<div> <div> <div> <p>As the demand and complexity of air traffic increase, it becomes crucial to maintain the safety and efficiency of the operations in airspaces, which, however, could lead to an increased workload for Air Traffic Controllers (ATCs) and delays in their decision-making processes. Although terminal airspaces are highly structured with the flight procedures such as standard terminal arrival routes and standard instrument departures, the aircraft are frequently instructed to deviate from such procedures by ATCs to accommodate given traffic situations, e.g., maintaining the separation from neighboring aircraft or taking shortcuts to meet scheduling requirements. Such deviation, called vectoring, could even increase the delays and workload of ATCs. This thesis focuses on developing a framework for trajectory pattern identification and classification that can provide ATCs, in vectored airspace, with real-time information of which possible vectoring pattern a new incoming aircraft could take so that such delays and workload could be reduced. This thesis consists of two parts, trajectory pattern identification and trajectory pattern classification. </p> <p>In the first part, a framework for trajectory pattern identification is proposed based on agglomerative hierarchical clustering, with dynamic time warping and squared Euclidean distance as the dissimilarity measure between trajectories. Binary trees with fixes that are provided in the aeronautical information publication data are proposed in order to catego- rize the trajectory patterns. In the second part, multiple recurrent neural network based binary classification models are trained and utilized at the nodes of the binary trees to compute the possible fixes an incoming aircraft could take. The trajectory pattern identifi- cation framework and the classification models are illustrated with the automatic dependent surveillance-broadcast data that were recorded between January and December 2019 in In- cheon international airport, South Korea . </p> </div> </div> </div>

Neste trabalho é proposto um método de carregamento incremental dos fluxos veiculares para a estimação de matriz O-D sintética. A principal motivação para o desenvolvimento deste trabalho está na complexidade dos métodos de estimação de matriz sintética pelo método iterativo, que tem conduzido a resultados não satisfatórios. O método de carregamento incremental, ora proposto neste trabalho, pode ser definido como o inverso do método de alocação incremental de viagens aos arcos de uma rede viária. A matriz O-D obtida com este método é o resultado da soma sucessiva das sub-matrizes estimadas através das parcelas dos fluxos observados nos arcos da rede. Este método pode ser aplicado em qualquer tipo de rede viária: congestionada ou não congestionada e com ou sem continuidade de fluxo. Para verificação do desempenho do método foram realizados testes experimentais, nos quais os resultados obtidos foram comparados com os valores observados. O desempenho do método incremental não se mostrou satisfatório. Assim, com o intuito de verificar a sua utilidade como um método alternativo os mesmos dados foram processados através de dois métodos iterativos. Os resultados mostraram que os erros são ainda maiores do que os obtidos pelo método proposto. A principal conclusão deste trabalho é que o método incremental pode ser usado como uma alternativa aos métodos iterativos. / A synthetic O-D matrix estimation method, based on incremental loading of traffic flow, was proposed in this work. This research was motivated because of the complexity of the iterative methods for synthetic matrix estimation that might produce bias accumulation in the results. The referred incremental loading method could be defined as the inverse of the incremental assignment method for trips to links of a traffic network. The O-D matrix is gathered by successively summing the sub-matrices obtained from parts of the traffic flow counted on the links of the traffic network. This method could be applied to any traffic networks: congested or uncongested and with or without volumetric continuity. As a part of verification proceeding, several experimental tests were carried out to evaluate the method performance. In these tests the estimated results were compared with the real values. These results show that the incremental loading method performance was not satisfactory. Thus, aiming to test the utility of the incremental method, a second round of experimental tests was conducted to evaluate two iterative methods. In these second round tests, the results show that theses methods performance was worse those of the incremental method. The main conclusion of this work is that the incremental loading method for synthetic matrices estimation could be used as an alternative to the iterative methods.

