semantic linking mechanism to improve retrieval quality. The evaluation, conducted on well-established datasets including SQuAD, HotpotQA, and a newly developed manufacturing dataset, demonstrates consistent performance gains over a naive RAG baseline across both retrieval and generation metrics. The results indicate that GraphRAG improves Context Relevance metrics, with task-dependent optimizations for chunk size, keyword density, and top-k retrieval further enhancing performance. Notably, multi-hop questions benefit most from GraphRAG's structured retrieval strategy, highlighting its advantages in complex reasoning tasks.}, language = {en} } @article{GresshakeBoschTutunaruetal.2025, author = {Greßhake, Lukas and Bosch, Stephan and Tutunaru, Robin and Holzhammer, Uwe}, title = {What do you mean by '(un-)suitable'? Analysing the diversity of social acceptance towards the deployment of renewable energies in different landscapes}, volume = {20}, journal = {Journal of Land Use Science}, number = {1}, publisher = {Taylor \& Francis}, address = {London}, issn = {1747-4248}, doi = {https://doi.org/10.1080/1747423X.2025.2499280}, pages = {117 -- 150}, year = {2025}, abstract = {Local energy transitions are shaped by diverse stakeholder perspectives on land use, reflecting competing values, knowledge systems, and political views. This study applies the landscape services framework to systematically assess renewable energy (RE) suitability across different landscapes, capturing both ecological and socio-cultural dimensions. Through stakeholder surveys in two German regions and statistical comparative analysis, we reveal how suitability perceptions vary significantly: (1) between stakeholder groups (e.g. conservationists vs. developers), (2) across regions (industrial vs. ecological-cultural contexts), and (3) even within groups sharing similar objectives. Key findings show strong preference for RE development in industrial and agricultural zones ('acceptance corridors') and opposition in ecologically sensitive areas, though with notable regional exceptions. The landscape services approach proves effective in mapping these conflicts and consensus areas, providing actionable insights for spatially sensitive RE planning. Our results underscore the need to complement technical siting criteria with structured assessments of social landscape values to enable just and locally accepted energy transitions.}, language = {en} }