The following doctoral thesis, sponsored by Autostrada del Brennero S.p.A. (an Italian highway concession company in charge of managing toll roads) consists on empirical essays at the crossroad between transport and regional economics. They focus on different aspects that directly involve motorways (i.e, safety, intermodality, and commuting dynamics) and they are aimed at providing further evidences that transport institutions and policy makers could take into account throughout their decision-making processes. The first chapter presents a research article that seeks to determine the impact of an average speed enforcement system in reducing highway accidents. Indeed, at the end of 2005, Autostrade per l'Italia (ASPI) and the Italian traffic police progressively deployed along the Italian tolled motorway network an average speed enforcement system, named Safety Tutor, able to determine the average speed of vehicles over a long section to encourage drivers to comply with speed limits and improve safety. To empirically test the extent to which Safety Tutor led to a reduction in both total and fatal accidents on Italian highways during the period of 2001-2017, we carried out a generalized difference-in-differences estimation using a unique panel dataset that exploits the heterogeneous accident data within all tolled motorway sectors in a quasi-experimental setting. To deal with the potential endogeneity of the non-random placement of Safety Tutor sites, we utilized an instrumental variable strategy by using the network of motorway sectors managed by ASPI and its controlled concessionaires from 2005 onwards (i.e., when the technology was available) as an instrument to predict Safety Tutor adoption. We found that a 10% increase in Safety Tutor coverage led to an average reduction in total accidents of 3.9%, whereas there is no evidence of a significant causal effect of Safety Tutor in reducing fatal accidents. The second chapter presents a research article that seeks to investigate the inter-modal competition between motorway and high-speed rail (HSR) services, as the extent to which HSR demand could be the result of a modal shift from motorways is a relevant issue in any cost-benefit analysis of HSR investments. Indeed, the development of HSR has had a notable impact on modal market shares on the routes on which its services have been implemented. To analyse whether the HSR expansion in Italy has led to a modal shift from motorway to HSR, we empirically test i) whether HSR openings adjacent to motorway sectors have reduced the total km travelled by light vehicles on these sectors during the period 2001-2017; and ii) whether this reduction has been persistent or even more evident after the opening of on-track competition between two HSR operators. To do so, we carried out a generalized difference-in-differences estimation, using a unique panel dataset that exploits the heterogeneous traffic data within all tolled motorway sectors in a quasi-experimental setting. Our findings reveal that neither HSR openings nor the opening of on-track competition led to a modal shift from motorway to HSR services, as the two transport modes are non-competing. Conversely, HSR expansion had a slightly positive impact on motorway traffic. The third chapter presents a data article in a “data in brief” format that describes a dataset on municipality-to-municipality commuting patterns in Italy over the 1991, 2001, and 2011 censuses aimed at investigating the role of transport infrastructures and the structural transformation of the economy on worker mobility. At this purpose, a core origin-destination dataset on the number of workers moving between municipalities, or within the same municipality, has been linked with further municipality covariates on jobs location, population, and the distances in meters and journey times in minutes between all municipalities. Even though these data are freely available online, they require some tedious work to organize. Therefore, this data article brings the necessary information together and makes the dataset available on request. The dataset offers applied researchers an alternative source of information to shed new lights on the changing shape of urban systems by analysing i) the impact of infrastructural endowment in providing better job accessibility, or ii) the connection between increasing commuting patterns and the structural transformation of the economy due to the tertiarization process from 1991 to 2011.

This report delves into the early developmental phase of an autonomous vehicle designed for defense applications. Navigating diverse terrains, this unmanned ground vehicle (UGV) poses unique challenges, particularly in the absence of clearly defined directives found in typical traffic scenarios. The analysis employs the Systems-Theoretic Process Analysis (STPA) to identify and anticipate risks inherent in the conceptual stage of product development. Beyond the specific UGV case, the report explores the broader landscape of validating autonomous systems. It discusses prevalent methods, emphasizing adaptability to different contexts and stages of development. By shedding light on the risks and challenges of autonomy in vehicles and examining effective validation strategies, this report aims to contribute valuable insights to the ongoing discourse surrounding autonomous vehicle development.