Neste trabalho é proposto um método de carregamento incremental dos fluxos veiculares para a estimação de matriz O-D sintética. A principal motivação para o desenvolvimento deste trabalho está na complexidade dos métodos de estimação de matriz sintética pelo método iterativo, que tem conduzido a resultados não satisfatórios. O método de carregamento incremental, ora proposto neste trabalho, pode ser definido como o inverso do método de alocação incremental de viagens aos arcos de uma rede viária. A matriz O-D obtida com este método é o resultado da soma sucessiva das sub-matrizes estimadas através das parcelas dos fluxos observados nos arcos da rede. Este método pode ser aplicado em qualquer tipo de rede viária: congestionada ou não congestionada e com ou sem continuidade de fluxo. Para verificação do desempenho do método foram realizados testes experimentais, nos quais os resultados obtidos foram comparados com os valores observados. O desempenho do método incremental não se mostrou satisfatório. Assim, com o intuito de verificar a sua utilidade como um método alternativo os mesmos dados foram processados através de dois métodos iterativos. Os resultados mostraram que os erros são ainda maiores do que os obtidos pelo método proposto. A principal conclusão deste trabalho é que o método incremental pode ser usado como uma alternativa aos métodos iterativos. / A synthetic O-D matrix estimation method, based on incremental loading of traffic flow, was proposed in this work. This research was motivated because of the complexity of the iterative methods for synthetic matrix estimation that might produce bias accumulation in the results. The referred incremental loading method could be defined as the inverse of the incremental assignment method for trips to links of a traffic network. The O-D matrix is gathered by successively summing the sub-matrices obtained from parts of the traffic flow counted on the links of the traffic network. This method could be applied to any traffic networks: congested or uncongested and with or without volumetric continuity. As a part of verification proceeding, several experimental tests were carried out to evaluate the method performance. In these tests the estimated results were compared with the real values. These results show that the incremental loading method performance was not satisfactory. Thus, aiming to test the utility of the incremental method, a second round of experimental tests was conducted to evaluate two iterative methods. In these second round tests, the results show that theses methods performance was worse those of the incremental method. The main conclusion of this work is that the incremental loading method for synthetic matrices estimation could be used as an alternative to the iterative methods.

Within the fields of network operation and performance measurement, it is a common requirement that the technologies involved must provide the basis for an effective, reliable, measurable and controllable service. In order to comply with the service performance criteria, the constrains often lead to very complex techniques and methodologies for the simulation, control, test, and measurement processes. This thesis addresses some of the factors that contribute to the overall spectrum of statistical performance measurements in telecommunication services. Specifically, it is concerned with the development of three low complexity and effective techniques for real-time traffic generation, control and measurement. These techniques have proved to be accurate and near optimum. In the three cases the work starts with a literature survey of known methodologies, and later new techniques are proposed and investigated by simulating the processes involved. The work is based on the use of high-speed Asynchronous Transfer Mode (ATM) networks. The problem of developing a fast traffic generation technique for the simulation of Variable Bit Rate traffic sources is considered in the first part of this thesis. For this purpose, statistical measures are obtained from the analysis of different traffic profiles or from the literature. With the aid of these measures, a model for the fast generation of Variable Bit Rate traffic at different time resolutions is developed. The simulated traffic is then analysed in order to obtain the equivalent set of statistical measures and these are compared against those observed in real traffic traces. The subject of traffic control comprises a very wide area in communication networks. It refers to the generalised classification of actions such as Connection Admission and Flow Control, Traffic Policing and Shaping. In the second part of this thesis, a method to modify the instantaneous traffic profile of a variable rate source is developed. It is particularly useful for services which have a hard bound on the cell loss probability, but a soft bound on the admissible delay, matching the characteristics of some of the services provided by ATM networks. Finally, this thesis is also concerned with a particular aspect of the operation and management of high speed networks, or OAM functions plane, namely with the monitoring of network resources. A monitoring technique based on numerical approximation and statistical sampling methods is developed and later used to characterise a particular traffic stream, or a particular connection, within a high speed network. The resulting algorithms are simple and computationally inexpensive, but effective and accurate at the same time, and are suitable for real-time processing.

Air traffic networks are essential to today’s global society. They are the fastest means of transporting physical goods and people and are a major contributor to the globalisation of the world’s economy. This increasing reliance requires these networks to have high resilience; however, previous events show that they can be susceptible to natural hazards. We assess two strategies to improve the resilience of air traffic networks and show an adaptive reconfiguration strategy is superior to a permanent re-routing solution. We find that, if traffic networks have fixed air routes, the geographical location of airports leaves them vulnerable to spatial hazard.

