Comparing spatial concentration and assessing relative market structure in air traffic

Traffic distributions of air traffic and their concentration have been measured through Gini, an index that contrasts in many ways with other more established ones, such as Herfindahl's. This research is extended in the sense that it perceives spatial concentration in air transport as an aggregate of complex networks that are subject to multiple constraints, such as geopolitics or technology. We propose a multi-layered analytic approach where network operators are economic agents that behave in strategic ways. It allows for comparing air traffic between airports in Europe with that of the US and, in particular, introduces a normative component by isolating patterns in airlines' strategies that coincide with more or less welfare-oriented degrees of spatial concentration in light of the above constraints.     

Air transport and tourism—Perspectives and challenges for destinations,airlines and governments

Air transport and tourism are interlinked. Tourism is a driving factor for and, in some cases, a stimulator of change in air transport; most notably the development of new business models such as charter airlines. On the other hand, air transport opened new destinations and tourism forms such as long-haul excursions. Here these interlinks are analyzed in a system model. For the strategic development of destinations, a clear airline policy and air access strategy seems to be necessary. For airlines an assessment and understanding of the business models of destinations is essential. By shaping the external regulative environment of air traffic, government may influence air traffic as well as tourism.     

Assessing strategic flight schedules at an airport using machine learning-based flight delay and cancellation predictions

To mitigate air traffic demand-capacity imbalances, large European airports implement strategic flight schedules, where flights are assigned arrival/departure slots several months prior to execution. We propose a generic assessment of such strategic schedules using predictions about arrival/departure flight delays and cancellations. We demonstrate our approach for strategic flight schedules in the period 2013–2018 at London Heathrow Airport. Together with the development of dedicated strategic flight schedule optimization models, our proposed approach supports an integrated strategic flight schedule assessment, where schedules are evaluated with respect to flight delays and cancellations.     

Spillover effects of the development constraints in London Heathrow Airport

In this article we assess the growth impact of London Heathrow’s development constraints on other airports in the UK. To test the relationship we use a two-stage methodology yielding an estimate of a congestion spillover effect. Our data are passenger traffic from 1990 to 2012 containing both intercontinental and European air traffic. For intercontinental air traffic, our results show high congestion spillover effect between Heathrow and Gatwick airports, and significant but lesser effect to Stansted airport. We also find significant congestion spillover effects from Heathrow to the spatially more distant Manchester and Birmingham airports, showing the extensive spatial impact of Heathrow’s development constraints. For European air traffic, controlling for low-cost air carrier growth, only two airports show significant congestion spillover effects: Gatwick and London City Airports. Illustrating that low-cost carriers do not operate from Heathrow, so its limitations cannot affect the predominant low-cost air traffic in other airports. The novel methodology we present in this paper can be applied to congestion research in general to assess regional and modal spills within networks.     

The impact of airport capacity constraints on future growth in the US air transportation system

This paper simulates airline strategic decision making and its impact on passenger demand, flight delays and aircraft emissions. Passenger flows, aircraft operations, flight delays and aircraft emissions are simulated for 22 airports in the US, under three airport capacity scenarios. The simulation results indicate that most system-wide implications for operations and environmental impact seem to be manageable, but local impacts at congested hub airports may be significant. The response of the air transportation system to avoid airports with high delays could significantly impact passenger demand and air traffic for these and directly dependent airports. The simulations also suggest that frequency competition effects could maintain flight frequencies at high levels, preventing a significant shift toward larger aircraft, which would otherwise reduce the impact of the capacity constraints.     

The geographical efficiency of Spain's regional airports: A quantitative analysis

Previous studies of the role of regional airports in the Spanish economy have focused on calculating efficiency using air traffic as the output and airport infrastructure data as the input. We present an alternative quantitative analysis based upon the geographical structure within the airport's market basin. We formulate a ‘geographical efficiency’ model that considers territorial variables within the airport hinterland. Input data for our model include the socio-economic structure of the population, intermodal transport links, industrial and tourism potential and existing leisure-related services. The output is the annual number of passengers associated with such constraints. The result is a relative efficiency estimate that shows uneven patterns of geographical efficiency amongst Spain's regional airports and also provides insights into opportunities for expanding some of these critical items of infrastructure. They suggest that some of Spain's regional airports may be better placed than others to compete in a liberalized market that exhibits a clear tendency in favor of coastal, tourism-based airports.     

