Novel Validation Techniques for Autonomous Vehicles

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Novel Validation Techniques for Autonomous Vehicles

The automotive industry is facing challenges in producing electrical, connected, and autonomous vehicles. Even if these challenges are, from a technical point of view, independent from each other, the market and regulatory bodies require them to be developed and integrated simultaneously. The development of autonomous vehicles implies the development of highly dependable systems. This is a multidisciplinary activity involving knowledge from robotics, computer science, electrical and mechanical engineering, psychology, social studies, and ethics. Nowadays, many Advanced Driver Assistance Systems (ADAS), like Emergency Braking System, Lane Keep Assistant, and Park Assist, are available. Newer luxury cars can drive by themselves on highways or park automatically, but the end goal is to develop completely autonomous driving vehicles, able to go by themselves, without needing human interventions in any situation. The more vehicles become autonomous, the greater the difficulty in keeping them reliable. It enhances the challenges in terms of development processes since their misbehaviors can lead to catastrophic consequences and, differently from the past, there is no more a human driver to mitigate the effects of erroneous behaviors. Primary threats to dependability come from three sources: misuse from the drivers, design systematic errors, and random hardware failures. These safety threats are addressed under various aspects, considering the particular type of item to be designed. In particular, for the sake of this work, we analyze those related to Functional Safety (FuSa), viewed as the ability of a system to react on time and in the proper way to the external environment. From the technological point of view, these behaviors are implemented by electrical and electronic items. Various standards to achieve FuSa have been released over the years. The first, released in 1998, was the IEC 61508. Its last version is the one released in 2010. This standard defines mainly: • a Functional Safety Management System (FSMS); • methods to determine a Safety Integrated Level (SIL); • methods to determine the probability of failures. To adapt the IEC61508 to the automotive industry’s peculiarity, a newer standard, the ISO26262, was released in 2011 then updated in 2018. This standard provides guidelines about FSMS, called in this case Safety Lifecycle, describing how to develop software and hardware components suitable for functional safety. It also provides a different way to compute the SIL, called in this case Automotive SIL (ASIL), allowing us to consider the average driver’s abilities to control the vehicle in case of failures. Moreover, it describes a way to determine the probability of random hardware failures through Failure Mode, Effects, and Diagnostic Analysis (FMEDA). This dissertation contains contributions to three topics: • random hardware failures mitigation; • improvementoftheISO26262HazardAnalysisandRiskAssessment(HARA); • real-time verification of the embedded software. As the main contribution of this dissertation, I address the safety threats due to random hardware failures (RHFs). For this purpose, I propose a novel simulation-based approach to aid the Failure Mode, Effects, and Diagnostic Analysis (FMEDA) required by the ISO26262 standard. Thanks to a SPICE-level model of the item, and the adoption of fault injection techniques, it is possible to simulate its behaviors obtaining useful information to classify the various failure modes. The proposed approach evolved from a mere simulation of the item, allowing only an item-level failure mode classification up to a vehicle-level analysis. The propagation of the failure modes’ effects on the whole vehicle enables us to assess the impacts on the vehicle’s drivability, improving the quality of the classifications. It can be advantageous where it is difficult to predict how the item-level misbehaviors propagate to the vehicle level, as in the case of a virtual differential gear or the mobility system of a robot. It has been chosen since it can be considered similar to the novel light vehicles, such as electric scooters, that are becoming more and more popular. Moreover, my research group has complete access to its design since it is realized by our university’s DIANA students’ team. When a SPICE-level simulation is too long to be performed, or it is not possible to develop a complete model of the item due to intellectual property protection rules, it is possible to aid this process through behavioral models of the item. A simulation of this kind has been performed on a mobile robotic system. Behavioral models of the electronic components were used, alongside mechanical simulations, to assess the software failure mitigation capabilities. Another contribution has been obtained by modifying the main one. The idea was to make it possible to aid also the Hazard Analysis and Risk Assessment (HARA). This assessment is performed during the concept phase, so before starting to design the item implementation. Its goal is to determine the hazards involved in the item functionality and their associated levels of risk. The end goal of this phase is a list of safety goals. For each one of these safety goals, an ASIL has to be determined. Since HARA relies only on designers expertise and knowledge, it lacks in objectivity and repeatability. Thanks to the simulation results, it is possible to predict the effects of the failures on the vehicle’s drivability, allowing us to improve the severity and controllability assessment, thus improving the objectivity. Moreover, since simulation conditions can be stored, it is possible, at any time, to recheck the results and to add new scenarios, improving the repeatability. The third group of contributions is about the real-time verification of embedded software. Through Hardware-In-the-Loop (HIL), a software integration verification has been performed to test a fundamental automotive component, mixed-criticality applications, and multi-agent robots. The first of these contributions is about real-time tests on Body Control Modules (BCM). These modules manage various electronic accessories in the vehicle’s body, like power windows and mirrors, air conditioning, immobilizer, central locking. The main characteristics of BCMs are the communications with other embedded computers via the car’s vehicle bus (Controller Area Network) and to have a high number (hundreds) of low-speed I/Os. As the second contribution, I propose a methodology to assess the error recovery system’s effects on mixed-criticality applications regarding deadline misses. The system runs two tasks: a critical airplane longitudinal control and a non-critical image compression algorithm. I start by presenting the approach on a benchmark application containing an instrumented bug into the lower criticality task; then, we improved it by injecting random errors inside the lower criticality task’s memory space through a debugger. In the latter case, thanks to the HIL, it is possible to pause the time domain simulation when the debugger operates and resume it once the injection is complete. In this way, it is possible to interact with the target without interfering with the simulation results, combining a full control of the target with an accurate time-domain assessment. The last contribution of this third group is about a methodology to verify, on multi-agent robots, the synchronization between two agents in charge to move the end effector of a delta robot: the correct position and speed of the end effector at any time is strongly affected by a loss of synchronization. The last two contributions may seem unrelated to the automotive industry, but interest in these applications is gaining. Mixed-criticality systems allow reducing the number of ECUs inside cars (for cost reduction), while the multi-agent approach is helpful to improve the cooperation of the connected cars with respect to other vehicles and the infrastructure. The fourth contribution, contained in the appendix, is about a machine learning application to improve the social acceptance of autonomous vehicles. The idea is to improve the comfort of the passengers by recognizing their emotions. I started with the idea to modify the vehicle’s driving style based on a real-time emotions recognition system but, due to the difficulties of performing such operations in an experimental setup, I move to analyze them offline. The emotions are determined on volunteers’ facial expressions recorded while viewing 3D representa- tions showing different calibrations. Thanks to the passengers’ emotional responses, it is possible to choose the better calibration from the comfort point of view

