Abstract

The call for papers resulted in a high number of submis- sions, from which we have been able to select 12 excellent papers dealing with the different aspects of satellite commu- nications and navigation. Multiple-input multiple-output (MIMO) techniques are attracting a considerable amount of attention from within the terrestrial wireless community. The first paper of this spe- cial issue, “Multisatellite MIMO communications at Ku band and above: investigations on spatial multiplexing for capac- ity improvement and selection diversity for interference mit- igation,” considers the application of such technology over a satellite platform operating in the Ku band and above. The paper considers how MIMO can be used to increase capac- ity by using a satellite spatial multiplexing system and how antenna selection can be used to mitigate interference. The next paper “Investigations in satellite MIMO channel model- ing: accent on polarization” looks at MIMO systems from the polarization diversity point of view and dwells on the satellite cooperative communication concepts. Switch and stay combining (SSC) is a form of diversity technique used in digital receivers to compensate for fade events introduced by the mobile channel. The third paper “Performance analysis of SSC diversity receivers over corre- lated Ricean fading satellite channels” investigates the per- formance of dual-branch SSC receivers for different fading channel characteristics. The next four papers deal with the emerging scenario of mobile digital video broadcasting (DVB-S2 and RCS mo- bile). Alternative approaches to counteracting fading chan- nels introduced when operating in a train environment re- ceiving satellite DVB-S2 are presented in the paper “Ad- vanced fade countermeasures for DVB-S2 systems in railway scenarios.” Here, as a result of simulation analysis, antenna diversity and packet-level forward error correction mecha- nisms are proposed and their impact is evaluated with respect to the receiver design and system complexity. The theme of DVB-S2 is continued with the paper “Capacity versus bit er- ror rate trade-off in the DVB-S2 forward link,” which inves- tigates how satellite capacity can be optimised for DVB-S2 transmissions. The DVB return channel via satellite (DVB- RCS) is then addressed in “Frequency estimation in iterative interference cancellation applied to multibeam satellite sys- tems,” which considers the application of interference cancel- lation on the reverse link of a multibeam satellite system, us- ing DVB-RCS with convolutional coding as an example. The paper “A QoS architecture for DVB-RCS next-generation satellite networks” proceeds to design and emulate a quality- of-service (QoS) architecture that demonstrates using real multimedia applications how QoS can be supported over a DVB-RCS network. 2 EURASIP Journal on Wireless Communications and Networking Synchronization aspects are dealt with in “Maximum likelihood timing and carrier synchronization in burst-mode satellite transmissions.” The paper addresses the problem of achieving synchronisation for a burst-mode satellite trans- mission over an AWGN channel. The subject of burst trans- mission continues with the paper “Burst format design for optimum joint estimation of Doppler-shift and Doppler- rate in packet satellite communications,” which considers optimising the burst-format of packet-oriented transmis- sions by proposing very-low-complexity algorithms for car- rier Doppler-shift and Doppler-rate estimation. A network comprising satellite and high-altitude plat- forms is considered in the paper “TCP-call admission con- trol interaction in multiplatform space architectures.” Cross- layer techniques are implemented by means of TCP feeding back into call admission control (CAC) procedures for the purpose of prevention of congestion and improvement in QoS. Finally, since navigation is an extremely important part of the satellite system family, we have included two papers. The first paper “Efficient delay tracking methods with side- lobes cancellation for BOC-modulated signals” deals with bi- nary offset carrier (BOC) modulation, which is adopted in typical navigation systems. The paper considers how to improve the tracking of the main lobe of the BOC-modulated signal by using sidelobe suppression techniques. An alternative approach based on filter bank processing is presented in “Analysis of filter-bank-based methods for fast serial acqui- sition of BOC-modulated signals” to conclude the special issue. Document type: Part of book or chapter of book

