Intelligent computing methods in Air Traffic Flow Management

This research presents the application of intelligent computing models in Air Traffic Flow Management (ATFM). Firstly, multi-agent system in grid computing environment is applied to deal with the problem of ATFM synchronization. The developed system consists of software agents, which are implemented in a Computational Grid platform for congestions identification, conflicts resolution and agreements negotiation among the participating airports. A metric criterion, called Agent’s Balancing Standard (ABS), is used as a basic index to measure the effectiveness of reducing both the amount of communication among agents and the delay of flights. Secondly, a brief discussion about the Meta-Level Control model is introduced in ATFM issues to improve the efficiency of communication among the agents. The system is developed to analyze the traffic flow information received, identify its importance and process it in the most adequate order.     

基于功能定位的国际航空枢纽评价

针对我国国际枢纽机场未按照设计之初功能定位发展的现状,运用AHP法构建国际枢纽机场综合评价指标体系,将国际航空运输规模指标、国际节点网络连通度指标、枢纽功能指标、综合交通指标纳入体系当中。首先对国内外大型国际枢纽机场进行评价,其次对我国机场布局规划中的10个国际枢纽机场进行评价。结果表明我国国际枢纽机场国际业务发展、航空枢纽建设与国外对标机场有一定差距,与自身战略规划有所偏差,针对薄弱指标项基于自身优势给出发展建议。最后基于一市两场与机场群的视角,分析了如何根据自身功能定位进行协同发展问题。     

Network structure,capacity growth and route hierarchies: the case of China’s air traffic system revisited

This paper examines air traffic patterns among China’s scheduled airlines in January 2006 and January 2011, using Official Airline Guide data on carrier schedules. The author classifies Chinese carriers into one of four classes. Airports are also organized into a classification scheme based on several criteria related to the total volume of traffic, the carriers serving the airports and the nature of the airports to which they are connected. Counts, sums, percentage shares and changes in these calculations between 2006 and 2011 are presented in tabular form. Inferences about the fundamental structure and future patterns of capacity growth for the yet not fully emerged Chinese air traffic system can be drawn.     

Real-time airport surface movement planning: Minimizing aircraft emissions

This paper presents a study towards the development of a real-time taxi movement planning system that seeks to optimize the timed taxiing routes of all aircraft on an airport surface, by minimizing the emissions that result from taxiing aircraft operations. To resolve this online planning problem, one of the most commonly employed operations research methods for large-scale problems has been successfully used, viz., mixed-integer linear programming (MILP). The MILP formulation implemented herein permits the planning system to update the total taxi planning every 15 s, allowing to respond to unforeseen disturbances in the traffic flow. Extensive numerical experiments involving a realistic (hub) airport environment bear out that an estimated environmental benefit of 1–3 percent per emission product can be obtained. This research effort clearly demonstrates that a surface movement planning system capable of minimizing the emissions in conjunction with the total taxiing time can be beneficial for airports that face dense surface traffic and stringent environmental requirements.     

Validating expert system prototypes using the turing test

High-performance, expert-level computer systems require that the expert system prototype be continously evaluated during its development. Expert system validation—that is, testing systems to ascertain whether they achieve acceptable performance levels—has with few exceptions been ad hoc, informal, and of dubious value. This paper describes a variant of the Turing Test technique that may be used to formalize the validation process. A microcomputer-based prototype expert system, the Hazardous Location Analyst (HLA), in the accident location analysis domain was used as a case study of the technique. Turing tests provide a blind method for multiple experts to assess expert system performance qualitatively, and provide a means of determining reasonable performance levels for the particular domain. The HLA has been modified based upon findings from the case study work done previously. The improved prototype was implemented in the City of Greensboro, North Carolina, and a set of 10 case studies are analyzed using the HLA, and by a Greensboro traffic engineer. The results were summarized in identical form and mailed to four traffic engineers outside of Greensboro. Their ratings of case study findings were summarized, and the results used to find a reasonable performance level for this application and to assess the performance of the HLA. The consistency of the expert ratings was also assessed. It was concluded that there exists excellent consistency among experts with regard to human performance, but not with regard to the HLA. This paper demonstrates that the Turing Test as a validation methodology provides an objective, quantitative way to assess system performance.     

