Control theoretic concept for intuitive guidance of pilots during taxiing

Haus, Steffen; Sendobry, Alexander; Urvoy, Carole; Klingauf, Uwe

doi:10.1109/dasc.2011.6096261

Cited by 4 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the third generation of A-SMGCS, the SESAR project of Europe [11] and the NextGen of America [9] believe that introducing complete 4D traces (4DTS) composed of 3D spaces and time could lay a solid foundation for studies on air traffic. Estimates indicate that introducing 4DTS into taxiing on an airport's surface may decrease taxiing delays by approximately 55% [22]. During aircraft surface taxiing, since all dimensions are unnecessary, the unique positional information of aircraft can be defined by their route and speed curves.…”

Section: A-smgcs Variables Optimizationmentioning

confidence: 99%

Multi-Objective Optimization of Aircraft Taxiing on the Airport Surface with Consideration to Taxiing Conflicts and the Airport Environment

et al. 2019

View full text Add to dashboard Cite

High-efficiency taxiing for safe operations is needed by all types of aircraft in busy airports to reduce congestion and lessen fuel consumption and carbon emissions. This task is a challenge in the operation and control of the airport’s surface. Previous studies on the optimization of aircraft taxiing on airport surfaces have rarely integrated waiting constraints on the taxiway into the multi-objective optimization of taxiing time and fuel emissions. Such studies also rarely combine changes to the airport’s environment (such as airport elevation, field pressure, temperature, etc.) with the multi-objective optimization of aircraft surface taxiing. In this study, a multi-objective optimization method for aircraft taxiing on an airport surface based on the airport’s environment and traffic conflicts is proposed. This study aims to achieve a Pareto optimized taxiing scheme in terms of taxiing time, fuel consumption, and pollutant emissions. This research has the following contents: (1) Previous calculations of aircraft taxiing pathways on the airport’s surface have been based on unimpeded aircraft taxiing. Waiting on the taxiway is excluded from the multi-objective optimization of taxiing time and fuel emissions. In this study, the waiting points were selected, and the speed curve was optimized. A multi-objective optimization scheme under aircraft taxiing obstacles was thus established. (2) On this basis, the fuel flow of different aircraft engines was modified with consideration to the aforementioned environmental airport differences, and a multi-objective optimization scheme for aircraft taxiing under different operating environments was also established. (3) A multi-objective optimization of the taxiing time and fuel consumption of different aircraft types was realized by acquiring their parameters and fuel consumption indexes. A case study based on the Shanghai Pudong International Airport was also performed in the present study. The taxiway from the 35R runway to the 551# stand in the Shanghai Pudong International Airport was optimized by the non-dominant sorting genetic algorithm II (NSGA-II). The taxiing time, fuel consumption, and pollutant emissions at this airport were compared with those of the Kunming Changshui International Airport and Lhasa Gonggar International Airport, which have different airport environments. Our research conclusions will provide the operations and control departments of airports a reference to determine optimal taxiing schemes.

show abstract

Section: A-smgcs Variables Optimizationmentioning

confidence: 99%

Multi-Objective Optimization of Aircraft Taxiing on the Airport Surface with Consideration to Taxiing Conflicts and the Airport Environment

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Both in European's 'Single European Sky Air Traffic Management' (SESAR) [27] and the USA's 'Next Generation Air Transport System' (NextGen) [29], it is conceived that the introduction of complete 4-Dimensional trajectories (4DTs), representing the aircraft path consisting of three space dimensions plus time, will form the major cornerstone of air traffic research and facilitate gate to gate operation. It is also predicted that the introduction of 4DTs on the ground would significantly reduce taxi delay up to 55% [30]. However, in the context of ground movement, not all dimensions are required as aircraft move on airport surface.…”

Section: Rd Generation: Active Routing and Guidancementioning

confidence: 99%

“…where a d min is defined in (30) and represents the situation where there is only one deceleration phase with a small deceleration rate a d min and aircraft has to decelerate earlier.…”

Section: A Metaheuristic Multi-objective Optimization Frameworkmentioning

confidence: 99%

Toward a More Realistic, Cost-Effective, and Greener Ground Movement Through Active Routing—Part I: Optimal Speed Profile Generation

Chen

Weiszer

Stewart

et al. 2016

IEEE Trans. Intell. Transport. Syst.

View full text Add to dashboard Cite

Among all airport operations, aircraft ground movement plays a key role in improving overall airport capacity as it links other airport operations. Moreover, ever-increasing air traffic, rising costs, and tighter environmental targets create pressure to minimize fuel burn on the ground. However, current routing functions envisioned in Advanced Surface Movement, Guidance and Control Systems almost exclusively consider the most timeefficient solution and apply a conservative separation to ensure conflict-free surface movement, sometimes with additional buffer times to absorb small deviations from the taxi times. Such an overly constrained routing approach may result in either a too tight planning for some aircraft so that fuel efficiency is compromised due to multiple acceleration phases, or performance could be further improved by reducing the separation and buffer times. In light of this, Parts I and II of this paper present a new Active Routing (AR) framework with the aim of providing a more realistic, cost-effective, and environmental friendly surface movement, targeting some of the busiest international hub airports. Part I of this paper focuses on optimal speed profile generation using a physics-based aircraft movement model. Two approaches based, respectively, on the Base of Aircraft Data and the International Civil Aviation Organization engine emissions database have been employed to model fuel consumption. These models are then embedded within a multiobjective optimization framework to capture the essence of different speed profiles in a Pareto optimal sense. The proposed approach represents the first attempt to systematically address speed profiles with competing objectives. Results reveal an apparent tradeoff between fuel burn and taxi times irrespective of fuel consumption modeling approaches. This will have a profound impact on the routing and scheduling and open the door for the new concept of AR discussed in Part II of this paper.

show abstract

Real-Time Four-Dimensional Trajectory Generation Based on Gain-Scheduling Control and a High-Fidelity Aircraft Model

et al. 2021

View full text Add to dashboard Cite

Control theoretic concept for intuitive guidance of pilots during taxiing

Cited by 4 publications

References 0 publications

Multi-Objective Optimization of Aircraft Taxiing on the Airport Surface with Consideration to Taxiing Conflicts and the Airport Environment

Multi-Objective Optimization of Aircraft Taxiing on the Airport Surface with Consideration to Taxiing Conflicts and the Airport Environment

Toward a More Realistic, Cost-Effective, and Greener Ground Movement Through Active Routing—Part I: Optimal Speed Profile Generation

Real-Time Four-Dimensional Trajectory Generation Based on Gain-Scheduling Control and a High-Fidelity Aircraft Model

Contact Info

Product

Resources

About