Les systèmes temps-réel critiques doivent exécuter leurs tâches dans les délais impartis. En cas de défaillance, des événements peuvent avoir des catastrophes économiques. Des classifications des défaillances par rapport aux niveaux des risques encourus ont été établies, en particulier dans les domaines des transports aéronautique et automobile. Des niveaux de criticité sont attribués aux différentes fonctions des systèmes suivant les risques encourus lors d'une défaillance et des probabilités d'apparition de celles-ci. Ces différents niveaux de criticité influencent les choix d'architecture logicielle et matérielle ainsi que le type de composants utilisés pour sa réalisation. Les systèmes temps-réels modernes ont tendance à intégrer sur une même plateforme de calcul plusieurs applications avec différents niveaux de criticité. Cette intégration est nécessaire pour des systèmes modernes comme par exemple les drones (UAV) afin de réduire le coût, le poids et la consommation d'énergie. Malheureusement, elle conduit à des difficultés importantes lors de leurs conceptions. En plus, ces systèmes doivent être certifiés en prenant en compte ces différents niveaux de criticités.Il est bien connu que le problème d'ordonnancement des systèmes avec différents niveaux de criticités représente un des plus grand défi dans le domaine de systèmes temps-réel. Les techniques traditionnelles proposent comme solution l’isolation complète entre les niveaux de criticité ou bien une certification globale au plus haut niveau. Malheureusement, une telle solution conduit à une mauvaise des ressources et à la perte de l’avantage de cette intégration. En 2007, Vestal a proposé un modèle pour représenter les systèmes avec différents niveaux de criticité dont les tâches ont plusieurs temps d’exécution, un pour chaque niveau de criticité. En outre, les conditions de validité des stratégies d’ordonnancement ont été définies de manière formelle, permettant ainsi aux tâches les moins critiques d’échapper aux délais, voire d’être abandonnées en cas de défaillance ou de situation d’urgence.Les politiques de planification conventionnelles et les tests d’ordonnoncement se sont révélés inadéquats.Dans cette thèse, nous contribuons à l’étude de l’ordonnancement dans les systèmes avec différents niveaux de criticité. La surcharge d'un système est représentée sous la forme d'un ensemble de tâches pouvant décrire l'exécution sur l'hyper-période de tâches ou sur une durée donnée. Ce modèle nous permet d’étudier la viabilité des tests de correction basés sur la simulation pour les systèmes avec différents niveaux de criticité. Nous montrons que les tests de simulation peuvent toujours être utilisés pour ces systèmes, et la possibilité de l’ordonnancement du pire des scénarios ne suffit plus, même pour le cas de l’ordonnancement avec priorité fixe. Nous montrons que les politiques d'ordonnancement ne sont généralement pas prévisibles. Nous définissons le concept de faible prévisibilité pour les systèmes avec différents niveaux de criticité et nous montrons ensuite qu'une classe spécifique de stratégies à priorité fixe sont faiblement prévisibles. Nous proposons deux tests de correction basés sur la simulation qui fonctionnent pour des stratégies faiblement prévisibles.Nous montrons également que, contrairement à ce que l’on croyait, le contrôle de l’exactitude ne peut se faire que par l’intermédiaire d’un nombre linéaire de préemptions.La majorité des travaux reliés à notre domaine portent sur des systèmes à deux niveaux de criticité en raison de la difficulté du problème. Mais pour les systèmes automobiles et aériens, les normes industrielles définissent quatre ou cinq niveaux de criticité, ce qui nous a motivés à proposer un algorithme de planification qui planifie les systèmes à criticité mixte avec théoriquement un nombre quelconque de niveaux de criticité. Nous montrons expérimentalement que le taux de réussite est supérieur à celui de l’état de la technique. / Real-time safety-critical systems must complete their tasks within a given time limit. Failure to successfully perform their operations, or missing a deadline, can have severe consequences such as destruction of property and/or loss of life. Examples of such systems include automotive systems, drones and avionics among others. Safety guarantees must be provided before these systems can be deemed usable. This is usually done through certification performed by a certification authority.Safety evaluation and certification are complicated and costly even for smaller systems.One answer to these difficulties is the isolation of the critical functionality. Executing tasks of different criticalities on separate platforms prevents non-critical tasks from interfering with critical ones, provides a higher guaranty of safety and simplifies the certification process limiting it to only the critical