Browsing by Keyword "General Computer Science"
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Item Algorithm development for night charging electric vehicles optimization in big data applications(2017) Alvaro-Hermana, Roberto; Fraile-Ardanuy, Jesús; Merino, Julia; Tecnalia Research & InnovationIn this paper a night charging method that optimizes the recharging process of electric vehicles (EVs) depending on hourly energy price in a peer to peer (P2P) energy trading system is presented. This algorithm determines how much energy should be recharged in the battery of each EV and the corresponding time slot to do it, avoiding the discontinuities in the charging process and considering the users’ personal mobility constraints.Item AMASS: A Large-Scale European Project to Improve the Assurance and Certification of Cyber-Physical Systems: A Large-Scale European Project to Improve the Assurance and Certification of Cyber-Physical Systems(Springer Nature, 2019) de la Vara, Jose Luis; Parra, Eugenio; Ruiz, Alejandra; Gallina, Barbara; Franch, Xavier; Männistö, Tomi; Martínez-Fernández, Silverio; QuantumMost safety-critical systems must undergo assurance and certification processes. The associated activities can be complex and labour-intensive, thus practitioners need suitable means to execute them. The activities are further becoming more challenging as a result of the evolution of the systems towards cyber-physical ones, as these systems have new assurance and certification needs. The AMASS project (Architecture-driven, Multi-concern and Seamless Assurance and Certification of Cyber-Physical Systems) tackled these issues by creating and consolidating the de-facto European-wide open tool platform, ecosystem, and self-sustainable community for assurance and certification of cyber-physical systems. The project defined a novel holistic approach for architecture-driven assurance, multi-concern assurance, seamless interoperability, and cross- and intra-domain reuse of assurance assets. AMASS results were applied in 11 industrial case studies to demonstrate the reduction of effort in assurance and certification, the reduction of (re)certification cost, the reduction of assurance and certification risks, and the increase in technology harmonisation and interoperability.Item Architecture-driven, Multi-concern and Seamless Assurance and Certification of Cyber-Physical Systems.(Springer International Publishing, 2016-09-01) Ruiz, Alejandra; Gallina, Barbara; de la Vara, Jose Luis; Mazzini, Silvia; Espinoza, Huascar; Guiochet, Jérémie; Schoitsch, Erwin; Bitsch, Friedemann; Skavhaug, Amund; Quantum; Tecnalia Research & InnovationUnlike practices in electrical and mechanical equipment engineering, Cyber-Physical Systems (CPS) do not have a set of standardized and harmonized practices for assurance and certification that ensures safe, secure and reliable operation with typical software and hardware architectures. This paper presents a recent initiative called AMASS (Architecture-driven, Multi-concern and Seamless Assurance and Certification of Cyber-Physical Systems) to promote harmonization, reuse and automation of labour-intensive certification-oriented activities via using model-based approaches and incremental techniques. AMASS will develop an integrated and holistic approach, a supporting tool ecosystem and a self-sustainable community for assurance and certification of CPS. The approach will be driven by architectural decisions (fully compatible with standards, e.g. AUTOSAR and IMA), including multiple assurance concerns such as safety, security and reliability. AMASS will support seamless interoperability between assurance/certification and engineering activities along with third-party activities (external assessments, supplier assurance). The ultimate aim is to lower certification costs in face of rapidly changing product features and market needs.Item Autofluorescence image reconstruction and virtual staining for in-vivo optical biopsying(2021-02) Picon, Artzai; Medela, Alfonso; Sanchez-Peralta, Luisa F.; Cicchi, Riccardo; Bilbao, Roberto; Alfieri, Domenico; Elola, Andoni; Glover, Ben; Saratxaga, Cristina L.; COMPUTER_VISION; VISUALModern photonic technologies are emerging, allowing the acquisition of in-vivo endoscopic tissue imaging at a microscopic scale, with characteristics comparable to traditional histological slides, and with a label-free modality. This raises the possibility of an ‘optical biopsy’ to aid clinical decision making. This approach faces barriers for being incorporated into clinical practice, including the lack of existing images for training, unfamiliarity of clinicians with the novel image domains and the uncertainty of trusting ‘black-box’ machine learned image analysis, where the decision making remains inscrutable. In this paper, we propose a new method to transform images from novel photonics techniques (e.g. autofluorescence microscopy) into already established domains such as Hematoxilyn-Eosin (H-E) microscopy through virtual reconstruction and staining. We introduce three main innovations: 1) we propose a transformation method based on a Siamese structure that simultaneously learns the direct and inverse transformation ensuring domain back-transformation quality of the transformed data. 2) We also introduced an embedding loss term that ensures similarity not only at pixel level, but also at the image embedding description level. This drastically reduces the perception distortion trade-off problem existing in common domain transfer based on generative adversarial networks. These virtually stained images can serve as reference standard images for comparison with the already known H-E images. 