Belief State Planning for Autonomous Driving: Planning with Interaction, Uncertain Prediction and Uncertain Perception

This work presents a behavior planning algorithm for automated driving in urban environments with an uncertain and dynamic nature. The algorithm allows to consider the prediction uncertainty (e.g. different intentions), perception uncertainty (e.g. occlusions) as well as the uncertain interactive behavior of the other agents explicitly. Simulating the most likely future scenarios allows to find an optimal policy online that enables non-conservative planning under uncertainty

Belief State Planning for Autonomous Driving: Planning with Interaction, Uncertain Prediction and Uncertain Perception

This thesis presents a behavior planning algorithm for automated driving in urban environments with an uncertain and dynamic nature. The uncertainty in the environment arises by the fact that the intentions as well as the future trajectories of the surrounding drivers cannot be measured directly but can only be estimated in a probabilistic fashion. Even the perception of objects is uncertain due to sensor noise or possible occlusions. When driving in such environments, the autonomous car must predict the behavior of the other drivers and plan safe, comfortable and legal trajectories. Planning such trajectories requires robust decision making when several high-level options are available for the autonomous car. Current planning algorithms for automated driving split the problem into different subproblems, ranging from discrete, high-level decision making to prediction and continuous trajectory planning. This separation of one problem into several subproblems, combined with rule-based decision making, leads to sub-optimal behavior. This thesis presents a global, closed-loop formulation for the motion planning problem which intertwines action selection and corresponding prediction of the other agents in one optimization problem. The global formulation allows the planning algorithm to make the decision for certain high-level options implicitly. Furthermore, the closed-loop manner of the algorithm optimizes the solution for various, future scenarios concerning the future behavior of the other agents. Formulating prediction and planning as an intertwined problem allows for modeling interaction, i.e. the future reaction of the other drivers to the behavior of the autonomous car. The problem is modeled as a partially observable Markov decision process (POMDP) with a discrete action and a continuous state and observation space. The solution to the POMDP is a policy over belief states, which contains different reactive plans for possible future scenarios. Surrounding drivers are modeled with interactive, probabilistic agent models to account for their prediction uncertainty. The field of view of the autonomous car is simulated ahead over the whole planning horizon during the optimization of the policy. Simulating the possible, corresponding, future observations allows the algorithm to select actions that actively reduce the uncertainty of the world state. Depending on the scenario, the behavior of the autonomous car is optimized in (combined lateral and) longitudinal direction. The algorithm is formulated in a generic way and solved online, which allows for applying the algorithm on various road layouts and scenarios. While such a generic problem formulation is intractable to solve exactly, this thesis demonstrates how a sufficiently good approximation to the optimal policy can be found online. The problem is solved by combining state of the art Monte Carlo tree search algorithms with near-optimal, domain specific roll-outs. The algorithm is evaluated in scenarios such as the crossing of intersections under unknown intentions of other crossing vehicles, interactive lane changes in narrow gaps and decision making at intersections with large occluded areas. It is shown that the behavior of the closed-loop planner is less conservative than comparable open-loop planners. More precisely, it is even demonstrated that the policy enables the autonomous car to drive in a similar way as an omniscient planner with full knowledge of the scene. It is also demonstrated how the autonomous car executes actions to actively gather more information about the surrounding and to reduce the uncertainty of its belief state

Strategien zu Umsetzung tierbezogener Kriterien entwickeln - Legehennengesundheit: Status quo und Zielgrößen

In dem workshop wurden erste Ergebnisse von 19 deutschen ökologischen Legehennenbetrieben aus dem europäischen Forschungsprojekt HealthyHens präsentiert. Auf dieser Basis wurden folgende Punkte diskutiert - die Anwendbarkeit der Tieruntersuchungen auf den Betrieben - der Nutzen der Untersuchungsergebnisse für die HennenhalterInnen, Zertifizierungs- und Kontrollstellen, KonsumentInnen und die Wissenschaft - Szenarien zur zukünftigen Anwendung - Vor- und Nachteile von Grenzwerten zu den Tiergesundheits-Parameter

Ethische Dimensionen des pikturalen und textuellen Erzählens.: Nora Bernings Propädeutik einer ‚ethischen‘ Narratologie

Nora Berning: Towards a Critical Ethical Narratology. Analyzing Value Construction in Literary Non-Fiction across Media. Trier: Wissenschaftlicher Verlag Trier 2013 (= WVT-Handbücher und Studien zur Medienkulturwissenschaft, Bd. 9). 191 S. EUR 25,00. ISBN 978-3-86821-455-

Das Monitoring Minimaler Resterkrankung bei Patienten mit akuter myeloischer Leukämie und Myelodysplastischem Syndrom nach allogener Blutstammzelltransplantation mit reduzierter Konditionierung