FPGA design methodology for industrial control systems—a review

This paper reviews the state of the art of fieldprogrammable gate array (FPGA) design methodologies with a focus on industrial control system applications. This paper starts with an overview of FPGA technology development, followed by a presentation of design methodologies, development tools and relevant CAD environments, including the use of portable hardware description languages and system level programming/design tools. They enable a holistic functional approach with the major advantage of setting up a unique modeling and evaluation environment for complete industrial electronics systems. Three main design rules are then presented. These are algorithm refinement, modularity, and systematic search for the best compromise between the control performance and the architectural constraints. An overview of contributions and limits of FPGAs is also given, followed by a short survey of FPGA-based intelligent controllers for modern industrial systems. Finally, two complete and timely case studies are presented to illustrate the benefits of an FPGA implementation when using the proposed system modeling and design methodology. These consist of the direct torque control for induction motor drives and the control of a diesel-driven synchronous stand-alone generator with the help of fuzzy logic

Multilevel Simulation Methodology for FMECA Study Applied to a Complex Cyber-Physical System

Complex systems are composed of numerous interconnected subsystems, each designed to perform specific functions. The different subsystems use many technological items that work together, as for the case of cyber-physical systems. Typically, a cyber-physical system is composed of different mechanical actuators driven by electrical power devices and monitored by sensors. Several approaches are available for designing and validating complex systems, and among them, behavioral-level modeling is becoming one of the most popular. When such cyber-physical systems are employed in mission- or safety-critical applications, it is mandatory to understand the impacts of faults on them and how failures in subsystems can propagate through the overall system. In this paper, we propose a methodology for supporting the failure mode, effects, and criticality analysis (FMECA) aimed at identifying the critical faults and assessing their effects on the overall system. The end goal is to analyze how a fault affecting a single subsystem possibly propagates through the whole cyber-physical system, considering also the embedded software and the mechanical elements. In particular, our approach allows the analysis of the propagation through the whole system (working at high level) of a fault injected at low level. This paper provides a solution to automate the FMECA process (until now mainly performed manually) for complex cyber-physical systems. It improves the failure classification effectiveness: considering our test case, it reduced the number of critical faults from 10 to 6. The remaining four faults are mitigated by the cyber-physical system architecture. The proposed approach has been tested on a real cyber-physical system in charge of driving a three-phase motor for industrial compressors, showing its feasibility and effectiveness