3) We also incorporate an uncertainty margin concept that allows the network to measure its own confidence, and demonstrate that these reconstructed and virtually stained images can be used on previously-studied classification models of H-E images that have been computationally degraded and de-stained. The three proposed methods can be seamlessly incorporated on any existing architectures. We obtained balanced accuracies of 0.95 and negative predictive values of 1.00 over the reconstructed and virtually stained image-set on the detection of color-rectal tumoral tissue. This is of great importance as we reduce the need for extensive labeled datasets for training, which are normally not available on the early studies of a new imaging technology.Item A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living(Springer International Publishing, 2016) Amato, Giuseppe; Bacciu, Davide; Chessa, Stefano; Dragone, Mauro; Gallicchio, Claudio; Gennaro, Claudio; Lozano, Hector; Micheli, Alessio; O´HARE, Gregory M.; Renteria, Arantxa; Vairo, Claudio; O’Hare, Gregory M.P.; De Paz, Juan F.; Yoe, Hyun; Villarrubia, Gabriel; Novais, Paulo; Lindgren, Helena; Fernández-Caballero, Antonio; Ramírez, Andres Jiménez; Medical Technologies; Robótica MédicaWe present a data benchmark for the assessment of human activity recognition solutions, collected as part of the EU FP7 RUBICON project, and available to the scientific community. The dataset provides fully annotated data pertaining to numerous user activities and comprises synchronized data streams collected from a highly sensor-rich home environment. A baseline activity recognition performance obtained through an Echo State Network approach is provided along with the dataset.Item Burnable Pseudo-Identity: A Non-Binding Anonymous Identity Method for Ethereum: A Non-Binding Anonymous Identity Method for Ethereum(2021) Gutierrez-Aguero, Ivan; Anguita, Sergio; Larrucea, Xabier; Gomez-Goiri, Aitor; Urquizu, Borja; Tecnalia Research & Innovation; CIBERSEC&DLTThe concept of identity has become one common research topic in security and privacy where the real identity of users must be preserved, usually covered by pseudonym identifiers. With the rise of Blockchain-based systems, identities are becoming even more critical than before, mainly due to the immutability property. In fact, many publicly accessible Blockchain networks like Ethereum rely on pseudonymization as a method for identifying subject actions. Pseudonyms are often employed to maintain anonymity, but true anonymity requires unlinkability. Without this property, any attacker can examine the messages sent by a specific pseudonym and learn new information about the holder of this pseudonym. This use of Blockchain collides with regulations because of the right to be forgotten, and Blockchain-based solutions are ensuring that every data stored within the chain will not be modified. In this paper we define a method and a tool for dealing with digital identities within Blockchain environments that are compliant with regulations. The proposed method provides a way to grant digital pseudo identities unlinked to the real identity. This new method uses the benefits of key derivation systems to ensure a non-binding interaction between users and the information model associated with their identity. The proposed method is demonstated in the Ethereum context and illustrated with a case study.Item Cascaded- and Modular-Multilevel Converter Laboratory Test System Options: A Review: A Review(2021-03) Heath, Theodor; Barnes, Mike; Judge, Paul D.; Chaffey, Geraint; Clemow, Phil; Green, Tim C.; Green, Peter R.; Wylie, James; Konstantinou, Georgios; Ceballos, Salvador; Pou, Josep; Belhaouane, Mohamed Moez; Zhang, Haibo; Guillaud, Xavier; Andrews, Jack; POWER ELECTRONICS AND SYSTEM EQUIPMENTThe increasing importance of cascaded multilevel converters (CMCs), and the sub-category of modular multilevel converters (MMCs), is illustrated by their wide use in high voltage DC connections and in static compensators. Research is being undertaken into the use of these complex pieces of hardware and software for a variety of grid support services, on top of fundamental frequency power injection, requiring improved control for non-traditional duties. To validate these results, small-scale laboratory hardware prototypes are often required. Such systems have been built by many research teams around the globe and are also increasingly commercially