The present thesis aimed to investigate different traffic models and provide their analysis in context to traffic management decision support tools and evaluate the potential application of Dynameq software as a decision support system in Stockholm. A literature study, as well as a simulation case study, was used to meet the aim of the thesis. The main arguments for decision support systems were described in the context of traffic management and traffic control centres as a supportive tool for making informed decisions. The key features of the decision support system were identified as an advance knowledge-based system, inference system, or other AI system, and a simulation tool. In total, 18 traffic simulation tools were described and their applicability as decision support systems was assessed. Next, Dynameq traffic simulation software was examined both from the literature perspective and in context with a practical traffic simulation case study. The aim was to describe Dynameq software and its functionality in terms of a decision support system. Last, 5 incidents representing typical non-recurring congestion in forms of traffic incidents historically occurred during the Autumn 2019 were simulated and responses from Dynameq model were examined along with an investigation of a provided Stockholm traffic model in Dynameq. Limiting factors include the traffic data used, limited literature available for traffic software, and the quantity and quality of available incident data. The overall results were intended to provide answers to the formulated research questions. / <p>Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet</p>

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This dissertation contributes to the ongoing national project concerning the \emph{Next Generation Air Transportation System} (NextGen) that endeavors, in particular, to reshape the management of air traffic in the continental United States. Our work is part of this effort and mainly concerns modeling and algorithmic enhancements to the Airspace Planning and Collaborative Decision-Making Model (APCDM). First, we augment the APCDM to study an \emph{Airspace Flow Program} (AFP) in the context of weather-related disruptions. The proposed model selects among alternative flight plans for the affected flights while simultaneously (a) integrating slot-exchange mechanisms induced by multiple Ground Delay Programs (GDPs) to permit airlines to improve flight efficiencies through a mediated bartering of assigned slots, and (b) considering issues related to sector workloads, airspace conflicts, as well as overall equity concerns among the involved airlines in regard to accepted slot trades and flight plans. More specifically, the APCDM is enhanced to include the following: a. The revised model accommodates continuing flights, where some flight cannot depart until a prerequisite flight has arrived. Such a situation arises, for example, when the same aircraft will be used for the departing flight. b. We model a slot-exchange mechanism to accommodate flights being involved in multiple trade offers, and to permit slot trades at multiple GDP airports (whence the flight connection constraints become especially relevant). We also model flight cancelations whereby, if a flight assigned to a particular slot is canceled, the corresponding vacated slot would be made available for use in the slot-exchange process. c. Alternative equity concepts are presented, which more accurately reflect the measures used by the airlines. d. A reduced variant of the APCDM, referred to as \textbf{APCDM-Light}, is also developed. This model serves as a fast-running version of APCDM to be used for quick-turn analyses, where the level of modeling detail, as well as data requirements, are reduced to focus only on certain key elements of the problem. e. As an alternative for handling large-scale instances of APCDM more effectively, we present a \emph{sequential variable fixing heuristic} (SFH). The list of flights is first partitioned into suitable subsets. For the first subset, the corresponding decision variables are constrained to be binary-valued (which is the default for these decision variables), while the other variables are allowed to vary continuously between 0 and 1. If the resulting solution to this relaxed model is integral, the algorithm terminates. Otherwise, the binary variables are fixed to their currently prescribed values and another subset of variables is designated to be binary constrained. The process repeats until an integer solution is found or the heuristic encounters infeasibility. f. We experiment with using the APCDM model in a \emph{dynamic, rolling-horizon framework}, where we apply the model on some periodic basis (e.g., hourly), and where each sequential run of the model has certain flight plan selections that are fixed (such as flights that are already airborne), while we consider the selection among alternative flight plans for other imminent flights in a look-ahead horizon (e.g., two hours). These enhancements allow us to significantly expand the functionality of the original APCDM model. We test the revised model and its variants using realistic data derived from the \emph{Enhanced Traffic Management System} (ETMS) provided by the \emph{Federal Aviation Administration} (FAA). One of the new equity methods, which is based on average delay per passenger (or weighted average delay per flight), turns out to be a particularly robust way to model equity considerations in conjunction with sector workloads, conflict resolution, and slot-exchanges. With this equity method, we were able to solve large problem