Reliability in Power Electronics and Power Systems

L'abstract è presente nell'allegato / the abstract is in the attachmen

Moving Towards Analog Functional Safety

Over the past century, the exponential growth of the semiconductor industry has led to the creation of tiny and complex integrated circuits, e.g., sensors, actuators, and smart power systems. Innovative techniques are needed to ensure the correct functionality of analog devices that are ubiquitous in every smart system. The standard ISO 26262 related to functional safety in the automotive context specifies that fault injection is necessary to validate all electronic devices. For decades, standardizing fault modeling, injection and simulation mainly focused on digital circuits and disregarding analog ones. An initial attempt is being made with the IEEE P2427 standard draft standard that started to give this field a structured and formal organization. In this context, new fault models, injection, and abstraction methodologies for analog circuits are proposed in this thesis to enhance this application field. The faults proposed by the IEEE P2427 standard draft standard are initially evaluated to understand the associated fault behaviors during the simulation. Moreover, a novel approach is presented for modeling realistic stuck-on/off defects based on oxide defects. These new defects proposed are required because digital stuck-at-fault models where a transistor is frozen in on-state or offstate may not apply well on analog circuits because even a slight variation could create deviations of several magnitudes. Then, for validating the proposed defects models, a novel predictive fault grouping based on faulty AC matrices is applied to group faults with equivalent behaviors. The proposed fault grouping method is computationally cheap because it avoids performing DC or transient simulations with faults injected and limits itself to faulty AC simulations. Using AC simulations results in two different methods that allow grouping faults with the same frequency response are presented. The first method is an AC-based grouping method that exploits the potentialities of the S-parameters ports. While the second is a Circle-based grouping based on the circle-fitting method applied to the extracted AC matrices. Finally, an open-source framework is presented for the fault injection and manipulation perspective. This framework relies on the shared semantics for reading, writing, or manipulating transistor-level designs. The ultimate goal of the framework is: reading an input design written in a specific syntax and then allowing to write the same design in another syntax. As a use case for the proposed framework, a process of analog fault injection is discussed. This activity requires adding, removing, or replacing nodes, components, or even entire sub-circuits. The framework is entirely written in C++, and its APIs are also interfaced with Python. The entire framework is open-source and available on GitHub. The last part of the thesis presents abstraction methodologies that can abstract transistor level models into Verilog-AMS models and Verilog- AMS piecewise and nonlinear models into C++. These abstracted models can be integrated into heterogeneous systems. The purpose of integration is the simulation of heterogeneous components embedded in a Virtual Platforms (VP) needs to be fast and accurate

Exposure to food environments, diet and weight status in children

There is a growing interest in understanding how the built food environment influences health behaviours. Whilst policy interest in the influence of food environments on diet and body weight is growing, the evidence base is limited, particularly for environments beyond the home neighbourhood. Research in children is of particular importance, as it is known that dietary behaviours and weight tend to track into adulthood. This thesis addresses the gap in knowledge surrounding the influence of exposure to the food environment on weight and diet in children. It also takes into consideration the interactions with socio-economic status. Existing research exploring the environmental influences on diet and weight in children is reviewed, and a conceptual framework of key determinants identified is presented. Three studies are presented which investigate associations between different measures of exposure to the food environment and diet and weight. A systematic review investigating the use of GPS in studies of the food environment is also conducted. Additionally, a novel method for assessing environmental exposure is presented. The results from this research suggest that unhealthy food environments measured at an area level are generally conducive to weight gain and poorer diet, while the opposite is true for healthier food environments. Furthermore, this thesis supports the hypothesis that diet, weight and access to food are patterned by social class, and that the food environment partially mediates the well-known association between socio-economic status and weight status. However, findings were equivocal when using measuring exposure to the food environment at an individual level. This suggests that correctly measuring the characteristics of the food environment is important in order to disentangle their effects on health outcomes, and calls for efforts to attempt to reduce the heterogeneity in measures of the food environment employed

