TY - JOUR A1 - Axenie, Cristian A1 - Bauer, Roman A1 - Rodríguez Martínez, María T1 - The Multiple Dimensions of Networks in Cancer: A Perspective JF - Symmetry N2 - This perspective article gathers the latest developments in mathematical and computational oncology tools that exploit network approaches for the mathematical modelling, analysis, and simulation of cancer development and therapy design. It instigates the community to explore new paths and synergies under the umbrella of the Special Issue “Networks in Cancer: From Symmetry Breaking to Targeted Therapy”. The focus of the perspective is to demonstrate how networks can model the physics, analyse the interactions, and predict the evolution of the multiple processes behind tumour-host encounters across multiple scales. From agent-based modelling and mechano-biology to machine learning and predictive modelling, the perspective motivates a methodology well suited to mathematical and computational oncology and suggests approaches that mark a viable path towards adoption in the clinic. UR - https://doi.org/10.3390/sym13091559 KW - mathematical and computational oncology KW - cancer KW - networks KW - mechano-biology KW - machine learning Y1 - 2021 UR - https://doi.org/10.3390/sym13091559 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13053 SN - 2073-8994 VL - 13 IS - 9 PB - MDPI CY - Basel ER - TY - JOUR A1 - Kleiner, Jan A1 - Stuckenberger, Magdalena A1 - Komsiyska, Lidiya A1 - Endisch, Christian T1 - Advanced monitoring and prediction of the thermal state of intelligent battery cells in electric vehicles by physics-based and data-driven modeling JF - Batteries N2 - Novel intelligent battery systems are gaining importance with functional hardware on the cell level. Cell-level hardware allows for advanced battery state monitoring and thermal management, but also leads to additional thermal interactions. In this work, an electro-thermal framework for the modeling of these novel intelligent battery cells is provided. Thereby, a lumped thermal model, as well as a novel neural network, are implemented in the framework as thermal submodels. For the first time, a direct comparison of a physics-based and a data-driven thermal battery model is performed in the same framework. The models are compared in terms of temperature estimation with regard to accuracy. Both models are very well suited to represent the thermal behavior in novel intelligent battery cells. In terms of accuracy and computation time, however, the data-driven neural network approach with a Nonlinear AutoregRessive network with eXogeneous input (NARX) shows slight advantages. Finally, novel applications of temperature prediction in battery electric vehicles are presented and the applicability of the models is illustrated. Thereby, the conventional prediction of the state of power is extended by simultaneous temperature prediction. Additionally, temperature forecasting is used for pre-conditioning by advanced cooling system regulation to enable energy efficiency and fast charging. UR - https://doi.org/10.3390/batteries7020031 KW - lithium-ion battery KW - electro-thermal model KW - smart cell KW - intelligent battery KW - neural network KW - temperature prediction Y1 - 2021 UR - https://doi.org/10.3390/batteries7020031 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13068 SN - 2313-0105 VL - 7 IS - 2 PB - MDPI CY - Basel ER - TY - JOUR A1 - von Sawitzky, Tamara A1 - Grauschopf, Thomas A1 - Riener, Andreas T1 - “Attention! A Door Could Open.”—Introducing Awareness Messages for Cyclists to Safely Evade Potential Hazards JF - Multimodal Technologies and Interaction N2 - Numerous statistics show that cyclists are often involved in road traffic accidents, often with serious outcomes. One potential hazard of cycling, especially in cities, is “dooring”—passing parked vehicles that still have occupants inside. These occupants could open the vehicle door unexpectedly in the cyclist’s path—requiring a quick evasive response by the cyclist to avoid a collision. Dooring can be very poorly anticipated; as a possible solution, we propose in this work a system that notifies the cyclist of opening doors based on a networked intelligent transportation infrastructure. In a user study with a bicycle simulator (N = 24), we examined the effects of three user interface designs compared to a baseline (no notifications) on cycling behavior (speed and lateral position), perceived safety, and ease of use. Awareness messages (either visual message, visual message + auditory icon, or visual + voice message) were displayed on a smart bicycle helmet at different times before passing a parked, still-occupied vehicle. Our participants found the notifications of potential hazards very easy to understand and appealing and felt that the alerts could help them navigate traffic more safely. Those concepts that (additionally) used auditory icons or voice messages were preferred. In addition, the lateral distance increased significantly when a potentially opening door was indicated. In these situations, cyclists were able to safely pass the parked vehicle without braking. In summary, we are convinced that notification systems, such as the one presented here, are an important component for increasing road safety, especially for vulnerable road users. UR - https://doi.org/10.3390/mti6010003 KW - accident prevention KW - awareness message KW - connected traffic KW - cycling KW - head-mounted display KW - lateral position KW - simulation KW - vulnerable road users Y1 - 2021 UR - https://doi.org/10.3390/mti6010003 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13079 SN - 2414-4088 VL - 6 IS - 1 PB - MDPI CY - Basel ER - TY - JOUR A1 - Theiler, Michael A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Float Current Analysis for Fast Calendar Aging Assessment of 18650 Li(NiCoAl)O2/Graphite Cells JF - Batteries N2 - Float currents are steady-state self-discharge currents after a transient phase—caused by anode overhang, polarization, etc.—is accomplished. The float current is measured in this study with a standard test bench for five 18650 cells (Samsung 25R) at potentiostatic conditions while the temperature is changed in 5 K steps from 5 °C to 60 °C. The entire test is performed in about 100 days resulting in 12 measurement points per cell potential for an Arrhenius representation. The float current follows the Arrhenius law with an activation energy of about 60 kJ/mol. The capacity loss measured at reference condition shows a high correlation to the results of float currents analysis. In contrast to classical calendar aging tests, the performed float current analysis enables determining the aging rate with high precision down to at least 10 °C. Returning from higher temperatures to 30 °C reference temperature shows reducing float currents at 30 °C for increasing temperature steps that may originate from an hysteresis effect that has to be investigated in future publications. UR - https://doi.org/10.3390/batteries7020022 KW - 18650 KW - NCA KW - graphite KW - float current KW - self-discharge KW - calendar aging KW - Arrhenius Y1 - 2021 UR - https://doi.org/10.3390/batteries7020022 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13081 SN - 2313-0105 VL - 7 IS - 2 PB - MDPI CY - Basel ER - TY - JOUR A1 - Mayer, Sebastian A1 - Classen, Tobias A1 - Endisch, Christian T1 - Modular production control using deep reinforcement learning: proximal policy optimization JF - Journal of Intelligent Manufacturing N2 - EU regulations on CO2 limits and the trend of individualization are pushing the automotive industry towards greater flexibility and robustness in production. One approach to address these challenges is modular production, where workstations are decoupled by automated guided vehicles, requiring new control concepts. Modular production control aims at throughput-optimal coordination of products, workstations, and vehicles. For this np-hard problem, conventional control approaches lack in computing efficiency, do not find optimal solutions, or are not generalizable. In contrast, Deep Reinforcement Learning offers powerful and generalizable algorithms, able to deal with varying environments and high complexity. One of these algorithms is Proximal Policy Optimization, which is used in this article to address modular production control. Experiments in several modular production control settings demonstrate stable, reliable, optimal, and generalizable learning behavior. The agent successfully adapts its strategies with respect to the given problem configuration. We explain how to get to this learning behavior, especially focusing on the agent’s action, state, and reward design. UR - https://doi.org/10.1007/s10845-021-01778-z KW - modular production KW - production control KW - production scheduling KW - deep reinforcement learning KW - proximal policy optimization KW - automotive industry Y1 - 2021 UR - https://doi.org/10.1007/s10845-021-01778-z UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13092 SN - 1572-8145 VL - 32 IS - 8 SP - 2335 EP - 2351 PB - Springer Nature CY - Cham ER - TY - JOUR A1 - Handwerker, Michael A1 - Kessler, Jörg A1 - Marzbani, Hormoz T1 - Review of mechanical properties of and optimisation methods for continuous fibre‑reinforced thermoplastic parts manufactured by fused deposition modelling JF - Progress in Additive Manufacturing N2 - A new way of manufacturing continuous fibre-reinforced plastics is the embedding of fibres in the filament of a 3D printer. This method could be used in manufacturing composite materials with a thermoplastic matrix containing glass, Kevlar and carbon fibres. This paper provides an overview of research on the mechanical and physical properties of these parts as well as optimisation approaches of additively manufactured thermoplastics. Furthermore, applicable testing and analysis methods and their corresponding standards are included. Several studies, which represent the current state of the art, are reviewed in detail for the analysis of the mechanical performance of different fibre reinforcements. In addition, an overview of different optimisation approaches is given. The ultimate tensile strength of Kevlar and glass fibre-reinforced parts are similar to those of common Aluminium alloys whereas the carbon fibre reinforced parts