instances (1,000 flights) within 30 seconds on average using a 1\% optimality tolerance. The model also produced comparable solutions within about 20 seconds on average using the Sequential Fixing Heuristic (SFH). The actual solutions obtained for these largest problem instances were well within 1\% of the best known solution. Furthermore, our computations revealed that APCDM-Light can be readily optimized to a 0.01\% tolerance within about 5 seconds on average for the 1,000 flight problems. Thus, the augmented APCDM model offers a viable tool that can be used for tactical air traffic management purposes as an airspace flow program (particularly, APCDM-Light), as well as for strategic applications to study the impact of different types of trade restrictions, collaboration policies, equity concepts, and airspace sectorizations. The modeling of slot ownership in the APCDM motivates another problem: that of generating detoured flight plans that must arrive at a particular slot time under severe convective weather conditions. This leads to a particular class of network flow problems that seeks a shortest path, if it exists, between a source node and a destination node in a connected digraph $G(N,A)$, such that we arrive at the destination at a specified time while leaving the source no earlier than a lower bounding time, and where the availability of each network link is time-dependent in the sense that it can be traversed only during specified intervals of time. We refer to this problem as the \emph{reverse time-restricted shortest path problem} (RTSP). We show that RTSP is NP-hard in general and propose a dynamic programming algorithm for finding an optimal solution in pseudo-polynomial time. Moreover, under a special regularity condition, we prove that the problem is polynomially solvable with a complexity of order $O(|N / A|)$. Computational results using real flight generation test cases as well as random simulated problems are presented to demonstrate the efficiency of the proposed solution procedures. The current airspace configuration consists of sectors that have evolved over time based on historical traffic flow patterns. \citet{kopardekar_dyn_resect_2007} note that, given the current airspace configuration, some air traffic controller resources are likely under-utilized, and they also point out that the current configuration limits flexibility. Moreover, under the free-flight concept, which advocates a relaxation of waypoint traversals in favor of wind-optimized trajectories, the current airspace configuration will not likely be compatible with future air traffic flow patterns. Accordingly, one of the goals for the \emph{NextGen Air Transportation System} includes redesigning the airspace to increase its capacity and flexibility. With this motivation, we present several methods for defining sectors within the \emph{National Airspace System} (NAS) based on a measure of sector workload. Specifically, given a convex polygon in two-dimensions and a set of weighted grid points within the region encompassed by the polygon, we present several mixed-integer-programming-based algorithms to generate a plane (or line) bisecting the region such that the total weight distribution on either side of the plane is relatively balanced. This process generates two new polygons, which are in turn bisected until some target number of regions is reached. The motivation for these algorithms is to dynamically reconfigure airspace sectors to balance predicted air-traffic controller workload. We frame the problem in the context of airspace design, and then present and compare four algorithmic variants for solving these problems. We also discuss how to accommodate monitoring, conflict resolution, and inter-sector coordination workloads to appropriately define grid point weights and to conduct the partitioning process in this context. The proposed methodology is illustrated using a basic example to assess the overall effect of each algorithm and to provide insights into their relative computational efficiency and the quality of solutions produced. A particular competitive algorithmic variant is then used to configure a region of airspace over the U.S. using realistic flight data. The development of the APCDM is part of an ongoing \emph{NextGen} research project, which envisages the sequential use of a variety of models pertaining to three tiers. The \emph{Tier 1} models are conceived to be more strategic in scope and attempt to identify potential problematic areas, e.g., areas of congestion resulting from a severe convective weather system over a given time-frame, and provide aggregate measures of sector workloads and delays. The affected flow constrained areas (FCAs) highlighted by the results from these \emph{Tier 1} models would then be analyzed by more detailed \emph{Tier 2} models, such as APCDM, which consider more specific alternative flight plan trajectories through the different sectors along with related sector workload, aircraft conflict, and airline equity issues. Finally, \emph{Tier 3} models are being developed to dynamically examine smaller-scaled, localized fast-response readjustments in air traffic flows within the time-frame of about an hour prior to departure (e.g., to take advantage of a break in the convective weather system). The APCDM is flexible, and perhaps unique, in that it can be used effectively in all three tiers. Moreover, as a strategic tool, analysts could use the APCDM to evaluate the suitability of potential airspace sectorization strategies, for example, as well as identify potential capacity shortfalls under any given sector configuration. / Ph. D.

