A Global Optimization Approach to Solve Multi-Aircraft Routing Problems

This chapter describes the formulation and solution of a multi-aircraft routing problem which is posed as a global optimization calculation. The chapter extends previous work (involving a single aircraft using two dimensions) which established that the algorithm DIRECT is a suitable solution technique. The present work considers a number of ways of dealing with multiple routes using different problem decompositions. A further enhancement is the introduction of altitude to the problems so that full threedimensional routes can be produced. Illustrative numerical results are presented involving up to three aircraft and including examples which feature routes over real-life terrain data.

Cooperative Control for Ground Traffic at Airports

With the sustained increase in air transportation, resulting in increased operational costs, potential danger with conflictive traffic conditions and delays for passengers and airlines, ground traffic has become a critical issue for many airports. In this communication the ground traffic at an airport is considered to be composed of three dependent flows: aircraft, passenger vehicles and servicing vehicles. It is assumed in this study that each type of vehicles belongs to a common pool which attends every arriving or departing aircraft. The objective here is to propose a global control structure based on cooperation between the different agents responsible for the management of each fleet to reduce overall aircraft traffic delays at airside.

Balance Modelling and Implementation of Flow Balance for Application in Air Traffic Management

This work describes a decision making support system with Graph Theory and Artificial Intelligence methodologies applied to the Brazilian Air Traffic Flow Management. It consists of a flow management model based on graphs with heuristic adaptations for the dynamic regulation of the air traffic flow. The model lays the foundation of the architecture of the Flow Balancing Model (FBM) which integrates the Distributed Decision Support System applied to the Tactical Management of the Traffic Flow (SISCONFLUX), under development, and has the objective of improving the national airspace management. The FBM was proposed to give support to the system in operation at the First Air Defence and Air Traffic Control Integrated Centre (CINDACTA I), by providing additional information to the process applied by the controllers, in order to mitigate the workload and improve the results of their actions. Using flow maximization techniques adapted from Graph Theory, FBM was developed as a model of analysis which determines the separation time between departures from terminals integrating the Brasilia Flight Information Region (FIR-BS), and distributes the slack capacity along the controlled airspace, in order to prevent or reduce traffic congestion in various sectors of FIR-BS. The FBM gives support to traffic flow regulation, assisting the controllers and other units within the SISCONFLUX.

The SYNCROMAX Solution for Air Traffic Flow Management in Brazil

This chapter charts Brazil’s participation and strategy in dealing with Air Traffic Flow Management (ATFM). First a review of ATFM concepts is provided, where the demand and capacity balancing problem is defined. Afterwards the Brazilian air traffic scenario is laid out and a short history is presented. Finally, the SYNCROMAX system architecture is presented as defined for it’s first implementation phase. Internal details to the system are given and finally current directions indicate a higher level of decision making tools required in the future, in order to face the growing air navigation requirements.

Component-Based Development of Aeronautical Software

Modern aircraft heavily relies on software to fly and operate, which lessens pilot workload, increases flight stability and fuel efficiency, and provides several other benefits. However, the more automated an aircraft is, the more prone to complexity its software modules are, raising special safety issues to be considered in the project. This chapter presents an overview of the Verification and Validation requirements for safety-critical software in aeronautics and, given the high costs to meet them, explains in detail a component-based methodology which can contribute to reduce the overall costs of software development and, at the same time, provide enhanced safety.

Collaborative Decision Making and Information Sharing for Air Traffic Management Operations

One of the most notable concepts related to the future cooperative Air Traffic Management (ATM) is the Collaborative Decision Making (CDM). This new management philosophy of using collaborative technologies and procedures to enable ATM partners drives efforts towards the common goals of sharing and exchanging information. To support the implementation of CDM, a likely solution was found in the context of System of Systems (SoS), system integration, and interoperability. Service-Oriented Architecture (SOA) principles and technologies were recognized as one of the best alternatives to allow this implementation. Within this architecture, the System Wide Information Management (SWIM) has been developed on the last decade, and SWIM applications will be accessible to all ATM partners on the next decade by providing full airspace information, updated in real-time by all involved partners. This chapter presents an overview of key elements in information sharing for ATM and explains how SOA, SWIM, Aeronautical Information Management (AIM) and CDM support each other development.

Using the Continuum Equilibrium Approach to Solve Airport Competition Problems

This chapter presents a computational method using the continuum equilibrium approach to solve airport competition problems. The mathematical formulation and solution algorithm are given. The Hong Kong-Pearl River Delta region is used as a case study to demonstrate the effectiveness of the approach in solving real-life large-scale airport competition problems. Behavioral choices of both international and domestic air travelers in the region are modeled. The results show the distinctive value of the continuum approach in understanding the spatial dynamics of air passenger flows in multi-airport regions.

Critical Review and Analysis of Air-Travel Demand

Demand forecasting may be the most critical factor in the development of airports and airline networks. This chapter reviews various approaches used to forecast air travel and airport demand forecasting. It classifies existing methods according to the modeling approach used to evaluate the available data; then, the forecasting approaches are viewed in relation to data requirements. Finally, a new matrix classification scheme is introduced that combines both the data available and the technique used to evaluate this data in a more concise and manner.

A Distributed Systems Approach to Airborne Self-Separation

This chapter introduces the reader to the benefits of distributed computing in air transportation. It presents a solution to airborne self-separation based on RAPTOR, a stack of distributed protocols that allows aircraft to reach different types of agreement in the presence of faults, both of accidental and malicious nature. These protocols are used as primitives to implement specific services for airborne self-separation, which are created within the context of a conflict resolution algorithm based on game theory.

Real-Time Non-Destructive Evaluation of Airport Pavements Using Neural Network Based Models

Nondestructive test (NDT) and evaluation methods are well-suited for characterizing materials and determining structural integrity of airfield pavement systems. The Heavy Weight Deflectometer (HWD) test is one of the most widely used NDT impulse device for assessing the structural condition of airport pavements in a non-destructive manner. Through inverse analysis of HWD deflection data (more commonly referred to as backcalculation), the structural stiffness parameters of the individual airport pavement layers are, in general, determined using iterative optimization routines. In recent years, Artificial Neural Networks (ANN) aided inverse analysis has emerged as a successful alternative for predicting pavement layer moduli from HWD deflection data in real-time. Especially, the use of Finite Element (FE) based pavement modeling results for training the ANN aided inverse analysis is considered to be accurate in realistically characterizing the non-linear stress-sensitive response of underlying pavement layers. The development of an effective tool for real-time backcalculation of flexible airfield pavement layer moduli based on HWD test data is discussed in this Chapter. The ANN-based backcalculation tool is validated using actual field data acquired from a full-scale, state-of-the-art airport pavement test facility.