outperform their aluminium counterparts. Major performance limitations include a poor adhesion between layers as well as a high air void ratio. UR - https://doi.org/10.1007/s40964-021-00187-1 KW - fused filament fabrication KW - fused deposition modelling KW - continuous fibre KW - thermoplastics Y1 - 2021 UR - https://doi.org/10.1007/s40964-021-00187-1 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13103 SN - 2363-9520 VL - 6 IS - 4 SP - 663 EP - 677 PB - Springer Nature CY - Cham ER - TY - JOUR A1 - Mathias, Selvine George A1 - Großmann, Daniel A1 - Bhanja, Tapanta T1 - Exploring distance based approaches for reducing sensor data in defect related prognosis JF - Procedia Computer Science N2 - Vibration data consists of batches of time series which if accumulated over a period of time is a huge collection of numeric data. Reducing such data for use in deep learning models for computational effciency is a challenge. Combinatorial and discrete approaches, on the other hand, is not an extensively explored area when it comes to datasets. This paper aims to identify feature reduction techniques based on discrete approaches such as euclidean distance using dot products on vibration data samples from accelerometers fitted on bearings. In this limited experimentation, the procured dataset by this approach is considerably smaller in size as compared to the actual complete data, and with comparable results in prediction models, it can be used as a smaller representation of a sensor timeline. The results based on different models show that such reductions can be considered in building IoT applications in industries based on sensors. UR - https://doi.org/10.1016/j.procs.2021.03.076 KW - sensors KW - data KW - reduced distance KW - machine learning KW - accuracy scores Y1 - 2021 UR - https://doi.org/10.1016/j.procs.2021.03.076 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13111 SN - 1877-0509 VL - 2021 IS - 184 SP - 614 EP - 621 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Sequeira, Gerald Joy A1 - Patel, Akshay A1 - Afraj, Shahabaz A1 - Lugner, Robert A1 - Brandmeier, Thomas T1 - FEM-based methodology for crash severity estimation in frontal crash scenarios JF - IOP Conference Series: Materials Science and Engineering N2 - With the technological development of forward-looking sensors, researchers are exploring their use not only for advanced driver assistance systems but also to gain important pre-crash information. Based on this pre-crash information, if the occupant motion inside the vehicle structure can be predicted for the oncoming crash scenario, then an optimal restraint strategy can be planned before the crash. This paper introduces a two-step FEM simulation based methodology for predicting the occupant severity in head-on crash scenarios. In the first step, we simulate the vehicle level model with different impact positions and relative approach angles. The results of these simulations, linear velocities in the longitudinal and lateral direction and angular velocities (roll, pitch, and yaw) during in-crash phase are the loading conditions for next simulation step (occupant level). This step simulates the motion of the driver in different crash scenarios. In this paper, we investigate the head, neck, and chest injury risks from vehicle-to-vehicle crash both traveling at 50 kilometers per hour. Prediction of the head injury criterion, identifying the cases where additional deployment of side-airbags and discussion of injury criteria with contour plots are the main outcome of this paper. UR - https://doi.org/10.1088/1757-899X/831/1/012019 Y1 - 2020 UR - https://doi.org/10.1088/1757-899X/831/1/012019 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13159 SN - 1757-899X SN - 1757-8981 VL - 2020 IS - 831 PB - IOP CY - Bristol ER - TY - JOUR A1 - Weigl, Klemens A1 - Ponocny, Ivo T1 - Group sequential designs applied in psychological research JF - Methodology: European Journal of Research Methods for the Behavioral and Social Sciences N2 - Psychological research is confronted with ever-increasing demands to save resources such as time and money while assuring high ethical standards. In medical and pharmaceutical research, group sequential designs have fundamentally changed traditional statistical testing approaches featuring only one analysis at the end of a single-stage study. They enable early stopping at an interim stage, after a group of observations, for efficacy or futility in case of an overwhelmingly large or small effect, respectively. Otherwise, the trial is continued to the next stage. On average over many studies time and money are saved and more ethical trials are facilitated by diminishing the risk of patients' exposure to inferior treatments. We provide an easy-to-use tutorial for psychological research replete with easily understandable figures highlighting the core idea of different group sequential designs, a workflow chart, an empirical real-world data set, and the annotated R code. Finally, we demonstrate the application of early stopping for efficacy. UR - https://doi.org/10.5964/meth.2811 KW - group sequential designs KW - interim analyses KW - workflow chart KW - R Code KW - tutorial Y1 - 2020 UR - https://doi.org/10.5964/meth.2811 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13190 SN - 1614-2241 VL - 16 IS - 1 SP - 75 EP - 91 PB - PsychOpen CY - Trier ER - TY - JOUR A1 - Mathias, Selvine George A1 - Schmied, Sebastian A1 - Großmann, Daniel T1 - An investigation on database connections in OPC UA applications JF - Procedia Computer Science N2 - Open Platform Communications - Unified Architecture (OPC UA) as a communication protocol has been one of the front running IoT enablers in recent years. Many use cases in manufacturing domains demonstrate the vast inter-operability and cross-platform connectivity strengths of OPC UA. However, to consolidate its position in the IoT world, OPC UA needs to be able to bridge certain gaps, like interconnections across multiple database engines over different networks. This paper aims to investigate aggregation dynamics of OPC UA consisting of multiple database servers from a specific environment such as manufacturing. Prevailing databases over restricted networks such as production floors cannot be accessed by respective clients outside the system. In these cases, OPC UA services can provide an a selective but imperative view of data from these databases to the clients. The investigations in this paper are demonstrated with two different implementations of databases related to manufacturing with OPC UA. These applications show that using OPC UA as a means of connection and distribution of information from databases can be an effective solution to a common data view of all connections not necessarily of factory floor network. UR - https://doi.org/10.1016/j.procs.2020.03.132 KW - OPC UA KW - databases KW - implementations KW - SQL server KW - clients Y1 - 2020 UR - https://doi.org/10.1016/j.procs.2020.03.132 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-12349 SN - 1877-0509 VL - 2020 IS - 170 SP - 602 EP - 609 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Schmid, Maximilian A1 - Bhogaraju, Sri Krishna A1 - Liu, E A1 - Elger, Gordon T1 - Comparison of Nondestructive Testing Methods for Solder, Sinter, and Adhesive Interconnects in Power and Opto-Electronics JF - Applied Sciences N2 - Reliability is one of the major requirements for power and opto-electronic devices across all segments. High operation temperature and/or high thermomechanical stress cause defects and degradation of materials and interconnects, which may lead to malfunctions with costly or even life-threatening consequences. To avoid or at least reduce failures, nondestructive testing (NDT) methods are common within development and production of power and opto-electronics. Currently, the dominating NDT methods are X-ray, scanning acoustic microscopy (SAM), and transient thermal analysis (TTA). However, they have different strengths and weaknesses with respect to materials and mechanical designs. This paper compares these NDT methods for different interconnect technologies, i.e., reflow soldering, adhesive, and sintered interconnection. While X-ray provided adequate results for soldered interfaces, inspection of adhesives and sintered interconnects was not possible. With SAM, evaluation of adhesives and sintered interconnects was also feasible, but quality depended strongly on the sample under test. TTA enabled sufficiently detailed results for all the interconnect applications. Automated TTA equipment, as the in-house developed tester used within this investigation, enabled measurement times compatible with SAM and X-ray. In the investigations, all methods revealed their pros and cons, and their selection has to depend on the sample under tests and the required analysis depth and data details. In the paper, guidelines are formulated for an appropriate decision on the NDT method depending on sample and requirements. UR - https://doi.org/10.3390/app10238516 KW - reliability KW - nondestructive testing KW - power electronics KW - X-ray KW - scanning acoustic microscopy KW - transient thermal analysis KW - TTA KW - sintering KW - LED KW - MOSFET Y1 - 2020 UR - https://doi.org/10.3390/app10238516 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-12518 SN - 2076-3417 VL - 10 IS - 23 PB - MDPI CY - Basel ER - TY - CHAP A1 - Schmid, Kyrill A1 - Belzner, Lenz A1 - Linnhoff-Popien, Claudia T1 - Learning to penalize other learning agents T2 - Proceedings of the Artificial Life Conference 2021 UR - https://doi.org/10.1162/isal_a_00369 Y1 - 2021 UR - https://doi.org/10.1162/isal_a_00369 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-12966 VL - 2021 PB - MIT Press CY - Cambridge ER - TY - INPR A1 - Flohr, Lukas A. A1 - Schuß, Martina A1 - Wallach, Dieter P. A1 - Krüger, Antonio A1 - Riener, Andreas T1 - Designing for Passengers’ Information Needs on Fellow Travelers: A Comparison of Day and Night Rides in Shared Automated Vehicles N2 - Shared automated mobility-on-demand promises efficient, sustainable, and flexible transportation. Nevertheless, security concerns, resilience, and their mutual influence - especially at night - will likely be the most critical barriers to public adoption since passengers have to share