The railway industry in Ethiopia has been an important way of communication and transportation for a long time. It is a developing sector with many national plans for future investments. However, the current major corridors of Ethio­-Djibouti and Awash­-Weldiya have interoperability issues due to two different signalling systems being used. Thus, this study was undertaken with the objectives of assessing technical interoperability of the Chinese signalling system (CTCS) and the European signalling system (ETCS), identifying a possible technical solution regarding the interoperability issues, and assessing the economic benefits of a harmonized system. Compatibility of the two signalling systems was analyzed particularly with respect tothe technical configurations by thoroughly investigating each system’s features and making interviews and having discussions with professionals who worked with the two systems. In addition, a life cycle cost analysis of the Ethio­Djibouti signalling system was done with data obtained from Ethiopian Railway Corporation and compared with average life cycle costs of ETCS level 1. After analyzing each system, two possible technical solutions were found to achieve interoperability between the two systems used in Ethiopia currently. The first technical solution is upgrading Ethio­Djiboutirailway line from the current CTCS level 0 to CTCS level 2 to be compatible with the new Awash­Weldiya line which will use ETCS level 1. The second technical solution to make the two systems interoperable is to install ERTMS as an overlay on the existing CTCS level 0 as ERTMS is designed as an overlay system that could be installed on top of an existing national infrastructure and vehicles. However, these technical solutions have to be tested in laboratory and onsite with respect to their practical and economical feasibility. / Järnvägsindustrin i Etiopien har länge varit viktig för kommunikation och transport. Det är en sektor under utveckling med många nationella planer för framtida investeringar. De nuvarande korridorerna i Ethio­Djibouti och Awash­Weldiya har emellertid interoperabilitetsproblem på grund av två olika signalsystem. Detta examensarbete har analyserat kompatibiliteten för de två signalsystemen särskilt med avseende på de tekniska konfigurationerna genom att noggrant undersöka varje systems funktioner och genom intervjuer och diskussioner med yrkesverksamma somhar arbetat med de två systemen. Dessutom genomfördes en livscykelkostnadsanalys av Ethio­Djibouti signalssystemet med den data som erhölls från Ethiopian Railway Corporation. Efter analys av varje system hittades två möjliga tekniska lösningar för att uppnå interoperabilitet mellan de två systemen som används i Etiopien för närvarande. Den första tekniska lösningen är att uppgradera Ethio­Djiboutis järnvägslinje från nuvarande CTCS nivå 0 till CTCS nivå 2 för att vara kompatibel med den nya Awash­Weldiya­linjen som kommer att använda ETCS nivå 1. Den andra tekniska lösningen för att göra de två systemen interoperabla är att installera ERTMS som ett överlägg på det befintliga CTCS­0 signalsystemet, eftersom ERTMS är utformat som ett överläggssystem som kan installeras ovanpå en befintlig nationell infrastruktur. Dessa tekniska lösningar måste dock testas i laboratorium och i fält med avseende på deras praktiska och ekonomiska genomförbarhet.

This research is concerned with the technoeconomic aspects of modern and next-generation telecommunications including the Internet service. The goal of this study thereof is tailored to address the following: (i) Reviewing the technoeconomic considerations prevailing in telecommunication (telco) systems and their implicating futures; (ii) studying relevant considerations by depicting the modern/next-generation telecommunications as a digital ecosystem viewed in terms of underlying complex system evolution (akin to biological systems); (iii) pursuant to the digital ecosystem concept, co-evolution modeling of competitive business structures in the technoeconomics of telco services using dichotomous (flip-flop) states as seen in prey-predator evolution; (iv) specific to Internet pricing economics, deducing the profile of consumer surplus versus pricing model under DiffServ QoS architecture pertinent to dynamic- , smart- and static-markets; (v) developing and exemplifying decision-making pursuits in telco business under non-competitive and competitive markets (via gametheoretic approach); (vi) and modeling forecasting issues in telco services addressed in terms of a simplified ARIMA-based time-series approach, (which includes seasonal and non-seasonal data plus goodness-fit estimations in time- and frequency-domains). Commensurate with the topics indicated above, necessary analytical derivations/models are proposed and computational exercises are performed (with MatLabTM R2006b and other software as needed). Extensive data gathered from open literature are used thereof and, ad hoc model verifications are performed. Lastly, results are discussed, inferences are made and open-questions for further research are identified. / by Renata Cristina Tourinho Sardenberg. / Thesis (Ph.D.)--Florida Atlantic University, 2010. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.

