Impact of climate costs on airline network and trajectory optimization: a parametric study

Rosenow, Judith; Lindner, Mirko; Fricke, Hartmut

doi:10.1007/s13272-017-0239-2

Cited by 31 publications

(24 citation statements)

References 12 publications

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“…Note that non-operational, i.e., research-related optimization tools include estimates for climate impacts in route optimization (e.g., [1]). However, only recently climate impact indicators were considered in more detail, which take into account more than mere emission amounts, for example contrail occurrence and ozone changes from NO x emissions [2][3][4][5][6][7][8]. The reasons for this include a low TRL (technology readiness level) of a flight planning method that considers a multi-criteria environmental impact assessment and remaining uncertainty on strategic metrics of environmental impact to motivate environmental flight planning.…”

Section: Introductionmentioning

confidence: 99%

A Concept for Multi-Criteria Environmental Assessment of Aircraft Trajectories

et al. 2017

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Comprehensive assessment of the environmental aspects of flight movements is of increasing interest to the aviation sector as a potential input for developing sustainable aviation strategies that consider climate impact, air quality and noise issues simultaneously. However, comprehensive assessments of all three environmental aspects do not yet exist and are in particular not yet operational practice in flight planning. The purpose of this study is to present a methodology which allows to establish a multi-criteria environmental impact assessment directly in the flight planning process. The method expands a concept developed for climate optimisation of aircraft trajectories, by representing additionally air quality and noise impacts as additional criteria or dimensions, together with climate impact of aircraft trajectory. We present the mathematical framework for environmental assessment and optimisation of aircraft trajectories. In that context we present ideas on future implementation of such advanced meteorological services into air traffic management and trajectory planning by relying on environmental change functions (ECFs). These ECFs represent environmental impact due to changes in air quality, noise and climate impact. In a case study for Europe prototype ECFs are implemented and a performance assessment of aircraft trajectories is performed for a one-day traffic sample. For a single flight fuel-optimal versus climate-optimized trajectory solution is evaluated using prototypic ECFs and identifying mitigation potential. The ultimate goal of such a concept is to make available a comprehensive assessment framework for environmental performance of aircraft operations, by providing key performance indicators on climate impact, air quality and noise, as well as a tool for environmental optimisation of aircraft trajectories. This framework would allow studying and characterising changes in traffic flows due to environmental optimisation, as well as studying trade-offs between distinct strategic measures.

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Section: Introductionmentioning

confidence: 99%

A Concept for Multi-Criteria Environmental Assessment of Aircraft Trajectories

et al. 2017

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“…. , x(T)) as shown in (4) and (5). The looped structure of RNN allows information to be passed from one step to the next.…”

Section: Neural Network Modelsmentioning

confidence: 99%

“…A standard recurrent neural network (RNN) computes the hidden vector sequence h = (h(1), …, h(T)) and output vector sequence y = (y(1), …, y(T)) for a given input sequence x = (x(1), …, x(T)) as shown in (4) and (5). The looped structure of RNN allows information to be passed from one step to the next.…”

Section: Neural Network Modelsmentioning

confidence: 99%

“…If the aircraft is departing from one airport, changes with regards to arrival time at the next are comparatively small [4]. Current research in the field of flight operations addresses economic, operational and ecological efficiency [5][6][7][8][9][10][11]. To evaluate these operational deviations in the economic context, reference values are provided for the cost of delay to European airlines [12].…”

Section: Introductionmentioning

confidence: 99%

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Consideration of Passenger Interactions for the Prediction of Aircraft Boarding Time

Schultz

Reitmann

2018

Aerospace

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In this paper we address the prediction of aircraft boarding using a machine learning approach. Reliable process predictions of aircraft turnaround are an important element to further increase the punctuality of airline operations. In this context, aircraft turnaround is mainly controlled by operational experts, but the critical aircraft boarding is driven by the passengers' experience and willingness or ability to follow the proposed procedures. Thus, we used a developed complexity metric to evaluate the actual boarding progress and a machine learning approach to predict the final boarding time during running operations. A validated passenger boarding model is used to provide reliable aircraft status data, since no operational data are available today. These data are aggregated to a time-based complexity value and used as input for our recurrent neural network approach for predicting the boarding progress. In particular we use a Long Short-Term Memory model to learn the dynamical passenger behavior over time with regards to the given complexity metric. Status QuoOur research is connected to three different topics: Aircraft turnaround, passenger behavior, and machine learning. Comprehensive overviews are provided for aircraft turnaround [16], for boarding [17], and for the corresponding economic impact [12,18,19]. Relevant studies include, but are not limited to, the following current examples.Aircraft turnaround, as part of the aircraft trajectory over the day of operations, has to be part of the optimization strategies for minimizing flight delays [20] and ensuring flight connections considering operational uncertainties [21,22]. In this context, turnaround absorbs inbound delay [15] and could enhance slot adherence at airports [23] or mitigate problems of push-back scheduling [24]. A microscopic turnaround model provides an open and closed-loop process control for higher automation levels in turnaround management [25]. The inter-aircraft propagated delay is focused on in Reference [26], since individual delays could result in parallel demand of turnaround resources (personnel, space, and equipment). Furthermore, delayed use of infrastructure may cause excessive demand in later time frames, and both turnaround stability and resource efficiency will provide significant benefits for airline and airport operations [15,27]. The compatibility of airline operations, existing ground handling procedures and airport infrastructure requirements were analyzed in the context of alternative energy concepts [28]. With a focus on efficient aircraft boarding, Milne and Kelly [29] develop a method that assigns passengers to seats so that their luggage is distributed evenly throughout the cabin, assuming a less time-consuming process for finding available storage in the overhead compartment. Qiang et al. [30] propose a boarding strategy that allows passengers with a large amount of hand luggage to board first. Milne and Salari [31] assign passengers to seats according to the number of hand luggage items and propose that passenge...

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“…Current research in the field of air traffic management primarily addresses the economic and ecological impact of flight trajectories (cf. [10][11][12][13]) but has to include efficient aircraft ground operations as well in order to ensure an efficient aircraft trajectory over the day of operations [14]. In this context, research was conducted with regards to the turnaround performance implementing collaborative management [15] or addressing the future airport performance [16].…”

Section: Introductionmentioning

confidence: 99%

Advancements in Passenger Processes at Airports from Aircraft Perspective

Schultz

Schmidt

2018

Sustainability

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We provide an overview about the research done in the field of airport and airline operations with a specific focus on a fast, reliable and sustainable passenger boarding. The reliable prediction operational processes along the aircraft air-ground trajectory demands a comprehensive consideration of economic, environmental, and handling constraints of airlines and airports. In particular, the critical process of passenger boarding is driven by passengers' ability to follow the proposed boarding procedures and is not controlled by operational experts. In this paper we implement and compare two individual-based approaches which cover both specific passenger behavior during boarding and operational airline constraints. Both models used similar input values, but exhibit different magnitudes in the benefit evaluation. Furthermore, we demonstrate that there are still unused potentials to further improve boarding progress by using innovative infrastructural adaptations inside the aircraft cabin.

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Impact of climate costs on airline network and trajectory optimization: a parametric study

Cited by 31 publications

References 12 publications

A Concept for Multi-Criteria Environmental Assessment of Aircraft Trajectories

A Concept for Multi-Criteria Environmental Assessment of Aircraft Trajectories

Consideration of Passenger Interactions for the Prediction of Aircraft Boarding Time

Advancements in Passenger Processes at Airports from Aircraft Perspective

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