Head movements predict pedestrian crossing decisions earlier than walking speed

Understanding the behaviour of pedestrians when crossing roads is crucial to improving safety, as pedestrians are the most vulnerable road users, but also the most difficult to predict. Previous research has examined how pedestrians, who intend to cross a road, assess vehicle speed and distance for gap acceptance. However, little attention has been given to the role of head movements as predictor for crossing decisions. Besides by the crossing intention, head movements are also influenced by the approach process to the kerb and the potential traffic directions, but both factors are rarely studied. Here, we compare the predictive power of head movements and walking speed for crossing decisions by examining how pedestrians approach a crossing location while simultaneously looking for crossing opportunities. We used an omnidirectional treadmill combined with a head-mounted display to investigate the crossing behaviour of 36 participants. Our results demonstrate that in the first seconds after pedestrians notice the car, the head-turning frequency is a stronger predictor for the crossing decision than the walking speed. As time passes, the walking speed becomes more useful than the head information and reaches a perfect predictive power shortly before pedestrians cross the kerb. These findings suggest that head orientation could be used as a predictive feature in the initial phase of the crossing and walking speed in the later phase. Ultimately, this research highlights the need for future studies that investigate pedestrian behaviour under more realistic conditions, providing insights relevant to behaviour prediction models for pedestrian protection in automated driving

Rotation Invariance in Floor Plan Digitization using Zernike Moments

Nowadays, a lot of old floor plans exist in printed form or are stored as scanned raster images. Slight rotations or shifts may occur during scanning. Bringing floor plans of this form into a machine readable form to enable further use, still poses a problem. Therefore, we propose an end-to-end pipeline that pre-processes the image and leverages a novel approach to create a region adjacency graph (RAG) from the pre-processed image and predict its nodes. By incorporating normalization steps into the RAG feature extraction, we significantly improved the rotation invariance of the RAG feature calculation. Moreover, applying our method leads to an improved F1 score and IoU on rotated data. Furthermore, we proposed a wall splitting algorithm for partitioning walls into segments associated with the corresponding rooms

Innovating at the Intersection: Software Engineering Research for Science and Industry

Since the inception of the discipline at the NATO Software Engineering Conferences in the late 1960s, software engineering research and practice have primarily concentrated on business and embedded software, particularly in industrial sectors like finance and automotive. Research software that is designed and developed to facilitate research activities in various fields of science or engineering has been largely overlooked by software engineering research. However, there is an increasing acknowledgment of research software as an essential artifact and of research software engineers as a vital profession. On the one hand, research software propels scientific advancements, fosters open science principles, and plays a pivotal role in informing significant policy decisions, such as those related to climate action. On the other hand, it frequently serves as the foundation for software stacks in cutting-edge technologies like Quantum Computing, Artificial Intelligence, and Digital Twin applications. Thus, there is an increasing demand for software engineering methods specifically tailored to research software, with the potential to benefit software development in traditional business domains as well. Drawing from my experiences in academic research at universities, research software engineering at the German Aerospace Center (DLR), as well as software engineering in industry, in this talk I will explore the commonalities and differences between software engineering in industrial and scientific settings. I will also shed light on the landscape of research software engineering and clarify its significance to modern software engineering research

Experimentelle Untersuchung der Carbonatisierung des thermochemischen Speichermaterials Ca(OH)2/CaO

Um erneuerbare Energien effizienter einsetzen zu können, werden thermische Langzeitspeicher entwickelt. Diese können auf Basis von reversiblen chemischen Reaktionen Energie speichern und die Differenz zwischen Verfügbarkeit von grünen Energiequellen und Nachfrage an Energie überbrücken. In dieser Arbeit wird das Speichermaterial Calciumhydroxid/Calciumoxid, Ca(OH)2/CaO, untersucht. Im Reaktor reagiert das Material mit CO2, was zu einer Minderung der Effizienz führt. Diese Reaktion wird mit der thermogravimetrischen Analyse genauer untersucht. Der Fokus hier liegt auf dem Betrieb des Speichers mit Umgebungsluft. Dass dies möglich ist, soll in dieser Arbeit gezeigt werden. Dafür werden mögliche Prozesssteuerungen für den Reaktor vorgeschlagen. Die Ergebnisse zeigen, dass der Speicher im offenen System betrieben werden kann. Es werden zwei Prozesssteuerungen untersucht. Diese Messergebnisse unterstützen die Entwicklung des Reaktors für Einsätze in kleinem Maßstab, wie zum Beispiel in Privathaushalten, um den Einsatz erneuerbarer Energien zu fördern. In weiterführenden Arbeiten können mit Hilfe entsprechender Labormessungen die Prozesssteuerungen entwickelt werden, und anschließend in Reaktoren getestet werden