Robust identification of air traffic flow patterns in Metroplex terminal areas under demand uncertainty

Multi-Airport Systems (MAS), or Metroplexes, serve air traffic demand in cities with two or more airports. Due to the spatial proximity and operational interdependency of the airports, Metroplex airspaces are characterized by high complexity, and current system structures fail to provide satisfactory utilization of the available airspace resources. In order to support system-level design and management towards increased operational efficiency in such systems, an accurate depiction of major demand patterns is a prerequisite. This paper proposes a framework for the robust identification of significant air traffic flow patterns in Metroplex systems, which is aligned with the dynamic route service policy for the effective management of Metroplex operations. We first characterize deterministic demand through a spatio-temporal clustering algorithm that takes into account changes in the traffic flows over the planning horizon. Then, in order to handle uncertainties in the demand, a Distributionally Robust Optimization (DRO) approach is proposed, which takes into account demand variations and prediction errors in a robust way to ensure the reliability of the demand identification. The DRO-based approach is applied on pre-tactical (i.e. one-day planning) as well as operational levels (i.e. 2-h rolling horizon). The framework is applied to Time Based Flow Management (TBFM) data from the New York Metroplex. The framework and results are validated by Subject Matter Experts (SMEs).     

Congestion spill effects of Heathrow and Frankfurt airports on connection traffic in European and Gulf hub airports

We develop two stage fixed-effects single-spill and double-spill models for congestion connection spills of London Heathrow and Frankfurt airports on 9 hub airports in Europe and the Gulf. Our panel data covers connection traffic from 1997 to 2013 for Heathrow and 1997 to 2011 for Frankfurt. The single-spill results support strongly that the connection spills from Heathrow’s capacity limitations do strengthen competing hub airports of major alliance groups and to a lesser degree one Gulf hub. The double-spill model for Heathrow and Frankfurt shows nearly asymmetric overall spill characteristics between the two airports. Our results underline the influence of airline network strategies on congestion spills as European airline networks are shaped by alliances and umbrella mergers. Thus, the airline network perspective in airport capacity expansion decisions needs to play a greater role, as indicated by our asymmetric results for overall spill effects between Heathrow and Frankfurt airports.     

Predicting and planning airport acceptance rates in metroplex systems for improved traffic flow management decision support

Efficient planning of Airport Acceptance Rates (AARs) is key for the overall efficiency of Traffic Management Initiatives such as Ground Delay Programs (GDPs). Yet, precisely estimating future flow rates is a challenge for traffic managers during daily operations as capacity depends on a number of factors/decisions with very dynamic and uncertain profiles. This paper presents a data-driven framework for AAR prediction and planning towards improved traffic flow management decision support. A unique feature of this framework is to account for operational interdependency aspects that exist in metroplex systems and affect throughput performance. Gaussian Process regression is used to create an airport capacity prediction model capable of translating weather and metroplex configuration forecasts into probabilistic arrival capacity forecasts for strategic time horizons. To process the capacity forecasts and assist the design of traffic flow management strategies, an optimization model for capacity allocation is developed. The proposed models are found to outperform currently used methods in predicting throughput performance at the New York airports. Moreover, when used to prescribe optimal AARs in GDPs, an overall delay reduction of up to 9.7% is achieved. The results also reveal that incorporating robustness in the design of the traffic flow management plan can contribute to decrease delay costs while increasing predictability.     