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<p dir="ltr">The deep human drive to explore and inhabit new frontiers underpins the emerging field of space architecture, as evidenced by the proliferation of diverse design concepts and growing momentum in extraterrestrial construction. However, the endeavor of building off-world environments remains in its infancy, facing numerous challenges due to remoteness, novelty, complexity, and other inherent characteristics. Significant technical and methodological gaps exist between visionary designs and the practical engineering and management intricacies of complex projects. These gaps must be addressed to overcome the challenges in extraterrestrial construction.</p><p dir="ltr">The field is limited by the scarcity of both failures and successes in extraterrestrial construction from which to draw lessons. Furthermore, the understanding of construction system failures is constrained by the limited application of systems perspectives in construction safety literature. Existing accident causation models in system safety literature are ill-suited for describing construction system failures.</p><p dir="ltr">The overall objective of this research is to inform the planning and design of extraterrestrial construction to mitigate the risk of building and installing defective systems in space. To achieve this goal, the research process followed iterative cycles of failure case studies, extracting insights through the lens of a new accident causation model. The cycles of model application evolved through three major stages: (1) developing a model specifically tailored to construction system failures, (2) deriving concepts and principles for interpreting the model depictions, and (3) compiling lessons from a systematically selected set of failure cases for planners, designers, and key stakeholders of future extraterrestrial construction projects.</p><p dir="ltr">Following a comprehensive literature review, this study developed an accident model termed the framed-and-layered accident pathogen propagation (FLAPP) model. The basic concept of the model consists of frames representing the temporal dimension, layers depicting the hierarchical aspects of the sociotechnical framework of construction projects, and graphical notation illustrating the sequence of defective processes and pathogens embedded in the constructed artifact.</p><p dir="ltr">To interpret the graphical illustrations of failure cases, the study introduced the concept of pathogen threads to describe multiple sequences of defective processes ultimately interacting with the physical artifact. To further explain the underlying mechanisms of how design decisions incubate into system failures, the concept of design-induced strains was proposed. This concept represents the lingering effects that design solutions can have on physical artifacts and downstream organizational processes. Additionally, categories of inadequate organizational factors from the Human Factors Analysis and Classification System (HFACS) were incorporated to explain the underlying causes within project organizations that allowed the mishandling of physical and organizational strains.</p><p dir="ltr">To evaluate the applicability of the FLAPP model and observe general trends in system failures across various contexts, the study selected failure cases attributable to embedded pathogens with sufficient available information. Ensuring that the case set included diverse cases and covered all specific technical challenges of extraterrestrial construction, the selection resulted in a set of 40 cases comprising 10 space systems, 13 buildings, 10 bridges and tunnels, and 7 systems in specialized environments. Results highlighted typical and exceptional cases among different systems and the general trends of occurrence prevalence of concept instances among different system contexts (space, building, bridge/tunnel, specialized environment) and duration ranges (short, medium, long). The comparison of Earth-based and space-based systems revealed several critical questions for the space domain: how to ensure, maintain, and improve the reliability and quality of unique and site-specific systems; how to establish and enforce minimum quality standards to reduce unintended physical strains; and how to prepare for extended project timelines with dynamic and transient organizational networks.</p><p dir="ltr">Future research should address the theoretical and methodological limitations of the FLAPP model by extending it to investigation methods and risk assessment techniques. Additionally, the failure case study approach should be enhanced by expanding the case set, exploring source documents, and applying additional analysis approaches. This dissertation concludes by demonstrating that guidance and principles with discipline-specific vocabulary can be derived by referencing documented best practices in systems engineering and project management.</p><p><br></p>

