A Low-Altitude Air Route Network Planning Method Based on Combinatorial Clustering

The structured and networked planning of urban low-altitude air routes is an effective approach to alleviating the shortage of low-altitude airspace resources and ensuring operational safety. Considering the actual requirements of route deployment and traffic flow in urban low-altitude logistics scenarios, this paper proposes a low-altitude “trunk-feeder” route network planning method based on combined clustering, with the layout of takeoff and landing sites and actual operational traffic volumes as input conditions. Initially, the optimal orientation of trunk route was determined using principal component analysis (PCA) and numerical optimization, respectively. Meanwhile, the quality of the clustering results was evaluated using a Gaussian distribution model and a geometric similarity model, and four differentiated route network clustering schemes were constructed. Secondly, a comprehensive evaluation system encompassing the total route network length, construction costs, and route intersection points was established to assess the performance of the four clustering methods. Finally, the feasibility and effectiveness of the method were validated using Shaoxing City as a case study. The results show that, compared with the initial planning scheme, the total construction cost of the route network decreases by 21.39% and the number of route intersections decreases by 34.41% under the high-density scenario. Under the medium-density scenario, the total construction cost decreases by 36.44% and the number of route intersections decreases by 16.92%. The findings indicate that the proposed “principal component analysis-geometric similarity” combined clustering method adopted in this paper can significantly improve the safety and cost-effectiveness of low-altitude operations, and can provide theoretical foundations and technical support for the scientific planning of urban low-altitude traffic systems.