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In response to the current inadequacies in quantitative assessment methodologies for runway incursion risks, which hinder the accurate identification of high-risk segments in airport operational management and contribute to frequent safety incidents and operational efficiency constraints, this study proposes an integrated cloud model framework based on integrated weighting principles for refined risk identification. By systematically applying the Latent Dirichlet Allocation(LDA) topic modeling technique, thematic elements and relevant keywords were extracted from a comprehensive collection of 122 global runway incursion accident investigation reports spanning the past two decades. The derived thematic content underwent rigorous validation by a panel of aviation safety experts, ultimately establishing a well-structured runway incursion risk indicator system comprising four primary indicators—human factors, communication failures, airport environment, and management factors—along with 24 carefully defined secondary indicators. Regarding the weighting methodology, an improved Analytic Hierarchy Process(AHP) was employed to calculate subjective weights for each indicator, while the Kendall concordance coefficient was utilized to verify the reliability of these weight assignments. Simultaneously, the enhanced entropy weight method was implemented to derive objective weights based on data characteristics. Through the application of game theory principles, the final combined weights were determined to be 0.153 for subjective dimensions and 0.847 for objective dimensions, respectively. The validity of these final indicator weights was further confirmed through both additive and multiplicative combinatorial weighting approaches. Utilizing the cloud model as the theoretical foundation for risk quantification, empirical data from four representative Chinese airports were selected for comprehensive model validation: a 4E-category airport in North China, a 4F-category airport in East China, a 4C-category airport in Southwest China, and a 3C-category airport in Northwest China. The validation results demonstrated risk level assessments of medium-high(0.665), medium-low(0.553), medium-low(0.715), and medium-high(0.628), respectively, showing strong alignment with actual operational conditions. Furthermore, the model exhibited satisfactory stability under various parameter variations, providing valuable practical references for targeted improvements in specific risk factors across different airport environments, ultimately contributing to the effective reduction of runway incursion risks.
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Basic Information:
DOI：10.13637/j.issn.1009-6094.2025.1533
China Classification Code:V328;V355
Citation Information:
[1]Zhang Yuhui,Sun Zeyuan,Liao Shujiao.Research on a cloud model for assessing airport runway incursion risk using integrated weighting[J].Journal of Safety and Environment,2026,26(08):2959-2968.DOI:10.13637/j.issn.1009-6094.2025.1533.
Fund Information:
中央高校基本科研基金项目(3122025103)
2026-06-02
2026-06-02
2026-06-02