Business connectivity,air transport and the urban hierarchy: A case study in East Asia

This paper explores the effect of business connectivity between cities on their air traffic connections, and in turn on their place in a region's urban hierarchy. Its focus of attention is East Asia, where economic development is underpinned by a complex set of international flows of trade and investment. Business connectivity is a key part of these flows. The research incorporates a measure of business connections in a regression model that previously relied on GDP per head, population and distance to account for international air links. Results confirm that business connectivity is a more important influence on the level of international air links within East Asia, and plays a major role in explaining the changes in city rank over time. The paper concludes with suggestions that possible incorporation of domestic air travel (itself larger than the intra-regional flows in this region) could enrich the insight of this approach.     

The global distribution of the burden of road traffic injuries: Evolution and intra-distribution mobility

This research examines the evolution of the distribution across 187 countries of mortalities per 100,000, disability-adjusted life years (DALYs), years of life lost (YLL) and years lived with disabilities (YLD) due to road traffic injuries between 1990 and 2010 using the distribution dynamics approach. Fatal and non-fatal burdens of road traffic injuries display contrasting external shape dynamics and intra-distribution mobility. The results show that while the shape of the global distribution of YLD due to road traffic injuries (RTIs) has become tighter over time, the cross-country distributions of mortalities, DALYs, and YLL from road crashes have become more dispersed. The implication of the results is that international efforts should make a priority of targeting the prevention of a greater spreading out of the distribution of the burden of fatal RTIs. The exchange of relative positions within the distributions is substantial, but there is no linear relationship between a country's change in its relative position for the burden of fatal and non-fatal RTI distributions. Thus, further research is needed to determine whether policy interventions dealing with the burden of fatal RTIs also alleviate the burden of non-fatal RTIs and vice versa.     

Customer issues related to limited air connectivity

Air access can be crucial for regional economic development, especially when global industries are involved. However, air traffic generates negative impacts, such as noise and air pollution that can lead to politically motivated calls to reduce air traffic. This paper investigates customer issues and potential responses of frequent flyers to non-market-driven limitations on air transport. Based on a survey conducted at Zurich International Airport we show that frequent air travelers tend to be more senior and to work in industries that involve travel outside of the worker's country of origin. Consequently, they are more critical of potential restrictions on air travel.     

Investigations on the distribution of air transport traffic and CO2 emissions within the European Union

This study analyses the structure of air traffic and its distribution among the different countries in the European Union, as well as traffic with an origin or destination in non-EU countries. Data sources are Eurostat statistics and actual flight information from EUROCONTROL. Relevant variables such as the number of flights, passengers or cargo tonnes and production indicators (RPKs) are used together with fuel consumption and CO₂ emissions data. The segmentation of air traffic in terms of distance permits an assessment of air transport competition with surface transport modes.The results show a clear concentration of traffic in the five larger countries (France, Germany, Italy, Spain and UK), in terms of RPKs. In terms of distance the segment between 500 and 1000 km in the EU, has more flights, passengers, RTKs and CO₂ emissions than larger distances. On the environmental side, the distribution of CO₂ emissions within the EU Member States is presented, together with fuel efficiency parameters. In general, a direct relationship between RPKs and CO₂ emissions is observed for all countries and all distance bands. Consideration is given to the uptake of alternative fuels. Segmenting CO₂ emissions per distance band and aircraft type reveals which flights contribute the most the overall EU CO₂ emissions. Finally, projections for future CO₂ emissions are estimated, according to three different air traffic growth and biofuel introduction scenarios.     

