Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/146675
Title: Multiple air route crossing waypoints optimization via artificial potential field method
Authors: Pang, Bizhao
Dai, Wei
Hu, Xinting
Dai, Fuqing
Low, Kin Huat
Keywords: Engineering::Aeronautical engineering
Issue Date: 2021
Source: Pang, B., Dai, W., Hu, X., Dai, F., & Low, K. H. (2021). Multiple air route crossing waypoints optimization via artificial potential field method. Chinese Journal of Aeronautics, 34(4), 279-292. doi:10.1016/j.cja.2020.10.008
Journal: Chinese Journal of Aeronautics 
Abstract: Air route crossing waypoint optimization is one of the effective ways to improve airspace utilization, capacity and resilience in dealing with air traffic congestion and delay. However, research is lacking on the optimization of multiple Crossing Waypoints (CWPs) in the fragmented airspace separated by Prohibited, Restricted and Dangerous areas (PRDs). To tackle this issue, this paper proposes an Artificial Potential Field (APF) model considering attractive forces produced by the optimal routes and repulsive forces generated by obstacles. An optimization framework based on the APF model is proposed to optimize the different airspace topologies varying the number of CWPs, air route segments, and PRDs. Based on the framework, an adaptive method is developed to dynamically control the optimization process in minimizing the total air route cost. The proposed model is applied to busy controlled airspace. And the obtained results show that after optimization the safety-related indicators: conflict number and controller workload reduced by 7.75% and 6.51% respectively. As for the cost-effectiveness indicators: total route length, total air route cost and non-linear coefficient, declined by 1.74%, 3.13% and 1.70% respectively. While the predictability indicator, total flight delay, saw a notable reduction by 7.96%. The proposed framework and methodology can also provide an insight in the understanding of the optimization to other network systems.
URI: https://hdl.handle.net/10356/146675
ISSN: 1000-9361
DOI: 10.1016/j.cja.2020.10.008
Rights: © 2020 Production and hosting by Elsevier Ltd. on behalf of Chinese Society of Aeronautics and Astronautics.This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ATMRI Journal Articles

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