Transactions of Nanjing University of Aeronautics & Astronautics
Air Route Network Planning Based on Improved Cellular Automata Algorithm
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Abstract:
In order to optimize airspace resources and reduce operational costs， this paper investigates the air route network planning problem considering the avoidance of prohibited， restricted， and danger zones （PRDs）. Firstly， the airspace is discretized using the grid method， and the airspace information is binarized to enable the avoidance of these three zones. Then， a mathematical model is established with the objective of minimizing the total route length， considering factors such as nonlinear coefficient and flow constraints. The pathfinding process incorporates distance priority coefficients and collision risk coefficients， and the cellular automata algorithm is employed to solve the problem. Additionally， the results are further smoothed to obtain the shortest path. Finally， a case study is conducted using the air route network planning of Guangzhou FIR for verification. The results demonstrate that， compared to the current routes， the proposed approach effectively reduces the route length， decreases the number of waypoints， and lowers the nonlinear coefficient of the routes. These findings highlight the effectiveness of the improved cellular automata algorithm， which has important implications for real-world air route network planning.
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Project Supported:
The work was supported by the Foundation of Graduate Innovation Center in Nanjing University of Aeronautics and Astronautics（No. xcxjh20220735）.
Clc Number:
V355
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