Abstract

Traffic engineering encompasses a set of techniques that can be used to control the flow of traffic in data networks. We discuss several of those techniques that have been developed during the last few years. Some techniques are focused on pure IP networks while others have been designed with emerging technologies for scalable Quality of Service (QoS) such as Differentiated Services and MPLS in mind. We first discuss traffic engineering techniques inside a single domain. We show that by using a non-linear programming formulation of the traffic engineering problem it is possible to meet the requirements of demanding customer traffic, while optimising the use of network resources, through the means of an automated provisioning system. We also extend the functionality of the traffic engineering system through policies. In the following, we discuss the techniques that can be used to control the flow of packets between domains. First, we briefly describe interdomain routing and the Border Gateway Protocol (BGP). Second, we summarise the characteristics of interdomain traffic based on measurements with two different Internet Service Providers. We show by simulations the limitations of several BGP-based traffic engineering techniques that are currently used on the Internet. Then, we discuss the utilisation of BGP to exchange QoS information between domains by using the QOS_NLRI attribute to allow BGP to select more optimum paths. Finally, we consider the multi-homing problem and analyse the current proposed IPv6 multi-homing solutions are analysed along with their impact on communication quality. Document type: Part of book or chapter of book

Abstract

The data demands and economics surrounding IP internetworking are such that IP routers are now connecting directly to SDH or DWDM systems. As such, many of the traditional mechanisms used to engineer the traffic over the physical infrastructure are no longer available. Consequently a new approach is required. This paper outlines a set of mechanisms and procedures, including enhancements to the layer 3 routeing and signalling protocols ad MPLS forwarding that, when combined, provide the capabilities to provide traffic engineering capabilities in an optical IP environment. Document type: Book

Abstract

Most prior work on congestion in datagram systems focuses on buffer management. We find it illuminating to consider the case of a packet switch with infinite storage. Such a packet switch can never run out of buffers. It can, however, still become congested. The meaning of congestion in an infinite-storage system is explored. We demonstrate the unexpected result that a datagram network with infinite storage, first-in, first-out queueing, at least two packet switches, and a finite packet lifetime will, under overload, drop all packets. By attacking the problem of congestion for the infinite-storage case, we discover new solutions applicable to switches with finite storage. Document type: Report

Abstract

This paper provides an overview of the reliability-centered maintenance (RCM) engineering process. RCM is a unique tool used by reliability, safety, and/or maintenance engineers for developing optimum maintenance plans which define requirements and tasks to be performed in achieving, restoring, or maintaining the operational capability of a system or equipment. Implementing the RCM process requires the application of a decision logic that enables systematic analysis of failure mode, rate, and criticality data to determine the most effective maintenance requirements for maintenance-important items. It is through this process that the scheduled maintenance burden and support costs are reduced while sustaining the necessary readiness state. The RCM process is designed to focus engineering attention to the part level in a formal and disciplined manner leading logically to the formulation of a maintenance strategy and plan. RCM benefits include: *The development of high quality maintenance plans in less time and at lower cost. *The availability of a maintenace history for each system; one is able to correlate this experience with specific parts and their failure modes and criticalities. *The assurance that all maintenance-important parts and their failure modes and criticality are considered in the development of maintenance requirements. *The increased probability that the level and content of the maintenance requirement is optimally specified. *The basis for routine, on-line information exchange among the engineering staff and management even in a widely dispersed organization. Document type: Report

Abstract

Advanced Driver Assistance Systems (ADAS) already make a major contribution to driving safety. To further increase this contribution, it is, however, vital that future intelligent vehicles perceive, predict, and assess their environment more comprehensively. In this context, the present dissertation approaches the questions i) how to represent the driving environment adequately within an environment model, ii) how to obtain such a representation, and iii) how to predict the future traffic scene evolution for proper criticality assessment. Bayesian inference provides the common theoretical framework of all designed methods. Based on the shortcomings of existing environment representations, a novel parametric representation of general driving environments is first introduced in this work. It consists of a combination of dynamic object maps for moving objects and so-called Parametric Free Space (PFS) maps for static environment structures. PFS maps model the environment by a closed curve around the vehicle, which encloses relevant drivable free space. The representation compactly describes all essential information contained in common occupancy grid maps, suppresses irrelevant details, and consistently separates between static and dynamic environment objects. A novel method for grid mapping in dynamic road environments provides the basis to realize this representation. Therein, dynamic cell hypothesis are detected, clustered, and subsequently tracked and classified with an adaptive Bayesian multiple model filter for jump Markov nonlinear systems – the so-called Interacting Multiple Model Unscented Kalman Probabilistic Data Association Filter (IMM-UK-PDAF). The intermediate result is a dynamic object map and an optimized grid of the static driving environment. From the optimized grid, relevant free space is then extracted by methods of image analysis, and robustly converted to a PFS map in a final B-Spline contour tracking step. Evaluations and experiments, which were performed with an experimental vehicle equipped with radars and a stereo camera in real driving environments, confirm the advantages of the real-time capable approach. The so-obtained representation additionally forms the basis of a novel method for long-term trajectory prediction and criticality assessment. Therein, a three-layered Bayesian network is used to infer current driving maneuvers of traffic participants initially. A trash maneuver class allows the detection of irrational driving behavior and the seamless application from highly-structured to non-structured environments. Subsequently, maneuver-based prediction models in form of stochastic processes are presented and employed to predict the vehicle configurations under consideration of uncertainties in the maneuver executions. Finally, the criticality time metric Time-To-Critical-Collision-Probability (TTCCP) is introduced as a generalization of the time metric Time-To-Collision (TTC) for arbitrary, uncertain, multi-object driving environments and longer prediction horizons. The TTCCP considers all uncertain, maneuver-based predictions and is estimated via Monte Carlo simulations. Simulations confirm its potential to suppress false warnings, to generate timely true warnings, and to generate warnings in critical almost-collision situations effectively. All methods are part of the driver assistance system PRORETA 3, which has been co-developed in the context of this thesis. It constitutes a novel, integrated approach to collision avoidance and vehicle automation and thereby makes a valuable contribution to realize the Vision Zero – the vision of a future without traffic deaths.