Assessing the effect of urban socioeconomic factors and the financial crisis of 2008 on domestic air cargo traffic in Florida

In this paper, we investigate the relationship between the social and economic attributes of metropolitan areas and their corresponding domestic cargo traffic. We considered a period of 14 years (2003–2016) and studied the impact of population demographics, employment, and regional industries on domestic cargo traffic of a sampled set of metropolitan areas in Florida. We considered all-cargo carriers and mixed passenger–cargo carriers. Our results provide empirical insights into factors determining the air cargo traffic in Florida. Both population and age demographics of a region is shown to be influential on cargo traffic. Manufacturing industries are shown to prefer all-cargo carriers to mixed passenger–cargo carriers and their concentration in a metro area results in an increase of cargo traffic. In contrast, service industries generate low demand for air cargo. Our results show that larger airports tend to attract cargo traffic away from smaller airports in their close proximity. We also provide insights into the impact of the financial crisis of 2008 on domestic cargo traffic in the region. We study the recovery trend and the impact of the high fuel jet prices on slowing down this trend.

     

Airport congestion and near-midair collisions

This paper presents a model that systematically integrates, for the first time, the association between a region's aviation near-midair collision risk and its traffic levels, its type and amount of air traffic control, and the complexity of its airspace. The model incorporates the tight interrelatedness (and correlation) between traffic, airspace complexity, and air traffic controller staffing. An estimation of the model using cross-sectional data on 143 U.S. airports in 1985 indicates that the frequency of reported near-midair collisions (NMACs) is positively associated with regional traffic and airspace complexity, despite the fact that busier, more complex regions generally have more air traffic controllers. Also, in regions governed by “terminal radar service areas” (TRSAs), the reported near-midair collisions are positively associated with the presence of more satellite airports than would be expected on the basis of traffic alone. Finally, deviations from controller staffing levels that would be expected on the basis of traffic and airspace complexity alone are significantly associated with variations in reported NMACs in terminal control areas but not in terminal radar service areas.     

Benchmarking airports with specific safety performance measures

The purpose of this paper is to develop safety performance measures and test the measures on data for air traffic management failure events. Failure events are classified by the severity of the consequence of occurrence, resulting in the rate of occurrence in severity categories. The safety measures are standard statistics calculated from this “distribution” for comparison of airport operations by stochastic ordering. For comparisons a benchmark is developed from the aggregation of failure data on a set of comparable airports. Airport performance is then compared with the benchmark using the defined safety measures. The benchmark comparison was implemented with failure data for major airports in Canada from 2005 to 2012. The results show a number of patterns and anomalies and some airports perform poorly in comparison to a class of similar operations. We conclude by suggesting benchmarking safety measures as a natural addition to the information system on aviation safety compiled by a national regulatory body to unravel anomalies such as implementation problems of a safety management system.     

Statistical mechanics for analytic planning: an application to domestic air traffic in China

Abstract

Statistical mechanics has shown its usefulness when assessing the topology of many networks, including those of infrastructure. Its principles take into account the large-scale and network-wide effects of changes in its key parameters, which in turn may provide critical input when planning for infrastructure projects. One objective would be to modify the pattern of capacity expansions inside a system to make it less exposed to local shortfalls in demand. To illustrate our point, we shall use domestic air traffic in China; airports are spatially distributed and they also need to respond to the potential demand that they face locally. Airlines that control parts of the traffic system are identified as agents. A relationship between the agent's behavior and the system-wide level of variance in traffic flows can be established by regression analysis. It is shown how intervention on these agents would reduce negative traffic variance while enhancing a more balanced, less costly growth of the system itself.     