rides with strangers without a human driver on board. As related work points out that information about fellow travelers might mitigate passengers' concerns, we designed two user interface variants to investigate the role of this information in an exploratory within-subjects user study (N = 24). Participants experienced four automated day and night rides with varying personal information about co-passengers in a simulated environment. The results of the mixed-method study indicate that having information about other passengers (e.g., photo, gender, and name) positively affects user experience at night. In contrast, it is less necessary during the day. Considering participants' simultaneously raised privacy demands poses a substantial challenge for resilient system design. UR - https://doi.org/10.48550/arXiv.2308.02616 Y1 - 2023 UR - https://doi.org/10.48550/arXiv.2308.02616 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59892 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Song, Rui A1 - Liu, Dai A1 - Chen, Dave Zhenyu A1 - Festag, Andreas A1 - Trinitis, Carsten A1 - Schulz, Martin A1 - Knoll, Alois T1 - Federated Learning via Decentralized Dataset Distillation in Resource Constrained Edge Environments N2 - In federated learning, all networked clients contribute to the model training cooperatively. However, with model sizes increasing, even sharing the trained partial models often leads to severe communication bottlenecks in underlying networks, especially when communicated iteratively. In this paper, we introduce a federated learning framework FedD3 requiring only one-shot communication by integrating dataset distillation instances. Instead of sharing model updates in other federated learning approaches, FedD3 allows the connected clients to distill the local datasets independently, and then aggregates those decentralized distilled datasets (e.g. a few unrecognizable images) from networks for model training. Our experimental results show that FedD3 significantly outperforms other federated learning frameworks in terms of needed communication volumes, while it provides the additional benefit to be able to balance the trade-off between accuracy and communication cost, depending on usage scenario or target dataset. For instance, for training an AlexNet model on CIFAR-10 with 10 clients under non-independent and identically distributed (Non-IID) setting, FedD3 can either increase the accuracy by over 71% with a similar communication volume, or save 98% of communication volume, while reaching the same accuracy, compared to other one-shot federated learning approaches. UR - https://doi.org/10.48550/arXiv.2208.11311 Y1 - 2022 UR - https://doi.org/10.48550/arXiv.2208.11311 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60054 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Novicki Neto, Leonardo A1 - Reway, Fabio A1 - Poledna, Yuri A1 - Funk Drechsler, Maikol A1 - Parente Ribeiro, Eduardo A1 - Huber, Werner A1 - Icking, Christian T1 - TWICE Dataset: Digital Twin of Test Scenarios in a Controlled Environment N2 - Ensuring the safe and reliable operation of autonomous vehicles under adverse weather remains a significant challenge. To address this, we have developed a comprehensive dataset composed of sensor data acquired in a real test track and reproduced in the laboratory for the same test scenarios. The provided dataset includes camera, radar, LiDAR, inertial measurement unit (IMU), and GPS data recorded under adverse weather conditions (rainy, night-time, and snowy conditions). We recorded test scenarios using objects of interest such as car, cyclist, truck and pedestrian -- some of which are inspired by EURONCAP (European New Car Assessment Programme). The sensor data generated in the laboratory is acquired by the execution of simulation-based tests in hardware-in-the-loop environment with the digital twin of each real test scenario. The dataset contains more than 2 hours of recording, which totals more than 280GB of data. Therefore, it is a valuable resource for researchers in the field of autonomous vehicles to test and improve their algorithms in adverse weather conditions, as well as explore the simulation-to-reality gap. UR - https://doi.org/10.48550/arXiv.2310.03895 Y1 - 2023 UR - https://doi.org/10.48550/arXiv.2310.03895 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59887 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Fidelis, Eduardo A1 - Reway, Fabio A1 - Ribeiro, Herick Y. S. A1 - Campos, Pietro A1 - Huber, Werner A1 - Icking, Christian A1 - Faria, Lester A1 - Schön, Torsten T1 - Generation of Realistic Synthetic Raw Radar Data for Automated Driving Applications using Generative Adversarial Networks N2 - The main approaches for simulating FMCW radar are based on ray tracing, which is usually computationally intensive and do not account for background noise. This work proposes a faster method for FMCW radar simulation capable of generating synthetic raw radar data using generative adversarial networks (GAN). The code and pre-trained weights are open-source and available on GitHub. This method generates 16 simultaneous chirps, which allows the generated data to be used for the further development of algorithms for processing radar data (filtering and clustering). This can increase the potential for data augmentation, e.g., by generating data in non-existent or safety-critical scenarios that are not reproducible in real life. In this work, the GAN was trained with radar measurements of a motorcycle and used to generate synthetic raw radar data of a motorcycle traveling in a straight line. For generating this data, the distance of the motorcycle and Gaussian noise are used as input to the neural network. The synthetic generated radar chirps were evaluated using the Frechet Inception Distance (FID). Then, the Range-Azimuth (RA) map is calculated twice: first, based on synthetic data using this GAN and, second, based on real data. Based on these RA maps, an algorithm with adaptive threshold and edge detection is used for object detection. The results have shown that the data is realistic in terms of coherent radar reflections of the motorcycle and background noise based on the comparison of chirps, the RA maps and the object detection results. Thus, the proposed method in this work has shown to minimize the simulation-to-reality gap for the generation of radar data. UR - https://doi.org/10.48550/arXiv.2308.02632 Y1 - 2023 UR - https://doi.org/10.48550/arXiv.2308.02632 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59872 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Han, Longfei A1 - Kefferpütz, Klaus A1 - Beyerer, Jürgen T1 - Decentralized Fusion of 3D Extended Object Tracking based on a B-Spline Shape Model N2 - 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. UR - https://doi.org/10.48550/arXiv.2504.18708 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2504.18708 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59648 PB - arXiv CY - Ithaca ER - TY - JOUR A1 - Hahn, Christoph A1 - Bednarz, Martin T1 - Economics of Polymer Electrolyte Membrane Fuel Cells JF - Tehnički glasnik N2 - Hydrogen is considered a key component of the renewable energy transition for the 21st century, with potential applications using fuel cells in the transportation sector, decentralized heating systems, and energy storage. However, the conversion from fossil fuels to hydrogen implies comprehensive research to address technological and socio economic challenges, enabling its widespread adoption. This paper discusses the economics of fuel cells. A cost analysis of the polymer electrolyte membrane fuel cells (PEMFC) is performed, and current market data and developments are presented. UR - https://doi.org/10.31803/tg-20250303145130 Y1 - 2025 UR - https://doi.org/10.31803/tg-20250303145130 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59496 SN - 1848-5588 VL - 19 IS - si1 SP - 124 EP - 129 PB - University North CY - Koprivnica ER - TY - JOUR A1 - Brummer, Alexander A1 - German, Reinhard A1 - Djanatliev, Anatoli T1 - Methodology and Performance Assessment of Three-Dimensional Vehicular Ad-Hoc Network Simulation JF - IEEE Access N2 - Packet-based simulation is a key tool for the research and development of Vehicular Ad-hoc Networks (VANETs). Over the last decade, many models throughout the communication stack have been presented, which have increased the degree of realism that can be achieved with popular simulation frameworks. Nevertheless, the three-dimensional aspects of many real-world traffic situations barely find consideration. In this paper, we present a holistic approach to simulate large-scale three-dimensional VANET scenarios. We briefly summarize our previously presented models covering different aspects of communication in 3D scenarios, including an environmental diffraction model, an n-ray ground interference model, and the consideration of multi-floor communication. We then describe the principle of a model selector, which applies the appropriate models depending on the environment of the currently transmitted packet. Subsequently, we use the outlined methodology implemented in our Veins 3D framework to simulate a large urban reference scenario. The results differ significantly from comparable 2D simulations, demonstrating the necessity of three-dimensional considerations. However, they also show strongly increased execution times. Therefore, we further suggest different approaches to improve the simulation performance. Based on these optimizations, simulation durations in the same order of magnitude as a comparable 2D simulation can be achieved. UR - https://doi.org/10.1109/ACCESS.2023.3264668 Y1 - 2023 UR - https://doi.org/10.1109/ACCESS.2023.3264668 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59810 SN - 2169-3536 VL - 11 SP - 36349 EP - 36364 PB - IEEE CY - New York ER - TY - JOUR A1 - Morales Torricos, Pablo A1 - Berg, Sascha A1 - Figgemeier, Egbert A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - The important role of lithiation-induced pressure change on apparent aging of lithium-ion batteries during accelerated cyclic aging tests JF - Journal of Energy Storage N2 - 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. UR - https://doi.org/10.1016/j.est.2025.117323 Y1 - 2025 UR - https://doi.org/10.1016/j.est.2025.117323 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60173 SN - 2352-1538 VL - 2025 IS - 131, Part A PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Behret, Valentino A1 - Kushtanova, Regina A1 - Fadl, Islam A1 - Weber, Simon A1 - Helmer, Thomas A1 - Palme, Frank ED - Bashford-Rogers, Thomas ED - Meneveaux, Daniel ED - Ammi, Mehdi ED - Ziat, Mounia ED - Jänicke, Stefan ED - Purchase, Helen ED - Radeva, Petia ED - Furnari, Antonino ED - Bouatouch, Kadi ED - Sousa, A. Augusto T1 - Sensor Calibration and Data Analysis of the MuFoRa Dataset T2 - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - (Volume 2) N2 - Autonomous driving sensors face significant challenges under adverse weather conditions such as fog and rain, which can seriously degrade their performance and reliability. Existing datasets often lack the reproducible and measurable data needed to adequately quantify these effects. To address this gap, a new multimodal dataset (MuFoRa) has been collected under controlled adverse weather conditions at the CARISSMA facility, using a stereo camera and two solid-state LiDAR sensors. This dataset is used to quantitatively assess sensor degradation by measuring the entropy for images and the number of inliers for point clouds on a spherical target. These metrics are used to evaluate the impact on performance under varying conditions of fog (5 to 150 m visibility) and rain (20 to 100 mm/h intensity) at different distances (5 to 50 m). Additionally, two calibration target detection approaches - Deep-learning and Hough-based - are evaluated to achieve accurate sensor alignment. The contributions include the introduction of a new dataset focused on fog and rain, the evaluation of sensor degradation, and an improved calibration approach. This dataset is intended to support the development of more robust sensor fusion and object detection algorithms for autonomous driving. UR - https://doi.org/10.5220/0013310400003912 Y1 - 2025 UR - https://doi.org/10.5220/0013310400003912 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58088 SN - 978-989-758-728-3 SP - 622 EP - 631 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Kedilioglu, Oguz A1 - Nova, Tasnim Tabassum A1 - Landesberger, Martin A1 - Wang, Lijiu A1 - Hofmann, Michael A1 - Franke, Jörg A1 - Reitelshöfer, Sebastian ED - Bashford-Rogers, Thomas ED - Meneveaux, Daniel ED - Ammi, Mehdi ED - Ziat, Mounia ED - Jänicke, Stefan ED - Purchase, Helen ED - Radeva, Petia ED - Furnari, Antonino ED - Bouatouch, Kadi ED - Sousa, A. Augusto T1 - PrIcosa: High-Precision 3D Camera Calibration with Non-Overlapping Field of Views T2 - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - (Volume 2) N2 - Multi-camera systems are being used more and more frequently, from autonomous mobile robots to intelligent visual servoing cells. Determining the pose of the cameras to each other very accurately is essential for many applications. However, choosing the most suitable calibration object geometry and utilizing it as effectively as possible still remains challenging. Disadvantageous geometries provide only subpar datasets, increasing the need for a larger dataset and decreasing the accuracy of the calibration results. Moreover, an unrefined calibration method can lead to worse accuracies even with a good dataset. Here, we introduce a probabilistic method to increase the accuracy of 3D camera calibration. Furthermore, we analyze the effects of the calibration object geometry on the data properties and the resulting calibration accuracy for the geometries cube and icosahedron. The source code for this project is available at GitHub (Nova, 2024). UR - https://doi.org/10.5220/0013088700003912 Y1 - 2025 UR - https://doi.org/10.5220/0013088700003912 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58120 SN - 978-989-758-728-3 SP - 801 EP - 809 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Knollmeyer, Simon A1 - Caymazer, Oğuz A1 - Koval, Leonid A1 - Akmal, Muhammad Uzair A1 - Asif, Saara A1 - Mathias, Selvine George A1 - Großmann, Daniel ED - Gruenwald, Le ED - Masciari, Elio ED - Bernardino, Jorge T1 - Benchmarking of Retrieval Augmented Generation: A Comprehensive Systematic Literature Review on Evaluation Dimensions, Evaluation Metrics and Datasets T2 - Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2024) - Volume 3 N2 - Despite the rapid advancements in the field of Large Language Models (LLM), traditional benchmarks have proven to be inadequate for assessing the performance of Retrieval Augmented Generation (RAG) systems. Therefore, this paper presents a comprehensive systematic literature review of evaluation dimensions, metrics, and datasets for RAG systems. This review identifies key evaluation dimensions such as context relevance, faithfulness, answer relevance, correctness, and citation quality. For each evaluation dimension, several metrics and evaluators are proposed on how to assess them. This paper synthesizes the findings from 12 relevant papers and presents a concept matrix that categorizes each evaluation approach. The results provide a foundation for the development of robust evaluation frameworks and suitable datasets that are essential for the effective implementation and deployment of RAG systems in real-world applications. UR - https://doi.org/10.5220/0013065700003838 Y1 - 2024 UR - https://doi.org/10.5220/0013065700003838 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58342 SN - 978-989-758-716-0 SP - 137 EP - 148 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Fadl, Islam A1 - Schön, Torsten A1 - Behret, Valentino A1 - Brandmeier, Thomas A1 - Palme, Frank A1 - Helmer, Thomas ED - Bashford-Rogers, Thomas ED - Meneveaux, Daniel ED - Ammi, Mehdi ED - Ziat, Mounia ED - Jänicke, Stefan ED - Purchase, Helen ED - Radeva, Petia ED - Furnari, Antonino ED - Bouatouch, Kadi ED - Sousa, A. Augusto T1 - Environment Setup and Model Benchmark of the MuFoRa Dataset T2 - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - (Volume 3) N2 - Adverse meteorological conditions, particularly fog and rain, present significant challenges to computer vision algorithms and autonomous systems. This work presents MuFoRa a novel, controllable, and measured multimodal dataset recorded at CARISSMA’s indoor test facility, specifically designed to assess perceptual difficulties in foggy and rainy environments. The dataset bridges research gap in the public benchmarking datasets, where quantifiable weather parameters are lacking. The proposed dataset comprises synchronized data from two sensor modalities: RGB stereo cameras and LiDAR sensors, captured under varying intensities of fog and rain. The dataset incorporates synchronized meteorological annotations, such as visibility through fog and precipitation levels of rain, and the study contributes a detailed explanation of the diverse weather effects observed during data collection in the methods section. The dataset’s utility is demonstrated through a baseline evaluation example, asse ssing the performance degradation of state-of-the-art YOLO11 and DETR 2D object detection algorithms under controlled and quantifiable adverse weather conditions. The public release of the dataset (https://doi.org/10.5281/zenodo.14175611) facilitates various benchmarking and quantitative assessments of advanced multimodal computer vision and deep learning models under the challenging conditions of fog and rain. UR - https://doi.org/10.5220/0013307900003912 Y1 - 2025 UR - https://doi.org/10.5220/0013307900003912 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58070 SN - 978-989-758-728-3 SP - 729 EP - 737 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Bayerl, Dominik A1 - Hutzelmann, Thomas A1 - Hof, Hans-Joachim T1 - Efficient Cross-Architecture Binary Function Embeddings through Knowledge Distillation T2 - Proceedings of the 11th ACM Cyber-Physical System Security Workshop N2 - Deep learning has recently been shown to be effective in various tasks related to static binary analysis. One important analysis task is the binary function similarity problem: Given the binary code of two functions compiled with different compilers, different settings, and different processor architectures, the goal is to decide whether the functions are semantically equivalent (i.e. "similar") or not. This problem has numerous applications for embedded systems, for example plagiarism detection, validation of compliance restrictions with usable software licenses, more efficient reverse engineering of existing binary codebases, or vulnerability scanning by detecting known vulnerable functions. In this paper, we propose a novel training scheme for the popular transformer neural network architecture to learn function embeddings directly from instruction listings. Unlike existing approaches, our solution explicitly considers the cross-architecture scenario: we propose a training method to adapt the model to different instruction set architectures (ISA) without having to train a new model from scratch, which allows the model to also be used efficiently for embedded systems, where there are a variety of different processor architectures. We show that our solution achieves a similarity classification accuracy of 89.6% on a dataset consisting of several real-world open source software projects. Finally, we conduct extensive experiments to demonstrate the effectiveness of knowledge distillation in increasing the computational efficiency of the embedding model. We demonstrate a reduction in the number of parameters from 87M to 23M, while still maintaining a classification accuracy of 87.8%. Our code and artifacts are available as open source. UR - https://doi.org/10.1145/3709017.3737709 Y1 - 2025 UR - https://doi.org/10.1145/3709017.3737709 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-61584 SN - 979-8-4007-1413-9 SP - 43 EP - 51 PB - ACM CY - New York ER - TY - JOUR A1 - Vogt, Anna A1 - Schmidt, Philipp Heiner A1 - Mayer, Sebastian A1 - Stark, Rainer T1 - Production in the loop: the interoperability of digital twins of the product and the production system JF - Procedia CIRP N2 - The Internet of Things (IoT) era facilitates new possibilities at the interface between the lifecycle of the product and the manufacturing disciplines allowing to add value and meet growing legal