A data-driven operational model for traffic at the Dallas Fort Worth International Airport

Airports are on the front line of significant innovations, allowing the movement of more people and goods faster, cheaper, and with greater convenience. As air travel continues to grow, airports will face challenges in responding to increasing passenger vehicle traffic, which leads to lower operational efficiency, poor air quality, and security concerns. This paper evaluates methods for traffic demand forecasting combined with traffic microsimulation, which will allow airport operations staff to accurately predict traffic and congestion. Using two years of detailed data describing individual vehicle arrivals and departures, aircraft movements, and weather at Dallas-Fort Worth (DFW) International Airport, we evaluate multiple prediction methods including the Auto Regressive Integrated Moving Average (ARIMA) family of models, traditional machine learning models, and DeepAR, a modern recurrent neural network (RNN). We find that these algorithms are able to capture the diurnal trends in the surface traffic, and all do very well when predicting the next 30 minutes of demand. Longer forecast horizons are moderately effective, demonstrating the challenge of this problem and highlighting promising techniques as well as potential areas for improvement.Traffic demand is not the only factor that contributes to terminal congestion, because temporary changes to the road network, such as a lane closure, can make benign traffic demand highly congested. Combining a demand forecast with a traffic microsimulation framework provides a complete picture of traffic and its consequences. The result is an operational intelligence platform for exploring policy changes, as well as infrastructure expansion and disruption scenarios. To demonstrate the value of this approach, we present results from a case study at DFW Airport assessing the impact of a policy change for vehicle routing in high demand scenarios. This framework can assist airports like DFW as they tackle daily operational challenges, as well as explore the integration of emerging technology and expansion of their services into long term plans.     

Characterizing the Brazilian airspace structure and air traffic performance via trajectory data analytics

This paper presents a data-driven approach for multi-scale characterization of the Brazilian airspace structure and air traffic operational performance from aircraft tracking data recorded by surveillance systems. Unsupervised learning is performed with a flight trajectory clustering analysis to automatically identify spatial traffic patterns in both the terminal and the en route airspace for major origin-destination pairs of the Brazilian air transportation system. Based on the as-flown route structure learned, quantitative metrics are developed to describe the structural efficiency of the airspace and the operational efficiency of the traffic flows. For this, actual flight trajectories are projected onto reference nominal trajectories in space and time. The results allowed for cross-route comparisons of air traffic flow efficiency across multiple flight phases as well as for the identification of causal factors for trajectory deviations from nominal routes. An interactive data analytics tool is also created to output performance statistics and air traffic visualizations. With the provision of a systematic data-driven approach for characterizing actual air traffic operations, the analytics framework is envisioned to assist airspace design and performance monitoring processes and to provide the basis for developing predictive capabilities in support of traffic flow management.     

Airport slot allocation: From instruments to strategies

Slot allocation is widely used to tackle capacity shortfalls and manage delays in air traffic and airports. A variety of instruments are used, but little analysis has been conducted looking at the synergies that exist when these tools are integrated to form an overall slot allocation strategy. This paper aims to capitalise on existing research work in the field of airport slot allocation instruments to define a series of distinct and integrated strategies as the candidate strategic options for practical implementation.     

Methods of air traffic management in the airport area including the environmental factor

In the modern approach to air traffic management (ATM), issues related to air quality and climate protection have led to the introduction of a growing number of new restrictions instead of having these issues be the objectives of actions taken. The aim of the study was to investigate whether it is possible to improve air quality while controlling pollution emission by introducing changes in the organization of air traffic control at the airport. For this purpose, mathematical models of emissions were created. These concern the movement of aircraft near the airport and emission of carbon dioxide and the spread of human health related substances emitted from a landing airplane's engine. The first case refers to the possibility of using different arrival procedures. The second case was to adapt the Pasquill formula by treating landing aircraft as a sequence of point-source emissions. As a result of applying the designed models and software tools, it was proven that both a change in the arrival trajectory and a change of the runway can contribute to a reduction of CO₂ emission into the atmosphere. The emission maps created for different aircraft approach profiles show the ability to control the local concentration of harmful emissions. The study clearly shows that the current approach of maximizing throughput is not beneficial to air quality. ATM services should consider the use of other variants of air traffic organization, particularly during periods of reduced traffic.     

