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Extracting multi-objective multigraph features for the shortest path cost prediction:Statistics-based or learning-based?

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Green Energy and Intelligent Transportation 2024年第1期3卷 1-15页

作者： Songwei Liu Xinwei Wang michal weiszer Jun Chen School of Engineering and Materials Science Queen Mary University of LondonMile End RoadLondon E14NSUnited Kingdom

Efficient airport airside ground movement(AAGM)is key to successful operations of urban air *** studies have introduced the use of multi-objective multigraphs(MOMGs)as the conceptual prototype to formulate *** calculation of the shortest path costs is crucial for the algorithmic heuristic search on MOMGs,however,previous work chiefly focused on single-objective simple graphs(SOSGs),treated cost enquires as search problems,and failed to keep a low level of computational time and storage *** paper concentrates on the conceptual prototype MOMG,and investigates its node feature extraction,which lays the foundation for efficient prediction of shortest path *** extraction methods are implemented and compared:a statistics-based method that summarises 22 node physical patterns from graph theory principles,and a learning-based method that employs node embedding technique to encode graph structures into a discriminative vector *** former method can effectively evaluate the node physical patterns and reveals their individual importance for distance prediction,while the latter provides novel practices on processing multigraphs for node embedding algorithms that can merely handle *** regression models are applied to predict the shortest path costs to demonstrate the performance of *** experiments on randomly generated benchmark MOMGs show that(i)the statistics-based method underperforms on characterising small distance values due to severe overestimation;(ii)A subset of essential physical patterns can achieve comparable or slightly better prediction accuracy than that based on a complete set of patterns;and(iii)the learning-based method consistently outperforms the statistics-based method,while maintaining a competitive level of computational complexity.

关键词： Multi-objective multigraph Feature extraction Shortest path cost prediction Node patterns Node embeddings Regression

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A large-scale multi-objective flights conflict avoidance approach supporting 4D trajectory operation

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Science China(Information Sciences) 2017年第11期60卷 198-210页

作者： Xiangmin GUAN Xuejun ZHANG Renli LV Jun CHEN weiszer michal Department of General Aviation Civil Aviation Management Institute of China School of Electronic and Information Engineering Beihang University School of Engineering University of Lincoln

Recently, the long-term conflict avoidance approaches based on large-scale flights scheduling have attracted much attention due to their ability to provide solutions from a global point of view. However, current approaches which focus only on a single objective with the aim of minimizing the total delay and the number of conflicts, cannot provide controllers with variety of optional solutions, representing different tradeoffs. Furthermore, the flight track error is often overlooked in the current research. Therefore, in order to make the model more realistic, in this paper, we formulate the long-term conflict avoidance problem as a multi-objective optimization problem, which minimizes the total delay and reduces the number of conflicts simultaneously. As a complex air route network needs to accommodate thousands of flights, the problem is a large-scale combinatorial optimization problem with tightly coupled variables, which make the problem difficult to deal with. Hence,in order to further improve the search capability of the solution algorithm, a cooperative co-evolution(CC)algorithm is also introduced to divide the complex problem into several low dimensional sub-problems which are easier to solve. Moreover, a dynamic grouping strategy based on the conflict detection is proposed to improve the optimization efficiency and to avoid premature convergence. The well-known multi-objective evolutionary algorithm based on decomposition(MOEA/D) is then employed to tackle each sub-problem. Computational results using real traffic data from the Chinese air route network demonstrate that the proposed approach obtained better non-dominated solutions in a more effective manner than the existing approaches, including the multi-objective genetic algorithm(MOGA), NSGAII, and MOEA/D. The results also show that our approach provided satisfactory solutions for controllers from a practical point of view.

关键词： air traffic management conflict avoidance combinatorial optimization multi-objective coopera tive co-evolution

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

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Engineering 2021年第4期7卷 495-506页

作者： Olusayo Obajemu Mahdi Mahfouf Lohithaksha M.Maiyar Abrar Al-Hzndi michal weiszer Jun Chen Department of Automatic Control and Systems Engineering The University of SheffieldSheffield S14DWUK Business and Management Research Institute University of BedfordshireLuton LU13JUUK School of Engineering and Materials Science Queen Mary University of LondonLondon E14NSUK

Aircraft ground movement plays a key role in improving airport efficiency,as it acts as a link to all other ground *** novel approaches to coordinate the movements of a fleet of aircraft at an airport in order to improve system resilience to disruptions with increasing autonomy is at the center of many key studies for airport airside ***,autonomous taxiing is envisioned as a key component in future digitalized ***,state-of-the-art routing and scheduling algorithms for airport ground movements do not consider high-fidelity aircraft models at both the proactive and reactive planning *** majority of such algorithms do not actively seek to optimize fuel efficiency and reduce harmful greenhouse gas *** paper proposes a new approach for generating efficient four-dimensional trajectories(4DTs)on the basis of a high-fidelity aircraft model and gainscheduling control *** in conjunction with a routing and scheduling algorithm that determines the taxi route,waypoints,and time deadlines,the proposed approach generates fuel-efficient 4DTs in real time,while respecting operational *** proposed approach can be used in two contexts:①as a reactive decision support tool to generate new trajectories that can resolve unprecedented events;and②as an autopilot system for both partial and fully autonomous *** proposed methodology is realistic and simple to ***,simulation studies show that the proposed approach is capable of providing an up to 11%reduction in the fuel consumed during the taxiing of a large Boeing 747-100 jumbo jet.

关键词： Aircraft model Intelligent taxiing Optimization Four-dimensional trajectory

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