Abstract

This chapter discusses the common fundamental characteristics of digital signal processors. Most of the digital signal processing (DSP) chips are single processor devices. There exist chips that integrate multiple DSP processors on the same chip whereas others combine a DSP processor with a microcontroller. Some manufacturers offer DSP cores that are intended to be used as building blocks in creating a semi-custom chip. This allows the designer to integrate a programmable DSP and other custom circuitry onto a single application-specific integrated circuit (ASIC). The DSP core cuts design time and is most useful for high volume production designs for specific applications in areas such as telecommunications. In some cases, the vendor providing the core is also the foundry fabricating the ASIC. In other cases, the vendor simply licenses the core design to the customer, who then selects an appropriate foundry. All DSP chips have a multiplier that can multiply two native-sized data in a single instruction cycle. All DSP chips have a multiplier that can multiply two native-sized data in a single instruction cycle. But different designs lead to different characteristics. Most DSP chips implement what is known as the Harvard architecture, or multiple bus structure, one for program instructions and two for data.

Abstract

Mención Internacional en el título de doctor The Air Traffic Management (ATM) system in the busiest airspaces in the world is currently being overhauled to deal with multiple capacity, socioeconomic, and environmental challenges. One major pillar of this process is the shift towards a concept of operations centered on aircraft trajectories (called Trajectory-Based Operations or TBO in Europe) instead of rigid airspace structures. However, its successful implementation (and, thus, the realization of the associated improvements in ATM performance) rests on appropriate understanding and management of uncertainty. Due to its complex socio-technical structure, the design and operations of the ATM system are heavily impacted by uncertainty, proceeding from multiple sources and propagating through the interconnections between its subsystems. One major source of ATM uncertainty is weather. Due to its nonlinear and chaotic nature, a number of meteorological phenomena of interest cannot be forecasted with complete accuracy at arbitrary lead times, which leads to uncertainty or disruption in individual air and ground operations that propagates to all ATM processes. Therefore, in order to achieve the goals of SESAR and similar programs, it is necessary to deal with meteorological uncertainty at multiple scales, from the trajectory prediction and planning processes to flow and traffic management operations. This thesis addresses the problem of single-aircraft flight planning considering two important sources of meteorological uncertainty: wind prediction error and convective activity. As the actual wind field deviates from its forecast, the actual trajectory will diverge in time from the planned trajectory, generating uncertainty in arrival times, sector entry and exit times, and fuel burn. Convective activity also impacts trajectory predictability, as it leads pilots to deviate from their planned route, creating challenging situations for controllers. In this work, we aim to develop algorithms and methods for aircraft trajectory optimization that are able to integrate information about the uncertainty in these meteorological phenomena into the flight planning process at both pre-tactical (before departure) and tactical horizons (while the aircraft is airborne), in order to generate more efficient and predictable trajectories. To that end, we frame flight planning as an optimal control problem, modeling the motion of the aircraft with a point-mass model and the BADA performance model. Optimal control methods represent a flexible and general approach that has a long history of success in the aerospace field. As a numerical scheme, we use direct methods, which can deal with nonlinear systems of moderate and high-dimensional state spaces in a computationally manageable way. Nevertheless, while this framework is well-developed in the context of deterministic problems, the techniques for the solution of practical optimal control problems under uncertainty are not as mature, and the methods proposed in the literature are not applicable to the flight planning problem as it is now understood. The first contribution of this thesis addresses this challenge by introducing a framework for the solution of general nonlinear optimal control problems under parametric uncertainty. It is based on an ensemble