functions. But this separation, in turn, introduces undesirable results portrayed by an inefficient resource utilization, an increase in the cost, weight, size and energy consumption which can put a system in a competitive disadvantage.To overcome the drawbacks of isolation, Mixed Criticality (MC) systems can be used. These systems allow functionalities with different criticalities to execute on the same platform. In 2007, Vestal proposed a model to represent MC-systems where tasks have multiple Worst Case Execution Times (WCETs), one for each criticality level. In addition, correctness conditions for scheduling policies were formally defined, allowing lower criticality jobs to miss deadlines or be even dropped in cases of failure or emergency situations.The introduction of multiple WCETs and different conditions for correctness increased the difficulty of the scheduling problem for MC-systems. Conventional scheduling policies and schedulability tests proved inadequate and the need for new algorithms arose. Since then, a lot of work has been done in this field.In this thesis, we contribute to the study of schedulability in MC-systems. The workload of a system is represented as a set of jobs that can describe the execution over the hyper-period of tasks or over a duration in time. This model allows us to study the viability of simulation-based correctness tests in MC-systems. We show that simulation tests can still be used in mixed-criticality systems, but in this case, the schedulability of the worst case scenario is no longer sufficient to guarantee the schedulability of the system even for the fixed priority scheduling case. We show that scheduling policies are not predictable in general, and define the concept of weak-predictability for MC-systems. We prove that a specific class of fixed priority policies are weakly predictable and propose two simulation-based correctness tests that work for weakly-predictable policies.We also demonstrate that contrary to what was believed, testing for correctness can not be done only through a linear number of preemptions.The majority of the related work focuses on systems of two criticality levels due to the difficulty of the problem. But for automotive and airborne systems, industrial standards define four or five criticality levels, which motivated us to propose a scheduling algorithm that schedules mixed-criticality systems with theoretically any number of criticality levels. We show experimentally that it has higher success rates compared to the state of the art.We illustrate how our scheduling algorithm, or any algorithm that generates a single time-triggered table for each criticality mode, can be used as a recovery strategy to ensure the safety of the system in case of certain failures.Finally, we propose a high level concurrency language and a model for designing an MC-system with coarse grained multi-core interference.

This dissertation is devoted to study of complex systems in human physiology particularly heartbeats and brain dynamics. We have studied the dynamics of heartbeats that has been a subject of investigation of two independent groups. The first group emphasized the multifractal nature of the heartbeat dynamics of healthy subjects, whereas the second group had established a close connection between healthy subjects and the occurrence of crucial events. We have analyzed the same set of data and established that in fact the heartbeats are characterized by the occurrence of crucial and Poisson events. An increase in the percentage of crucial events makes the multifractal spectrum broader, thereby bridging the results of the former group with the results of the latter group. The crucial events are characterized by a power index that signals the occurrence of 1/f noise for complex systems in the best physiological condition. These results led us to focus our analysis on the statistical properties of crucial events. We have adopted the same statistical analysis to study the statistical properties of the heartbeat dynamics of subjects practicing meditation. The heartbeats of people doing meditation are known to produce coherent fluctuations. In addition to this effect, we made the surprising discovery that meditation makes the heartbeat depart from the ideal condition of 1/f noise. We also discussed how to combine the wave-like nature of the dynamics of the brain with the existence of crucial events that are responsible for the 1/f noise. We showed that the anomalous scaling generated by the crucial events could be established by means of a direct analysis of raw data. The efficiency of the direct analysis procedure is made possible by the fact that periodicity and crucial events is the product of a spontaneous process of self-organization. We argue that the results of this study can be used to shed light into the nature of this process of self-organization.