requirements. This work presents use cases from the automobile industry which are analyzed in order to derive requirements for data exchange. The analysis of the use cases shows clearly that we need to focus on the instance level for this purpose. This means that both, a specific unit of the product and the production system, must be considered. As a solution approach, a communication loop is proposed bringing the Digital Twin concept in a new field of usage. The key aspect of the proposed solution is the direct intercommunication between the Digital Twins of the product being produced as a Cyber-Physical System (CPS) and the production resources as Cyber-Physical Production Systems (CPPS). This solution enables the aggregation of production-related data within the products Digital Twin and therefore promotes maximal transparency throughout engineering disciplines, phases of the product lifecycle and the whole supply chain. UR - https://doi.org/10.1016/j.procir.2021.03.077 KW - digital twin KW - digital shadow KW - digital twin lifecycle KW - cyber-physical system KW - intelligent production systems KW - smart production Y1 - 2021 UR - https://doi.org/10.1016/j.procir.2021.03.077 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13120 SN - 2212-8271 VL - 2021 IS - 99 SP - 561 EP - 566 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Jauernig, Johanna A1 - Uhl, Matthias A1 - Pies, Ingo T1 - When Goliath sells to David: explaining price gouging perceptions through power JF - Public Choice N2 - AbstractExternal shocks (e.g., due to a pandemic) may lead to price jumps in the short term. Rather than being read as a signal of increased scarcity, the resulting “price gouging” is often ascribed to sellers’ selfish exploitation of the crisis. In our experimental study, we investigate the drivers of fairness perceptions regarding voluntary transactions in situations of increased scarcity and explore how they pertain to the economic policy debate on price gouging restrictions. Departing from previous research, our results show that perceptions of power, not of the seller as the profiteer (mercantilism), drive fairness perceptions. The more powerful a transaction partner is assumed to be, the less the respective transaction is regarded as fair. In line with the literature, we also find that fairness perceptions are correlated with zero-sum thinking (i.e., a denial of the mutuality of benefits implied by voluntary transactions). Our study helps to better understand why some market regulations appear attractive despite suboptimal outcomes, thus revealing a mixing of the micro and the macro cosmos, against which Hayek warned. By casting a light on the psychological mechanisms behind attitudes toward markets, we aim to improve the assessment of legitimacy issues and contribute to explaining (and overcoming) the moral paradox of modernity. UR - https://doi.org/10.1007/s11127-024-01191-z Y1 - 2024 UR - https://doi.org/10.1007/s11127-024-01191-z UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-49996 SN - 1573-7101 SN - 0048-5829 VL - 203 IS - 1-2 SP - 139 EP - 155 PB - Springer CY - New York ER - TY - JOUR A1 - Jauernig, Johanna A1 - Uhl, Matthias A1 - Walkowitz, Gari T1 - People prefer moral discretion to algorithms BT - algorithm aversion beyond intransparency JF - Philosophy & Technology N2 - We explore aversion to the use of algorithms in moral decision-making. So far, this aversion has been explained mainly by the fear of opaque decisions that are potentially biased. Using incentivized experiments, we study which role the desire for human discretion in moral decision-making plays. This seems justified in light of evidence suggesting that people might not doubt the quality of algorithmic decisions, but still reject them. In our first study, we found that people prefer humans with decision-making discretion to algorithms that rigidly apply exogenously given human-created fairness principles to specific cases. In the second study, we found that people do not prefer humans to algorithms because they appreciate flesh-and-blood decision-makers per se, but because they appreciate humans’ freedom to transcend fairness principles at will. Our results contribute to a deeper understanding of algorithm aversion. They indicate that emphasizing the transparency of algorithms that clearly follow fairness principles might not be the only element for fostering societal algorithm acceptance and suggest reconsidering certain features of the decision-making process. UR - https://doi.org/10.1007/s13347-021-00495-y KW - algorithm aversion KW - artificial intelligence KW - moral discretion KW - behavioral ethics Y1 - 2022 UR - https://doi.org/10.1007/s13347-021-00495-y UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-23207 SN - 2210-5441 SN - 2210-5433 VL - 35 IS - 1 PB - Springer Nature CY - Cham ER - TY - JOUR A1 - Feier, Till A1 - Gogoll, Jan A1 - Uhl, Matthias T1 - Hiding Behind Machines: Artificial Agents May Help to Evade Punishment JF - Science and Engineering Ethics N2 - The transfer of tasks with sometimes far-reaching implications to autonomous systems raises a number of ethical questions. In addition to fundamental questions about the moral agency of these systems, behavioral issues arise. We investigate the empirically accessible question of whether the imposition of harm by an agent is systematically judged differently when the agent is artificial and not human. The results of a laboratory experiment suggest that decision-makers can actually avoid punishment more easily by delegating to machines than by delegating to other people. Our results imply that the availability of artificial agents could provide stronger incentives for decision-makers to delegate sensitive decisions. UR - https://doi.org/10.1007/s11948-022-00372-7 KW - automation KW - ethics KW - experiment KW - responsibility KW - algorithm Y1 - 2022 UR - https://doi.org/10.1007/s11948-022-00372-7 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-23155 SN - 1471-5546 SN - 1353-3452 VL - 28 IS - 2 PB - Springer Nature CY - Cham ER - TY - JOUR A1 - Gogoll, Jan A1 - Uhl, Matthias T1 - Leviathan for sale BT - the fallacy of trusting in people instead of institutions JF - European Journal of Political Economy N2 - We experimentally test Hume’s hypothesis that people underappreciate the value of cooperation-enforcing institutions in impersonal interactions by relying on personal trust. Subjects played a game in groups of two or six. Each subject could defect at any time, leaving the others with zero payoff by unilaterally appropriating an amount of money that grew over a period of 5 ​minutes. All players received the maximum payoff only if nobody defected. Before the game, subjects could purchase a cooperation-enforcing institution. Their willingness to pay for this institution fell short of the loss caused by failed cooperation under institution-free play. This was even true for the best-off subject in an institution-free society. In the absence of learning, people indeed fell prey to the atavistic fallacy of trusting in people instead of institutions. Understanding this bias might help people in complex societies to acknowledge the value of institutions intellectually. UR - https://doi.org/10.1016/j.ejpoleco.2020.101898 KW - institutions KW - problem of two worlds KW - artificial virtues KW - trust KW - impersonal interactions KW - experiment Y1 - 2020 UR - https://doi.org/10.1016/j.ejpoleco.2020.101898 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-16350 SN - 0176-2680 VL - 2020 IS - 63 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Jauernig, Johanna A1 - Uhl, Matthias A1 - Waldhof, Gabi T1 - Genetically Engineered Foods and Moral Absolutism: A Representative Study from Germany JF - Science and Engineering Ethics N2 - There is an ongoing debate about genetic engineering (GE) in food production. Supporters argue that it makes crops more resilient to stresses, such as drought or pests, and should be considered by researchers as a technology to address issues of global food security, whereas opponents put forward that GE crops serve only the economic interests of transnational agrifood-firms and have not yet delivered on their promises to address food shortage and nutrient supply. To address discourse failure regarding the GE debate, research needs to understand better what drives the divergent positions and which moral attitudes fuel the mental models of GE supporters and opponents. Hence, this study investigates moral attitudes regarding GE opposition and support in Germany. Results show that GE opponents are significantly more absolutist than supporters and significantly less likely to hold outcome-based views. Furthermore, GE opponents are more willing to donate for preventing GE admission than supporters are willing to donate for promoting GE admission. Our results shed light on why the divide between opponents and supporters in the German GE debate could remain stark and stable for so long. UR - https://doi.org/10.1007/s11948-023-00454-0 KW - Genetic engineering (GE) KW - Moral absolutism KW - Technology aversion KW - Moral convictions KW - GE debate KW - Consumer skepticism Y1 - 2023 UR - https://doi.org/10.1007/s11948-023-00454-0 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-39681 SN - 1471-5546 SN - 1353-3452 VL - 29 IS - 5 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Schönmann, Manuela A1 - Bodenschatz, Anja A1 - Uhl, Matthias A1 - Walkowitz, Gari T1 - The Care-Dependent are Less Averse to Care Robots: An Empirical Comparison of Attitudes JF - International Journal of Social Robotics N2 - A growing gap is emerging between the supply of and demand for professional caregivers, not least because of the ever-increasing average age of the world’s population. One strategy to address this growing gap in many regions is the use of care robots. Although there have been numerous ethical debates about the use of robots in nursing and elderly care, an important question remains unexamined: how do the potential recipients of such care perceive situations with care robots compared to situations with human caregivers? Using a large-scale experimental vignette study, we investigated people’s affective attitudes toward care robots. Specifically, we studied the influence of the caregiver’s nature on