Nos últimos anos, os países desenvolvidos vêm dedicando crescentes esforços para integrar o Veículo Aéreo Não Tripulado (VANT) no espaço aéreo controlado, visando sua utilização para fins civis. Embora este tema ainda não tenha consenso quanto aos critérios a serem adotados, é de comum acordo na comunidade que, no mínimo, devam ser mantidos os atuais níveis de segurança (\"Safety\") praticados pela aviação civil mundial. Neste cenário, a convivência entre aeronaves comerciais, com cada vez mais passageiros e aeronaves não tripuladas, traz sérias preocupações com relação à capacidade que o sistema atual de navegação, controle, vigilância e de Gerenciamento de Tráfego Aéreo tem para lidar com situações de perigo decorrentes da aproximação entre estas duas categorias de aeronaves. Neste contexto, esta tese propõe uma modelagem de um VANT, tendo-se como ponto de partida os conceitos de robô móvel, cujo modelo de inteligência é fundamentado em Inteligência Artificial Distribuída (IAD), implementável segundo o paradigma de Sistemas Multi-Agentes (SMA) e que leve em consideração os principais requisitos de \"Safety\" exigidos pelo \"Communication Navigation System/Air Traffic Management\" (CNS/ATM), de modo a permitir a futura inserção destas aeronaves no espaço aéreo controlado. / During the last years, developed countries are conducting efforts to integrate Unmanned Aircraft Vehicles (UAVs) to the controlled airspace, aiming at their civilian use. So far, there has been no common consensus on the criteria to be adopted by the community that should, at least, keep the minimum safety levels international aviation has already attained. In this scenario, commercial aircrafts - with more and more passengers - and UAVs will share the same space. There will be a lot of concern related to the actual navigation, control and surveillance system capacity as well as to the air traffic control management ability to handle potentially dangerous situations due to the approximation between aircrafts of these two categories. Based on this scenario, this thesis proposes an UAV modeling having as starting point the mobile robot concept, of which the intelligence model based on Distributed Artificial Intelligence, can be implemented by using the Multi Agent Systems paradigm. This paradigm should take the main safety requirements as an obligation, as defined by the Communication Navigation System/Air Traffic Management (CNS/ATM), as a way of handling the future insertion of UAVs into the controlled airspace.

Modern traffic management systems often rely on static technologies, such as sensors and CCTV-cameras, in the gathering of data regarding the current traffic situation. Recent reports have shown that this method can result in a lack of coverage in Stockholm, Sweden. In addressing this issue, an alternative strategy to installing more sensors and CCTV-cameras could be to utilize crowdsourced traffic data from other sources, such as Waze. In order to examine the usage and potential utility of crowdsourced data in traffic management, the Swedish Transport Administration’s center in Stockholm, Trafik Stockholm, developed a web application which visualizes traffic data from both official sources and Waze. While the application was successful in doing so, it revealed the problem of integrating the traffic data from these two sources, as a significant portion of the data was redundant, and the reliability occasionally was questionable. This study aims at determining how issues regarding redundancy and reliability can be resolved in the integration of crowdsourced and official traffic data. Conducted using a design science research strategy, the study investigates these issues by designing and developing an artifact that implements integration methods to match alerts from the data sources based on temporal and spatial proximity constraints. The artifact was evaluated through test sessions in which real-time traffic data from all over Sweden was processed, and through acceptance testing with the stakeholders of the application. Analysis of the results from the evaluations shows that the artifact is effective in reducing the redundancy in the crowdsourced data and that it can provide a more solid ground for reliability assessment. Furthermore, the artifact met its expectations and requirements, demonstrating a proof-of-concept and a proof-of-acceptance. Based on these results, the study concludes that by analyzing temporal and spatial factors in crowdsourced data, redundancy issues in the integration of crowdsourced and official traffic can be resolved to a large extent. Furthermore, it is concluded that reliability issues in the same context can be resolved to a high degree by managing redundancy factors in combination with general traffic management factors. While the study is focused on traffic management, the issues of redundancy and reliability are not restricted to crowdsourced data in this context specifically. Thus, the results of the study are potentially of interest to researchers investigating other areas of application for crowdsourcing as well.