trajectory scheme, where the trajectories of the system under multiple scenarios are considered simultaneously within the same dynamical system and the uncertain optimal control problem is turned into a large conventional optimal control problem that can be then solved by standard, well-studied direct methods in optimal control. We then employ this approach to solve the robust flight plan optimization problem at the planning horizon. In order to model uncertainty in the wind and estimating the probability of convective conditions, we employ Ensemble Prediction System (EPS) forecasts, which are composed by multiple predictions instead of a single deterministic one. The resulting method can be used to optimize flight plans for maximum expected efficiency according to the cost structure of the airline; additionally, predictability and exposure to convection can be incorporated as additional objectives. The inherent tradeoffs between these objectives can be assessed with this methodology. The second part of this thesis presents a solution for the rerouting of aircraft in uncertain convective weather scenarios at the tactical horizon. The uncertain motion of convective weather cells is represented with a stochastic model that has been developed from the output of a deterministic satellite-based nowcast product, Rapidly Developing Thunderstorms (RDT). A numerical optimal control framework, based on the pointmass model with the addition of turn dynamics, is employed for optimizing efficiency and predictability of the proposed trajectories in the presence of uncertainty about the future evolution of the storm. Finally, the optimization process is initialized by a randomized heuristic procedure that generates multiple starting points. The combined framework is able to explore and as exploit the space of solution trajectories in order to provide the pilot or the air traffic controller with a set of different suggested avoidance trajectories, as well as information about their expected cost and risk. The proposed methods are tested on example scenarios based on real data, showing how different user priorities lead to different flight plans and what tradeoffs are then present. These examples demonstrate that the solutions described in this thesis are adequate for the problems that have been formulated. In this way, the flight planning process can be enhanced to increase the efficiency and predictability of individual aircraft trajectories, which would lead to higher predictability levels of the ATM system and thus improvements in multiple performance indicators. El sistema de gestión del tráfico aéreo (Air Traffic Management, ATM) en los espacios aéreos más congestionados del mundo está siendo reformado para lidiar con múltiples desafíos socioeconómicos, medioambientales y de capacidad. Un pilar de este proceso es el gradual reemplazo de las estructuras rígidas de navegación, basadas en aerovías y waypoints, hacia las operaciones basadas en trayectorias. No obstante, la implementación exitosa de este concepto y la realización de las ganancias esperadas en rendimiento ATM requiere entender y gestionar apropiadamente la incertidumbre. Debido a su compleja estructura socio-técnica, el diseño y operaciones del sistema ATM se encuentran marcadamente influidos por la incertidumbre, que procede de múltiples fuentes y se propaga por las interacciones entre subsistemas y operadores humanos. Uno de los principales focos de incertidumbre en ATM es la meteorología. Debido a su naturaleza no-linear y caótica, muchos fenómenos de interés no pueden ser pronosticados con completa precisión en cualquier horizonte temporal, lo que crea disrupción en las operaciones en aire y tierra que se propaga a otros procesos de ATM. Por lo tanto, para lograr los objetivos de SESAR e iniciativas análogas, es imprescindible tener en cuenta la incertidumbre en múltiples escalas espaciotemporales, desde la predicción de trayectorias hasta la planificación de flujos y tráfico. Esta tesis aborda el problema de la planificación de vuelo de aeronaves individuales considerando dos fuentes importantes de incertidumbre meteorológica: el error en la predicción del viento y la actividad convectiva. Conforme la realización del viento se desvía de su previsión, la trayectoria real se desviará temporalmente de la planificada, lo que implica incertidumbre en tiempos de llegada a sectores y aeropuertos y en consumo de combustible. La actividad convectiva también tiene un impacto en la predictibilidad de las trayectorias, puesto que obliga a los pilotos a desviarse de sus planes de vuelo para evitarla, cambiado así la situación de tráfico. En este trabajo, buscamos