A 4D-trajectory planning method based on hybrid optimization strategy for demand and capacity balancing
| dc.contributor.author | Chen, Yutong | |
| dc.contributor.author | Xu, Yan | |
| dc.contributor.author | Hu, Minghua | |
| dc.contributor.author | Huang, Fei | |
| dc.contributor.author | Nie, Qi | |
| dc.date.accessioned | 2022-01-18T14:03:37Z | |
| dc.date.available | 2022-01-18T14:03:37Z | |
| dc.date.issued | 2021-11-15 | |
| dc.description.abstract | To effectively solve the Demand and Capacity Balancing (DCB) in future Trajectory-Based Operation (TBO) scenarios, this article first proposes a pre-tactical-and-tactical integrated Four-Dimensional Trajectory (4DT) planning framework. The framework decomposes large-scale 4DT planning into two stages, namely, the General 4DT (G4DT) planning in the pre-tactical stage and the Special 4DT (S4DT) planning in the tactical stage. A Hybrid Optimization Strategy (HOS) based planning method is designed for G4DT planning. In this method, the sequential decision architecture based on time window, heuristic strategy (greedy strategy) and optimization algorithm are combined to realize the fast trajectory planning of large-scale flights. In the optimization model based on continuous time, the nonlinear model is transformed into a linear model by constructing the flight conflict correlation matrix, which greatly improves the solving speed of the model. Real flight schedule data for French and Spanish airspace were used to verify the effectiveness and efficiency of the HOS method. This method is compared with Computer-Assisted Slot Allocation (CASA). The results show that the proposed method can effectively reduce the flight delay time and improve the flight on-time rate. Due to its fast operation speed, the proposed method has great potential to dynamically update the planning results according to the real-time air space operation status in actual operation. | en_UK |
| dc.identifier.citation | Chen Y, Xu Y, Hu M, et al., (2021) A 4D-trajectory planning method based on hybrid optimization strategy for demand and capacity balancing. In: 2021 AIAA/IEEE 40th Digital Avionics Systems Conference (DASC), 3-7 October 2021, San Antonio, USA | en_UK |
| dc.identifier.eisbn | 978-1-6654-3420-1 | |
| dc.identifier.issn | 2155-7209 | |
| dc.identifier.uri | http://doi.org/10.1109/DASC52595.2021.9594296 | |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/17427 | |
| dc.language.iso | en | en_UK |
| dc.publisher | IEEE | en_UK |
| dc.rights | Attribution-NonCommercial 4.0 International | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | * |
| dc.subject | trajectory-based operation | en_UK |
| dc.subject | demand and capacity balancing | en_UK |
| dc.subject | hybrid optimization strategy | en_UK |
| dc.subject | time window | en_UK |
| dc.subject | sequential decision | en_UK |
| dc.title | A 4D-trajectory planning method based on hybrid optimization strategy for demand and capacity balancing | en_UK |
| dc.type | Conference paper | en_UK |