徐金华;李岩;张玉婷;

• 1:长安大学运输工程学院

摘要(Abstract)：

为探究平面交叉口不同严重程度交通事故影响因素的关联特性，从驾驶人、环境、道路、车辆4个维度出发，建立了带约束的二进制粒子群-蚁群算法以挖掘交叉口事故严重程度的关联规则。首先通过二进制粒子群算法确定最优提升度和支持度阈值，再利用蚁群算法挖掘最大频繁项集，并增加规则前项与后项的约束，以提高关联规则挖掘效率。对2 022条平面交叉口事故数据的分析结果表明，提出的BPSO-ACA算法可在精准识别潜在因素与事故等级关联结果的基础上减少冗余无效关联规则，并将规则挖掘效率提升17%～29%。驾驶人年龄、分心状态、交叉口形态、交叉口车道数和天气均与交叉口事故严重程度有强关联性；车道数少是导致轻微事故升级为一般事故的重要因素；路面湿滑是导致交叉口事故升级为重大事故的关键因素，尤其在雨雪雾等不良天气条件下，机非事故为重大等级的可能性最高。研究成果可为交通管理部门的主动防控措施提供理论指导，减少交叉口事故数量及降低事故严重程度。

关键词(KeyWords)： 安全工程;事故严重程度;关联规则;致因分析;二进制粒子群;蚁群算法;交叉口

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(71901036);; 国家重点研发计划项目(2017YFC0803906);; 陕西省自然科学基金项目(2020JM-222,2020JM-237)

作者(Authors): 徐金华;李岩;张玉婷;

DOI: 10.13637/j.issn.1009-6094.2021.1553

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