王岩韬. 基于危险天气不确定性的最小风险路径规划方法[J]. 工程科学学报. DOI: 10.13374/j.issn2095-9389.2023.04.27.004
引用本文: 王岩韬. 基于危险天气不确定性的最小风险路径规划方法[J]. 工程科学学报. DOI: 10.13374/j.issn2095-9389.2023.04.27.004
Minimum-risk Path Planning based on Hazardous Weather Uncertainty[J]. Chinese Journal of Engineering. DOI: 10.13374/j.issn2095-9389.2023.04.27.004
Citation: Minimum-risk Path Planning based on Hazardous Weather Uncertainty[J]. Chinese Journal of Engineering. DOI: 10.13374/j.issn2095-9389.2023.04.27.004

基于危险天气不确定性的最小风险路径规划方法

Minimum-risk Path Planning based on Hazardous Weather Uncertainty

  • 摘要: 为降低飞行过程中遭遇危险天气的概率,同时避免大范围绕飞导致的路径与耗油增加,针对航路中的雷暴、积冰和颠簸天气,使用数值预报和概率预报,面向航前飞行计划,提出一种基于危险天气不确定性的最小风险路径规划方法。首先,基于概率预报数据使用配料法和C-F模型计算雷暴发生概率,基于数值预报数据计算积冰预测指数和颠簸预测指数;然后,融合多类型危险天气,提出一种具备风险标识的栅格化地图;在此基础上,改进传统路径最短的规划算法,构建以风险最小化为目标的Dijkstra和A*算法;最后,使用2023年4月3日华中地区强对流天气预测数据建立风险地图,使用上述改进算法与传统Dijkstra、A*和RRT算法进行路径规划并对比分析。结果表明,传统Dijkstra和A*算法可计算得到最短飞行路径,而改进的A*算法可计算得到总风险最小路径;若综合考虑飞行风险与路径长度,改进的Dijkstra算法最为适合。

     

    Abstract: Hazardous weather such as thunderstorm, icing and turbulence is one of the main reasons for flight accidents. In order to avoid possible risk caused by temporary diversion of hazardous weather during the flight, numerical and probabilistic forecasting are used to predict enroute hazardous weather at the flight planning level. And considering the uncertainty of hazardous weather, a flight path planning method for uncertain weather is proposed, which can ensure flight operation safety to the greatest extent. Firstly, based on the probabilistic meteorological forecast data, the mapping relationship between the diagnostic elements of thunderstorms and the occurrence probability of thunderstorms is established by the mean of ingredients-based methodology from the perspective of the three occurrence conditions of thunderstorms, the water vapor condition, the instability condition and the lifting trigger condition. Then the C-F model is used to fuse the probability data of thunderstorm diagnostic elements, so that the probability of thunderstorms can be calculated and the thunderstorm area map has been set up. After that icing prediction index and turbulence prediction index are calculated based on numerical prediction data, and icing and turbulence regions were defined. Then a rasterized map that can identify the risk of hazardous weather is constructed by integrating the thunderstorms, icing and turbulence regions. On this basis, the traditional path planning algorithm is improved to maximize the flying safety, and a risk minimization Dijkstra algorithm and a risk minimization A* algorithm are proposed. Finally, by using the forecast data of a severe convective weather in Central China on April 3, 2023, a real risk map is established. Based on the map the improved risk minimization algorithms and traditional algorithms are used for path planning respectively, and the total risk and path length of each planned path are calculated for finding the minimum-risk path. The results show that the total risk of the path under risk minimization A* algorithm is minimum, the path length under traditional algorithm is minimum, and the comprehensive performance of risk minimization Dijkstra algorithm is the best. Therefore, if the flight risk is expected to be minimized, the flight path based on the risk minimization A* algorithm should be selected because the safety of that path is the highest. When the path length and risk are considered comprehensively, the flight path under the risk minimization Dijkstra algorithm can be chosen because compared with the risk minimization A* algorithm, this scheme is more economical.

     

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