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.
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 estab- lished by multi-factor time series analysis, taking autocorrelation into consideration. Analysis on the data of weekdays and weekends showed that the relationship between adverse weather condition and daily traf- fic accident amount in weekdays was more significant than it was in weakends. Precipitation, low temper- ature, low visibility were significantly correlated with the traffic accident. Daily precipitation below mod- erate intensity was positively related with daily traffic accident amount. The temperature between 2-12 ~C and the minimum visibility between 200-500 m were negatively correlated with daily traffic accident a- mount. 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 influences of meteorological factors on the daily traffic accident a- mount. Finally, the performance and results by the test of fitting goodness were compared between these two models, showing the AR model performs better than the SR model in weekdays.
出处
《气象科学》
CSCD
北大核心
2014年第3期305-309,共5页
Journal of the Meteorological Sciences
关键词
交通气象
自回归模型
拟合优度
Traffic meteorology
Automatic regression model
Goodness of fitting
