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Zanin M.,Innaxis Foundation and Research Institute | Zanin M.,New University of Lisbon | Belkoura S.,Innaxis Foundation and Research Institute | Zhu Y.,Aviation Data Communication Corporation
Chinese Journal of Aeronautics | Year: 2017

The Chinese air transport system has witnessed an important evolution in the last decade, with a strong increase in the number of flights operated and a consequent reduction of their punctuality. In this contribution, we propose modelling the process of delay propagation by using complex networks, in which nodes are associated to airports, and links between pairs of them are assigned when a delay propagation is detected. Delay time series are analysed through the well-known Granger Causality, which allows detecting if one time series is causing the dynamics observed in a second one. Results indicate that delays are mostly propagated from small and regional airports, and through flights operated by turbo-prop aircraft. These insights can be used to design strategies for delay propagation dampening, as for instance by including small airports into the system's Collaborative Decision Making. © 2017 Chinese Society of Aeronautics and Astronautics.

Zhang M.,Beihang University | Cai K.-Q.,Beihang University | Zhu Y.-B.,Aviation Data Communication Corporation
AIAA/IEEE Digital Avionics Systems Conference - Proceedings | Year: 2012

With the increasing incidence of malfunctions of air transportation system due to severe weather, the Air Traffic Flow Network Rerouting (ATFNR) is playing an important role in improving the global efficiency of air traffic. This paper adopts a multi-objective optimization model to solve the ATFNR problem to make a tradeoff between the total delay costs and the airlines fairness. Meanwhile, a specially-designed algorithm based on multi-objective comprehensive learning particle swarm optimizer (MOCLPSO) under the cooperative co-evolution framework is presented to handle this large scale, multi-objective real-world optimization problem. The empirical studies show that the presented methodology is effective and outperforms an existing approach to ATFNR problem as well as two well-known Multi-Objective Optimization Algorithms. © 2012 IEEE.

Fang K.,Beihang University | Xue R.,Beihang University | Zhu Y.,Aviation Data Communication Corporation
Proceedings of 2016 7th International Conference on Mechanical and Aerospace Engineering, ICMAE 2016 | Year: 2016

To eliminate the time correlation and model the heavy distribution tail of ground based augmentation system (GBAS) errors, a method utilizing generalized autoregressive conditional heteroscedasticity (GARCH) model is introduced in this paper. Considering the statistical uncertainty of model parameters, a strategy for using the GARCH model in nonstationary situations is proposed. Based on that, a protection level calculation framework is established with an online/offline structure to calculate error overbound and protection level in real time. As the heavy-tail errors are normalized to standard Gaussian distribution, and all the normalized errors from different satellites and elevation groups are mixed together to calculate Gaussian overbound, the Gaussian overbound is much tighter than the one calculated by classic heavy-tail errors. That leads to smaller protection levels and higher system availability. © 2016 IEEE.

Zhang X.,Beihang University | Guan X.,Beihang University | Zhu Y.,Beihang University | Zhu Y.,Aviation Data Communication Corporation | Lei J.,Beihang University
Chinese Journal of Aeronautics | Year: 2015

Abstract The continuous growth of air traffic has led to acute airspace congestion and severe delays, which threatens operation safety and cause enormous economic loss. Flight assignment is an economical and effective strategic plan to reduce the flight delay and airspace congestion by reasonably regulating the air traffic flow of China. However, it is a large-scale combinatorial optimization problem which is difficult to solve. In order to improve the quality of solutions, an effective multi-objective parallel evolution algorithm (MPEA) framework with dynamic migration interval strategy is presented in this work. Firstly, multiple evolution populations are constructed to solve the problem simultaneously to enhance the optimization capability. Then a new strategy is proposed to dynamically change the migration interval among different evolution populations to improve the efficiency of the cooperation of populations. Finally, the cooperative co-evolution (CC) algorithm combined with non-dominated sorting genetic algorithm II (NSGA-II) is introduced for each population. Empirical studies using the real air traffic data of the Chinese air route network and daily flight plans show that our method outperforms the existing approaches, multi-objective genetic algorithm (MOGA), multi-objective evolutionary algorithm based on decomposition (MOEA/D), CC-based multi-objective algorithm (CCMA) as well as other two MPEAs with different migration interval strategies. © 2015 The Authors. Production and hosting by Elsevier Ltd.

Liu Y.,Beihang University | Zhu Y.,Aviation Data Communication Corporation
Institute of Navigation International Technical Meeting 2014, ITM 2014 | Year: 2014

Outlier detection and isolation is critical for aviation navigation. For GNSS, outlier occurred in SIS segment is dominant to lead positioning failure. This paper proposes a historical data based methodology for the analysis of SIS range outliers. Historical SIS outliers are collected by comparing broadcasted ephemeris with precision ephemeris provided by IGS. SIS range outliers are computed around China's airspace. Both the spatial and temporal characteristics of outliers are carefully discussed. Outlier duration, magnitude and influenced area are considered as the most important parameters for the outlier pool establishment. The relationship between outliers and influenced aviation phase of LPV200 is also studied, with ICAO'S required navigation performance as criteria. Ten years' GPS data is used for experiments. The results show that temporal outliers are closely related to the outlier duration, spatial outliers are mainly linked to the outlier magnitude. With year increases from 2002 to 2010, total number of ephemeris outliers decreases. What's more, ephemeris outliers have significant influence on LPV200 performance. When the magnitude of outlier is large enough, the 99.999% availability is hardly meet with by current technical framework. Our work is valuable not only for GNSS integrity performance assessment and also brings benefits to the development of enhance integrity monitor system in near future.