Im Rahmen dieser Dissertation wurde retrospektiv die Minimale Resterkrankung von Patienten mit akuter myeloischer Leukämie und Myelodysplastischen Syndrom nach allogener Stammzelltransplantation mit minimaler Konditionierung untersucht. Hierfür wurden vier unterschiedliche Methoden zur Detektion der Minimalen Resterkrankung analysiert. Nach Etablierung einer quantitativen Real-Time PCR für das Wilms Tumor Gen 1 (WT1) im peripheren Blut wurden diese Ergebnisse mit bereits routinemäßig erhobenen Daten des Chimärismus im Gesamtknochenmark und in CD34+ Zellen sowie der Fluoreszenz-in-situ-Hybridisierung (FISH) krankheitsspezifischer chromosomaler Aberrationen von insgesamt 88 Patienten verglichen und statistisch ausgewertet. Es konnte gezeigt werden, dass die Genexpressionanalysen des WT1 sowie die Chimärismusanalysen ein Rezidiv im Gegensatz zu den FISH Analysen vier Wochen im Voraus detektieren können. In Reiceiver Operating Curve Analysen wurden eine WT1 Expression von > 24 WT1/10.000 ABL1 Kopien und der Abfall des CD34+ Spenderchimärismus von ≥ 5% als diagnostisch stärkste Methoden identifiziert. In uni- und multivariaten Analysen von insgesamt 20 Parametern wurden die beiden Methoden als unabhängige Variablen für ein frühes Rezidiv, progressionsfreies Überleben und Gesamtüberleben bestätigt. Kombiniert man beide Methoden, so kann bei jeweiligem negativen Testergebnis ein Rezidiv innerhalb der nächsten vier Wochen nahezu ausgeschlossen werden

GaAs nanowires: Epitaxy, crystal structure-related properties and magnetic heterostructures

The intention of this work is twofold: On the one hand, we explore the controlability of GaAs nanowire growth concerning orientation, shape and crystal structure. These are necessary steps, since the growth of GaAs nanowires proceeds not necessarily uniformly, and in GaAs nanowires the in bulk unstable wurtzite phase, and the usual observed zinc-blende crystal phase may coexist in one and the same nanowire. On the other hand, we include ferromagnetic materials into GaAs nanowires. To do that, we produce either "core/shell" structures, where the GaAs nanowire is coated with a ferromagnetic "shell" material, or grow ferromagnetic nanoscale segments in GaAs nanowires

Enhanced spin-orbit coupling in core/shell nanowires

The spin-orbit coupling (SOC) in semiconductors is strongly influenced by structural asymmetries, as prominently observed in bulk crystal structures that lack inversion symmetry. Here, we study an additional effect on the SOC: the asymmetry induced by the large interface area between a nanowire core and its surrounding shell. Our experiments on purely wurtzite GaAs/AlGaAs core/shell nanowires demonstrate optical spin injection into a single free-standing nanowire and determine the effective electron g-factor of the hexagonal GaAs wurtzite phase. The spin relaxation is highly anisotropic in time-resolved micro-photoluminescence measurements on single nanowires, showing a significant increase of spin relaxation in external magnetic fields. This behavior is counterintuitive compared to bulk wurtzite crystals. We present a model for the observed electron spin dynamics highlighting the dominant role of the interface-induced SOC in these core/shell nanowires. This enhanced SOC may represent an interesting tuning parameter for the implementation of spin-orbitronic concepts in semiconductor-based structures

Improved linkage analysis of Quantitative Trait Loci using bulk segregants unveils a novel determinant of high ethanol tolerance in yeast

Background: Bulk segregant analysis (BSA) coupled to high throughput sequencing is a powerful method to map genomic regions related with phenotypes of interest. It relies on crossing two parents, one inferior and one superior for a trait of interest. Segregants displaying the trait of the superior parent are pooled, the DNA extracted and sequenced. Genomic regions linked to the trait of interest are identified by searching the pool for overrepresented alleles that normally originate from the superior parent. BSA data analysis is non-trivial due to sequencing, alignment and screening errors. Results: To increase the power of the BSA technology and obtain a better distinction between spuriously and truly linked regions, we developed EXPLoRA (EXtraction of over-rePresented aLleles in BSA), an algorithm for BSA data analysis that explicitly models the dependency between neighboring marker sites by exploiting the properties of linkage disequilibrium through a Hidden Markov Model (HMM). Reanalyzing a BSA dataset for high ethanol tolerance in yeast allowed reliably identifying QTLs linked to this phenotype that could not be identified with statistical significance in the original study. Experimental validation of one of the least pronounced linked regions, by identifying its causative gene VPS70, confirmed the potential of our method. Conclusions: EXPLoRA has a performance at least as good as the state-of-the-art and it is robust even at low signal to noise ratio's i.e. when the true linkage signal is diluted by sampling, screening errors or when few segregants are available