Models and Algorithms for an Efficient Market-Driven Management Of

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Models and Algorithms for an Efficient Market-Driven Management Of Universita` degli Studi di Trieste DIPARTIMENTO DI INGEGNERIA E ARCHITETTURA XVIII Ciclo del Dottorato di Ricerca in Ingegneria e Architettura Indirizzo ingegneria Civile e Architettura Models and algorithms for an efficient market-driven management of European airspace demand Settore scientifico/disciplinare ICAR/05 TRASPORTI Supervisore di Tesi: Dottoranda: Chiar.mo Prof. Lorenzo Castelli Desir´eeRigonat Coordinatore: Chiar.ma Prof.ssa Paola di Biagi Anno Accademico 2014 - 2015 Alla mia famiglia Acknowledgements This work is co-financed by EUROCONTROL, acting on behalf of the SESAR Joint Undertak- ing (the SJU) and the European Union as part of Work Package E in the SESAR Programme under project E.02.33 SATURN (Strategic Allocation of Traffic Using Redistribution in the Net- work). Opinions expressed in this work reflect the authors views only and EUROCONTROL and/or the SJU shall not be considered liable for them or for any use that may be made of the information contained herein. Esposizione riassuntiva La gestione del traffico aereo in Europa (Air Traffic Management, ATM) `eun' attivit`acomplessa, poich´e molti attori e componenti vi interagiscono per garantire l’efficienza e la sicurezza delle operazioni. Negli ultimi dieci anni questo sistema ha iniziato a mostrare segni di debolezza in termini di capacit`adi sostenere in modo efficiente il traffico in costante crescita. Dal 2012, otto Centri di Controllo (Area Control Centre, ACC) hanno riferito sistematicamente gravi ritardi causati da carenza di capacit`adello spazio aereo. Tali carenze sono evidenti anche analizzando la distribuzione del traffico attuale e dal momento che le previsioni a lungo termine di crescita del traffico Europeo prospettano un inccremento del 50% dei voli nei prossimi venti anni, il livello di congestione non pu`oche aggravarsi. Questa tesi di dottorato `estata realizzata nell'ambito di un progetto SESAR WP-E denominato SATURN (Strategic Allocation of Traffic Using Redistribution in the Network), in il cui obiettivo era investigare sulla possibilit`adi mitigare questi squilibri della domanda di capacit`anella fase strategica della pianificazione dei voli, cio`econ mesi di anticipo dalla giornata delle operazioni, attraverso la modulazione delle tasse di sorvolo. Queste sono le tasse che le compagnie aeree devono corrispondere ai fornitori di servizi di navigazione (Air Navigation Service Provider, ANSP) per l'utilizzo del rispettivo spazio aereo. Le tasse di sorvolo sono raccolte da Eurocontrol e redistribuite agli ANSP per coprire i costi legati alla fornitura di servizi di comunicazione, navigazione e controllo. Il lavoro si sviluppa in due parti: la prima comprende un capitolo che descrive il funzionamento del sistema ATM attuale e i criteri con cui le tasse di sorvolo vengono attualmente calcolate. Il capitolo successivo fornisce una panoramica di quali metodi di tariffazione sono applicati in settori diversi dal trasporto aereo per affrontare i problemi di congestione. La seconda parte della tesi `edi carattere sperimentale e presenta un' applicazione di un approccio centralizzato di peak load pricing, PLP, al sistema ATM europeo. PLP `euna tecnica di tariffazione comunemente applicata a trasporti e utenze i cui picchi di domanda sono periodici e prevedibili. Nel PLP viene assegnato un prezzo pi`ualto per il consumo del servizio quando si prevede forte domanda, e uno pi`ubasso per l'utilizzo del servizio nel tempo e/o posizioni che non sono critici. L'applicazione al sistema ATM europeo `emodellata come un gioco di Stackelberg che rappresenta l'interazione tra un’autorit`acentrale che imposta le tasse di sorvolo per tutti gli ANSP europei, e le compagnie aeree che vogliono operare voli al costo minimo. Questa interazione `eformulata attraverso un problema di ottimizzazione bilivello, presentato nel terzo capitolo. Il capitolo successivo `ededicato alla preparazione e gestione di dati reali del traffico aereo al fine di ottenere istanze di dati che possano essere utilizzate per testare il modello presentato (e anche per le prove computazionali degli altri modelli studiati in SATURN). L'ultimo capitolo `ededicato agli approcci risolutivi adottati per la risoluzione esatta del modello di peak load pricing sulle istanze di dati ottenute. Questo obiettivo ha presentato diverse sfide dal punto di vista computazionale, sia per la difficolt`aintrinseca del modello bilivello, sia per le grandi dimensioni delle istanze di dati. I risultati ottenuti sono realistici nella prospettiva di un'applicazione reale e mostrano che la modulazione delle tasse di sorvolo pu`oindurre una redistribuzione pi`usosteni- bile del traffico attraverso la scelta di rotte alternative e moderate modifiche agli orari di partenze e arrivi. Parole chiave: gestione del traffico aereo, tasse di sorvolo, congestion pricing, peak load pricing, programmazione bilivello, ottimizzazione combinatoria, data engineering, basi di dati geografiche. Abstract European Air Traffic