Fault-Tolerance by Graceful Degradation for Car Platoons

The key advantage of autonomous car platoons are their short inter-vehicle distances that increase traffic flow and reduce fuel consumption. However, this is challenging for operational and functional safety. If a failure occurs, the affected vehicles cannot suddenly stop driving but instead should continue their operation with reduced performance until a safe state can be reached or, in the case of temporal failures, full functionality can be guaranteed again. To achieve this degradation, platoon members have to be able to compensate sensor and communication failures and have to adjust their inter-vehicle distances to ensure safety. In this work, we describe a systematic design of degradation cascades for sensor and communication failures in autonomous car platoons using the example of an autonomous model car. We describe our systematic design method, the resulting degradation modes, and formulate contracts for each degradation level. We model and test our resulting degradation controller in Simulink/Stateflow

Chaplygin gas braneworld inflation according to WMAP7 data

We consider a Chaplygin gas model with an exponential potential in framework of braneworld inflation. We apply the slow-roll approximation in the high-energy limit to derive various inflationary spectrum perturbation parameters. We show that the inflation observables depend only on the e-folding number N and the final value of the slow-roll parameter e(end). Whereas for small running of the scalar spectral index dns/dlnk, the inflation observables are in good agreement with recent WMAP7 data.Comment: 5 pages, 3 figure

A Stochastic Nonlinear Model Predictive Control with an Uncertainty Propagation Horizon for Autonomous Vehicle Motion Control

Employing Stochastic Nonlinear Model Predictive Control (SNMPC) for real-time applications is challenging due to the complex task of propagating uncertainties through nonlinear systems. This difficulty becomes more pronounced in high-dimensional systems with extended prediction horizons, such as autonomous vehicles. To enhance closed-loop performance in and feasibility in SNMPCs, we introduce the concept of the Uncertainty Propagation Horizon (UPH). The UPH limits the time for uncertainty propagation through system dynamics, preventing trajectory divergence, optimizing feedback loop advantages, and reducing computational overhead. Our SNMPC approach utilizes Polynomial Chaos Expansion (PCE) to propagate uncertainties and incorporates nonlinear hard constraints on state expectations and nonlinear probabilistic constraints. We transform the probabilistic constraints into deterministic constraints by estimating the nonlinear constraints' expectation and variance. We then showcase our algorithm's effectiveness in real-time control of a high-dimensional, highly nonlinear system-the trajectory following of an autonomous passenger vehicle, modeled with a dynamic nonlinear single-track model. Experimental results demonstrate our approach's robust capability to follow an optimal racetrack trajectory at speeds of up to 37.5m/s while dealing with state estimation disturbances, achieving a minimum solving frequency of 97Hz. Additionally, our experiments illustrate that limiting the UPH renders previously infeasible SNMPC problems feasible, even when incorrect uncertainty assumptions or strong disturbances are present

Élaboration d'un modèle de conception de système de mesure de performance

Les systèmes de mesure de performance jouent un rôle très important dans les organisations pour différentes raisons: la prise de décision, le contrôle, l'apprentissage et rétroaction et la diffusion de l'information aux parties prenantes notamment les actionnaires. Pendant longtemps la conception économique de la performance organisationnelle a dominé. L'évaluation de la performance ne reposait que sur des critères financiers qui ne reflétaient que la performance historique. Les systèmes de mesure de performance ont depuis évolué vers la mesure d'actifs intangible tels la compétence des ressources humaines et la propriété intellectuelle.\ud Plusieurs cadres conceptuels et systèmes de mesure de performance (SMP) ont été introduits dans la littérature dont le tableau de bord prospectif (TBP) (Kaplan et Norton, 1996, 2001, 2004) qui est largement utilisé. Le TBP conçoit la performance organisationnelle en quatre dimensions interreliées par des liens de cause à effet: 1) dimension financière, 2) dimension client, 3) dimension processus internes et, 4) dimension capacités d'apprentissage et d'innovation. Toutefois, ce modèle a été souvent critiqué pour ses dimensions externes limitées à la satisfaction des actionnaires et des clients alors que l'entreprise dépend de plusieurs parties prenantes. De cette problématique liée à la conception des SMP, découle la question de recherche suivante: Quelles sont les dimensions internes et environnementales qui doivent être prises en considération dans la conception d'un tableau de bord de mesure de performance organisationnelle? Ce projet de recherche poursuit deux principaux objectifs: 1) élaborer un modèle conceptuel, empirique, qui intègre les principales dimensions internes et environnementales permettant de mesurer la performance organisationnelle et, 2) répondre à un besoin, exprimé par les entreprises du secteur des nutraceutiques et aliments fonctionnels, qui consiste à identifier les indicateurs et les facteurs clés de performance de ces entreprises. Pour atteindre les objectifs de cette recherche, une stratégie par étude de trois cas d'entreprises dans le secteur des nutraceutiques et aliments fonctionnels a été employée. Les données ont été recueillies par le biais d'entrevues semi-structurées et de documents. Ensuite, des analyses intra et inter cas ont été réalisées. Les résultats de cette recherche montrent effectivement qu'il existe d'autres parties prenantes qu'il faut considérer dans la mesure de performance organisationnelle. Les dimensions communes identifiées sont sur deux volets : 1) les résultats de performance: actionnaires, clients, concurrents, employés et, 2) les déterminants de performance: parties prenantes (fournisseurs, centre de recherche/Université, employé et réglementation), performance des processus critiques et capacités. ______________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : Tableaux de bord (AIS ACO8), Balanced scorecard, Systèmes d'aide à la décision (MISQ : \ud DECISION SUPPORT SYSTEMS, HA03), Performance organisationnelle, Mesure de performance organisationnelle

