基于人工势场引导进化算法的多飞行器冲突解脱方法
Multi-aircraft Conflict Resolution Method Based on Potential Field and Differential Evolution
多飞行器冲突解脱是保证空域安全的关键技术。经典的人工势场法可以实时提供冲突解脱方案,但是容易导致路径质量不高,甚至不可行。基于优化的方法虽然可以提高求解质量,但是一般难以满足实时性要求。因此为了实时获得满意的解脱方案,本文提出一个基于人工势场引导进化算法的多飞行器冲突解脱方法。即由人工势场法求解高质量初始解,并作为先验知识,然后运用微分进化算法进行优化,不但减少搜索空间,提高求解速度,同时由于高质量的先验知识引导寻优,可以进一步提高求解质量。通过经典场景验证,本文提出的方法在几秒种内可以解决最多16架飞行器的冲突。
ircraft conflict resolution is a key technology for ensuring airspace safety. The classical conflict resolution approach, potential field (PF), can provide conflict-free paths, but it may result in unfeasible paths. On the other hand, the methods based on evolutionary algorithm cannot get satisfying solution in real time. In order to overcome these drawbacks, we proposed an improved potential field method. The solution obtained by PF is as priori knowledge, based on which the differential evolution (DE) algorithm is adopted to further optimization. Our method not only can reduce the searching space and obtain solutions in real time, but also can improve the solution quality. The experimental studies on classic scenario proved the improved PF performed much better than PF. What's more, the proposed method can also solve the conflict up to 16 aircraft in a short time.
雷佳兴、管祥民、张学军
航空航空航天技术
交通信息工程及控制冲突解脱微分进化算法人工势场多飞行器
raffic information engineering and controlconflict resolutionDE algorithmpotential fieldmulti-aircraft
雷佳兴,管祥民,张学军.基于人工势场引导进化算法的多飞行器冲突解脱方法[EB/OL].(2013-08-05)[2025-08-02].http://www.paper.edu.cn/releasepaper/content/201308-40.点此复制
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