With the advent of autonomous systems and deep learning systems, safety pertaining to these systems has become a major concern. The existing failure analysis techniques are not enough to thoroughly analyze the safety in these systems. Moreover, because these systems are created to operate in various conditions, they are susceptible to unknown safety issues. Hence, we need mechanisms which can take into account the complexity of operational design domains, identify safety issues other than failures, and expose unknown safety issues. Moreover, existing safety analysis approaches require a lot of effort and time for analysis and do not consider machine learning (ML) safety. To address these limitations, in this dissertation, we discuss an artificial-intelligence driven model-based methodology that aids in identifying unknown safety issues and analyzing ML safety. Our methodology consists of 4 major tasks: 1) automated model generation, 2) automated analysis of component state transition model specification, 3) undesired states analysis, and 4) causal factor analysis. In our methodology we identify unknown safety issues by finding undesired combinations of components' states and environmental entities' states as well as causes resulting in these undesired combinations. In our methodology, we refer to the behaviors that occur because of undesired combinations as off-nominal behaviors (ONBs). To identify undesired combinations and ONBs that aid in exposing unknown safety issues with less effort and time we proposed various approaches for each of the task and performed corresponding empirical studies. We also discussed machine learning safety analysis from the perspective of machine learning engineers as well as system and software safety engineers. The results of studies conducted as part of our research shows that our proposed methodology helps in identifying unknown safety issues effectively. Our results also show that combinatorial methods are effective in reducing effort and time for analysis of off-nominal behaviors without overlooking any dependencies among components and environmental entities of a system. We also found that safety analysis of machine learning components is different from analysis of conventional software components and detail the aspects we need to consider for ML safety.

Ces travaux s'intéressent à l'estimation de la fiabilité des évacuateurs de crues vannés. Le comportement fiabilistes de ces systèmes hydrauliques dépend à la fois d'événements aléatoires discrets, mais aussi de l'évolution d'une variable déterministe continue : ce sont des systèmes dynamiques hybrides. Pour ces systèmes, l'événement redouté est réalisé lorsque le niveau de la retenue atteint un seuil de sûreté. La démarche de fiabilité dynamique proposée dans cette thèse vise à prendre en compte l’information temporelle de la modélisation à la synthèse d'indicateurs fiabilistes pour l'aide à la décision et développe deux contributions :1) L'élaboration d'une base de connaissances dédiée à la description des évacuateurs de crue en termes de fiabilité dynamique. Chaque classe de composants est décrite par un automate stochastique hybride dont les états sont les différentes phases de son fonctionnement. 2) Le suivi de la simulation de Monte Carlo et le traitement et l'analyse des "histoires" (séquence de tous les états activés et des dates d'activation) obtenues en simulation pour construire des indicateurs de fiabilité classique (probabilité d'occurrence de l'évènement redouté, identification des coupes équivalentes prépondérantes, ...). Des indicateurs de fiabilité dynamique basés sur la classification des histoires en fonction des dates de défaillance des composants concernés et sur l'estimation de l'importance dynamique sont aussi proposés / Hydraulic systems are hybrid dynamic systems whose evolution is a combination between discrete stochastic events on the one hand and continuous deterministic phenomena on the other hand. The undesired event is achieved when the dam level reaches a security threshold. In the frame of gated spillways dynamic reliability, the proposed methodology takes into account the temporal information during modeling and synthesis of reliability indicators for decision support.The first contribution of this work is the development of a knowledge base to describe a class of systems. Each component is described by a stochastic hybrid automaton whose states are the different working modes.The second contribution is Monte Carlo simulation monitoring and treatment results. A story is the sequence of all activated states and activation dates during the algorithm passage for a simulation. The analysis of results provides classical reliability indicators, such as the time evolution of the undesired event probability or the identification of predominant equivalent cuts. Our predictive approach is based on stories classification depending on components failure dates, then dynamic importance is assessed

The content of this diploma thesis is description of semi-automatic assembly line, description of design and realization of electroprojection including electrical switchboard and control panel, together with description of design and implementation of control system including communications and user interface. Part of the thesis is also the analysis and solution of safety risks using a safety controller and overall verification and evaluation of the functionality of the whole system on described line.

