Conflict detection and resolution method for complex airport scene based on path dynamic grouping

Abstract

The present invention provides a complex airport scene conflict detection and relief method based on path dynamic grouping. The method combines the actual scene conflict detection and relief process to realize the scene taxiing simulation of incoming and outgoing flights, including the dynamic grouping of taxiing paths. The division of the taxiing process; the simulation logic based on "timing-point-sequence" embodies the abstraction of the objective operating process; the conflict detection and resolution based on path grouping realizes the identification and resolution of conflicts between groups first and then within groups avoidance mechanism. The algorithm is close to the actual control purpose, and can realize simulation deduction based on business requirements, so that the results are authentic and credible.

Description

technical field [0001] The invention relates to a complex airport scene conflict detection and relief method based on path dynamic grouping. Background technique [0002] As a basic technology, computer simulation technology is widely used in aviation subdivision fields such as flight path planning, program decision-making, capacity evaluation, and flow management. Efficient and detailed simulation algorithms can be used in planning and design, rehearsal demonstration, technical verification, and decision-making implementation Its research can effectively enhance and improve decision-making methods at all stages of operation. In recent years, with the continuous development of the air transport industry, the scale and complexity of airports have continued to increase, and the model of using computer simulation to measure the operational efficiency of airports has received widespread attention. Most of the current research usually aims at the local operation optimization of ...

AI Technical Summary

Problems solved by technology

Most of the current research usually aims at the local operation optimization of the scene, focusing on path planning and strategic-level conflict detection and resolution. Generally, ant colony algorithm, A* algorithm, etc. are used. Identification and elimination, but at the same time, the calculation results are relatively theoretical, the degree of execution is not high, and they do not have the ability to detect and eliminate in real time

In addition, most studies are often only aimed at airports with a small number of flights, and do not consider the operation simulation of complex airports and large flight flow conditions. plays a vital role

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