Flight schedule punctuality control and management: a stochastic approach

The insufficiency of infrastructure capacity in an air transport system is usually blamed for poor punctuality performance when implementing flight schedules. However, investigations have revealed that ground operations of airlines have become the second major cause of flight delay at airports. A stochastic approach is used in this paper to model the operation of aircraft turnaround and the departure punctuality of a turnaround aircraft at an airport. The aircraft turnaround model is then used to investigate the punctuality problem of turnaround aircraft. Model results reveal that the departure punctuality of a turnaround aircraft is influenced by the length of scheduled turnaround time, the arrival punctuality of inbound aircraft as well as the operational efficiency of aircraft ground services. The aircraft turnaround model proposed is then employed to evaluate the endogenous schedule punctuality of two turnaround aircraft. Model results, when compared with observation data, show that the operational efficiency of aircraft ground services varies among turnarounds. Hence, it is recommended that the improvement of departure punctuality of turnaround aircraft may be achieved from two approaches: airline scheduling control and the management of operational efficiency of aircraft ground services.     

An environmental assessment of air traffic speed constraints in the departure phase of flight: A case study at Gothenburg Landvetter Airport,Sweden

This paper considers the environmental effects of air traffic management speed constraints during the departure phase of flight. We present a CO₂ versus noise trade-off study that compares aircraft departure procedures subject to speed constraints with a free speed scenario. A departure route at Gothenburg Landvetter Airport in Sweden is used as a case study and the analysis is based on airline flight recorded data extracted from the Airbus A321 aircraft. Results suggest that CO₂ emissions could be reduced by 180 kg per flight if all departure speed constraints were removed at a cost of increased noise exposure below 70 dB(A).     

Evaluation of fuel cell auxiliary power units for heavy-duty diesel trucks

A large number of heavy-duty trucks idle a significant amount. Heavy-duty line-haul truck engines idle about 20–40% of the time the engine is running, depending on season and operation. Drivers idle engines to power climate control devices (e.g., heaters and air conditioners) and sleeper compartment accessories (e.g., refrigerators, microwave ovens, and televisions) and to avoid start-up problems in cold weather. Idling increases air pollution and energy use, as well as wear and tear on engines. Efforts to reduce truck idling in the US have been sporadic, in part because it is widely viewed in the trucking industry that further idling restrictions would unduly compromise driver comfort and truck operations. The auxiliary power units (APUs) available to replace the idling of the diesel traction engine all have had limited trucking industry acceptance. Fuel cells are a promising APU technology. Fuel cell APUs have the potential to greatly reduce emissions and energy use and save money. In this paper, we estimate costs and benefits of fuel cell APUs. We calculate the payback period for fuel cell APUs to be about 2.6–4.5 years. This estimate is uncertain since future fuel cell costs are unknown and cost savings from idling vary greatly across the truck fleet. The payback period is particularly sensitive to diesel fuel consumption at idle. Given the large potential environmental and economic benefits of fuel cell APUs, the first major commercial application of fuel cells may be as truck APUs.     

Heuristic search for the coupled runway sequencing and taxiway routing problem

This paper presents the first local search heuristic for the coupled runway sequencing (arrival & departure) and taxiway routing problems, based on the receding horizon (RH) scheme that takes into account the dynamic nature of the problem. As test case, we use Manchester Airport, the third busiest airport in the UK. From the ground movement perspective, the airport layout requires that departing aircraft taxi across the arrivals runway. This makes it impossible to separate arrival from departure sequencing in practice. Operationally, interactions between aircraft on the taxiways could prevent aircraft from taking off from, or landing on, runways during the slots assigned to them by an algorithm optimizing runway use alone. We thus consider the interactions between arrival and departure aircraft on the airport surface. Compared to sequentially optimized solutions, the results obtained with our approach indicate a significant decrease in the taxiway routing delay, with generally no loss in performance in terms of the sequencing delay for a regular day of operations. Another benefit of such a simultaneous optimization approach is the possibility of holding aircraft at the stands for longer, without the engines running. This significantly reduces the fuel burn, as well as bottlenecks and traffic congestion during peak hours that are often the cause of flight delays due to the limited amount of airport surface space available. Given that the maximum computing time per horizon is around 95 s, real-time operation might be practical with increased computing power.     

