| 摘要: |
| 为研究气象要素对城区交通安全的影响，选取发生在南充市城区2010年1月—2018年12月期间共3 287 d的2 602起伤亡交通事故作为分析样本，将其分为汛期和非汛期，并分别将气象信息进行因子分析，用因子作为自变量，建立汛期和非汛期的引发伤亡交通事故的概率模型。通过检验可知，非汛期的准确率为77.8%，汛期的准确率为63.8%，降雨因子全年都有影响，对交通安全的影响都是最大的。在汛期里，相对湿度增大容易增加交通安全的风险；高温天气减小伤亡交通事故发生的概率；在非汛期里，风力因子极易影响伤亡交通事故的发生，湿度因子次之，紧接着是能见度因子，日照因子，最后是温度因子。相较于汛期，非汛期的气象要素对伤亡交通事故的影响更加显著。 |
| 关键词: 气象要素；交通安全；伤亡交通事故；因子分析；概率模型 |
| DOI： |
| 投稿时间：2019-11-30 |
| 基金项目:高原与盆地暴雨旱涝灾害四川省重点实验室科技发展基金项目（SCQXKJZD2019004）：基于地理网格的高速公路气象服务系统研究 |
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| A Meteorological Probability Model of Traffic Accidents with Casualties in Urban Areas of Nanchong |
| LI Meng,LU Dequan,ZHOU Ziqin,SUN Leiguo,LIU Shuhui |
| (Nanchong Meteorological Bureau of Sichuan Province,Nanchong 637000 , China ;Key Laboratory of Rainstorm Drought and Flood Disaster in Plateau and Basin of Sichuan Province, Chengdu 610072 , China) |
| Abstract: |
| To study the effect of meteorological factors on urban traffic safety, a total of 2,602 traffic accidents with casualties occurring in the urban area of Nanchong City from January 2010 to December 2018 with 3 287 d were selected as the analysis samples, which were divided into flood season and non-flood season. The meteorological information was used for factor analysis respectively, and the factors were used as independent variables to establish the probability model of casualties traffic accidents caused in flood season and non-flood season. According to the test, the accuracy rate of non-flood season is 77.8%, and the accuracy rate of flood season is 63.8%. The rainfall factor has an impact throughout the year, which has the largest impact on traffic safety.In flood season, the increase of relative humidity is easy to increase the risk of traffic safety;High temperature weather reduces the probability of fatal traffic accidents;In the non-flood season, wind force factor is very likely to affect the occurrence of traffic accidents, followed by humidity factor, visibility factor, sunshine factor, and finally temperature factor.Compared with the flood season, meteorological factors in non-flood season have a more significant impact on traffic accidents. |
| Key words: meteorological elements；traffic safety；traffic accidents involving casualties；factor analysis；probability model |