In this thesis I investigate several aspects of local quantum criticality, a concept of key importance in a number of physical contexts ranging from critical heavy fermion compounds to quantum dot systems. Quantum critical points are associated with second order phase transitions at zero temperature. In contrast to their finite-temperature counterparts, the zero-point motion cannot be neglected near a quantum critical point. As a result, the incorporation of quantum dynamics leads to an effective dimension larger than the spatial dimension of the system for the order parameter fluctuations within the Ginzburg-Landau-Wilson treatment of criticality. This so-called quantum-to-classical mapping works well for the critical properties in insulating systems but apparently fails in systems containing gapless fermions. This has been experimentally most clearly been demonstrated within a particular class of intermetallic compounds called heavy fermions. A particular way in which the Ginzburg-Landau-Wilson paradigm fails is for critical Kondo destruction that seems to underlie the unconventional quantum criticality seen in the heavy fermions. I focus on studying the properties of critical Kondo destruction and the emergence of energy-over-temperature-scaling in systems without spatial degrees of freedom, i.e., so-called quantum impurity systems. In particular, I employ large-N techniques to address critical properties of this class of quantum phase transitions in and out of equilibrium. As quantum critical systems are characterized by a scale-invariant spectrum with many low-lying excitations, it may appear that any perturbation can lead to a response beyond the linear response regime. Understanding what governs the non-linear response regime near quantum criticality is an interesting area. Here, I first present a path integral version of the Schrieffer-Wolff transformation which relates the functional integral form of the partition function of the Anderson model to that of its effective low-energy model. The equivalence between the low-energy sector of the Anderson model in the Kondo regime and the spin-isotropic Kondo model is usually established via a canonical transformation performed on the Hamiltonian, followed by a projection. The resulting functional integral assumes the form of a spin path integral and includes a geometric phase factor, i.e. a Berry phase. The approach stresses the underlying symmetries of the model and allows for a straightforward generalization of the transformation to more involved models. As an example of the efficiency of the approach I apply it to a single electron transistor attached to ferromagnetic leads and derive the effective low-energy model of such a magnetic transistor. As Kondo screening is a local phenomenon, it and its criticality can be studied using the appropriate impurity model. A general impurity model to study critical Kondo destruction is the pseudogap Bose-Fermi Kondo model. Here, I concentrate on the multi-channel version of the model using the dynamical large-N study. This model allows to study the non-trivial interplay between two different mechanisms of critical Kondo destruction. The interplay of two processes that can each by itself lead to critical Kondo destruction. The zero-temperature residual entropy at various fixed points for the model is also discussed. The two channel Anderson model exhibits several continuous quantum phase transitions between weak- and strong-coupling phases. The non-crossing approximation (NCA) is believed to give reliable results for the standard two-channel Anderson model of a magnetic impurity in a metal. I revisit the reliability of the NCA for the standard two channel Anderson model (constant conduction electron density of states) and investigate its reliability for the two-channel pseudogap Anderson model. This is done by comparing finite-temperature, finite-frequency solutions of the NCA equations and asymptotically exact zero-temperature NCA solutions with numerical renormalization-group calculations. The phase diagram of this model is well established. The focus here will be on the dynamical scaling properties obtained within the NCA. Finally, I study the thermal and non-thermal steady state scaling functions and the steady-state dynamics of the pseudogap Kondo model. This model allows us to study the concept of effective temperatures near fully interacting as well as weak-coupling fixed points and compare the out-of-equilibrium scaling properties of critical Kondo destruction to those of the traditional spin-density wave (SDW) scenario. The differences I identify can be experimentally probed. This may be helpful in identifying the nature of the quantum critical points observed in certain heavy fermion compounds.