Assessment of carbon emission costs for air cargo transportation

This study presents a set of models that calculate carbon emissions in individual phases of flight during air cargo transportation, investigates resultant carbon footprints by aircraft type and flight route, and estimates increases in transportation costs for airlines due to carbon taxes imposed by the EU ETS. The estimated results provide useful references for airlines in aircraft assignment on different routes and in aircraft selection for new purchases. Validation of the model is conducted by simulating the potential impact of the implementation of the EU ETS on costs of air cargo transportation for six routes and six types of aircraft. Results show that the impact may be subject to various factors including unit carbon emissions per aircraft, aviation emission allowances per airline, and carbon trading prices; and that increases in costs of air cargo transportation range from 0% to 5.27% per aircraft per route. Therefore, the implementation of the EU ETS may encourage airlines to cut down their operating costs by reducing their carbon emissions, thereby ameliorating greenhouse gas pollution caused by air cargo transportation.     

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.     

Reducing the climate change impacts of aviation by restricting cruise altitudes

Two of the ways in which air travel affects climate are the emission of carbon dioxide and the creation of high-altitude contrails. One possible impact reduction strategy is to significantly reduce the formation of contrails. This could be achieved by limiting the cruise altitude of aircraft. If implemented, this could severely constrain air space capacity, especially in parts of Europe. In addition, carbon emissions would likely be higher due to less efficient aircraft operation at lower cruise altitudes. This paper describes an analysis of these trade-offs using an air space simulation model as applied to European airspace. The model simulates the flight paths and altitudes of each aircraft and is here used to calculate emissions of carbon dioxide and changes in the journey time. For a one-day Western European traffic sample, calculations suggest annual mean CO₂ emissions would increase by only 4% if cruise altitudes were restricted to prevent contrail formation. The change in journey time depended on aircraft type and route, but average changes were less than 1 min. Our analysis demonstrates that altitude restrictions on commercial aircraft could be an effective means of reducing climate change impacts, though it will be necessary to mitigate the increased controller workload conflicts that this will generate.     

A tool for calculating aircraft emissions and its application to Greek airspace

This paper quantifies the impact of aircraft emissions on local air quality and climate change. Aircraft emissions during the cruise cycle and the landing/take-off cycle are considered. A tool is developed that computes emission values using real-time air traffic data derived from various databases. Emissions include carbon dioxide, hydrocarbons, carbon monoxide and nitrogen oxides. The overall output is a detailed ‘emissions map’ of a given territory that enables the identification of critical emission spots including routes, airports, season, aircraft type and flight category. The method can be used for real-time monitoring of airline emissions and for policy analysis. The proposed tool and resulting outputs are illustrated in the case of the Greek airport system using domestic, international and overflights. Demand volatility driven mainly by tourism and its impact on emissions is assessed.     

Evaluation and implications of environmental charges on commercial flights

Environmental charges are one of the economic instruments for controlling externalities. Their application to commercial flights has become a preferred method of encouraging the sustainable development of the air transport industry. Two kinds of externalities, aircraft noise and engine emissions, both generating profound impacts on human beings and on the environment, are considered here. The hedonic price method is applied to calculate the social cost of aircraft noise during the landing and take-off stages of the flight. The marginal impact of each flight with specific aircraft/engine combinations is derived for the allocation of aggregate noise social costs. In contrast, the dose - response method is applied to estimate the social cost of each engine exhaust pollutant during different flight modes. The combination of aircraft noise and engine emissions social costs is then evaluated on the basis of several environmental charge mechanism scenarios, using Amsterdam Airport Schiphol as a case study. It is shown that the current noise or engine emissions related charges at airports are lower than the actual social costs of their respective externalities. The implications of charge mechanism scenarios are subsequently discussed and evaluated in terms of their impacts on airline costs, airfares and passenger demand.     