A review of spatial localization methodologies for the electric vehicle charging infrastructure

With view to the high share of the transport sector in total energy consumption, e-mobility should play an important role within the transition of the energy systems. Policymakers in several countries consider electric vehicles (EV) as an alternative to fossil-fueled vehicles. In order to allow for the development of EV, the charging infrastructure has to be set up at locations with high charging potential, identified by means of various criteria such as demand density or trip length. Many methodologies for locating charging stations (CS) have been developed in the last few years. First, this paper presents a broad overview of publications in the domain of CS localization. A classification scheme is proposed regarding modeling theory and empirical application; further on, models are analyzed, distinguishing between users, route or destination centricity of the approaches and outcomes. In a second step, studies in the field of explicit spatial location planning are reviewed in more detail, that is, in terms of their target criteria and the specialization of underlying analytical processes. One divergence of these approaches lies in the varying level of spatial planning, which could be crucial depending on the planning requirements. It is striking that almost all CS locating concepts are proposed for urban areas. Other constraints, such as the lack of extensive empirical EV traffic data for a better understanding of the driving behavior, are identified. This paper provides an overview of the CS models, a classification approach especially considering the problem’s spatial dimension, and derives perspectives for further research.     

Long-term manpower supply planning for air cargo terminals

Four strategic models, combining different manpower supply principles, flexible management strategies and related operating constraints, are developed to help an air cargo terminal manage its long-term manpower supply more effectively. The models are formulated as integer/mixed integer linear programs, which are solved using a mathematical programming solver. To evaluate how the models perform in practice, a case study, utilizing the operating data of a domestic air cargo terminal in Taiwan, is conducted. The preliminary test results show that the four models are efficient and effective, and could be applied to actual operations.     

Environmental sustainability,airport capacity and European air transport liberalization: irreconcilable goals?

The general aim of this paper is to discuss the apparently irreconcilable tensions that exist between policies for air transport liberalization in the European Union (EU), those directed at environmental sustainability, and the inadequacy of plans for additional airport capacity and modal shift to meet projected growth in air transport. The paper analyses the contradictory responses of the major stakeholders in the air transport industry to these problems, concentrating in particular on the environmentally incompatible strategies adopted by airlines in the competitive market-place. It concludes that environmentally driven capacity constraints at airports will effectively determine air transport's development within the EU, and that current laissez-faire attitudes of airlines and their regulators are unlikely to prevail as 'polluter pays' principles are more firmly implemented.     

Long-term route traffic forecasts and flight schedule pattern for a medium-sized European airport

This paper develops a methodology for assessing the future route network and flight schedule at a medium-sized European airport. The starting point is the existing origin and destination demand from the base airport across the world. This is expanded using growth rates by country or region for the period up to year 2015. The future origin and destination demand is then converted into route traffic, subject to a threshold for direct service. Where demand falls below this level, traffic is reallocated via various appropriate hubs. A model of frequency and aircraft size is applied to estimate the future air service on each route and a schedule created, allocating these flights to specific times of day. The scenario where the base airport operates as a hub is then investigated. This involves identifying a suitable hub model, considering geographical and competitive issues. The origin and destination demand is increased, resulting in an enlarged network of routes. Flights are then scheduled within the constraints of an optimal wave pattern. The outputs are of considerable interest in long-term airport planning and also offer an insight into future airline network strategies and opportunities.     

Accounting for population exposure to vehicle-generated pollutants and environmental equity in the toll design problem

The emissions generated by motor vehicles remain a major source of air pollutants that affect public health and contribute to anthropogenic climate change. These negative externalities can be reduced, in part, with the implementation of environmentally oriented road pricing schemes, which can be designed using optimization-based approaches. In this paper, a toll design problem is proposed for determining toll locations and levels that minimize the expected human exposure to air pollutants and the related environmental inequalities, subject to constraints on pollutant concentration levels and implementation costs. The practical use of the proposed problem is hindered in most real-world applications by the computational costs associated with the evaluation of candidate solutions, as is common for network design problems. Furthermore, the problem cannot be expressed analytically given the multiple types of models (e.g., traffic assignment, emissions, air dispersion models) that would be required to evaluate a single design alternative. For these reasons, a derivative-free surrogate-based solution algorithm is proposed for mixed integer problems like the ones considered here. Numerical examples are used to illustrate possible applications of the proposed model and to test the performance of the surrogate-based algorithm. Relative to a joint simulated annealing-genetic algorithm heuristic and a genetic algorithm-based approach, the proposed algorithm found better solutions in fewer function evaluations.