Apron capacity at hub airports—the impact of wave‐system structure

At hub airports, dominant airlines/alliance coordinate their flights in time with the aim of increasing the number (and quality) of connections, thus producing a wave‐system in traffic schedules. This paper addresses the impact of concentrating aircraft into waves on airport apron capacity. Existing models for apron capacity estimation are based on the number of stands, stand occupancy time, and demand structure, differing between representative groups of aircraft served at an airport. Criteria for aircraft grouping are aircraft type and/or airline and/or type of service (domestic, international, etc.). Modified deterministic analytical models proposed in this paper also take into account the wave‐system parameters, as well as runway capacity. They include the impact of these parameters on the number of flights in wave, stand occupancy time, and consequently apron capacity. Numerical examples illustrate the difference between apron capacity for an origin–destination airport and a hub airport, under the same conditions; utilization of the theoretical apron capacity at a hub airport, given the wave‐system structure; and utilization of the apron capacity at a hub airport when point‐to‐point traffic is allowed to use idle stands. Furthermore, the influence of different assignment strategies for aircraft stands in the case of hub airports is also discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

Integrated sequencing and merging aircraft to parallel runways with automated conflict resolution and advanced avionics capabilities

Congestion in Terminal Maneuvering Area (TMA) in hub airports is the main problem in Chinese air transportation. In this paper we propose a new system to integrated sequence and merge aircraft to parallel runways at Beijing Capital International Airport (BCIA). This system is based on the advanced avionics capabilities. Our methodology integrates a Multi-Level Point Merge (ML-PM) system, an economical descent approaches procedure, and a tailored heuristic algorithm to find a good, systematic, operationally-acceptable solution. First, Receding Horizontal Control (RHC) technique is applied to divide the entire 24 h of traffic into several sub-problems. Then in each sub-problem, it is optimized on given objectives (conflict, deviation from Estimated Time of Arrival (ETA) on the runway and makespan of the arrival flow). Four decision variables are designed to control the trajectory: the entry time, the entry speed, the turning time on the sequencing leg, and the landing runway allocation. Based on these variables, the real time trajectories are generated by the simulation module. Simulated Annealing (SA) algorithm is used to search the best solution for aircraft to execute. Finally, the conflict-free, least-delay, and user-preferred trajectories from the entry point of TMA to the landing runway are defined. Numerical results show that our optimization system has very stable de-conflict performance to handle continuously dense arrivals in transition airspace. It can also provide the decision support to assist flow controllers to handle the asymmetric arrival flows on different runways with less fuel consumption, and to assist tactical controllers to easily re-sequence aircraft with more relaxed position shifting. Moreover, our system can provide the fuel consumption prediction, and runway assignment information to assist airport and airlines managers for optimal decision making. Theoretically, it realizes an automated, cooperative and green control of routine arrival flows. Although the methodology defined here is applied to the airport BCIA, it could also be applied to other airports in the world.     

Comparing the impact of future airline network change on emissions in India and the United States

In this paper we use simulation to analyze how flight routing network structure may change in different world regions, and how this might impact future traffic growth and emissions. We compare models of the domestic Indian and US air transportation systems, representing developing and mature air transportation systems respectively. We explicitly model passenger and airline decision-making, capturing passenger demand effects and airline operational responses, including airline network change. The models are applied to simulate air transportation system growth for networks of 49 airports in each country from 2005 to 2050. In India, the percentage of connecting passengers simulated decreases significantly (from over 40% in 2005 to under 10% in 2050), indicating that a shift in network structure towards increased point-to-point routing can be expected. In contrast, very little network change is simulated for the US airport set modeled. The simulated impact of network change on system CO₂ emissions is very small, although in the case of India it could enable a large increase in demand, and therefore a significant reduction in emissions per passenger (by nearly 25%). NO_x emissions at major hub airports are also estimated, and could initially reduce relative to a case in which network change is not simulated (by nearly 25% in the case of Mumbai in 2025). This effect, however, is significantly reduced by 2050 because of frequency competition effects. We conclude that network effects are important when estimating CO₂ emissions per passenger and local air quality effects at hub airports in developing air transportation systems.     