participants’ perceived comfort levels when confronted with different care scenarios in nursing homes. Our results show that the care-robot-related views of actual care recipients (i.e., people who are already affected by care dependency) differ substantially from the views of people who are not affected by care dependency. Those who do not (yet) rely on care placed care robots’ value far below that of human caregivers, especially in a service-oriented care scenario. This devaluation was not found among care recipients, whose perceived level of comfort was not influenced by the caregiver’s nature. These findings also proved robust when controlled for people’s gender, age, and general attitudes toward robots. UR - https://doi.org/10.1007/s12369-023-01003-2 KW - Care robots KW - Nursing care KW - Robot aversion KW - Affective attitudes KW - Vignette experiment Y1 - 2023 UR - https://doi.org/10.1007/s12369-023-01003-2 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-38099 SN - 1875-4805 VL - 15 IS - 6 SP - 1007 EP - 1024 PB - Springer CY - Heidelberg ER - TY - JOUR A1 - Krügel, Sebastian A1 - Uhl, Matthias T1 - Internal whistleblowing systems without proper sanctions may backfire JF - Journal of Business Economics N2 - Internal whistleblowing systems are supposed to fight misconduct within organizations. Because it is difficult to study their efficacy in the field, scientific evidence on their performance is rare. This is problematic, because these systems bind substantial resources and might generate the erroneous impression of compliance in a company in which misconduct is prevalent. We therefore suggest a versatilely extendable experimental workhorse that allows the systematic study of internal whistleblowing systems in the lab. As a first step, we tested the efficacy of whistleblowing systems if internal punishment for misconduct is mild and hesitant which is usually the case in practice, as several fraud surveys confirm. Our results show that under these conditions almost nobody blew the whistle, and misconduct occurred even more frequently with than without a whistleblowing system. The institutionalization of whistleblowing seemed to crowd out the intrinsic motivation to act compliantly. Moreover, when a whistleblowing system was either unavailable or not used, misconduct was highly contagious and spread quickly. Yet, when we implemented severe and ensured punishment for misconduct, whistleblowing systems could deter wrongdoing. In such a setting, people were willing to blow the whistle and the prevalence of misconduct dropped substantially. Altogether, our results highlight the interaction between institutions and preferences and can support the design of compliance measures within organizations. For compliance managers a key takeaway is that if companies preach a zero-tolerance policy, they should practice it as well. Otherwise, they might even worsen the situation. UR - https://doi.org/10.1007/s11573-023-01144-w KW - Misconduct KW - Whistleblowing KW - Punishment KW - Crowding out Y1 - 2023 UR - https://doi.org/10.1007/s11573-023-01144-w UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-32074 SN - 1861-8928 SN - 0044-2372 VL - 93 IS - 8 SP - 1355 EP - 1383 PB - Springer CY - Wiesbaden ER - TY - JOUR A1 - Krügel, Sebastian A1 - Ostermaier, Andreas A1 - Uhl, Matthias T1 - Algorithms as partners in crime: A lesson in ethics by design JF - Computers in Human Behavior N2 - The human in the loop is often advocated as a panacea against concerns about AI-powered machines, which increasingly take decisions of consequence in all realms of life. However, can we rely on humans to prevent unethical decisions by machines? We run online experiments modeling both the case where the machine serves as a corrective to the human and where the human serves as a corrective to the machine. Our results suggest that, in the former case, humans make similar decisions whether the corrective is a machine or another human. In the latter case, humans take advantage of rather than correct bad decisions by machines, turning into partners in crime. These findings caution us not to count too much on the human in the loop as a moral corrective. Instead, they tend to argue for human–machine decision-making where the human makes the decision and the machine is the corrective. UR - https://doi.org/10.1016/j.chb.2022.107483 KW - Algorithm KW - Artificial intelligence KW - Ethics KW - HITL KW - Human in the loop Y1 - 2022 UR - https://doi.org/10.1016/j.chb.2022.107483 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-28800 SN - 0747-5632 VL - 2023 IS - 138 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Krügel, Sebastian A1 - Uhl, Matthias T1 - Is only one of my selves authentic? An empirical approach JF - Journal of Behavioral and Experimental Economics N2 - In behavioral economics, intrapersonal conflict is predominantly interpreted hierarchically. A “present-biased” intrapersonal doer may spoil the goal of a rational planner. This often suggests paternalistic interventions that help the “true” or “authentic” self to overwhelm its present-biased alter ego. Game theorist Schelling proposed a reciprocal interpretation of intrapersonal conflict that interprets both selves as strategic players, which Elster contradicted by claiming that in any conflict only one self is capable of strategic behavior and therefore authentic. Previous empirical studies, however, cannot test this interpretation, because their design provides commitment devices unilaterally to only one self. In an experiment, we provided commitment devices to both selves and find similar inclinations to use this strategic tool. Given this, the symmetric view on intrapersonal conflict seems no less plausible than the hierarchical one. Our results might contribute to a richer debate on intrapersonal conflict by feeding in some skepticism about the self-evidence with which paternalists take sides. UR - https://doi.org/10.1016/j.socec.2022.101971 KW - Self-commitment KW - Self-binding KW - Intrapersonal conflict KW - Conflict of selves KW - Libertarian paternalism KW - Consumer sovereignty Y1 - 2022 UR - https://doi.org/10.1016/j.socec.2022.101971 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-32063 SN - 2214-8051 SN - 2214-8043 VL - 2023 IS - 102 PB - Elsevier CY - Amsterdam ER - TY - INPR A1 - Krügel, Sebastian A1 - Ostermaier, Andreas A1 - Uhl, Matthias T1 - The moral authority of ChatGPT N2 - ChatGPT is not only fun to chat with, but it also searches information, answers questions, and gives advice. With consistent moral advice, it might improve the moral judgment and decisions of users, who often hold contradictory moral beliefs. Unfortunately, ChatGPT turns out highly inconsistent as a moral advisor. Nonetheless, it influences users' moral judgment, we find in an experiment, even if they know they are advised by a chatting bot, and they underestimate how much they are influenced. Thus, ChatGPT threatens to corrupt rather than improves users' judgment. These findings raise the question of how to ensure the responsible use of ChatGPT and similar AI. Transparency is often touted but seems ineffective. We propose training to improve digital literacy. UR - https://doi.org/10.48550/arXiv.2301.07098 KW - AI KW - ChatGPT KW - ethics KW - moral dilemma Y1 - 2023 UR - https://doi.org/10.48550/arXiv.2301.07098 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-32085 PB - arXiv CY - Ithaca ER - TY - JOUR A1 - Schönmann, Manuela A1 - Bodenschatz, Anja A1 - Uhl, Matthias A1 - Walkowitz, Gari T1 - Contagious humans: A pandemic's positive effect on attitudes towards care robots JF - Technology in Society N2 - History has shown that attitudes toward new technologies can change abruptly following disruptive events. During the COVID-19 pandemic, it became apparent that care robots enable increased social isolation. This feature of robotic care usually raises strong ethical concerns about potentially decreased comfort for the care-dependent. In a large-scale online study, we tested the influence of the pandemic on people's affective attitudes toward care robots. In vignettes on different care scenarios, we measured participants' perceived comfort levels in situations with care robots and human caregivers while controlling for their fear of infection with a viral disease. We found that people generally feel less comfortable with a care robot than with a human caregiver. However, those who had a strong fear of being infected during the pandemic did not devalue a care robot compared to a human caregiver. While care robots remain ethically contested, this study shows that affective attitudes toward care robots may change significantly if they can address an urgent need. UR - https://doi.org/10.1016/j.techsoc.2024.102464 Y1 - 2024 UR - https://doi.org/10.1016/j.techsoc.2024.102464 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-43998 SN - 1879-3274 VL - 2024 IS - 76 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Krügel, Sebastian A1 - Ostermaier, Andreas A1 - Uhl, Matthias T1 - ChatGPT’s inconsistent moral advice influences users’ judgment JF - Scientific Reports N2 - AbstractChatGPT is not only fun to chat with, but it also searches information, answers questions, and gives advice. With consistent moral advice, it can improve the moral judgment and decisions of users. Unfortunately, ChatGPT’s advice is not consistent. Nonetheless, it does influence users’ moral judgment, we find in an experiment, even if they know they are advised by a chatting bot, and they underestimate how much they are influenced. Thus, ChatGPT corrupts rather than improves its users’ moral judgment. While these findings call for better design of ChatGPT and similar bots, we also propose training to improve users’ digital literacy as a remedy. Transparency, however, is not sufficient to enable the responsible use of AI. UR - https://doi.org/10.1038/s41598-023-31341-0 Y1 - 2023 UR - https://doi.org/10.1038/s41598-023-31341-0 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-41835 SN - 2045-2322 VL - 13 PB - Springer Nature CY - London ER - TY - JOUR A1 - Weller, Julian A1 - Nalavade, Sumit A1 - Gmelch, Oliver A1 - Migenda, Nico A1 - Heuwinkel, Tim A1 - Dumitrescu, Roman T1 - Advanced Analytics in Smart Factories: Towards an actionable Taxonomy for Prescriptive