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OAFuser: Online Adaptive Extended Object Tracking and Fusion using automotive Radar Detections
(2020)
This paper presents the Online Adaptive Fuser: OAFuser, a novel method for online adaptive estimation of motion and measurement uncertainties for efficient tracking and fusion by applying a system of several estimators for ongoing noise along with the conventional state and state covariance estimation. In our system, process and measurement noises are estimated with steady-state filters to obtain combined measurement noise and process noise estimators for all sensors in order to obtain state estimation with a linear Minimum Mean Square Error (MMSE) estimator and accelerating the system’s performance. The proposed adaptive tracking and fusion system was tested based on high fidelity simulation data and several real-world scenarios for automotive radar, where ground truth data is available for evaluation. We demonstrate the proposed method’s accuracy and efficiency in a challenging, highly dynamic scenario where our system is benchmarked with Multiple Model filter in terms of error statistics and run time performance.
Our current mobility paradigm increasingly faces economic, ecological, and social limits in urban areas. The aim of this paper is to analyse if a fleet of shared autonomous electric vehicles (AEVs) can meet these challenges while satisfying the current requirements of privately-owned internal combustion engine vehicles (ICEVs). Therefore, analytical models have been developed to simulate and investigate the impacts of mobility behaviour in Berlin and Stuttgart (Germany). The collected data were used to calculate the fleet size, the energy consumption, the emission of particulate matter, nitrogen oxides, and the carbon footprint of different shared AEVs in comparison with privately owned ICEVs. The approach shows that the system of a shared AEV fleet could lower externalities (accident avoidance, traffic jams, free spaces, parking costs and lifetime losses) in cities and generate cost benefits for customers.
Application of Induction Thermography for Detection of Near Surface Defects in Steel Products
(2020)
Steel is one of the most important materials used in modern maritime vehicles. Modern production techniques make steel grades available that fulfill current requirements of these safety critical applications regarding their mechanical properties and their processing. However, constantly increasing demands on the quality and cost-effectiveness of steel products must be matched by the development and implementation of efficient testing methods.
This paper explores the possibility of using induction thermography as a non-destructive testing method for this measurement task. Therefore multiple experiments were conducted using representative pieces of steel in which defined artificial defects were incorporated through milling.
This paper describes the modelling, simulation and energy management of a fuel cell hybrid heavy-duty truck. For this purpose, a longitudinal dynamic model of a 26t truck was set up and the load requirement for the drive train was determined based on a driving cycle. To meet this load requirement as efficiently and dynamically as possible three different energy management strategies were implemented, tested and the impact on the overall system was analysed. In addition, the behaviour of the hybrid system with the various energy management strategies with different battery capacity is shown and analysed.
This paper provides an analysis of the trend in autonomous driving traffic and the development of infrastructural support, whereas the requirements on the infrastructural support will be analyzed. Then selected traffic scenes will be implemented in an autonomous driving simulator tool in order to figure out the required parameters to assist the autonomous vehicle from the infrastructure.
Sprache kommt in psychotherapeutischen Kontexten eine zentrale Rolle zu. Ausgehend von diesem Gedanken stellen wir mit unserem Beitrag das besondere Potenzial von Metaphern für psychotherapeutisches Arbeiten heraus. Die theoretische Basis unseres „metaphernreflexiven“ Vorgehens bildet die kognitive Metapherntheorie von Lakoff und Johnson. Anhand einer überblicksartigen Darstellung des Metaphernverständnisses der verschiedenen Psychotherapierichtungen werden wir zeigen, dass Metaphern schulenübergreifend auf gewinnbringende Weise eingesetzt werden können. Aus dieser Übersicht ergeben sich zwei grundlegend verschiedene Sichtweisen auf Metaphern: zum einen die einer umfassenden sozialwissenschaftlichen Analyse, zum anderen die (selbst metaphorische) Vorstellung von Metaphern als „Werkzeug“. Unser „metaphernreflexiver“ Vorschlag bewegt sich in der Mitte dieser beiden Pole. Anhand eines fünfschrittigen Vorgehens stellen wir vor, wie sich Metaphern in die psychotherapeutische Praxis aller Schulen integrieren lassen.
All around the world, the COVID-19 pandemic is accompanied by an ostensible increase in appreciation for the work of professional caregivers. As valuable as the public recognition may seem at first glance, it entails the danger that self-care of those who care professionally might fall into oblivion. Relating it to the challenges that the pandemic poses, we will outline the professional duty of care . We will then discuss the demanding situation of moral insecurity and moral stress as well as the health-related consequences it may lead to. Following this, we will deduce suggestions for the design of workplace factors and the practice of self-care. Finally, we will come to the conclusion that self-care of caregivers plays as crucial a role in the COVID-19 pandemic as their professional care for others.