Beauty and Artistic Values in the thought of Zaki Naguib Mahmoud

تهدف هذه الدراسة إلى بيان ماهية القيم الجمالية والفنية عند المفكر "زكى نجيب محمود" ،وكيف أنه يقر بنسبيتها،وعدم ثباتها،فى مواجهة الإتجاهات اللاّهوتية التى كانت تقول بالقيم المطلقة،وقد استند فى رؤيته هذه على تحليل العبارات الجمالية والأخلاقية، والتى رآها تعبيرًا عن انفعال، وأن الشخص هو الذى يضفى على الشئ قيمته الجمالية بناءً على رغبته، ولا وجود لشئ جميل فى ذاته.This study aims to explain what the aesthetic and artistic values of the thinker "Zaki Naguib Mahmoud" are, and how he acknowledges their relativity, and their inconsistency, in the face of theological trends that used to say absolute values. And that the person is the one who bestows on a thing its aesthetic value according to his desire, and that there is nothing beautiful in itself

R2^2NMPC: A Real-Time Reduced Robustified Nonlinear Model Predictive Control with Ellipsoidal Uncertainty Sets for Autonomous Vehicle Motion Control

In this paper, we present a novel Reduced Robustified NMPC (R$^2$NMPC) algorithm that has the same complexity as an equivalent nominal NMPC while enhancing it with robustified constraints based on the dynamics of ellipsoidal uncertainty sets. This promises both a closed-loop- and constraint satisfaction performance equivalent to common Robustified NMPC approaches, while drastically reducing the computational complexity. The main idea lies in approximating the ellipsoidal uncertainty sets propagation over the prediction horizon with the system dynamics' sensitivities inferred from the last optimal control problem (OCP) solution, and similarly for the gradients to robustify the constraints. Thus, we do not require the decision variables related to the uncertainty propagation within the OCP, rendering it computationally tractable. Next, we illustrate the real-time control capabilities of our algorithm in handling a complex, high-dimensional, and highly nonlinear system, namely the trajectory following of an autonomous passenger vehicle modeled with a dynamic nonlinear single-track model. Our experimental findings, alongside a comparative assessment against other Robust NMPC approaches, affirm the robustness of our method in effectively tracking an optimal racetrack trajectory while satisfying the nonlinear constraints. This performance is achieved while fully utilizing the vehicle's interface limits, even at high speeds of up to 37.5m/s, and successfully managing state estimation disturbances. Remarkably, our approach maintains a mean solving frequency of 144Hz

The islet estrogen receptor-alpha is induced by hyperglycemia and protects against oxidative stress-induced insulin-deficient diabetes

The female steroid, 17beta-estradiol (E2), is important for pancreatic beta-cell function and acts via at least three estrogen receptors (ER), ERalpha, ERbeta, and the G-protein coupled ER (GPER). Using a pancreas-specific ERalpha knockout mouse generated using the Cre-lox-P system and a Pdx1-Cre transgenic line (PERalphaKO (-)/(-)), we previously reported that islet ERalpha suppresses islet glucolipotoxicity and prevents beta-cell dysfunction induced by high fat feeding. We also showed that E2 acts via ERalpha to prevent beta-cell apoptosis in vivo. However, the contribution of the islet ERalpha to beta-cell survival in vivo, without the contribution of ERalpha in other tissues is still unclear. Using the PERalphaKO (-)/(-) mouse, we show that ERalpha mRNA expression is only decreased by 20% in the arcuate nucleus of the hypothalamus, without a parallel decrease in the VMH, making it a reliable model of pancreas-specific ERalpha elimination. Following exposure to alloxan-induced oxidative stress in vivo, female and male PERalphaKO (-)/(-) mice exhibited a predisposition to beta-cell destruction and insulin deficient diabetes. In male PERalphaKO (-)/(-) mice, exposure to E2 partially prevented alloxan-induced beta-cell destruction and diabetes. ERalpha mRNA expression was induced by hyperglycemia in vivo in islets from young mice as well as in cultured rat islets. The induction of ERalpha mRNA by hyperglycemia was retained in insulin receptor-deficient beta-cells, demonstrating independence from direct insulin regulation. These findings suggest that induction of ERalpha expression acts to naturally protect beta-cells against oxidative injury