To address the current challenges of achieving optimality and computational efficiency in dynamic airspace route optimization for urban air mobility,as well as the inadequacy in addressing mixed urban and suburban operational scenarios,an innovative approach to constructing a combined urban-suburban network is initially proposed to support both urban and suburban operations seamlessly.Based on the flight dynamics model of electric vertical take-off and landing(eVTOL)aircraft,an accurate eVTOL power consumption model is developed to optimize flight paths.A Dynamically Weighted Routing Network(RSA-DWRN)algorithm for dynamic airspace is introduced by leveraging the Ripple Spreading Algorithm.With a combined urban-suburban network framework that incorporates time-varying airflow patterns and obstacle zones,the optimization performance of the RSA-DWRN's is compared against the traditional DPO-A*algorithm across five scenarios through 600 experiments,considering path power consumption,flight time,computation time,and matching degree as key metrics.Simulation results show that RSA-DWRN algorithm performs best under the four indexes,especially as the complexity of dynamic airspace environmental factors increases.In scenarios with moving obstacles,the DPO-A* algorithm fails to predict their trajectories and requires frequent updates to the network state,significantly increasing the computational cost of path planning.In contrast,the RSA-DWRN algorithm co-evolves with changes in the dynamic environment,finally obtaining optimal solutions that simultaneously ensure optimization results and computational efficiency.
关键词
航空运输/城郊结合路网/涟漪扩散算法/电动垂直起降飞行器/动态空域/路径优化
Key words
air transportation/combined urban-suburban network/ripple spreading algorithm/electric vertical take-off and landing aircraft/dynamic airspace/path optimization
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