Management (ATM) is a complex system where many actors and components interact to ensure the efficiency and safety of operations. In the last ten years this system has started to show signs of weakness in terms of its ability to sustain a growing amount of traffic in an efficient way. Since 2012, eight Area Control Centres have systematically reported severe en route Air Traffic Flow Management delays due to shortages in airspace capacity. Such shortages are evident also in the current and short-term analysis of traffic distribution. Since long term forecasts of European air traffic growth expect the amount of flights to likely increase by 50% in the next twenty years, the level of congestion is only likely to become more severe. This thesis was carried out within a SESAR WP-E project named SATURN (Strategic Allocation of Traffic Using Redistribution in the Network), which investigated the possibility of mitigating these demand-capacity imbalances at the strategic level of flight planning, that is, months in advance of the day of operations, through the modulation of en-route charges. These are the charges that airspace users have to correspond to Air Navigation Service Providers (ANSPs) when flying through the respective airspace. They are collected by Eurocontrol and redistributed to ANSPs for covering the costs of air navigation and communication service provision. The work unfolds in two parts: the first comprises a chapter that illustrates how the current ATM system works and how airspace users are charged for air navigation services. Then an overview of how pricing methods are applied in industries other than air transport to tackle congestion issues is also provided. The second part of the thesis is experimental and presents an application of a centralised approach to peak load pricing (PLP) to European ATM. This is a common pricing technique in trans- ports and utilities where peaks in demand are periodic and predictable; PLP assigns a higher price for the consumption of the service when high demand is expected, and a lower one for using the ser- vice in time and/or locations that are not critical. The application to European ATM is modelled as a Stackelberg game that represents the interaction between a central authority that sets peak and off peak rates for all European ANSPs and airspace users that want to operate flights at the minimum cost. This interaction is formulated into a bilevel optimisation problem, that is illustrated in the third chapter. The following one is dedicated to preparation and management of actual air traffic data in order to obtain data instances that could be used for testing the presented model (and used for testing other models within SATURN also). The final chapter is dedicated to the exact resolution approaches attempted to solve the centralised peak load pricing model on the obtained data instances, a task that presented several computational challenges due to both the intrinsic difficulty of the bilevel model and to the large size of the data instances. A large size regional example on one country, together with some further insights obtained from a metaheuristic solving approach carried out within SATURN are also provided. Obtained results are realistic with regard to the application. They show that pricing modula- tion can, indeed, become an effective mean for tackling demand-capacity imbalances by inducing airspace users to apply reroutings and moderate schedule displacements to the flights involved in such imbalances. Keywords: air traffic management, en route charges, congestion pricing, peak load pricing, bilevel programming, combinatorial optimisation, data engineering, geographic databases. Contents Introduction 12 I Background and motivations for the study 17 1 Air Traffic Management in Europe 19 1.1 Relevant stakeholders . 19 1.1.1 Eurocontrol (EU designated Network Manager) . 19 1.1.2 Air Navigation Service Providers (ANSPs) . 21 1.1.3 Airline Operators (AOs) . 22 1.2 Introduction to European Air Traffic Management (ATM) . 25 1.2.1 Airspace structure and organisation . 26 1.2.2 Routes . 29 1.2.3 Air Traffic Flow Management and flight planning . 31 1.2.4 ANS charges . 32 1.3 Legislative framework: the Single European Sky (SES) initiative . 34 1.4 Air traffic today, congestion of airspace and growth forecasts . 37 1.4.1 Short term traffic growth forecasts: 2014-2019 . 38 1.4.2 Long term traffic growth forecasts: 2035 . 42 1.5 Route charges modulation as a mean to mitigate airspace congestion (project SATURN) . 44 2 Pricing in network-based industries 47 2.1 Relevant elements of theory of pricing . 47 2.2 Classification framework for pricing techniques . 49 2.3 Data networks (telecommunications) . 51 2.4 Electricity . 55 2.4.1 Wholesale market . 56 2.4.2 Retail market . 58 2.5 Road transport in Europe . 62 2.5.1 Pure pricing . 63 2.5.2 Congestion Pricing . 63 2.5.3 Hybrid (credit-based) pricing . 67 2.6 Rail transport in Europe . 69 2.6.1 Costs of a rail infrastructure . 70 2.6.2 Pricing principles . 72 2.6.3 Implementation . 74 2.6.4 Tariff systems currently in use . 75 1 2.6.5 Further relevant research .
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