Air traffic flow management under uncertainty using chance-constrained optimization

Chen, J.; Chen, L.; Sun, Dong

doi:10.1016/j.trb.2017.05.014

Cited by 59 publications

(25 citation statements)

References 19 publications

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“…The future of air traffic is unknown, but it is essential to have an idea of air traffic in order to plan current projects. Efficient ATFM relies on accurate air traffic forecasting [5]. Also, Ak?a shows that by analyzing future passenger demand, air traffic network performance and accessibility of the waypoints can be evaluated [2].…”

Section: Introductionmentioning

confidence: 99%

An Optimization Approach towards Air Traffic Forecasting: A Case Study of Air Traffic in Changi Airport

Sailauov

Zhong

2019

Stat., optim. inf. comput.

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SouthEast Asia is considered one of the fastest air traffic growing regions in the world. Congested air traffic and weather conditions have thus become major factors in air traffic management. In this paper the model for air traffic forecasting was able to forecast the country, city-pair and airport-pair air traffic. Results show that the passenger forecasting for Singapore has dependence not only on that country but on neighbouring countries as well. The paper predicts that the passenger movements in Changi airport will increase up to 81.65 million people by year 2023, which is 31.23 % more than that in 2017. Also, the number of passenger aircraft between Singapore and Jakarta city-pair will increase up to 34702 by year 2023, which is 26.6 % more than that in 2017. In addition, the number of passenger aircraft between Changi airport and KLIA airport-pair will be between 31698 and 40311 by year 2023.

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Section: Introductionmentioning

confidence: 99%

An Optimization Approach towards Air Traffic Forecasting: A Case Study of Air Traffic in Changi Airport

Sailauov

Zhong

2019

Stat., optim. inf. comput.

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“…These changes will no doubt impact their operational performance and taskload in terms of tactical radar monitoring, guiding of dynamic aircraft movements while maintaining high operational safety standards [9,26]. To better understand tactical air traffic complexity, researchers have explored various methods such as the study of the aircraft's air route and its conflict characteristics [27][28][29][30], and in the strategic time domain, by studying the air traffic flow patterns via optimisation, mathematical models and network theories in different phases of flight [31][32][33][34][35]. Air traffic complexity is then quantified through methods like the modelling of air traffic flow and analysis of the air transportation network mathematically, so as to better aid [37].…”

Section: Motivationmentioning

confidence: 99%

An eye-hand movement Model for traffic complexity evaluation and monitoring enhancement for air traffic controllers

Wee¹

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Dynamic changes in the field of Air Traffic Management in recent years, coupled with the increasing use of automation and new concepts like 4-Dimensional Trajectory Based Operations (4D-TBO) are being investigated. It is therefore postulated that future Air Traffic Controller (ATCO) tasks would likely be dedicated to performing more tactical monitoring activities presented on radar displays with lesser communication with the flight crew under regular circumstances, changing the way how ATCOs operate. This brings about a new set of challenges to ATCOs, as current approaches to address issues related to an ATCO's tactical control activity both operationally and in training, remain limited, due to the lack of knowledge

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“…However, their main focus is on increasing the accuracy of the trajectory predictions considering the global perspective for a better optimized ATN. In the existing literature, there are works which estimate the airport and airspace capacity under uncertainty conditions as well as their consideration in flow management, while the framework proposed in [55], [58], [59], [60], [61], [62] are for airport and [63], [64], [65], [66], [67], [68], [28] are for en-route airspace.…”

Section: Consideration Of Uncertaintymentioning

confidence: 99%

“…A chance-constrained optimization approach is proposed in [66] based on the deterministic formulation structure of the cell transmission model in [42]. The stochastic capacities are constrained for sectors, departure, and arrival airports in discrete time.…”

Section: Consideration Of Uncertaintymentioning

confidence: 99%

Real-time flight scheduling for optimal air traffic flow management

Guruge¹,

Sandamali²

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The contributions of the co-authors are as follows: • I reviewed the literature, came up with the new model formulation, prepared the manuscript, and performed simulations. • A/Prof. Su Rong provided the initial research direction, guided me through the process, and contributed with suggestions. • Yicheng Zhang participated in the initial brainstorming discussions, revised the manuscript, and provided several technical directions.

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Air traffic flow management under uncertainty using chance-constrained optimization

Cited by 59 publications

References 19 publications

An Optimization Approach towards Air Traffic Forecasting: A Case Study of Air Traffic in Changi Airport

An Optimization Approach towards Air Traffic Forecasting: A Case Study of Air Traffic in Changi Airport

An eye-hand movement Model for traffic complexity evaluation and monitoring enhancement for air traffic controllers

Real-time flight scheduling for optimal air traffic flow management

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