The punctuality performance of aircraft rotations in a network of airports

The aim of this paper is to investigate the influence of aircraft turnaround performance at airports on the schedule punctuality of aircraft rotations in a network of airports. A mathematical model is applied, composed of two sub-models, namely the aircraft turnaround model (turnaround simulations) and the enroute model (enroute flight time simulations). A Markovian type model is featured in the aircraft turnaround model to simulate the operation of aircraft turnarounds at an airport by considering operational uncertainties and schedule punctuality variance. In addition, stochastic Monte Carlo simulations are employed to carry out stochastic sampling and simulations in both the aircraft turnaround model and the enroute model. Results of simulations show the robustness of the aircraft rotation model in capturing uncertainties from aircraft rotations. The propagation of knock-on delays in aircraft rotations is found to be significant when the short-connection-time policy is used by an airline at its hub airport. It is also found that the proper inclusion of schedule buffer time in the aircraft rotation schedule helps control the propagation of knock-on delays and, therefore, stabilize the punctuality performance of aircraft rotations.     

Comparison of emerging ground propulsion systems for electrified aircraft taxi operations

Aviation is a mode with high fuel consumption per passenger mile and has significant environmental impacts. It is important to seek ways to reduce fuel consumption by the aviation sector, but it is difficult to improve fuel efficiency during the en-route cruise phase of flight because of technology barriers, safety requirements, and the mode of operations of air transportation. Recent efforts have emphasized the development of innovative Aircraft Ground Propulsion Systems (AGPS) for electrified aircraft taxi operations. These new technologies are expected to significantly reduce aircraft ground-movement-related fuel burn and emissions. This study compares various emerging AGPS systems and presents a comprehensive review on the merits and demerits of each system, followed with the local environmental impacts assessment of these systems. Using operational data for the 10 busiest U.S. airports, a comparison of environmental impacts is performed for four kinds of AGPS: conventional, single engine-on, external, and on-board systems. The results show that there are tradeoffs in fuel and emissions among these emerging technologies. On-board system shows the best performance in the emission reduction, while external system shows the least fuel burn. Compared to single-engine scenario, external AGPS shows the reduction of HC and CO emissions but the increase of NO_x emission. When a general indicator is considered, on-board AGPS shows the best potential of reducing local environmental impacts. The benefit-cost analysis shows that both external and on-board systems are worth being implemented and the on-board system appeals to be more beneficial.     

Spoke airports,intentional and unintentional ground travel,and the air travel decision-making process

For air travelers originating from the spokes of the US hub-and-spoke air network, price, flight frequency, and aircraft type are all known factors in their travel decision-making process. Less well known, however, is the extent to which different elements of ground travel enter into these travelers’ air journeys. Based on 51 interviews at four universities at spokes surrounding O’Hare International Airport, this article describes how considerations such as vehicle availability, individual driving ability, localized weather, and unanticipated ground travel are fundamentally part of the air travel decision-making process for spoke travelers.     

Airport taxi planning: Lagrangian decomposition

The airport taxi planning (TP) module is a decision tool intended to guide airport surface management operations. TP is defined by a flow network optimization model that represents flight ground movements and improves aircraft taxiing routes and schedules during periods of aircraft congestion. TP is not intended to operate as a stand‐alone tool for airport operations management: on the contrary, it must be used in conjunction with existing departing and arriving traffic tools and overseen by the taxi planner of the airport, also known as the aircraft ground controller. TP must be flexible in order to accommodate changing inputs while maintaining consistent routes and schedules already delivered from past executions. Within this dynamic environment, the execution time of TP may not exceed a few minutes. Classic methods for solving binary multi‐commodity flow networks with side constraints are not efficient enough; therefore, a Lagrangian decomposition methodology has been adapted to solve it. We demonstrate TP Lagrangian decomposition using actual data from the Madrid‐Barajas Airport. Copyright © 2011 John Wiley & Sons, Ltd.     

