摘要
为识别和控制气象条件对交通阻断的影响及程度,运用数据挖掘中的k-means聚类算法和风险管理中的风险矩阵法(RM),构建能够全面反映不同气象条件对交通阻断影响程度的综合评估模型。基于2018年~2019年江苏省42个公路管理处的交通阻断数据进行实证研究发现,在各种气象因素中,雾霾对交通阻断的影响最严重,体现在发生概率高,影响里程数大;降雪(积雪)和结冰的影响次之,产生的严重度中等且发生时间主要集中于全年第一、四季度;降雨(积水)相较于前几种因素影响较小,主要发生在第二、三季度;大风(横风)的影响程度最小,部分高速公路在第三季度还会受到台风天气的影响,尽管发生概率不高,但影响却不容忽视。因此,江苏省气象和交通部门应以此做好事前预防和事后处理工作。
In order to identify and control the impact and degree of meteorological conditions on traffic congestion,the k-means clustering algorithm in data exploring and the risk matrix method(RM)in risk management are used to construct a comprehensive evaluation model that can comprehensively reflect the impact of different meteorological conditions on traffic congestion.Based on the traffic blocking data of 42 highway management offices in Jiangsu Province from 2018 to 2019,it is found through the empirical study that among various meteorological factors,haze has the most serious impact on traffic blocking,which is expressed by the high probability of occurrence and long mileage.The impact of snowfall(accumulated snow)and icing is secondary,and the severity is medium and the occurrence time is mainly concentrated in the first and fourth quarter of the year.Rainfall(waterlogging)has less influence compared with the previous factors,mainly in the second and third quarters.The influence of gale(crosswind)is the smallest,and some highways are also affected by typhoon weather in the third quarter.Although the probability of occurrence is low,the influence cannot be ignored.Therefore,the meteorological and transportation departments in Jiangsu Province should be well prepared for prevention and post-processing.
作者
崔海蓉
费金峰
田华
周林义
CUI Hai-rong;FEI Jin-feng;TIAN Hua;ZHOU Lin-yi(School of Management Science and Engineering,Nanjing University of Information Science and Technology,Nanjing 210044,China;CMA Public Meteorological Service Centre,Beijing 100081,China;Jiangsu Institute of Meteorological Sciences,Nanjing 210009,China)
出处
《公路》
北大核心
2021年第11期227-233,共7页
Highway
基金
中国气象局公共气象服务中心项目,项目编号M2020029
江苏高校品牌专业建设工程资助项目,项目编号PPZY2015A072
江苏省高校哲学社会科学基金项目,项目编号2019SJA0153。
关键词
交通阻断
数据挖掘
聚类分析
风险矩阵
气象
traffic blocking
data explore
cluster analysis
risk matrix
meteorology
