山岭重丘区货车交通事故诱因识别与因素关联挖掘方法OACSCD
dentification of Causes and Factor Correlation Mining Methods for Truck Traffic Accidents in Mountainous Areas
针对货车交通事故诱因识别难、因素关联影响不清晰等问题,研究了山岭重丘区货车交通事故诱因识别与因素关联挖掘方法.收集了广东省某山岭重丘区货运高速公路1839起货车事故数据,通过数理统计方法,分析了山岭重丘区货车交通事故时空分布;基于改进的Apriori算法,挖掘了山岭重丘区货车交通事故影响因素的关联规则,得到全要素、自相关、特定维度(时间、道路要素)和事故维度之间共571条关联规则.关联挖掘模型评估结果表明:改进Apriori算法的准确性较传统Apriori算法提升了86.4%;关联规则挖掘结果显示:晴天、纵坡坡度小于2%与轻微事故关联的提升度大于1.0,即:轻微事故主要发生在该组合路段;操作不当、安全距离不足与侧翻和追尾事故的关联提升度大于1.8,即单车的侧翻和追尾主要由该因素导致;坡度-2%～-3%、半径大于1000m与重大事故关联的提升度大于1.6,即:重大、特大货车交通事故主要发生在坡度2%～3%、半径大于1000m的下坡路段;凌晨01:00-03:00与伤人事故的关联提升度大于1.3,即伤人事故主要集中在凌晨;研究结果揭示了山岭重丘区货车交通事故原因,发现了货车交通事故要素之间的关联性.
In response to the difficulties in identifying the causes of truck traffic accidents and the unclear influence of factors,a method for identifying the causes of truck traffic accidents and mining the relationships between factors in mountainous and hilly areas is studied.Data from 1,839 truck accidents on a freight expressway in a mountainous and hilly area of Guangdong Province are collected.Through mathematical statistical methods,the spatiotemporal distribution of truck traffic accidents in mountainous and hilly areas is analyzed.Employing an improved Apriori al-gorithm,the study mined association rules to uncover factors influencing truck traffic accidents,resulting in 571 rules across comprehensive,self-correlated,specific dimensions(time,road elements),and accident dimensions.The model evaluation results indicate that the accuracy of the improved Apriori algorithm is 86.4%higher than that of the traditional Apriori algorithm.The results of association rule mining reveal:Clear weather conditions and lon-gitudinal slopes less than 2%are significantly associated with minor accidents(lifted confidence>1.0),indicating that minor accidents primarily occur under these road conditions;Improper operation and insufficient safe distance are strongly associated with rollover and rear-end accidents(lifted confidence>1.8),suggesting that these accidents are predominantly caused by these factors;Slopes between-2%to-3%and radii greater than 1 000 m are signifi-cantly associated with major accidents(lifted confidence>1.6),indicating that major and severe truck accidents mainly occur on downhill sections with these slope and radius characteristics;Accidents causing injuries are signifi-cantly associated with the hours between 01:00 to 03:00 am(lifted confidence>1.3),highlighting a concentration of injury accidents during the early morning hours.The research results have revealed the causes of truck traffic acci-dents in mountainous and hilly areas and discovered the correlations among the elements of truck traffic accidents.
单东辉;刘贤勇;刘建蓓;杜豫川;屈秦洲
同济大学道路与交通工程教育部重点实验室,上海 201804||中交第一公路勘察设计研究院有限公司 西安 710065||交通安全应急保障技术交通运输行业研发中心 西安 710065中交第一公路勘察设计研究院有限公司 西安 710065||交通安全应急保障技术交通运输行业研发中心 西安 710065中交第一公路勘察设计研究院有限公司 西安 710065||交通安全应急保障技术交通运输行业研发中心 西安 710065同济大学道路与交通工程教育部重点实验室,上海 201804中交第一公路勘察设计研究院有限公司 西安 710065||交通安全应急保障技术交通运输行业研发中心 西安 710065
交通工程
交通安全货车交通事故关联挖掘方法Apriori算法山岭重丘区
traffic safetytuck accidentsassociation mining methodApriori algorithmmountainous Areas
《交通信息与安全》 2025 (5)
44-56,13
国家重点研发计划项目(2022YFC3002600)、陕西省重点研发计划项目(2024GX-ZDCYL-02-14)资助
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