Cycling offers many benefits, such as reducing traffic congestion, Iower emissions and health benefits. To further promote cycling, the cyclists' perceived safety needs to be addressed. In this context, automated vehicles offer high potential for designing safe and comfortable interactions with cyclists in the future. A key parameter in these interactions constitutes the proximity of vehicles passing cyclists to avoid causing discomfort. To evaluate specific scenarios with varying proximity, cycling simulators provide a safe and standardized environment for traffic safety research. Therefore, there are numerous efforts to implement cycling simulators for use in research. However, it is important to verify the simulator validity to ensure the generalizability of results. In this work, an implementation of a virtual reality (VR) cycling simulation is presented and it is aimed to investigate the simulator validity in terms of perceived criticality in traffic conflict scenarios as well as the participants' experience of presence within the VR cycling simulation. [from Introduction]

Interpreting the subtleness and complexity of vulnerable road user (VRU) behaviour is still a significant challenge for automated vehicles (AVs). Solutions for facilitating safe and acceptable interactions in future automated traffic include equipping AVs and VRUs with human-machine interfaces (HMl.s), such as awareness and notification systems, and connecting road users to a network of A Vs and infrastructure. The research on these solutions, however, primarily focuses on pedestrians. There is no overview ofthe type of systems or solutions supporting cyclists in future automated traffic. The objective ofthe present study is to synthesise current literature and provide an overview ofthe state-ofthe-art support systems available to cyclists. The aim is to identify, classify, and count the types of communicative technologies, systems, and devices capable of supporting the safety of cyclists in automated traffic. The overall goal is to understand A V-cyclist interaction better, pinpoint knowledge gaps in current literature, and develop strategies for optimising safe and pleasant cycling in future traffic environments with AVs.

Cycling as an active mode of transport is increasing across all Europe [1]. Multiple benefits are coming from cycling both for the single user and the society as a whole. With increasing cycling, we expect more conflicts to happen between cyclists and vehicles, as it is also shown by the increasing cyclists' share of fatalities, contrary to the passenger cars' share [2]. Understanding cyclists' behavioral patterns can help automated vehicles (AVs) to predict cyclist's behavior, and then behave safely and comfortably when they encounter them. As a result, developing reliable predictive models of cyclist behavior will help AVs to interact safely with cyclists.

With regard to the space field, the number of the sensors has grown for a middle-sized spacecraft from more than 500 at the beginning of the twenty-first century [1] to several thousands for nowadays applications. Meanwhile, Reusable Launch Vehicles (RLVs) moved their steps from demonstrators to commercial working systems. As a result, Health Monitoring (HM) is conquered its own space in the field and sensors are the primary elements required for implementing a monitoring unit. The innovative concept of reusable rockets requires, from the point of view of HM implementation, not only the evaluation of the vehicle health status but also the prediction of the reusability of the individual subsystems w.r.t. the next launch cycle. Therefore, the goal of this work is divided in two parts. The former is to identify the most critical points for the development of reusable rockets, focusing on theoretical working conditions and analysis or failures. The latter is to discuss the sensing units useful for addressing the defined points, describing the possible innovative approaches for sensing the system conditions. Among them, piezoelectric units, fiber optics, imaging units, and conductive layers can be identified for enhancing the comprehension of the system working conditions.

The localization of autonomous ground vehicles in dense urban environments poses a challenge. Applications in classical outdoor robotics rely on the availability of GPS systems in order to estimate the position. However, the presence of complex building structures in dense urban environments hampers a reliable localization based on GPS. Alternative approaches have to be applied In order to tackle this problem. This thesis proposes an approach which combines observations of a single perspective camera and odometry in a probabilistic framework. In particular, the localization in the space of appearance is addressed. First, a topological map of reference places in the environment is built. Each reference place is associated with a set of visual features. A feature selection is carried out in order to obtain distinctive reference places. The topological map is extended to a hybrid representation by the use of metric information from Geographic Information Systems (GIS) and satellite images. The localization is solved in terms of the recognition of reference places. A particle lter implementation incorporating this and the vehicle's odometry is presented. The proposed system is evaluated based on multiple experiments in exemplary urban environments characterized by high building structures and a multitude of dynamic objects.

Auf die Automobilindustrie wirken unterschiedliche Kräfte und eine Vielzahl weiterer Einflüsse. Das Auftreten von Veränderungen im Unternehmensumfeld, die eine Reaktion auf Ebene der Produktionszahlen bedürfen wird zunehmend kurzfristiger. Die bestehenden automobilen Fabriksysteme sind zu starr, um auf den hoch dynamischen Weltmarkt angemessen reagieren zu können. Ansätze zur Verbesserung der Ausgangslage für bestimmte Abschnitte wurden bereits erarbeitet und in einigen punktuellen Pilotanlagen umgesetzt. Zur Erfüllung der immer komplexeren Anforderungen in der Materialflusstechnik bedarf es jedoch einer Optimierung als Gesamtsystem, um eine Durchgängigkeit der Veränderlichkeit zu gewährleisten. Im Rahmen der vorliegenden Untersuchung wird ein solch ganzheitlicher Ansatz entwickelt. Dafür werden zunächst die Herausforderungen in der Weltwirtschaft und der Automobilindustrie im Speziellen analysiert. Einen besonderen Themenschwerpunkt bilden dabei die verschiedenen Ebenen der Veränderlichkeit. Mit der Ableitung von Prämissen unter Beachtung der gestellten Anforderungen kann eine Ordnung verschiedener Fördertechnologien erfolgen. Darauf bauend wird ein Modell entwickelt, das als Leitfaden zur Erarbeitung eines flexiblen Materialflusssystems für zukünftige Automobilproduktionen dient. Um dem Anspruch der fabrikübergreifenden Anwendbarkeit des Modells Rechnung zu tragen, erfolgt im letzten Schritt die Modellvalidierung anhand einer Fahrzeug-Fertigung in einem Brownfield-Werk.