desarrollar métodos y algoritmos para la optimización de trayectorias que puedan integrar información sobre la incertidumbre en estos fenómenos meteorológicos en el proceso de diseño de planes de vuelo en horizontes de planificación (antes del despegue) y tácticos (durante el vuelo), con el objetivo de generar trayectorias más eficientes y predecibles. Con este fin, formulamos la planificación de vuelo como un problema de control óptimo, modelando la dinámica del avión con un modelo de masa puntual y el modelo de rendimiento BADA. El control óptimo es un marco flexible y general con un largo historial de éxito en el campo de la ingeniería aeroespacial. Como método numérico, empleamos métodos directos, que son capaces de manejar sistemas dinámicos de alta dimensión con costes computacionales moderados. No obstante, si bien esta metodología es madura en contextos deterministas, la solución de problemas prácticas de control óptimo bajo incertidumbre en la literatura no está tan desarrollada, y los métodos propuestos en la literatura no son aplicables al problema de interés. La primera contribución de esta tesis hace frente a este reto mediante la introducción de un marco numérico para la resolución de problemas generales de control óptimo no-lineal bajo incertidumbre paramétrica. El núcleo de este método es un esquema de conjunto de trayectorias, en el que las trayectorias del sistema dinámico bajo múltiples escenarios son consideradas de forma simultánea, y el problema de control óptimo bajo incertidumbre es así transformado en un problema convencional que puede ser tratado mediante métodos existentes en control óptimo. A continuación, empleamos este método para resolver el problema de la planificación de vuelo robusta. La incertidumbre en el viento y la probabilidad de ocurrencia de condiciones convectivas son modeladas mediante el uso de previsiones de conjunto o ensemble, compuestas por múltiples predicciones en lugar de una única previsión determinista. Este método puede ser empleado para maximizar la eficiencia esperada de los planes de vuelo de acuerdo a la estructura de costes de la aerolínea; además, la predictibilidad de la trayectoria y la exposición a la convección pueden ser incorporadas como objetivos adicionales. El trade-off entre estos objetivos puede ser evaluado mediante la metodología propuesta. La segunda parte de la tesis presenta una solución para reconducir aviones en escenarios tormentosos en un horizonte táctico. La evolución de las células convectivas es representada con un modelo estocástico basado en las proyecciones de Rapidly Developing Thunderstorms (RDT), un sistema determinista basado en imágenes de satélite. Este modelo es empleado por un método de control óptimo numérico, basado en un modelo de masa puntual en el que se modela la dinámica de viraje, con el objetivo de maximizar la eficiencia y predictibilidad de la trayectoria en presencia de incertidumbre sobre la evolución futura de las tormentas. Finalmente, el proceso de optimizatión es inicializado por un método heurístico aleatorizado que genera múltiples puntos de inicio para las iteraciones del optimizador. Esta combinación permite explorar y explotar el espacio de trayectorias solución para proporcionar al piloto o al controlador un conjunto de trayectorias propuestas, así como información útil sobre su coste y el riesgo asociado. Los métodos propuestos son probados en escenarios de ejemplo basados en datos reales, ilustrando las diferentes opciones disponibles de acuerdo a las prioridades del planificador y demostrando que las soluciones descritas en esta tesis son adecuadas para los problemas que se han formulado. De este modo, es posible enriquecer el proceso de planificación de vuelo para incrementar la eficiencia y predictibilidad de las trayectorias individuales, lo que contribuiría a mejoras en el rendimiento del sistema ATM. These works have been financially supported by Universidad Carlos III de Madrid through a PIF scholarship; by Eurocontrol, through the HALA! Research Network grant 10-220210-C2; by the Spanish Ministry of Economy and Competitiveness (MINECO)'s R&D program, through the OptMet project (TRA2014-58413-C2-2-R); and by the European Commission's SESAR Horizon 2020 program, through the TBO-Met project (grant number 699294). Programa de Doctorado en Mecánica de Fluidos por la Universidad Carlos III de Madrid; la Universidad de Jaén; la Universidad de Zaragoza; la Universidad Nacional de Educación a Distancia; la Universidad Politécnica de Madrid y la Universidad Rovira i Presidente: Damián Rivas Rivas.- Secretario: Xavier Prats Menéndez.- Vocal: Benavar Sridhar Document type: Article