A Heuristic Algorithm for the Allocation of Airport Runway System Capacity

Abstract

This paper develops a heuristic algorithm for the allocation of airport runway capacity to minimise the cost of arrival and departure aircraft/flight delays. The algorithm is developed as a potential alternative to optimisation models based on linear and integer programming. The algorithm is based on heuristic (‘greedy’) criteria that closely reflect the ‘rules of thumb’ used by air traffic controllers. Using inputs such as arrival and departure demand, airport runway system capacity envelopes and cost of aircraft/flight delays, the main output minimises the cost of arrival and departure delays as well as the corresponding interdependent airport runway system arrival and departure capacity allocation. The algorithm is applied to traffic scenarios at three busy US airports. The results are used to validate the performance of the proposed heuristic algorithm against results from selected benchmarking optimisation models.     

The influence of the operational environment on efficiency of international airports

Heterogeneity must be considered in the efficiency analysis of decision‐making units; otherwise, the results will be strongly biased. This is also valid for airport management where the operational environment heavily influences efficiency. In this paper, conditional efficiency measures are applied to airports to incorporate heterogeneity in non‐parametric frontier models which are robust for outlying observations. In particular, the influence of the operational environment on airport efficiency is examined in a sample of 141 international airports. The conclusions show that the operational environment indeed matters and that privatisation, regulation, traffic transfer and the dominant carrier have a positive effect on efficiency, whereas aeronautical revenues influence it negatively. Copyright © 2014 John Wiley & Sons, Ltd.     

India’s air traffic: towards an empirical framework for systems analysis

The paper explores patterns of flows within India’s Air Traffic System through the lens of carriers’ networks and route structures between 2006 and 2014. Through observations of frequency distributions and their distinct patterns an analytic framework is derived heuristically by means of classification and aggregation. The well-known skewed traffic distribution which spatially concentrates traffic around relatively few airports serves as the starting point for decomposing the air traffic system (ATS) into its constituent route types. Airline operations along distinct route classes allows for classifying individual carrier’s network features as an embedded part of the system. Discussion of their role includes a spatial component. Inferences about development paths – past, present, future – of the Indian commercial ATS can be made.     

Determination and Applications of Environmental Costs at Different Sized Airports – Aircraft Noise and Engine Emissions

With the increasing trend of charging for externalities and the aim of encouraging the sustainable development of the air transport industry, there is a need to evaluate the social costs of these undesirable side effects, mainly aircraft noise and engine emissions, for different airports. The aircraft noise and engine emissions social costs are calculated in monetary terms for five different sized airports, ranging from hub airports to small regional airports. The number of residences within different levels of airport noise contours and the aircraft noise classifications are the main determinants for accessing aircraft noise social costs. The environmental impacts of aircraft engine emissions include both aircraft landing and take-off and 30-minute cruise. The social costs of aircraft emissions vary by engine type and aircraft category, depending on the damage caused by different engine pollutants on the human health, vegetation, materials, aquatic ecosystem and climate. The results indicate that the relationship appears to be curvilinear between environmental costs and the traffic volume of an airport. The results and methodology of environmental cost calculation could be applied to the proposed European wide harmonised noise charges as well as the social cost benefit analysis of airports.     

A time series analysis of the dynamic competition between major cargo airports

This paper models the dynamic competition between major cargo airports from the time series perspectives of long-term equilibriums and short-run dynamics. We first apply a unit root test to examine the stationarity of cargo throughput data. Airports are then analysed pairwise by region to test their equilibrium relationships through cointegration analysis. Meanwhile, we also utilise the error correction model to investigate the short-run impacts of cargo traffic between the airports. According to our findings, there are four positive long-term equilibriums, one positive short-run dynamic and three negative short-run dynamics in Asia. In addition, the airports in North America are found to have four positive long-term equilibriums, three negative long-run equilibriums, seven positive short-run impacts and three negative short-run impacts. As these dynamic relationships imply competition between cargo airports, our study can provide airport authorities with the reference to develop their long-term strategies and short-run operational plans.