Cognitive Computing' has initiated a new era in computer science. Cognitive computers are not rigidly programmed computers anymore, but they learn from their interactions with humans, from the environment and from information. They are thus able to perform amazing tasks on their own, such as driving a car in dense traffic, piloting an aircraft in difficult conditions, taking complex financial investment decisions, analysing medical-imaging data, and assist medical doctors in diagnosis and therapy. Cognitive computing is based on artificial intelligence, image processing, pattern recognition, robotics, adaptive software, networks and other modern computer science areas, but also includes sensors and actuators to interact with the physical world. Cognitive computers – also called 'intelligent machines' – are emulating the human cognitive, mental and intellectual capabilities. They aim to do for human mental power (the ability to use our brain in understanding and influencing our physical and information environment) what the steam engine and combustion motor did for muscle power. We can expect a massive impact of cognitive computing on life and work. Many modern complex infrastructures, such as the electricity distribution grid, railway networks, the road traffic structure, information analysis (big data), the health care system, and many more will rely on intelligent decisions taken by cognitive computers. A drawback of cognitive computers will be a shift in employment opportunities: A raising number of tasks will be taken over by intelligent machines, thus erasing entire job categories (such as cashiers, mail clerks, call and customer assistance centres, taxi and bus drivers, pilots, grid operators, air traffic controllers, …). A possibly dangerous risk of cognitive computing is the threat by “super intelligent machines” to mankind. As soon as they are sufficiently intelligent, deeply networked and have access to the physical world they may endanger many areas of human supremacy, even possibly eliminate humans. Cognitive computing technology is based on new software architectures – the “cognitive computing architectures”. Cognitive architectures enable the development of systems that exhibit intelligent behaviour.:Introduction 5 1. Applying the Subsumption Architecture to the Genesis Story Understanding System – A Notion and Nexus of Cognition Hypotheses (Felix Mai) 9 2. Benefits and Drawbacks of Hardware Architectures Developed Specifically for Cognitive Computing (Philipp Schröppe)l 19 3. Language Workbench Technology For Cognitive Systems (Tobias Nett) 29 4. Networked Brain-based Architectures for more Efficient Learning (Tyler Butler) 41 5. Developing Better Pharmaceuticals – Using the Virtual Physiological Human (Ben Blau) 51 6. Management of existential Risks of Applications leveraged through Cognitive Computing (Robert Richter) 61

The localization of autonomous ground vehicles in dense urban environments poses a challenge. Applications in classical outdoor robotics rely on the availability of GPS systems in order to estimate the position. However, the presence of complex building structures in dense urban environments hampers a reliable localization based on GPS. Alternative approaches have to be applied In order to tackle this problem. This thesis proposes an approach which combines observations of a single perspective camera and odometry in a probabilistic framework. In particular, the localization in the space of appearance is addressed. First, a topological map of reference places in the environment is built. Each reference place is associated with a set of visual features. A feature selection is carried out in order to obtain distinctive reference places. The topological map is extended to a hybrid representation by the use of metric information from Geographic Information Systems (GIS) and satellite images. The localization is solved in terms of the recognition of reference places. A particle lter implementation incorporating this and the vehicle's odometry is presented. The proposed system is evaluated based on multiple experiments in exemplary urban environments characterized by high building structures and a multitude of dynamic objects.

The paper proposes the management of bus disruption (e.g. fleet failure) and maintain a resilient transportation system through a synergy between shared autonomous vehicles and the existing public transport system based on the organizational structure and demand characteristics. The methodology is applied to the region of Rennes (France) and its surroundings.

Falls are responsible for a large proportion of serious injuries and deaths among cyclists [1-4]. A common fall scenario is loss of balance during an emergency braking maneuver to avoid another vehicle [5-7]. Automated Vehicles (AV) have the potential to prevent these critical scenarios between bicycle and cars. However, current Threat Assessment Algorithms (TAA) used by AVs only consider collision avoidance to decide upon safe gaps and decelerations when interacting wih cyclists and do not consider bicycle specific balance-related constraints. To date, no studies have addressed this risk of falls in safety critical scenarios. Yet, given the bicycle dynamics, we hypothesized that the existing TAA may be inaccurate in predicting the threat of cyclist falls and misclassify unsafe interactions. To test this hypothesis, this study developed a simple Newtonian mechanics-based model that calculates the performance of two existing TAAs in four critical scenarios with two road conditions. Tue four scenarios are: (1) a crossing scenario and a bicycle following lead car scenario in which the car either (2) suddenly braked, (3) halted or (4) accelerated from standstill. These scenarios have been identified by bicycle-car conflict studies as common scenarios where the car driver elicits an emergency braking response of the cyclist [8-11] and are illustrated in Figure 1. The two TAAs are Time-to-Collision (TTC) and Headway (H). These TAAs are commonly used by AVs in the four critical scenarios that will be modelled. The two road conditions are a flat dry road and also a downhill wet road, which serves as a worst-case condition for loss of balance during emergency braking [12].