Abstract

In this thesis we examine how fuel price variation affects the optimal mix of services in intercity transportation. Towards this end, we make two main contributions. The first is the development of an analytic total logistics cost model of intercity transportation, which is sensitive to fuel price and incorporates multiple classes of vehicles serving passengers with differentiated values of time. The second is an empirical investigation of the cost relationship between fuel price and operating cost for intercity transportation vehicles. The analytic total logistics cost models are combined with the empirical models to gain insights into the impact of fuel price on optimal service mixes in representative corridors. We consider a scheduled intercity transportation corridor on which different classes of intercity transportation vehicles serve passengers with differentiated values of time. In determining optimal service mix, we consider a central planner choosing the vehicles and service frequencies that provide the minimum total logistics cost for an intercity transportation corridor. The total logistics cost is the sum of the two main intercity transportation cost components: vehicle operator cost and passenger cost. In considering operating and passenger costs together, we balance cost efficiency and level of service of alternative vehicles with different cost structures and service attributes. In developing the total logistics cost model, we seek both analytic insights and numerical examples. To keep the model analytically tractable while at the same time incorporating multiple objectives, including fuel cost, operating cost, schedule delay, and line-haul time, we incorporate the continuum approximation method from logistics. In employing the continuum approximation, discrete variables are considered continuous, leading to analytic functions from which we can evaluate qualitatively the relationships among fuel price, service level, and comparative vehicle cost. An investigation of the analytic model suggests that, while a fuel price increase would increase costs for any corridor, the rate of cost increase for a corridor served by a mix of vehicle technologies diminishes more rapidly with fuel price. We also find that an increase in fuel price causes vehicles to become more differentiated with respect to the value of time of the passengers they serve. In other words, under high fuel prices the total logistics cost can be minimized by effectively segregating passengers on different types of vehicles according to their values of time. We complement the analytic findings with an empirical investigation of the cost relationship between fuel price and operating cost for different classes of intercity transportation vehicles. We perform this analysis for a subset of intercity transportation vehicles for which data is readily available: jet and turboprop aircraft. In developing a translog operating cost model for jet aircraft, we estimate a flexible functional form that provides a detailed representation of the empirical relationship between fuel cost and operating cost, allowing for substitution, scale, aircraft age, and other effects – including interactions – to be captured. The function reveals that as fuel price increases, airlines will take steps to use fuel more efficiently by leveraging other inputs; however, the potential for this supplier input substitution for fuel is rather modest. This finding reinforces the formulation of the analytic total logistics cost model, in which the only actions available to a central planner to reduce costs are changing technologies and service frequencies. It also proves that empirical models with simpler functional forms are able to accurately predict operating costs, despite the lack of variable interactions. Using linear empirical operating cost models, we estimate operating cost and total logistics costs for intercity transportation corridors served by single vehicle fleets of three different aircraft classes. We find that a specific turboprop aircraft model, with a relatively low fuel consumption rate, provides intercity transportation service with the minimum operating cost compared with a jet with smaller seating capacity over all fuel prices considered and medium-capacity jets for some fuel prices. However, this is no longer the case when total logistics cost is considered, due to the lower quality of passenger service turboprops provide. At a given intercity transportation corridor distance, the fuel price for which the total logistics cost per passenger is equal across turboprops and low-capacity jets is in the fuel price range experienced from 2004 and expected through 2020. For this fuel price range, the total logistics cost per passenger for the medium-capacity jet is generally lower than the turboprop and always lower the lowcapacity jet. This suggests that a mix of services between intercity transportation vehicles could minimize cost for this range of fuel price. To investigate the possibility of mixing services to reduce costs further, we combine the analytic total logistics cost model with the empirical models. In addition to a jet and turboprop aircraft model, we build a high speed rail cost model and consider high speed rail as an additional intercity transportation technology. We find the minimum cost vehicle combination to be sensitive to fuel price in a small transition zone within which the cost ordering of vehicle combinations changes significantly, whereas outside this zone the orderings are stable. As the transition area is in the range of fuel prices forecasted between the years 2010-2035, the results indicate fuel price changes between 2010 and 2035 may dramatically alter the most cost-effective ways to provide intercity passenger transport. We find that high speed rail is a part of a mixed vehicle service that can reduce total logistics cost, suggesting that an integrated air and rail strategy could be an effective tool to manage costs and fuel consumption for an intercity transportation system.