Accuracy of reinforcement learning algorithms for predicting aircraft taxi-out times: A case-study of Tampa Bay departures

Taxi-out delay is a significant portion of the block time of a flight. Uncertainty in taxi-out times reduces predictability of arrival times at the destination. This in turn results in inefficient use of airline resources such as aircraft, crew, and ground personnel. Taxi-out time prediction is also a first step in enabling schedule modifications that would help mitigate congestion and reduce emissions. The dynamically changing operation at the airport makes it difficult to accurately predict taxi-out time. In this paper we investigate the accuracy of taxi out time prediction using a nonparametric reinforcement learning (RL) based method, set in the probabilistic framework of stochastic dynamic programming. A case-study of Tampa International Airport (TPA) shows that on an average, with 93.7% probability, on any given day, our predicted mean taxi-out time for any given quarter, matches the actual mean taxi-out time for the same quarter with a standard error of 1.5 min. Also, for individual flights, the taxi-out time of 81% of them were predicted accurately within a standard error of 2 min. The predictions were done 15 min before gate departure. Gate OUT, wheels OFF, wheels ON, and gate IN (OOOI) data available in the Aviation System Performance Metric (ASPM) database maintained by the Federal Aviation Administration (FAA) was used to model and analyze the problem. The prediction accuracy is high even without the use of detailed track data.     

A comparative life-cycle energy and emissions analysis for intercity passenger transportation in the U.S. by aviation,intercity bus,and automobile

Intercity passenger trips constitute a significant source of energy consumption, greenhouse gas emissions, and criteria pollutant emissions. The most commonly used city-to-city modes in the United States include aircraft, intercity bus, and automobile. This study applies state-of-the-practice models to assess life-cycle fuel consumption and pollutant emissions for intercity trips via aircraft, intercity bus, and automobile. The analyses compare the fuel and emissions impacts of different travel mode scenarios for intercity trips ranging from 200 to 1600 km. Because these modes operate differently with respect to engine technology, fuel type, and vehicle capacity, the modeling techniques and modeling boundaries vary significantly across modes. For aviation systems, much of the energy and emissions are associated with auxiliary equipment activities, infrastructure power supply, and terminal activities, in addition to the vehicle operations between origin/destination. Furthermore, one should not ignore the embodied energy and initial emissions from the manufacturing of the vehicles, and the construction of airports, bus stations, highways and parking lots. Passenger loading factors and travel distances also significantly influence fuel and emissions results on a per-traveler basis. The results show intercity bus is generally the most fuel-efficient mode and produced the lowest per-passenger-trip emissions for the entire range of trip distances examined. Aviation is not a fuel-efficient mode for short trips (<500 km), primarily due to the large energy impacts associated with takeoff and landing, and to some extent from the emissions of ground support equipment associated with any trip distance. However, aviation is more energy efficient and produces less emissions per-passenger-trip than low-occupancy automobiles for trip distances longer than 700–800 km. This study will help inform policy makers and transportation system operators about how differently each intercity system perform across all activities, and provides a basis for future policies designed to encourage mode shifts by range of service. The estimation procedures used in this study can serve as a reference for future analyses of transportation scenarios.     

Methodologies to monetize the variations in load factor and GHG emissions per passenger-mile of airlines

Global GHG emissions from air travel are currently at 3% and it could increase to 15% of the total GHG emissions by 2050. To curb the growth of GHG emissions from air travel, the U.S. Federal Aviation Administration (FAA) has created a policy to achieve carbon neutral growth by 2020 relative to the 2005 baseline. If the airline industry is to both grow and meet the objectives set by this policy, new and innovative aircraft designs, operational efficiencies, and widespread use of alternate fuels are required. To accomplish this would require large research and development investment. The federal government and state governments have passed legislations that provide tax breaks and other incentives to encourage investments in new technologies. One such tax policies is cap and trade system. This had partial success in reducing GHG emissions in certain industries but was not successful in the airline industry. This paper presents alternate methods to raise capital to invest in GHG emissions reduction projects in the airline sector. The four methodologies presented here monetizes the GHG emissions resulting from differences in load factor (ratio of number of passengers to number of seats) and GHG emissions per passenger-mile among different airlines, among different flight sectors, etc. to raise the capital. Based on 2012 air travel data, these methodologies could raise more than $300 million dollars annually to invest in GHG emissions reduction projects.     