Ji X.,Beihang University | Fang J.,Aviation Data Communication Corporation | Yan R.,Aviation Data Communication Corporation
Proceedings of the World Congress on Intelligent Control and Automation (WCICA) | Year: 2015

Aircraft arrival sequencing and scheduling (ASS) is a hot topic in air traffic control, which has been proven to be an NP-hard problem. So far, many efforts have been made by modeling this problem in a static case, in which the information of all the landing aircrafts is known in advance. However, the air traffic environment in the airport is dynamic. As new aircrafts are arriving at the airport continually, the corresponding adjustment should be considered for the scheduling. From this point of view, an online method which is based on estimation of distribution algorithm (EDA) is introduced in this paper. At any moment in the sequencing operation, the method only focuses on those aircrafts which have already arrived at the airport but have not been assigned to land. Experiments show that the proposed method is effective and efficient to achieve a better result in solving the real-time ASS. © 2014 IEEE.

Zhao S.,Beihang University | Fang J.,Aviation Data Communication Corporation | Ji X.,Beihang University
Proceedings of the World Congress on Intelligent Control and Automation (WCICA) | Year: 2015

In this article, the cellular automation model is used to solve the problem of double-runway aircraft landing scheduling. A virtual model for simulating the landing process is established based on the cellular automation (CA), and the object of the model is aimed at minimizing the total cost of aircraft landing sequence. The simulation results show that this algorithm is capable of achieving high-quality scheduling results. Meanwhile, the computing time can also be significantly reduced, which shows great efficacy and efficiency of our algorithm in the double-runway aircraft landing scheduling. © 2014 IEEE.

Fang K.,Beihang University | Xue R.,Beihang University | Zhu Y.,Aviation Data Communication Corporation
IEEE CITS 2016 - 2016 International Conference on Computer, Information and Telecommunication Systems | Year: 2016

To reduce the inflation for statistical uncertainty and describe the real error distribution objectively, generalized autoregressive conditional heteroskedasticity (GARCH) model is utilized in this paper to model and overbound ground based augmentation system (GBAS) heavy-tail errors. Based on the GARCH model, heavy-tail errors are normalized to the standard Gaussian distribution, and error samples from all elevations are mixed together to calculate overbound without being grouped. By this means, compared with classic error distribution models, the heavy-tail errors are overbounded more tightly, and the calculated inflation factors, error confidence limits in pseudorange domain and protection levels in position domain are reduced correspondingly. © 2016 IEEE.

Yan S.,Beihang University | Cai K.,Beihang University | Zhu Y.,Aviation Data Communication Corporation
Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI | Year: 2016

The ever-growing air traffic flow has brought about great challenges to balance the airspace congestion and air traffic demands. This fact sparks numerous studies on Network-wide Flights Planning Optimization (NFPO) which aims to reconcile the contradiction between flight delay cost and airspace congestion by optimizing the pre-strategic flight plans from a network-wide point of view. In consideration of bi-objective and large-scale characteristics of the NFPO problem, this paper proposes a multi-objective Memetic Algorithm with Rerouting Meme (MARM) that incorporates an evolutionary global search framework with a problem-specific meme ulocal search operator). With the idea of heuristically reducing the interactions among flight trajectories to decongest the airspace, the Trajectories Correlation (TC) is defined as key network-wide knowledge and is applied to design the critical Rerouting Meme (RM). Additionally, to balance the ability of exploitation and exploration, the idea of simulated heating configuration setting is adopt for RM to integrate with the global search. Extensive empirical studies conducted on real large-scale traffic data of China air traffic network and flight plans support that MARM is beneficial to the NFPO problem via showing the improvement on effectiveness. © 2015 IEEE.

Liu Y.,Beihang University | Zhu Y.,Aviation Data Communication Corporation
Institute of Navigation International Technical Meeting 2014, ITM 2014 | Year: 2014

Safety is a critical issue for aviation. RAIM availability test is usually applied to insure safety service in civil aviation. At the same time, ability of airborne RAIM also requires enhancement to obtain high integrity performance. This paper proposes a flexible and easy-implementing multi-constellation RAIM algorithm based on airspace-ground cooperation. Supporting multi-constellation navigation, the proposed algorithm enables assessment of navigation measurement errors, and can provide multi-constellation RAIM availability for regional airspace to satisfy RNP for different phases of flight. To release calculation burden of aircraft, the algorithm is cascade implemented by three levels. Experiments were carried out for GPS/Beidou dual-constellation scenery. Compared with traditional RAIM, our algorithm performs superior with aspects of high failure detection probability, better integrity and availability.

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