available. Few publications go into detail on the construction options for prototype CMCs, and there is a lack of information on both design considerations and lessons learned from the build process, which will hinder research and the best application of these important units. This paper reviews options, gives key examples from leading research teams, and summarizes knowledge gained in the development of test rigs to clarify design considerations when constructing laboratory-scale CMCs.Item COEBA: A Coevolutionary Bat Algorithm for Discrete Evolutionary Multitasking: A coevolutionary bat algorithm for discrete evolutionary multitasking(Springer Nature, 2020) Osaba, Eneko; Del Ser, Javier; Yang, Xin-She; Iglesias, Andres; Galvez, Akemi; Krzhizhanovskaya, Valeria V.; Závodszky, Gábor; Lees, Michael H.; Sloot, Peter M.A.; Sloot, Peter M.A.; Sloot, Peter M.A.; Dongarra, Jack J.; Brissos, Sérgio; Teixeira, João; Quantum; IAMultitasking optimization is an emerging research field which has attracted lot of attention in the scientific community. The main purpose of this paradigm is how to solve multiple optimization problems or tasks simultaneously by conducting a single search process. The main catalyst for reaching this objective is to exploit possible synergies and complementarities among the tasks to be optimized, helping each other by virtue of the transfer of knowledge among them (thereby being referred to as Transfer Optimization). In this context, Evolutionary Multitasking addresses Transfer Optimization problems by resorting to concepts from Evolutionary Computation for simultaneous solving the tasks at hand. This work contributes to this trend by proposing a novel algorithmic scheme for dealing with multitasking environments. The proposed approach, coined as Coevolutionary Bat Algorithm, finds its inspiration in concepts from both co-evolutionary strategies and the metaheuristic Bat Algorithm. We compare the performance of our proposed method with that of its Multifactorial Evolutionary Algorithm counterpart over 15 different multitasking setups, composed by eight reference instances of the discrete Traveling Salesman Problem. The experimentation and results stemming therefrom support the main hypothesis of this study: the proposed Coevolutionary Bat Algorithm is a promising meta-heuristic for solving Evolutionary Multitasking scenarios.Item Collaboration-Centred Cities Through Urban Apps Based on Open and User-Generated Data. Springer(Springer International Publishing AG, 2015) López-de-Ipiña, Diego; Aguilera, Unai; Pérez-Velasco, Jorge; García-Chamizo, Juan M.; Fortino, Giancarlo; Ochoa, Sergio F.; Tecnalia Research & InnovationThis paper describes the IES Cities platform conceived to streamline the development of urban apps which combine heterogeneous datasets provided by diverse entities, namely, Government, citizens, sensor infrastructure and so on. Particularly, it focuses on the Query Mapper, a key component of this platform devised to democratize the development of Open Data based mobile urban apps. The advantages from the developers’ perspective brought forward by IES Cities are evaluated by describing an exemplary urban app created on top of it. This work pursues the challenge of achieving effective citizen collaboration by empowering them to prosume urban data across time.Item A Comparative Analysis of Self-Rectifying Turbines for the Mutriku Oscillating Water Column Energy Plant(2019) Otaola, Erlantz; Garrido, Aitor J.; Lekube, Jon; Garrido, Izaskun; Tecnalia Research & InnovationOscillating Water Column (OWC) based devices are arising as one of the most promising technologies for wave energy harnessing. However, the most widely used turbine comprising its power take-off (PTO) module, the Wells turbine, presents some drawbacks that require special attention. Notwithstanding different control strategies are being followed to overcome these issues; the use of other self-rectifying turbines could directly achieve this goal at the expense of some extra construction, maintenance, and operation costs. However, these newly developed turbines in turn show diverse behaviours that should be compared for each case. This paper aims to analyse this comparison for the Mutriku wave energy power plant.Item Dandelion-encoded harmony search heuristics for opportunistic traffic offloading in synthetically modeled mobile networks(Springer Verlag, 2016) Perfecto, Cristina; Bilbao, Miren Nekane; Del Ser, Javier; Ferro, Armando; Salcedo-Sanz, Sancho; Geem, Zong Woo; Kim, Joong Hoon; IAThe high data volumes being managed by and transferred through mobile networks in the last few years are the main rationale for the upsurge of research aimed at finding efficient technical means to offload exceeding traffic to alternative communication infrastructures with higher transmission bandwidths. This idea is solidly buttressed by the proliferation of short-range wireless communication technologies (e.g.mobile devices with multiple radio interfaces), which can be conceived as available opportunistic hotspots to which the operator