Open Access

The current transformation in the automotive industry is leading to new technologies with a higher software content, a higher degree of networking, and connections to cloud services. This development leads to an increase in the attack surface and the potential extent of damage. ISO/SAE 21434 and UNECE WP.29/R155 were published to address this development. The ISO/SAE 21434 proposes fuzz testing as a measure. In fuzzing, so-called fuzz data is generated and transmitted to a device under test to identify previously unknown and known vulnerabilities. This approach is already being used very successfully in other industries. But in the automotive sector, some challenges arise when testing hardware-related electronic control units. These include the fact that the internal system structures are often poorly known or not known, as well as the severely restricted access and hardware limitations for monitoring. One way to solve these challenges is to use side-channel information to monitor the device under test. Such information includes power consumption, temperature, and noise levels, for example. In this paper, we present a fuzz testing experiment to determine anomalies, data, and requirements for analyzing various side channels. Basic procedures were used to generate the fuzz data. Monitoring of the device under test was performed manually at the beginning. In addition, a side-channel measurement system with various measurement devices and a test setup are presented. Based on the identified fuzz messages, the behavior of the respective side channels during the abnormal behavior is analyzed and described.

As autonomous driving becomes increasingly feasible, the German government has introduced a legal framework to enable the operation of vehicles with Level 4 automated driving functionality. A key requirement is the maintenance of a continuous connection between such vehicles and a remote technical supervisor. If this link is lost, the vehicle must transition into a safe state by bringing itself to a controlled stop. To mitigate the risk of connection loss, accurate forecasting of mobile network availability along routes is essential. This paper describes a spatio-temporal analysis of mobile network signal quality metrics along a fixed rural route based on 48 repeated measurement drives. The route was segmented into 320 spatial reference sections to enable consistent cross-trip comparison and stability assessment. A classification into usable and non-usable connectivity states reveals that more than half of the sections show pronounced trip-to-trip variability. The results show that mobile network quality is not only dependent on geographic location but is also influenced by environmental conditions. While global correlations between weather parameters and raw signal metrics remain weak, moderate relationships can be seen when analyzing the share of functionally usable connectivity in spatially unstable sections. A walk-forward forecasting model demonstrates that the inclusion of temperature in the model reduces prediction error compared to a purely historical baseline in 73.7% of evaluated trips. The findings show the importance of feature selection and also the limitations of linear modeling approaches. Rather than acting as deterministic predictors of signal strength, contextual parameters primarily modulate connectivity uncertainty in spatially unstable regions. These findings underscore the importance of contextual information and localized modeling to predict network availability for safety-critical systems, such as autonomous vehicles.

Autonomous Driving (AD) has advanced significantly in recent years, yet widespread deployment remains limited. One of the most enduring challenges in Autonomous Vehicle (AV) development is planning a safe, comfortable, and efficient motion in complex, real-world environments. This thesis addresses motion planning across three distinct domains: urban shuttles, passenger vehicles, and truck-trailer systems. It contributes practical insights and novel approaches toward scalable autonomous mobility. The first part of this work presents an integrated motion planning framework for the Continental Urban Mobility Experience (CUbE) driverless shuttle. Extensive real-world testing over several years highlights the system’s robustness and underscores the importance of long-term validation in urban settings. Key innovations include a multi-layered planning stack and a data-driven motion forecasting approach that enhances interaction with human traffic participants. The second part investigates the behavior of human drivers in understructured traffic environments. Those are areas that fall between well-defined road systems and fully unstructured spaces. A novel analysis framework is introduced for mining patterns from naturalistic trajectory datasets, enabling AVs to better blend into human traffic and navigate ambiguous scenarios with improved predictability and safety. The final part of the thesis explores Deep Reinforcement Learning (DRL) for planning and controlling complex truck-trailer maneuvers. A DRL-based approach is developed and evaluated in simulated environments, demonstrating the method’s potential to handle the nonlinear dynamics of articulated vehicles. These contributions advance the field of motion planning by combining theoretical insights, system-level integration, and empirical evaluation. They offer pathways for improving AV behavior across diverse platforms and use cases, ultimately supporting the broader adoption of AD technologies.

Das Verstärken von Betonbauteilen mit geklebter Bewehrung ist dank des Engagements von Herrn Prof. Dr.-Ing. Dr.-Ing. E.h. Konrad Zilch in Forschung und Normung in Deutschland ein gängiges und sicheres Verfahren beim Bauen im Bestand. In Europa wurden im Rahmen der Überarbeitung der Eurocodes in den letzten Jahren ebenfalls Regelung für diese Bauweise geschaffen, welche größtenteils auf den Deutschen Ansätzen beruhen. Aufgrund der neuen Eurocodes werden auch in Deutschland die Regelung für das Verstärken von Betonbauteilen nun überarbeitet und für weitere Verstärkungsfahren wie den Carbonbeton erweitert. As a result of the engagement of Prof. Dr.-Ing. Dr.-Ing. E.h. Konrad Zilch in research and standardisation, strengthening of concrete structures with adhesively bonded reinforcement is a standard and safe method for building in existing structures. In Europe, regulations for this strengthening method have also been created in recent years as part of the revision of the Eurocodes, which are largely based on the German approaches. Due to the new Eurocodes, the regulations for the strengthening of concrete structures are now also being revised in Germany and extended for further reinforcement methods such as carbon concrete Das Verstärken von Betonbauteilen mit geklebter Bewehrung ist dank des Engagements von Herrn Prof. Dr.-Ing. Dr.-Ing. E.h. Konrad Zilch in Forschung und Normung in Deutschland ein gängiges und sicheres Verfahren beim Bauen im Bestand. In Europa wurden im Rahmen der Überarbeitung der Eurocodes in den letzten Jahren ebenfalls Regelung für diese Bauweise geschaffen, welche größtenteils auf den Deutschen Ansätzen beruhen. Aufgrund der neuen Eurocodes werden auch in Deutschland die Regelung für das Verstärken von Betonbauteilen nun überarbeitet und für weitere Verstärkungsfahren wie den Carbonbeton erweitert. // Das Verstärken von Betonbauteilen mit geklebter Bewehrung ist dank des Engagements von Herrn Prof. Dr.-Ing. Dr.-Ing. E.h. Konrad Zilch in Forschung und Normung in Deutschland ein gängiges und sicheres Verfahren beim Bauen im Bestand. In Europa wurden im Rahmen der Überarbeitung der Eurocodes in den letzten Jahren ebenfalls Regelung für diese Bauweise geschaffen, welche größtenteils auf den Deutschen Ansätzen beruhen. Aufgrund der neuen Eurocodes werden auch in Deutschland die Regelung für das Verstärken von Betonbauteilen nun überarbeitet und für weitere Verstärkungsfahren wie den Carbonbeton erweitert.