This thesis deals with the analysis and design changes to a specific company information system under real conditions, and is therefore more practically oriented. The information system is studied both from the perspective of the end user, which is the focus, and in terms of operation and implementation of program solutions. The information system is studied as a whole in a broader context, not only in terms of applications (software), but also in terms of the flow of information, storage and organization of data, users, security, hardware, etc. It should serve to the company as a guide for the elimination of inefficient and / or risk areas, thereby helping to improve work productivity and employee satisfaction.

Les travaux présentés dans ce manuscrit visent à développer des modèles de coût/performances pour améliorer les décisions de maintenance sur les infrastructures ferroviaires exploitées dans un environnement de plus en plus contraint: trafic accru, détérioration accélérée, temps de maintenance réduits. Les modèles de maintenance proposés sont construits à base de réseaux de Petri colorés ; ils sont animés par simulation de Monte Carlo pour estimer les performances (en termes de coût et de disponibilité) des politiques de maintenance considérées. Ils sont développés aux niveaux "composant" et "réseau", et plusieurs problèmes de maintenance différents sont étudiés. Au niveau "composant" (rail), des politiques de maintenance mettant en jeu différents niveaux d'information de surveillance sont comparées pour montrer l'intérêt de surveiller la détérioration graduelle du composant. L'effet de l'existence d'un délai de maintenance est également étudié pour les politiques conditionnelle et périodique. Au niveau système (ligne), une maintenance mettant en jeu différents types d'inspections complémentaires (automatique ou visuelle) est d'abord étudiée. On s'intéresse ensuite au cas de figure où l'évolution de la détérioration dépend du mode d'utilisation et de la charge de la voie : le problème de maintenance étudié vise alors à définir un réglage optimal des paramètres d'exploitation de la voie (vitesse limite) et de maintenance (délai d'intervention) / The aim of this thesis research work is to propose maintenance models for railways infrastructures that can help to make better maintenance decisions in the more constrained environment that the railway industry has to face, e.g. increased traffic loads, faster deterioration, longer maintenance planning procedures, shorter maintenance times. The proposed maintenance models are built using Coloured Petri nets; they are animated through Monte Carlo simulations to estimate the performance of the considered maintenance policies in terms of cost and availability. The maintenance models are developed both at the component and network levels, and several different maintenance problems are considered. At the rail component level, maintenance policies with different level of monitoring information (level of gradual deterioration vs binary working state) are compared to show the benefits of gathering monitoring information on the deterioration level. The effect of preventive maintenance delays is also investigated for both condition-based inspection policies and periodic inspection policies on a gradually deteriorating component. At the line level, a maintenance policy based on a two-level inspection procedure is first investigated. Then, considering the case when the deterioration process depends on the operation modes (normal vs limited speed), a maintenance optimization problem is solved to determine an optimal tuning of the repair delay and speed restriction

Each year people are injured and even die in crowd related accidents, often during planned events. Recent studies have emphasized the need for using a systems approach to study these events. In this study the systems approach of resilience theory is combined with the crowd psychology-models Extended Social Identity Model and the Aggravation and Mitigation Model to examine event safety at a music festival, a domain previously largely unexplored by these perspectives. By using an ethnographic approach as well as interviewing visitors the study set out to answer questions about when and how the safety organization adjusted itself under conditions relating to crowds. Another goal was to study the social identity of the visitors as well as the interaction between the safety organization and the visitors at the festival to explain the presence or absence of crowd conflict. Using thematic analysis several situations were identified where the safety organization adjusted itself, as well as the strategies that the organization used in these different circumstances. It was also concluded that the absence of crowd conflict could best be explained by three factors. First of all, no history of crowd conflict existed between the safety organization and the visitors, secondly, there were no groups present with the goal of creating conflict, and thirdly, the social processes taking place between the safety organization and the visitors were all mitigating in nature. The mitigating nature of the social processes was partly attributable to the strategies identified for adjusting to crowd conditions.