can reroute exceeding network traffic depending on the contractual clauses of the owner at hand. Furthermore, by offloading to such hotspots a higher effective coverage can be attained by those operators providing both mobile and fixed telecommunication services. In this context, the operator must decide if data generated by its users will be sent over conventional 4G+/4G/3G communication links, or if they will instead be offloaded to nearby opportunistic networks assuming a contractual cost penalty. Mathematically speaking, this problem can be formulated as a spanning tree optimization subject to cost-performance criteria and coverage constraints. This paper will elaborate on the efficient solving of this optimization paradigm by means of the Harmony Search meta-heuristic algorithm and the so-called Dandelion solution encoding, the latter allowing for the use of conventional meta-heuristic operators maximally preserving the locality of tree representations. The manuscript will discuss the obtained simulation results over different synthetically modeled setups of the underlying communication scenario and contractual clauses of the users.Item Data Augmentation for Industrial Prognosis Using Generative Adversarial Networks(Springer, 2020-10-27) Ortego, Patxi; Diez-Olivan, Alberto; Del Ser, Javier; Sierra, Basilio; Analide, Cesar; Novais, Paulo; Camacho, David; Yin, Hujun; Tecnalia Research & Innovation; IAThe Industry 4.0 revolution allows monitoring and intelligent processing of big amounts of data. When monitoring certain assets, very few data is found for operation under faulty conditions because the cost of not operating properly is unacceptable and thus preventive strategies are put in practice. Because machine learning algorithms are data exhaustive, synthetic data can be created for these cases. Deep learning techniques have been proven to work very well for these cases. Generative Adversarial Networks (GANs) have been deployed in numerous applications with data augmentation objectives, but not so much for balancing unidimensional series with few data. In this paper, a GAN is applied in order to augment data for assets operating under faulty conditions. The proposed method is validated on a real industrial case, yielding promising results with respect to the case with no strategy for class imbalance whatsoever.Item Design and implementation of an extended corporate crm database system with big data analytical functionalities(2015-07-25) Torre-Bastida, Ana I.; Villar-Rodriguez, Esther; Gil-Lopez, Sergio; Del Ser, Javier; HPA; Quantum; IAThe amount of open information available on-line from heterogeneous sources and domains is growing at an extremely fast pace, and constitutes an important knowledge base for the consideration of industries and companies. In this context, two relevant data providers can be highlighted: the “Linked Open Data” (LOD) and “Social Media” (SM) paradigms. The fusion of these data sources – structured the former, and raw data the latter –, along with the information contained in structured corporate databases within the organizations themselves, may unveil significant business opportunities and competitive advantage to those who are able to understand and leverage their value. In this paper, we present two complementary use cases, illustrating the potential of using the open data in the business domain. The first represents the creation of an existing and potential customer knowledge base, exploiting social and linked open data based on which any given organization might infer valuable information as a support for decision making. The second focuses on the classification of organizations and enterprises aiming at detecting potential competitors and/or allies via the analysis of the conceptual similarity between their participated projects. To this end, a solution based on the synergy of Big Data and semantic technologies will be designed and developed. The first will be used to implement the tasks of collection, data fusion and classification supported by natural language processing (NLP) techniques, whereas the latter will deal with semantic aggregation, persistence, reasoning and information retrieval, as well as with the triggering of alerts based on the semantized information.Item Development and Operation of Trustworthy Smart IoT Systems: The ENACT Framework(Springer, 2020) Ferry, Nicolas; Dominiak, Jacek; Gallon, Anne; González, Elena; Iturbe, Eider; Lavirotte, Stéphane; Martinez, Saturnino; Metzger, Andreas; Muntés-Mulero, Victor; Nguyen, Phu H.; Palm, Alexander; Rego, Angel; Rios, Erkuden; Riviera, Diego; Solberg, Arnor; Song, Hui; Tigli, Jean Yves; Winter, Thierry; Bruel, Jean-Michel; Mazzara, Manuel; Meyer, Bertrand; CIBERSEC&DLT; Tecnalia Research & InnovationTo unleash the full potential of IoT, it is critical to facilitate threation and operation of trustworthy Smart IoT Systems (SIS). Software development and delivery of SIS would greatly benefit from DevOps as devices and IoT services requirements for reliability, quality, security and safety are