Analytics Use Cases JF - Procedia CIRP N2 - Prescriptive analytics use cases support in the decision-making process and focus on providing actionable guidance (e.g. in the smart factory) based on a set of problems and possible solutions. Smart factories represent the core of Industry 4.0 and can greatly benefit from the implementation of advanced analytics use cases. Prescriptive analytics enables operational excellence in smart factories by providing actionable insights and decisions to (autonomously) steer and govern areas of a factory. Still, a widespread adoption of principles of prescriptive analytics is not reached, due to the complexity and interconnectivity of different use cases. Additionally, a lack of methodological support for developing prescriptive analytics use cases is observed. We support the adoption and ideation of prescriptive analytics use cases by providing a taxonomy for prescriptive analytics use cases in smart factories for researchers. To make the findings from the taxonomy actionable, we develop a concept on how to transform existing analytics use cases or use case ideas into prescriptive analytics use cases to support practitioners. We focus on the transformation of existing analytics use cases into prescriptive analytics use cases to lower the barrier to entry for the development of prescriptive use cases. The findings are based on the taxonomy development method by Nickerson. Our evaluation is supported by expert interviews as well as focus groups. UR - https://doi.org/10.1016/j.procir.2025.03.016 Y1 - 2025 UR - https://doi.org/10.1016/j.procir.2025.03.016 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-61634 SN - 2212-8271 VL - 2025 IS - 134 SP - 229 EP - 234 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Schönmann, Alexander A1 - Ulverich, Michael A1 - Intra, Carsten A1 - Reinhart, Gunther T1 - Considering External and Internal Cycles of a Manufacturer for Planning and Evaluating Production Technologies JF - Procedia CIRP N2 - Anticipating a production company's internal and external influencing factors is seen as key driver of the ability to act appropriately to sustain a competitive advantage within a dynamic market environment. In this connection, some factors within the production environment manifest as temporally and structurally recurring patterns (defined as cycles) and are predictable. Modeling and analyzing the cyclic behavior of products, technologies, and manufacturing resources, for example, facilitates a proactive planning approach to production technologies. This paper uses the example of the commercial vehicle industry to focus on a manufacturer's internal cyclic influencing factors. Based on the results of an industrial case study and a review of existing methods, a conceptual framework is presented for managing the complex interdependencies of the lifecycle of a product, its components, and production technologies. UR - https://doi.org/10.1016/j.procir.2016.08.006 KW - manufacturing process KW - production planning KW - cycle management KW - commercial verhicle industry Y1 - 2016 UR - https://doi.org/10.1016/j.procir.2016.08.006 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-32465 SN - 2212-8271 VL - 2016 IS - 55 SP - 47 EP - 52 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Rosbach, Emely A1 - Ammeling, Jonas A1 - Krügel, Sebastian A1 - Kießig, Angelika A1 - Fritz, Alexis A1 - Ganz, Jonathan A1 - Puget, Chloé A1 - Donovan, Taryn A1 - Klang, Andrea A1 - Köller, Maximilian C. A1 - Bolfa, Pompei A1 - Tecilla, Marco A1 - Denk, Daniela A1 - Kiupel, Matti A1 - Paraschou, Georgios A1 - Kok, Mun Keong A1 - Haake, Alexander F. H. A1 - de Krijger, Ronald R. A1 - Sonnen, Andreas F.-P. A1 - Kasantikul, Tanit A1 - Dorrestein, Gerry M. A1 - Smedley, Rebecca C. A1 - Stathonikos, Nikolas A1 - Uhl, Matthias A1 - Bertram, Christof A1 - Riener, Andreas A1 - Aubreville, Marc ED - Yamashita, Naomi ED - Evers, Vanessa ED - Yatani, Koji ED - Ding, Xianghua ED - Lee, Bongshin ED - Chetty, Marshini ED - Toups-Dugas, Phoebe T1 - "When Two Wrongs Don't Make a Right" - Examining Confirmation Bias and the Role of Time Pressure During Human-AI Collaboration in Computational Pathology T2 - CHI'25: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems N2 - Artificial intelligence (AI)-based decision support systems hold promise for enhancing diagnostic accuracy and efficiency in computational pathology. However, human-AI collaboration can introduce and amplify cognitive biases, like confirmation bias caused by false confirmation when erroneous human opinions are reinforced by inaccurate AI output. This bias may increase under time pressure, a ubiquitous factor in routine pathology, as it strains practitioners’ cognitive resources. We quantified confirmation bias triggered by AI-induced false confirmation and examined the role of time constraints in a web-based experiment, where trained pathology experts (n=28) estimated tumor cell percentages. Our results suggest that AI integration fuels confirmation bias, evidenced by a statistically significant positive linear-mixed-effects model coefficient linking AI recommendations mirroring flawed human judgment and alignment with system advice. Conversely, time pressure appeared to weaken this relationship. These findings highlight potential risks of AI in healthcare and aim to support the safe integration of clinical decision support systems. UR - https://doi.org/10.1145/3706598.3713319 Y1 - 2025 UR - https://doi.org/10.1145/3706598.3713319 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58797 SN - 979-8-4007-1394-1 PB - ACM CY - New York ER - TY - JOUR A1 - Greßhake, Lukas A1 - Bosch, Stephan A1 - Tutunaru, Robin A1 - Holzhammer, Uwe T1 - What do you mean by ‘(un-)suitable’? Analysing the diversity of social acceptance towards the deployment of renewable energies in different landscapes JF - Journal of Land Use Science N2 - 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. UR - https://doi.org/10.1080/1747423X.2025.2499280 Y1 - 2025 UR - https://doi.org/10.1080/1747423X.2025.2499280 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59512 SN - 1747-4248 SN - 1747-423X VL - 20 IS - 1 SP - 117 EP - 150 PB - Taylor & Francis CY - London ER - TY - INPR A1 - Kammerlander, Calvin A1 - Kolb, Viola A1 - Luegmair, Marinus A1 - Scheermann, Lou A1 - Schmailzl, Maximilian A1 - Seufert, Marco A1 - Zhang, Jiayun A1 - Dalic, Denis A1 - Schön, Torsten T1 - Machine Learning Models for Soil Parameter Prediction Based on Satellite, Weather, Clay and Yield Data N2 - Efficient nutrient management and precise fertilization are essential for advancing modern agriculture, particularly in regions striving to optimize crop yields sustainably. The AgroLens project endeavors to address this challenge by develop ing Machine Learning (ML)-based methodologies to predict soil nutrient levels without reliance on laboratory tests. By leveraging state of the art techniques, the project lays a foundation for acionable insights to improve agricultural productivity in resource-constrained areas, such as Africa. The approach begins with the development of a robust European model using the LUCAS Soil dataset and Sentinel-2 satellite imagery to estimate key soil properties, including phosphorus, potassium, nitrogen, and pH levels. This model is then enhanced by integrating supplementary features, such as weather data, harvest rates, and Clay AI-generated embeddings. This report details the methodological framework, data preprocessing strategies, and ML pipelines employed in this project. Advanced algorithms, including Random Forests, Extreme Gradient Boosting (XGBoost), and Fully Connected Neural Networks (FCNN), were implemented and finetuned for precise nutrient prediction. Results showcase robust model performance, with root mean square error values meeting stringent accuracy thresholds. By establishing a reproducible and scalable pipeline for soil nutrient prediction, this research paves the way for transformative agricultural applications, including precision fertilization and improved resource allocation in underresourced regions like Africa. UR - https://doi.org/10.48550/arXiv.2503.22276 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2503.22276 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59345 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Axenie, Cristian A1 - Saveriano, Matteo T1 - Antifragile Control Systems: The case of mobile robot trajectory tracking in the presence of uncertainty N2 - Mobile robots are ubiquitous. Such vehicles benefit from well-designed and calibrated control algorithms ensuring their task execution under precise uncertainty bounds. Yet, in tasks involving humans in the loop, such as elderly or mobility impaired, the problem takes a new dimension. In such cases, the system needs not only to compensate for uncertainty and volatility in its operation but at the same time to anticipate and offer responses that go beyond robust. Such robots operate in cluttered, complex environments, akin to human residences, and need to face during their operation sensor and, even, actuator faults, and still operate. This is where our thesis comes into the foreground. We propose a new control design framework based on the principles of antifragility. Such a design is meant to offer a high uncertainty anticipation given previous exposure to failures and faults, and exploit this anticipation capacity to provide performance beyond robust. In the current instantiation of antifragile control applied to mobile robot trajectory tracking, we provide controller design steps, the analysis of performance under parametrizable uncertainty and faults, as well as an extended comparative evaluation against state-of-the-art controllers. We believe in the potential antifragile control has in achieving closed-loop performance in the face of uncertainty and volatility by using its exposures to uncertainty to increase its capacity to anticipate and compensate for such events. UR - https://doi.org/10.48550/arXiv.2302.05117 Y1 - 2023 UR - https://doi.org/10.48550/arXiv.2302.05117 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58440 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Song, Rui A1 - Liang, Chenwei A1 - Xia, Yan A1 - Zimmer, Walter A1 - Cao, Hu A1 - Caesar, Holger A1 - Festag, Andreas A1 - Knoll, Alois T1 - CoDa-4DGS: Dynamic Gaussian Splatting with Context and Deformation Awareness for Autonomous Driving N2 - Dynamic scene rendering opens new avenues in autonomous driving by enabling closed-loop simulations with photorealistic data, which is crucial for validating end-to-end algorithms. However, the complex and highly dynamic nature of traffic environments presents significant challenges in accurately rendering these scenes. In this paper, we introduce a novel 4D Gaussian Splatting (4DGS) approach, which incorporates context and temporal deformation awareness to improve dynamic scene rendering. Specifically, we employ a 2D semantic segmentation foundation model to self-supervise the 4D semantic features of Gaussians, ensuring meaningful contextual embedding. Simultaneously, we track the temporal deformation of each Gaussian across adjacent frames. By aggregating and encoding both semantic and temporal deformation features, each Gaussian is equipped with cues for potential deformation compensation within 3D space, facilitating a more precise representation of dynamic scenes. Experimental results show that our method improves 4DGS's ability to capture fine details in dynamic scene rendering for autonomous driving and outperforms other self-supervised methods in 4D reconstruction and novel view synthesis. Furthermore, CoDa-4DGS deforms semantic features with each Gaussian, enabling broader applications. UR - https://doi.org/10.48550/arXiv.2503.06744 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2503.06744 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58313 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Heinl, Patrizia A1 - Patapovas, Andrius A1 - Pilgermann, Michael T1 - Towards AI-enabled Cyber Threat Assessment in the Health Sector N2 - Cyber attacks on the healthcare industry can have tremendous consequences and the attack surface expands continuously. In order to handle the steadily rising workload, an expanding amount of analog processes in healthcare institutions is digitized. Despite regulations becoming stricter, not all existing infrastructure is sufficiently protected against cyber attacks. With an increasing number of devices and digital processes, the system and network landscape becomes more complex and harder to manage and therefore also more difficult to protect. The aim of this project is to introduce an AI-enabled platform that collects security relevant information from the outside of a health organization, analyzes it, delivers a risk score and supports decision makers in healthcare institutions to optimize investment choices for security measures. Therefore, an architecture of such a platform is designed, relevant information sources are identified, and AI methods for relevant data collection, selection, and risk scoring are explored. UR - https://doi.org/10.48550/arXiv.2409.12765 Y1 - 2024 UR - https://doi.org/10.48550/arXiv.2409.12765 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58381 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Kalyanasundaram, Abinav A1 - Chandra Sekaran, Karthikeyan A1 - Stäuber, Philipp A1 - Lange, Michael A1 - Utschick, Wolfgang A1 - Botsch, Michael T1 - Uncertainty-Aware Hybrid Machine Learning in Virtual Sensors for Vehicle Sideslip Angle Estimation N2 - 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. UR - https://doi.org/10.48550/arXiv.2504.06105 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2504.06105 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59578 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Han, Longfei A1 - Xu, Qiuyu A1 - Kefferpütz, Klaus A1 - Elger, Gordon A1 - Beyerer, Jürgen T1 - Applying Extended Object Tracking for Self-Localization of Roadside Radar Sensors N2 - Intelligent Transportation Systems (ITS) can benefit from roadside 4D mmWave radar sensors for large-scale traffic monitoring due to their weatherproof functionality, long sensing range and low manufacturing cost. However, the localization method using external measurement devices has limitations in urban environments. Furthermore, if the sensor mount exhibits changes due to environmental influences, they cannot be corrected when the measurement is performed only during the installation. In this paper, we propose self-localization of roadside radar data using Extended Object Tracking (EOT). The method analyses both the tracked trajectories of the vehicles observed by the sensor and the aerial laser scan of city streets, assigns labels of driving behaviors such as "straight ahead", "left turn", "right turn" to trajectory sections and road segments, and performs Semantic Iterative Closest Points (SICP) algorithm to register the point cloud. The method exploits the result from a down stream task -- object tracking -- for localization. We demonstrate high accuracy in the sub-meter range along with very low orientation error. The method also shows good data efficiency. The evaluation is done in both simulation and real-world tests. UR - https://doi.org/10.48550/arXiv.2407.03084 Y1 - 2024 UR - https://doi.org/10.48550/arXiv.2407.03084 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58361 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Han, Longfei A1 - Kefferpütz, Klaus A1 - Beyerer, Jürgen T1 - 3D Extended Object Tracking based on Extruded B-Spline Side View Profiles N2 - Object tracking is an essential task for autonomous systems. With the advancement of 3D sensors, these systems can better perceive their surroundings using effective 3D Extended Object Tracking (EOT) methods. Based on the observation that common road users are symmetrical on the right and left sides in the traveling direction, we focus on the side view profile of the object. In order to leverage of the development in 2D EOT and balance the number of parameters of a shape model in the tracking algorithms, we propose a method for 3D extended object tracking (EOT) by describing the side view profile of the object with B-spline curves and forming an extrusion to obtain a 3D extent. The use of B-spline curves exploits their flexible representation power by allowing the control points to move freely. The algorithm is developed into an Extended Kalman Filter (EKF). For a through evaluation of this method, we use simulated traffic scenario of different vehicle models and realworld open dataset containing both radar and lidar data. UR - https://doi.org/10.48550/arXiv.2503.10730 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2503.10730 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58331 PB - arXiv CY - Ithaca ER - TY - CHAP A1 - Barbosa da Silva, Leonardo A1 - Lobo, Silas A1 - Fernández, Evelio A1 - Facchi, Christian ED - Vinel, Alexey ED - Berns, Karsten ED - Ploeg, Jeroen ED - Gusikhin, Oleg T1 - What Is the Right Bounding Box of a VRU Cluster in V2X Communication? How to Form a Good Shape? T2 - Vehits 2024: 10th International Conference on Vehicle Technology and Intelligent Transport Systems Proceedings N2 - Among the possible traffic members on a Vehicle-to-Everything network, the term Vulnerable Road User (VRU) is assigned e.g. to pedestrians and cyclists. The VRU Awareness Message (VAM) is used by VRUs to inform other users of their presence and ensure they are perceived in a traffic system. Since the number of VRUs in crowded areas might be very high, the over-the-air traffic might be overloaded. To reduce channel overload, VAMs offer a clustering feature in which VRUs with similar kinematics and positions can group themselves so that only one device transmits messages. The VRU Basic Service specification describes the cluster as a bounding box that must cover all its members using a geometric shape so that other vehicles in the vicinity can avoid colliding with the contained VRUs. This paper contributes to the standardization effort by introducing a data structure, the Cluster Map, for the clustering in the VRU Basic Service. Furthermore, this work is the first to suggest strategies for forming bounding box shapes. Simulation results show that each of the geometry types is useful in different situations, thus further research on the topic is advised. UR - https://doi.org/10.5220/0012699100003702 Y1 - 2024 UR - https://doi.org/10.5220/0012699100003702 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-48553 SN - 978-989-758-703-0 SP - 144 EP - 155 PB - SciTePress CY - Setúbal ER - TY - JOUR A1 - Yu, Qing A1 - Kiran, Iqra A1 - Ehrensberger, Moritz A1 - Streck, Luiza A1 - Roth, Thomas A1 - Jossen, Andreas A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Assigning Calendar Aging during Open Circuit and Float Current Analysis to Anode and Cathode Aging Using Three-Electrode Cells JF - Journal of the Electrochemical Society N2 - Analyzing calendar aging by float current analysis, instead of solely repeating capacity tests, gains more insights into aging. However, the underlying mechanisms of the recharge current required to keep the voltage constant are not yet fully understood. Therefore, this study performs float current and additional open circuit voltage (OCV) tests on 3-electrode cells for four different voltages at 30 °C. By monitoring the potentials of the anode and the cathode over time individually, the aging rate on both electrodes and the present capacity can be calculated based on adjusting the electrode-specific OCV curves according to the voltage slippery theory. The electrode-specific aging and the capacity prediction show high agreement among both methods and the capacity tests at the end of the experiment. As a result, the capacity loss appears linear-like and is associated with the loss of active lithium mainly due to SEI formation on the anode. Additionally, a significant cathode voltage decay is observed especially for higher cell voltage. According to the literature, this is associated with cathode lithiation where the conductive salt is decomposed by inserting active lithium into the cathode masking SEI losses. Finally, OCV and float current analysis return comparable results and support present 2-electrode evaluation approaches. UR - https://doi.org/10.1149/1945-7111/ade295 Y1 - 2025 UR - https://doi.org/10.1149/1945-7111/ade295 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60504 SN - 1945-7111 VL - 172 IS - 6 PB - IOP Publishing CY - Bristol ER -