Healthy built environments: A review of the literature

The Healthy Built Environments Program has completed a major scholarly literature review examining the role of the built environment in supporting human health as part of everyday living. The principal aim of the Review is to establish an evidence base that supports the development, prioritisation and implementation of healthy built environment policies and practices. The Review identifies current gaps in the evidence to inform future research directions. It includes an annotated bibliography of key research articles and a glossary of terms to assist practitioners, policy makers and researchers working in this interdisciplinary realm.  The focus of the Review is on the three key built environment domains that support human health: The Built Environment and Getting People Active. The Built Environment and Connecting and Strengthening Communities. The Built Environment and Providing Healthy Food Options. These built environment domains address three of the major risk factors for contemporary chronic disease - physical inactivity, social isolation and obesity. The Literature Review is available for download as the whole document or its individual sections. Whole document (12MB) Cover and Acknowledgements (1.11MB)List of Abbreviations and Contents (2.11MB)The Healthy Built Environments Program Overview (291KB)Executive Summary (295KB)1.0 Introduction (255KB)2.0 Structure of this Review (2.46MB)3.0 Aims and Parameters (2.99MB)4.0 Scope and Methodology (3.20MB)5.0 The Evidence (200KB)5.1 The Built Environment and Getting People Active (653KB)5.2 The Built Environment and Connecting and Strengthening Communities (546KB)5.3 The Built Environment and Providing Healthy Food Options (416KB)6.0 Professional Development (284KB)7.0 Conclusion (114KB)References (490KB)Appendix 1: Diary of Database Searches (202KB)Appendix 2: Glossary (282KB)Appendix 3: Annotated Bibliography (2.57MB

Fault-based Analysis of Industrial Cyber-Physical Systems

The fourth industrial revolution called Industry 4.0 tries to bridge the gap between traditional Electronic Design Automation (EDA) technologies and the necessity of innovating in many indus- trial fields, e.g., automotive, avionic, and manufacturing. This complex digitalization process in- volves every industrial facility and comprises the transformation of methodologies, techniques, and tools to improve the efficiency of every industrial process. The enhancement of functional safety in Industry 4.0 applications needs to exploit the studies related to model-based and data-driven anal- yses of the deployed Industrial Cyber-Physical System (ICPS). Modeling an ICPS is possible at different abstraction levels, relying on the physical details included in the model and necessary to describe specific system behaviors. However, it is extremely complicated because an ICPS is com- posed of heterogeneous components related to different physical domains, e.g., digital, electrical, and mechanical. In addition, it is also necessary to consider not only nominal behaviors but even faulty behaviors to perform more specific analyses, e.g., predictive maintenance of specific assets. Nevertheless, these faulty data are usually not present or not available directly from the industrial machinery. To overcome these limitations, constructing a virtual model of an ICPS extended with different classes of faults enables the characterization of faulty behaviors of the system influenced by different faults. In literature, these topics are addressed with non-uniformly approaches and with the absence of standardized and automatic methodologies for describing and simulating faults in the different domains composing an ICPS. This thesis attempts to overcome these state-of-the-art gaps by proposing novel methodologies, techniques, and tools to: model and simulate analog and multi-domain systems; abstract low-level models to higher-level behavioral models; and monitor industrial systems based on the Industrial Internet of Things (IIOT) paradigm. Specifically, the proposed contributions involve the exten- sion of state-of-the-art fault injection practices to improve the ICPSs safety, the development of frameworks for safety operations automatization, and the definition of a monitoring framework for ICPSs. Overall, fault injection in analog and digital models is the state of the practice to en- sure functional safety, as mentioned in the ISO 26262 standard specific for the automotive field. Starting from state-of-the-art defects defined for analog descriptions, new defects are proposed to enhance the IEEE P2427 draft standard for analog defect modeling and coverage. Moreover, dif- ferent techniques to abstract a transistor-level model to a behavioral model are proposed to speed up the simulation of faulty circuits. Therefore, unlike the electrical domain, there is no extensive use of fault injection techniques in the mechanical one. Thus, extending the fault injection to the mechanical and thermal fields allows for supporting the definition and evaluation of more reliable safety mechanisms. Hence, a taxonomy of mechanical faults is derived from the electrical domain by exploiting the physical analogies. Furthermore, specific tools are built for automatically instru- menting different descriptions with multi-domain faults. The entire work is proposed as a basis for supporting the creation of increasingly resilient and secure ICPS that need to preserve functional safety in any operating context