In der vorliegenden Arbeit wurde der elektrische Transport im Schwere-Fermionen-System YbRh2Si2 sowohl in seiner stöchiometrischen Form als auch mit teilweiser isoelektronischer Substitution von Ir oder Co auf dem Rh-Platz untersucht. In YbRh2Si2 liegt ein quantenkritischer Punkt vor, der zugänglich ist, indem der antiferromagnetische Phasenübergang mittels eines kleinen Magnetfelds zum absoluten Nullpunkt der Temperatur unterdrückt wird. Die zentralen Messungen des Hallkoeffizienten zeigen einen Übergang der in der Extrapolation zu T=0 zu einer Diskontinuität wird und somit auf eine Rekonstruktion der Fermifläche am quantenkritischen Punkt schließen lässt. Dies belegt die unkonventionelle Natur der Quantenkritikalität in YbRh2Si2. Unterstützt wird dies auf fundamentale Weise durch verknüpfungen mit unkonventionellem Skalierungsverhalten. In den Proben mit teilweiser Substitution wird der Einfluss einer Veränderung der Gitterparameter auf die Quantenkritikalität mit Hilfe von Widerstandsmessungen untersucht. Dabei zeigt sich, dass der magnetische Übergang von der Fermiflächenrekonstruktion separiert wird. Für Proben mit teilweiser Ir-Substitution, welche negativen Drücken entspricht, scheint im Zwischenbereich eine neuartige metallische Spinflüssigkeit hervorzutreten. / This work investigates the electrical transport of the heavy-fermion compound YbRh2Si2 in its stoichiometric form as well as with slight isoelectronic substitution of Ir or Co on the Rh site. A quantum critical point is present in YbRh2Si2 which is accessed by tuning the transition temperature of the antiferromagnetic order to absolute zero via the application of a small magnetic field. The central measurements of the Hall coefficient reveal a crossover which sharpens to a discontinuity in the extrapolation to zero temperature implying a reconstruction of the Fermi surface at the quantum critical point. This allows to rule out conventional descriptions of the quantum criticality in YbRh2Si2. A scaling analysis corroborates this on a fundamental basis. In the samples with partial substitution the effect of unit cell volume change on the quantum criticality was investigated by means of resistivity measurements. Surprisingly, the magnetic transition is separated from the Fermi surface reconstruction. For samples with Ir substitution corresponding to negative chemical pressure, a new metallic spin liquid seems to emerge in the intermediate regime.

L’émergence de la complexité, et de la vie en particulier, demeure l’une des énigmes les plus complexes pour la science moderne. Des travaux récents ont souligné la pertinence d’un apport de la physique statistique et de la théorie des phénomènes critiques — et en particulier de la théorie des phénomènes à criticalité auto-régulée — relativement à ces champs d’intérêt, tout autant que du rôle des phénomènes de coopération biochimique dans les premiers instants du vivant. La description des mécanismes par lesquels la vie a pu apparaître est par ailleurs d’un intérêt pratique pour l’astrophysique, puisque notre compréhension de ceux-ci module la manière dont l’analyse de biosignatures s’effectue dans le cadre de la recherche de la vie ailleurs dans l’Univers. L’analyse proposée ici porte sur un modèle en théorie des jeux permettant d’étudier les phénomènes de coopération implémenté dans un contexte spatial servant à émuler la dynamique d’un système ayant pu voir apparaître la vie. Une analyse de l’espace des paramètres du modèle révèle que celui-ci affiche des phénomènes de transition de phase et d’auto-organisation de structures spatiales, ces éléments se révélant des adjuvants à l’émergence de la coopération entre joueurs a priori égoïstes, dans un contexte qui à prime abord n’est pas d’emblée favorable à l’apparition de comportements coopératifs. Les résultats obtenus ici semblent supporter que la coopération biochimique puisse apparaître via un phénomène de transition de phase et que le modèle sous-jacent de dilemme du prisonnier itéré sur réseau présenté ici agit comme un système à criticalité autorégulée. / The emergence of complexity, and of life more specifically, is still one of the most intractable conundrums for modern science. Recent work emphasized the relevance of statistical physics and critical phenomena theory’s contribution to those questions — especially of self-organized criticality theory — just as much as the role of biochemical cooperation in life’s first moments. Moreover, the description of the mechanisms by which life could have appeared is of particular interest for astrophysics, because our comprehension of those mechanisms influences how biosignatures are analyzed in the context of the search for life elsewhere in the Universe. The analysis presented here concerns a model in game theory that allows to study cooperation phenomena — implemented in spatial context as to emulate the dynamics of a system in which life could have appeared. An analysis of the model’s parameter space reveals that it displays phase transition and self-organization of spatial structures phenomenon, those elements being adjuvants to the emergence of cooperation between a priori egoist players, in a context that is initially not favorable to the emergence of cooperative behavior. The results obtained here thus seem to support the idea that both biochemical cooperation can emerge through phase transition phenomena, and that the underlying lattice iterated prisoner’s dilemma model used here behaves like a self-organized critical system.