Ground delay program planning under uncertainty in airport capacity

Abstract

This paper presents an algorithm for assigning flight departure delays under probabilistic airport capacity. The algorithm dynamically adapts to weather forecasts by revising, if necessary, departure delays. The proposed algorithm leverages state-of-the-art optimization techniques that have appeared in recent literature. As a case study, the algorithm is applied to assigning departure delays to flights scheduled to arrive at San Francisco International Airport in the presence of uncertainty in the fog clearance time. The cumulative distribution function of fog clearance time was estimated from historical data. Using daily weather forecasts to update the probabilities of fog clearance times resulted in improvement of the algorithm's performance. Experimental results also indicate that if the proposed algorithm is applied to assign ground delays to flights inbound at San Francisco International airport, overall delays could be reduced up to 25% compared to current level.     

The influence of attitude towards individuals’ choice for a remotely piloted commercial flight: A latent class logit approach

The Remotely Piloted Commercial Passenger Aircraft Attitude Scale (RPCPAAS) was created to measure positive and negative attitudes towards a new and plausible form of air travel. This information was then used, in combination with a latent class logit model built on data generated from a stated choice experiment to gain insight into the choice behaviour between conventionally piloted aircraft (CPA) with a pilot on-board and remotely piloted aircraft (RPA) with a pilot on the ground. The results revealed that individuals, on-average, if presented a choice between a CPA and a RPA of equivalent attributes, would elect for the CPA option. However, there is variability in the passengers’ sensitivity to various flight attributes, and these sensitivities were influenced by individuals’ attitude towards the new technology (i.e., RPA). From an operational perspective, and assuming that one day passengers of commercial airlines are offered the choice between CPA and RPA, the strategies employed by airlines to encourage the use of the new technology need to be different, based on individuals’ attitude towards RPA.     

Determinants of airports’ environmental effects

Aviation is a fast growing sector with increasing environmental concerns linked to aircraft emissions at airports and noise nuisance. This paper investigates the factors affecting the annual environmental effects produced by a national aviation system. The environmental effects are computed using certification data for each aircraft-engine combination. Moreover, we also take into account for the amount of environmental effects that is internalized at the airport, mainly through noise regulation. We study a dataset covering information on Italian airports during the period 1999–2008. We show that a 1% increase in airport’s yearly movements yields a 1.05% increase in environmental effects, a 1% in aircraft size (measured in MTOW) gives rise to a 1.8% increase and a 1% increase in aircraft age generates a 0.69% increase in environmental effects. Similar results but with smaller magnitudes are observed if airport internalization is considered. Our policy implications are that the tariff internalizing the total amount of externality is about euro 180 per flight, while the tariff limiting only pollution is about euro 60 and the one reducing noise is about euro 110. Moreover, our airport examples show that managers should prefer to address additional capacity by increasing frequency rather than aircraft size, since the former strategy is more environmental friendly.     

Rapid estimation of global civil aviation emissions with uncertainty quantification

In this paper we describe the methods used to develop the open source Aviation Emissions Inventory Code and produce a global emissions inventory for scheduled civil aviation, with quantified uncertainty. We estimate that in 2005, scheduled civil aviation was responsible for 180.6 Tg of fuel burn, which agrees to within 4% of other published emissions inventories for 2004 and 2006. By comparing the Aviation Emissions Inventory Code with flight data records, we show that the mean bias in predicted fuel burn at the airport-pair level is +1% for an ensemble of 132 flights, and less than 10% for 5 of the 6 aircraft types used in the validation.