paramount. However, DevOps practices are far from widely adopted in the IoT, in particular, due to a lack of key enabling tools. In last year paper at DevOps’18, we presented the ENACT research roadmap that identified the critical challenges to enable DevOps in the realm of trustworthy SIS. In this paper, we present the ENACT DevOps Framework as our current realization of these methods and tools.Item A Discrete and Improved Bat Algorithm for solving a medical goods distribution problem with pharmacological waste collection(2019-02) Osaba, Eneko; Yang, Xin-She; Fister, Iztok; Del Ser, Javier; Lopez-Garcia, Pedro; Vazquez-Pardavila, Alejo J.; Tecnalia Research & Innovation; Quantum; IAThe work presented in this paper is focused on the resolution of a real-world drugs distribution problem with pharmacological waste collection. With the aim of properly meeting all the real-world restrictions that comprise this complex problem, we have modeled it as a multi-attribute or rich vehicle routing problem (RVRP). The problem has been modeled as a Clustered Vehicle Routing Problem with Pickups and Deliveries, Asymmetric Variable Costs, Forbidden Roads and Cost Constraints. To the best of authors knowledge, this is the first time that such a RVRP problem is tackled in the literature. For this reason, a benchmark composed of 24 datasets, from 60 to 1000 customers, has also been designed. For the developing of this benchmark, we have used real geographical positions located in Bizkaia, Spain. Furthermore, for the proper dealing of the proposed RVRP, we have developed a Discrete and Improved Bat Algorithm (DaIBA). The main feature of this adaptation is the use of the well-known Hamming Distance to calculate the differences between the bats. An effective improvement has been also contemplated for the proposed DaIBA, which consists on the existence of two different neighborhood structures, which are explored depending on the bat's distance regarding the best individual of the swarm. For the experimentation, we have compared the performance of our presented DaIBA with three additional approaches: an evolutionary algorithm, an evolutionary simulated annealing and a firefly algorithm. Additionally, with the intention of obtaining rigorous conclusions, two different statistical tests have been conducted: the Friedman's non-parametric test and the Holm's post-hoc test. Furthermore, an additional experimentation has been performed in terms of convergence. Finally, the obtained outcomes conclude that the proposed DaIBA is a promising technique for addressing the designed problem.Item Distributed Coordination of Heterogeneous Robotic Swarms Using Stochastic Diffusion Search(Springer, 2020-10-27) Osaba, Eneko; Del Ser, Javier; Jubeto, Xabier; Iglesias, Andrés; Fister, Iztok; Gálvez, Akemi; Analide, Cesar; Novais, Paulo; Camacho, David; Yin, Hujun; Quantum; IAThe term Swarm Robotics collectively refers to a population of robotic devices that efficiently undertakes diverse tasks in a collaborative way by virtue of computational intelligence techniques. This paradigm has given rise to a profitable stream of contributions in recent years, all sharing a clear consensus on the performance benefits derived from the increased exploration capabilities offered by Swarm Robotics. This manuscript falls within this topic: specifically, it gravitates on an heterogeneous Swarm Robotics system that relies on Stochastic Diffusion Search (SDS) as the coordination heuristics for the exploration, location and delimitation of areas scattered over the area in which robots are deployed. The swarm is composed by agents of diverse kind, which can be ground robots or flying devices. These agents communicate to each other and cooperate towards the accomplishment of the exploration tasks comprising the mission of the overall swarm. Furthermore, maps contain several obstacles and dangers, implying that in order to enter a specific area, robots should meet certain conditions. Experiments are conducted over three different maps and three implemented solving approaches. Conclusions are drawn from the obtained results, confirming that i) SDS allows for a lightweight, heuristic mechanism for the coordination of the robots; and ii) the most efficient swarming approach is the one comprising a heterogeneity of ground and aerial robots.Item Driver Monitoring System Based on CNN Models: An Approach for Attention Level Detection: An Approach for Attention Level Detection(Springer, 2020-10-27) Vaca-Recalde, Myriam E.; Pérez, Joshué; Echanobe, Javier; Analide, Cesar; Novais, Paulo; Camacho, David; Yin, Hujun; CCAMDrivers provide a wide range of focus characteristics that can evaluate their attention level and analyze their behavioral states while driving. This information is critical for the development of new automated driving functionalities that support and assist the driver according to his/her state, ensuring safety for them and other users on the road. In this sense, this paper proposes a Driver Monitoring System (DMS) based on image processing and Convolutional Neural Networks (CNN), that analyzes two important driver distraction aspects: inattention of the road and drowsiness. Our approach makes use of CNN models for detecting the gaze and the head direction, which involves training datasets with different pre-defined labels. Additionally, the system is complemented with the drowsiness level measurement, using face features to detect the time that the eyes are closed or opened, and the blinking rate. Crossing the inference results of these models, the system can provide an accurate estimation of driver attention level. The different parts of the presented DMS have been trained in a Hardware-in-the-loop driving simulator with an eye fish camera. It has been tested as a real-time application recording driver with different characteristics.Item DTN routing optimised by human routines: the HURRy protocol: The HURRy protocol(Springer. The final publication is available at link.springer.com, 2015) Pérez-Sánchez, Susana; Cabero, José María; Urteaga, Iñigo; Aguayo-Torres, Mari Carmen; Gómez, Gerardo; Poncela, Javier; Tecnalia Research & Innovation; GENERALThis paper proposes the HURRy (HUman Routines used for Routing) protocol, which infers and benefits from the social behaviour of nodes in disruptive networking environments. HURRy incorporates the contact duration to the information retrieved from historical encounters among neighbours, so that smarter routing decisions can be made. The specification of HURRy is based on the outcomes of a thorough experiment, which highlighted the importance of distinguishing between short and long contacts and deriving mathematical relations in order to optimally prioritize the available routes to a destination. HURRy introduces a novel and more meaningful rating system to evaluate the quality of each contact and overcome the limitations of other routing approaches in social environments.Item Dual-modular architecture for developing and validation of decision and control modules for automated vehicles: Arquitectura dual-modular para desarrollos y validación de módulos de decisión y control en vehículos automatizados(2020) Lattarulo, R.; Matute, J. A.; Pérez, J.; Gomez Garay, V.; CCAMEl avance logrado durante las últimas décadas en los sistemas avanzados de asistencia a la conducción (ADAS, Advanced Driver Assistance System) ha posibilitado mejorar múltiples aspectos en los vehículos comerciales, como por ejemplo la seguridad, robustez de los sistemas, eficiencia energética, detección de peatones, aparcamiento asistido y ayudas a la navegación, entre otros. Algunos desarrollos, como el control lateral y la generación óptima de trayectorias en tiempo real, están en pleno desarrollo. En este trabajo se presenta una arquitectura dual-modular cuyas principales características son su capacidad para integrar y probar nuevos algoritmos de control y decisión (modular), y la posibilidad de llevar a cabo pruebas en entornos simulados y en plataformas reales (dual), reduciendo los tiempos y costes de desarrollo. Con esta arquitectura se han podido probar diferentes técnicas de control y de generación de trayectorias, realizando además simulaciones, y comparando los resultados obtenidos con un vehículo real.Item Early Safety Assessment of Automotive Systems Using Sabotage Simulation-Based Fault Injection Framework(Springer Verlag, 2017) Juez, Garazi; Amparan, Estibaliz; Lattarulo, Ray; Ruíz, Alejandra; Perez, Joshue; Espinoza, Huascar; Bitsch, Friedemann; Tonetta, Stefano; Schoitsch, Erwin; Tecnalia Research & Innovation; CIBERSEC&DLT; CCAM; QuantumAs road vehicles increase their autonomy and the driver reduces his role in the control loop, novel challenges on dependability assessment arise. Model-based design combined with a simulation-based fault injection technique and a virtual vehicle poses as a promising solution for an early safety assessment of automotive systems. To start with, the design, where no safety was considered, is stimulated with a set of fault injection simulations (fault forecasting). By doing so, safety strategies can be evaluated during early development phases estimating the relationship of an individual failure to the degree of misbehaviour on vehicle level. After having decided the most suitable safety concept, a second set of fault injection experiments is used to perform an early safety validation of the chosen architecture. This double-step process avoids late redesigns, leading to significant cost and time savings. This paper presents a simulation-based fault injection approach aimed at finding acceptable safety properties for model-based design of automotive systems. We focus on instrumenting the use of this technique to obtain fault effects and the maximum response time of a system before a hazardous event occurs. Through these tangible outcomes, safety concepts and mechanisms can be more accurately dimensioned. In this work, a prototype tool called Sabotage has been developed to set up, configure, execute and analyse the simulation results. The feasibility of this method is demonstrated by applying it to a Lateral Control system.