Low-altitude aircraft green route planning method and system based on digital twinning

CN122062706BActive Publication Date: 2026-07-03URBAN PLANNING & DESIGN INST OF SHENZHEN UPDIS

Patent Information

Authority / Receiving Office: CN · China
Patent Type: Patents(China)
Current Assignee / Owner: URBAN PLANNING & DESIGN INST OF SHENZHEN UPDIS
Filing Date: 2026-04-21
Publication Date: 2026-07-03

AI Technical Summary

Technical Problem

Existing low-altitude aircraft route planning technologies fail to effectively integrate real-time meteorological data with aircraft energy consumption characteristics, resulting in insufficient accuracy in energy consumption and carbon emission accounting. This makes it difficult to achieve dynamic low-carbon optimization and adapt to changes in the low-altitude environment. Furthermore, the lack of a virtual-real linkage calibration mechanism affects the reliability and greenness of route planning.

Method used

A dual twin system of airspace and aircraft is constructed. Virtual and real linkage calibration is performed through test data of physical aircraft. Combined with multi-objective optimization algorithms, the optimal pre-planned route that meets the objectives of safety, timeliness and low carbon is generated, realizing full-process simulation and accurate energy consumption and carbon emission accounting.

Benefits of technology

It has enabled more refined and greener route planning for low-altitude aircraft, improved the intelligence level of route planning, adapted to the dynamic changes in the low-altitude environment, and ensured safe, efficient, and low-carbon operation.

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Abstract

The present application relates to the technical field of artificial intelligence, in particular to a low-altitude aircraft green route planning method and system based on digital twinning, the method comprising: collecting airspace environment, aircraft state, and task demand parameters containing take-off and landing point information and low-carbon target threshold, and preprocessing to obtain a standardized data set; obtaining entity aircraft test data, combining the standardized data to construct airspace and aircraft digital twins, and obtaining a state bidirectional mapping double twin through virtual-real linkage calibration; generating a safety constraint candidate route based on the double twin and the take-off and landing point information, calling a dynamic weight allocation rule to determine the weight proportion of safety, timeliness and low-carbon target; driving the double twin to simulate and deduce the candidate route, accounting for the segmented energy consumption and total carbon emissions, and selecting the optimal pre-planned route meeting multiple constraints through a multi-objective optimization algorithm. The present application relies on digital twinning to realize precise low-carbon constraints, and improves the green and intelligent level of route planning.

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