<p dir="ltr">Urban traffic networks encompass the collection and interlinking of urban entities, including but not limited to road networks, congested segments, mobile populations, and emergency occurrences. These entities facilitate daily human activities, support economic endeavors, and influence the trajectory of societal advancement. Comprehending the characteristics and anticipating the evolution of dynamic urban traffic networks have been fundamental building blocks in urban science. Typical examples include the primal and dual representations of road networks, the macroscopic fundamental diagram applied to congested roads, and models on the spread of diseases. Current seminal studies either devise physics metrics and models to elucidate universal traits of urban traffic networks, or exploit data-driven approaches to depict the urban landscape using vast amounts of urban data. However, these physics and data-driven methods primarily function separately, resulting in a lack of a comprehensive framework to accurately and interpretably (1) characterize the topology and dynamics of urban traffic networks; and (2) forecast the evolution of dynamics within urban traffic networks.</p><p dir="ltr">In this dissertation, we develop physics-informed graph learning methods to learn and forecast urban traffic networks in manners that are accurate, interpretable, adaptable, and applicable, aiming to advance urban science theories and support urban decision-making processes.</p><p dir="ltr">In Chapters 3 and 4, we explore novel physics knowledge of urban traffic networks in terms of new metrics and equations. In Chapter 3, we define new morphological metrics for urban road networks. Specifically, we present a network metric called spatial homogeneity (SH), which gauges the topological similarities among urban road networks using graph neural networks. Employing this metric, we analyze 11,790 urban road networks across 30 cities worldwide. Our findings reveal the inherent correlations between innercity SH, gross domestic product, and population growth. Furthermore, we quantify learning trajectories between cities from intercity SH and connect them with existing qualitative urban studies. In Chapter 4, we establish new differential equations governing dynamic urban traffic. Through a symbolic regression-based learning approach, we come up with network-level dynamic traffic equations (NDTEs), which capture time-of-day traffic flow and traffic occupancy dynamics. The advantages of NDTEs are twofold: (1) all input variables are easily obtainable; (2) they incorporate vehicle count-related variables. Our experiments on road networks in Zurich and Toronto demonstrate that the generated NDTEs offer enhanced fitting accuracy compared to the baseline model while maintaining a moderate level of equation complexity.</p><p dir="ltr">In Chapters 5, 6, and 7, we harness physics knowledge to devise graph learning approaches for urban prediction and imputation. In Chapter 5, we present NMFD-GNN, a physics-informed machine learning method that integrates the network macroscopic fundamental diagram and the graph neural network for traffic state imputation. Our approach is the first physics-informed machine learning model specifically designed for real-world traffic networks with multiple roads, while existing studies have primarily focused on individual road corridors. In Chapter 6, we develop the spatio-temporal physics ordinary differential equation (ST-PODE), which connects PODEs with spatio-temporal neural networks. ST-PODE is composed of the spatio-temporal neural network module, the PODE module, and the state transition module. We downscale our focus to the prediction of morning traffic patterns and evaluate our models using datasets from the Bay Area and Los Angeles. In Chapter 7, we address the multiwave COVID-19 prediction challenge on urban mobility networks. The proposed social awareness-based graph neural network (SAB-GNN) models the evolution of public awareness across multiple pandemic waves as an exponential function with learnable parameters. We employ the mobility, web search, and infection data in Tokyo from April 2020 to May 2021 to validate its performance. </p><p dir="ltr">The intended audiences of this dissertation comprise colleagues in the fields of artificial intelligence, urban science, transportation engineering, and network science. Our goal is to offer instructive insights to the community to (1) explore universal properties, (2) foresee future evolution, and (3) interpret models and results using massive graph-structured data in urban traffic networks.</p>

In this extended abstract, we propose an Artificial Intelligence-based model dedicated to the representation of a multi-class traffic flow, i.e. a traffic flow in which different vehicle classes (at least cars and trucks) are explicitly represented, with the aim of using it for the development of freeway traffic control schemes based on ramp management. Specifically, the goal of this work is to develop a hybrid modelling technique in which a Machine Learning component and the multi-class version of METANET model are adopted to determine a better estimation and forecasting tool for freeway traffic. The resulting model is specifically devised in order to be included in a Model Predictive Control (MPC) scheme for the required traffic state prediction.