Environ 25% de la population mondiale est atteinte de troubles psychiatriques qui sont typiquement associés à des problèmes comportementaux, fonctionnels et/ou cognitifs et dont les corrélats neurophysiologiques sont encore très mal compris. Non seulement ces dysfonctionnements réduisent la qualité de vie des individus touchés, mais ils peuvent aussi devenir un fardeau pour les proches et peser lourd dans l’économie d’une société. Cibler les mécanismes responsables du fonctionnement atypique du cerveau en identifiant des biomarqueurs plus robustes permettrait le développement de traitements plus efficaces. Ainsi, le premier objectif de cette thèse est de contribuer à une meilleure caractérisation des changements dynamiques cérébraux impliqués dans les troubles mentaux, plus précisément dans la schizophrénie et les troubles d’humeur. Pour ce faire, les premiers chapitres de cette thèse présentent, en intégral, deux revues de littératures systématiques que nous avons menées sur les altérations de connectivité cérébrale, au repos, chez les patients schizophrènes, dépressifs et bipolaires. Ces revues révèlent que, malgré des avancées scientifiques considérables dans l’étude de l’altération de la connectivité cérébrale fonctionnelle, la dimension temporelle des mécanismes cérébraux à l’origine de l’atteinte de l’intégration de l’information dans ces maladies, particulièrement de la schizophrénie, est encore mal comprise. Par conséquent, le deuxième objectif de cette thèse est de caractériser les changements cérébraux associés à la schizophrénie dans le domaine temporel. Nous présentons deux études dans lesquelles nous testons l’hypothèse que la « disconnectivité temporelle » serait un biomarqueur important en schizophrénie. Ces études explorent les déficits d’intégration temporelle en schizophrénie, en quantifiant les changements de la dynamique neuronale dite invariante d’échelle à partir des données magnétoencéphalographiques (MEG) enregistrés au repos chez des patients et des sujets contrôles. En particulier, nous utilisons (1) la LRTCs (long-range temporal correlation, ou corrélation temporelle à longue-distance) calculée à partir des oscillations neuronales et (2) des analyses multifractales pour caractériser des modifications de l’activité cérébrale arythmique. Par ailleurs, nous développons des modèles de classification (en apprentissage-machine supervisé) pour mieux cerner les attributs corticaux et sous-corticaux permettant une distinction robuste entre les patients et les sujets sains. Vu que ces études se basent sur des données MEG spontanées enregistrées au repos soit avec les yeux ouvert, ou les yeux fermées, nous nous sommes par la suite intéressés à la possibilité de trouver un marqueur qui combinerait ces enregistrements. La troisième étude originale explore donc l’utilité des modulations de l’amplitude spectrale entre yeux ouverts et fermées comme prédicteur de schizophrénie. Les résultats de ces études démontrent des changements cérébraux importants chez les patients schizophrènes au niveau de la dynamique d’invariance d’échelle. Elles suggèrent une dégradation du traitement temporel de l’information chez les patients, qui pourrait être liée à leurs symptômes cognitifs et comportementaux. L’approche multimodale de cette thèse, combinant la magétoencéphalographie, analyses non-linéaires et apprentissage machine, permet de mieux caractériser l’organisation spatio-temporelle du signal cérébrale au repos chez les patients atteints de schizophrénie et chez des individus sains. Les résultats fournissent de nouvelles preuves supportant l’hypothèse d’une « disconnectivité temporelle » en schizophrénie, et étendent les recherches antérieures, en explorant la contribution des structures cérébrales profondes et en employant des mesures non-linéaires avancées encore sous-exploitées dans ce domaine. L’ensemble des résultats de cette thèse apporte une contribution significative à la quête de nouveaux biomarqueurs de la schizophrénie et démontre l’importance d’élucider les altérations des propriétés temporelles de l’activité cérébrales intrinsèque en psychiatrie. Les études présentées offrent également un cadre méthodologique pouvant être étendu à d’autres psychopathologie, telles que la dépression. / Psychiatric disorders affect nearly a quarter of the world’s population. These typically bring about debilitating behavioural, functional and/or cognitive problems, for which the underlying neural mechanisms are poorly understood. These symptoms can significantly reduce the quality of life of affected individuals, impact those close to them, and bring on an economic burden on society. Hence, targeting the baseline neurophysiology associated with psychopathologies, by identifying more robust biomarkers, would improve the development of effective treatments. The first goal of this thesis is thus to contribute to a better characterization of neural dynamic alterations in mental health illnesses, specifically in schizophrenia