Digital twinborn decision-making method for city-level low-altitude economy

By acquiring three-dimensional geographic information of the city and monitoring flight status in real time, and combining digital twin models to optimize landing points and path adjustments, the problem of insufficient adaptability and robustness of flight paths in traditional methods has been solved, realizing efficient, safe and energy-saving flight scheduling in urban-level low-altitude economy.

CN121115873APending Publication Date: 2025-12-12HUNAN LOW-ALTITUDE PILOT GENERAL AVIATION CO LTD
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Patent Information

Application Number
CN202511272618.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-09-08
Publication Date
2025-12-12

AI Technical Summary

Technical Problem

Traditional digital twin decision-making methods lack the ability to jointly model real-time weather, airspace dynamics, and time-varying building attributes in urban-level low-altitude economies, resulting in a lack of adaptability and robustness in flight paths and an inability to effectively handle real-time conflict prediction and dynamic adjustment in low-altitude traffic.

Method used

By acquiring three-dimensional geographic information of the city, determining the landing area using the three-dimensional outline of buildings, optimizing the landing point using a pre-trained digital twin model, and combining flight status monitoring and energy consumption analysis, the path is adjusted in real time to avoid strong winds and reverse flight sections, thus realizing multi-path generation and dynamic avoidance.

Benefits of technology

It improves the precision and dynamic response capability of urban airspace modeling, reduces the risk of flight conflicts, enhances the safety and timeliness of flight missions, optimizes power allocation and range management, and improves the stability and endurance efficiency of UAV operation.

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Abstract

The invention relates to the technical field of digital twinning, in particular to a digital twinning decision-making method for city-level low-altitude economy. The method comprises the following steps: acquiring three-dimensional geographic information of a city; detecting a building three-dimensional contour in the urban three-dimensional geographic information; determining a landing area by using the three-dimensional contour of the building; performing unmanned aerial vehicle landing point optimization on the landable area by adopting a pre-trained digital twin model to generate landing point data; unmanned aerial vehicle distribution task information is acquired; determining a first distribution path based on the unmanned aerial vehicle distribution task information and the landing point data; continuously monitoring the flight state of the unmanned aerial vehicle in the first distribution path; and detecting the energy consumption of the unmanned aerial vehicle based on the flight state, and if the energy consumption of the unmanned aerial vehicle is greater than a preset energy consumption threshold, determining that the flight state is abnormal. The stability and the energy efficiency utilization rate of unmanned aerial vehicle distribution are improved based on the digital twin technology.
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