夏敏洁,曹杰,周文君.气象条件与南京地区道路交通事故量的分析.气象科学,,(): XIA Minjie,CAO Jie,ZHOU Wenjun.Analysis on relation between meteorological condition and road traffic accident in Nanjing.Journal of the Meteorological Sciences,,():
气象条件与南京地区道路交通事故量的分析
Analysis on relation between meteorological condition and road traffic accident in Nanjing
投稿时间:2013-10-17  修订日期:2013-12-02
DOI:10.3969/2014jms.0002
中文关键词:  交通气象  自回归模型  拟合优度
英文关键词:Traffic meteorology  Automatic regression model  Goodness of fitting
基金项目:公益性行业(气象)科研专项 (GYHY201106019,GYHY201306043)
作者单位E-mail
夏敏洁 南京信息工程大学, 南京 210044  
曹杰 南京信息工程大学, 南京 210044 cj@nuist.edu.cn 
周文君 盐城市气象局, 江苏 盐城 224000  
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中文摘要:
      用南京地区2012年逐日交通事故数据和实测气象资料,在考虑自相关性的前提下,通过多因子时间序列分析,构建南京地区2012年道路日交通事故量的AR气象影响模型,对工作日和非工作日分别分析发现:不利气象条件与日交通事故量,工作日比非工作日相关显著;降水、低温、低能见度等都与交通事故显著相关,中雨以下日降水量与日交通事故量呈正相关,日平均气温在2~12 ℃、日最低能见度在200~500 m范围内,都与日交通事故量呈显著负相关;但大的降水、极端气温、低能见度与发生交通事故的相关性反而减小。又根据不同气象要素在日交通事故量中的作用大小,构建气象影响逐步线性回归模型;最后比较两种模型的优劣,拟合优度分析显示,工作日期间AR模型的拟合效果比逐步回归模型更好。
英文摘要:
      Based on the daily traffic accidents data and the observed meteorological data in Nanjing region in 2012, the automatic regression (AR) model of the daily traffic accidents amount was established by multi-factor time series ahalysis under consideration of autocorrelation. Analysis on the data of weekdays and weekends showed that the relationship between adverse weather condition and daily traffic accident amount was more significant in weekdays. Precipitation, low temperature, low visibility were significantly correlated with the traffic accident. Daily precipitation below moderate intensity was positively related with daily traffic accident amount. The temperature between 2-12 ℃ and the minimum visibility between 200-500 m were negatively correlated with daily traffic accident amount. However, the larger precipitation intensity, the lower temperature and the minimum visibility were all slightly correlated with daily traffic accident amount. Furthermore, a stepwise regression (SR) model was established on the basis of different influence of meteorological factors on the daily traffic accident amount. Lastly, the performance and results of the test of goodness of fitting were compared between these two models, showing the AR model performs better than the SR model in weekdays.
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