and mood disorders. Accordingly, the first chapter of this thesis presents two systematic literature reviews, which investigate the resting-state changes in brain connectivity in schizophrenia, depression and bipolar disorder patients. Great strides have been made in neuroimaging research in identifying alterations in functional connectivity. However, these two reviews reveal a gap in the knowledge about the temporal basis of the neural mechanisms involved in the disruption of information integration in these pathologies, particularly in schizophrenia. Therefore, the second goal of this thesis is to characterize the baseline temporal neural alterations of schizophrenia. We present two studies for which we hypothesize that the resting temporal dysconnectivity could serve as a key biomarker in schizophrenia. These studies explore temporal integration deficits in schizophrenia by quantifying neural alterations of scale-free dynamics using resting-state magnetoencephalography (MEG) data. Specifically, we use (1) long-range temporal correlation (LRTC) analysis on oscillatory activity and (2) multifractal analysis on arrhythmic brain activity. In addition, we develop classification models (based on supervised machine-learning) to detect the cortical and sub-cortical features that allow for a robust division of patients and healthy controls. Given that these studies are based on MEG spontaneous brain activity, recorded at rest with either eyes-open or eyes-closed, we then explored the possibility of finding a distinctive feature that would combine both types of resting-state recordings. Thus, the third study investigates whether alterations in spectral amplitude between eyes-open and eyes-closed conditions can be used as a possible marker for schizophrenia. Overall, the three studies show changes in the scale-free dynamics of schizophrenia patients at rest that suggest a deterioration of the temporal processing of information in patients, which might relate to their cognitive and behavioural symptoms. The multimodal approach of this thesis, combining MEG, non-linear analyses and machine-learning, improves the characterization of the resting spatiotemporal neural organization of schizophrenia patients and healthy controls. Our findings provide new evidence for the temporal dysconnectivity hypothesis in schizophrenia. The results extend on previous studies by characterizing scale-free properties of deep brain structures and applying advanced non-linear metrics that are underused in the field of psychiatry. The results of this thesis contribute significantly to the identification of novel biomarkers in schizophrenia and show the importance of clarifying the temporal properties of altered intrinsic neural dynamics. Moreover, the presented studies offer a methodological framework that can be extended to other psychopathologies, such as depression.

No description available.

Sr₃Ru₂O₇ is a quasi-two-dimensional metal and has a paramagnetic ground state that is heavily renormalised by electron-electron correlations and magnetic exchange interactions. Inextricably linked to this renormalisation is the metamagnetism of Sr₃Ru₂O₇ - a rapid rise in uniform magnetisation over a narrow range of applied magnetic field. Knowledge of the zero-field physics is essential to any description of the metamagnetism. Light may be shed on the enigmatic ground state of Sr₃Ru₂O₇ by doping the crystal lattice with foreign cations: this is the primary purpose of the original research referred to in this thesis, in which studies of some of the electronic properties of crystals of cation-doped Sr₃Ru₂O₇ are reported. Single crystals of Sr₃(Ru[subscript(1-x)]Ti[subscript(x)])₂O₇ and Sr₃(Ru[subscript(1-x)]Cr[subscript(x)])₂O₇ have been synthesised in an image furnace and some of the properties of these crystals have been measured. Evidence that indicates the emergence of a spin density wave as a function of Ti-doping in Sr₃(Ru[subscript(1-x)]Ti[subscript(x)])₂O₇ is presented. Time-dependent magnetic irreversibility has been observed in samples of Sr₃(Ru[subscript(1-x)]Cr[subscript(x)])₂O₇, thus hinting at the involvement of the RKKY mechanism in these materials. Regarding cation doping out of the conducting RuO₂ planes, samples of (Sr[subscript(1-y)]La[subscript(y)])₃Ru₂O₇ have been grown and investigated. Both the Sommerfeld coefficient and the Fermi liquid A coefficient of (Sr[subscript(1-y)]La[subscript(y)])₃Ru₂O₇ are found to decrease as a function of y (0 ≤ y ≤ 0.02); these observations point towards a reduction in the thermodynamic mass of the Landau quasiparticles. Results from magnetoresistance and magnetisation measurements indicate that the metamagnetism of the (Sr[subscript(1-y)]La[subscript(y)])₃Ru₂O₇ series probably cannot be explained by a rigid band-shift model. Also, some aspects of these data imply that the metamagnetism cannot be fully accounted for by a spin fluctuation extension to the Ginzburg-Landau theory of uniform magnetisation.

