Reroute Optimization Based on Route Segment Availability Under Convective Weather

Abstract

With the rapid growth of global traffic flow, the flight anomalies caused by convective weather are becoming worse. More efficient traffic control measures can be implemented to improve airspace’s effective utilization and reduce the resulting ground and air waiting times if reroute optimization during cruise under convective weather can be realized before taking off. Based on vertical integrated liquid water, echo top, and flight altitude, this paper establishes a three-dimensional deviation probability distribution and defines a method of segment availability and capacity in convective weather. The optimization algorithms named Floyd, Rapidly-exploring Random Tree Star (RRT*), and informed-Rapidly-exploring Random Tree Star (Informed-RRT*) are used to minimize reroute distances. The deviation probability distribution is established based on 6146 historical flights under convective weather from 11 to 20 August 2018 in some upper area control centers under the administration of central and southern air traffic management bureaus. The Floyd and informed-RRT* algorithms are compared for reroute optimization for several flights in a given scenario. Based on the time to compute optimized reroutes and the quality of the reroute results, the Floyd algorithm is shown to provide the best rerouting optimization.