Plus d’un quart de siècle après la chute du Mur de Berlin, la radicalité des changements politiques et économiques, caractérisés par l’intégration dans l’économie-monde et l’Union européenne, ainsi que par la récente montée du nationalisme, continue à poser des questions quant au devenir de l’espace centre-est européen. Ce contexte amène à appréhender dans ce travail l’effet de ces bouleversements au prisme des villes et de leurs évolutions. Trois forces majeures ayant guidé les transformations en Europe centrale et orientale sont examinées depuis 1989 : l’européanisation, la mondialisation et le changement endogène – relevant des traces du passé. Les dynamiques respectives de ces trois forces sont évaluées au moyen d’une approche interurbaine. Les échanges économiques entre villes centre-est européennes et celles du reste du monde sont examinés au travers de réseaux transnationaux et mondialisés – de transport aérien et de firmes. Ces échanges sont confrontés aux réseaux commerciaux entre pays. Cette thèse contribue à montrer que l’intégration à l’économie-monde s’est accompagnée d’un renforcement des logiques de polarisation divisant l’espace centre-est européen entre le Nord-Ouest et le Sud-Est. Cette intégration en cours, ou plutôt ces différentes « intégrations », ne se sont toutefois pas opérées uniquement au profit des métropoles. En effet, malgré une prédominance de l’européanisation, les liens de l’époque communiste constituent une force économique majeure pour certaines petites et moyennes villes – à l’image de l’entre-deux historique de l’espace centre-est européen. / A quarter of century after the fall of the Berlin Wall, radical political and economic changes, integration into the world economy and the European Union, and the recent reinforcement of nationalism are still persistent subjects of debate with regards to the future of Central and Eastern Europe. This thesis examines three major transformative forces in Central and Eastern Europe since 1989 at city-level: europeanisation, globalization and endogenous changes – related to path dependence effects. The dynamics of these three forces are analyzed by looking at the evolution of economic exchanges of CEE cities with other worldwide cities in the context of transnational and globalized networks – air traffic and firms. They are confronted with trade networks at country level. This dissertation illustrates that integration into the world-economy has deepened polarization in Central and Eastern Europe between the Nord-West and the South-West. This integration process or different types of integration are not only a matter for big cities and metropolises. In spite of the predominance of europeanisation, links from the communist period continue to be a major economic force, especially for small and medium-sized cities, reflecting the historical in-between situation of Central and Eastern Europe. / Ćwierć wieku później, radykalne zmiany polityczne i gospodarcze po upadku Muru Berlińskiego, integracja z gospodarką światową, przystąpienie do Unii Europejskiej oraz nasilające się tendencje nacjonalistyczne są wciąż bieżącymi tematami w dyskusji o przyszłości Europy Środkowo-Wschodniej. W tym kontekście, dysertacja proponuje analizę zmian systemowych, które dokonały się w regionie na poziomie miast. Przedmiotem badania są trzy procesy towarzyszące transformacjom po 1989: europeizacja, globalizacja oraz przemiany w regionie uwarunkowane relacjami z przeszłości. Dynamika wymienionych trzech procesów zostanie zbadana w odniesieniu do wymian ekonomicznych między miastami Europy Środkowo-Wschodniej a innymi miastami Europy i świata w sferze międzynarodowych powiązań lotniczych i firmowych, porównanych z siecią handlową ukształtowaną między państwami regionu. Wnioski badawcze wykazują, że w rezultacie integracji z gospodarką światową pogłębia się polaryzacja przestrzeni Europy Środkowo-Wschodniej w układzie północny zachód i południowy wschód. Różnorodność typów integracji odnosi się nie tylko do metropolii i dużych miast. Wobec dominującej siły europeizacji, powiązania z miastami z czasów komunistycznych są nadal ważnym aspektem funkcjonowania miast małych i średnich, ilustrując zarazem historyczną sytuację entre-deux Europy Środkowo-Wschodniej.