New automated vehicles have the chance of high improvements to road safety. Nevertheless, from today's perspective, accidents will always be a part of future mobility. Following the “Vision Zero”, this thesis proposes the quantification of the driving situation's criticality as the basis to intervene by newly integrated safety systems. In the example application of trajectory planning, a continuous, real-time, risk-based criticality measure is used to consider uncertainties by collision probabilities as well as technical accident severities. As result, a smooth transition between preventative driving, collision avoidance, and collision mitigation including impact point localization is enabled and shown in fleet data analyses, simulations, and real test drives. The feasibility in automated driving is shown with currently available test equipment on the testing ground. Systematic analyses show an improvement of 20-30 % technical accident severity with respect to the underlying scenarios. That means up to one-third less injury probability for the vehicle occupants. In conclusion, predicting the risk preventively has a high chance to increase the road safety and thus to take the “Vision Zero” one step further.:Abstract Acknowledgements Contents Nomenclature 1.1 Background 1.2 Problem statement and research question 1.3 Contribution 2 Fundamentals and relatedWork 2.1 Integral safety 2.1.1 Integral applications 2.1.2 Accident Severity 2.1.2.1 Severity measures 2.1.2.2 Severity data bases 2.1.2.3 Severity estimation 2.1.3 Risk assessment in the driving process 2.1.3.1 Uncertainty consideration 2.1.3.2 Risk as a measure 2.1.3.3 Criticality measures in automated driving functions 2.2 Operational motion planning 2.2.1 Performance of a driving function 2.2.1.1 Terms related to scenarios 2.2.1.2 Evaluation and approval of an automated driving function 2.2.2 Driving function architecture 2.2.2.1 Architecture 2.2.2.2 Planner 2.2.2.3 Reference planner 2.2.3 Ethical issues 3 Risk assessment 3.1 Environment model 3.2 Risk as expected value 3.3 Collision probability and most probable collision configuration 4 Accident severity prediction 4.1 Mathematical preliminaries 4.1.1 Methodical approach 4.1.2 Output definition for pedestrian collisions 4.1.3 Output definition for vehicle collisions 4.2 Prediction models 4.2.1 Eccentric impact model 4.2.2 Centric impact model 4.2.3 Multi-body system 4.2.4 Feedforward neural network 4.2.5 Random forest regression 4.3 Parameterisation 4.3.1 Reference database 4.3.2 Training strategy 4.3.3 Model evaluation 5 Risk based motion planning 5.1 Ego vehicle dynamic 5.2 Reward function 5.3 Tuning of the driving function 5.3.1 Tuning strategy 5.3.2 Tuning scenarios 5.3.3 Tuning results 6 Evaluation of the risk based driving function 6.1 Evaluation strategy 6.2 Evaluation scenarios 6.3 Test setup and simulation environment 6.4 Subsequent risk assessment of fleet data 6.4.1 GIDAS accident database 6.4.2 Fleet data Hamburg 6.5 Uncertainty-adaptive driving 6.6 Mitigation application 6.6.1 Real test drives on proving ground 6.6.2 Driving performance in simulation 7 Conclusion and Prospects References List of Tables List of Figures A Extension to the tuning process