Journals
  Publication Years
  Keywords
Search within results Open Search
Please wait a minute...
For Selected: Toggle Thumbnails
Study of Quantitative Relationship Between Highway Traffic Accidents and Meteorological Conditions in Hebei Province
QU Xiaoli, LIU Huayue, QI Yuchao, FU Guiqin, ZHANG Di, WANG Jie
Journal of Arid Meteorology    2020, 38 (1): 169-175.  
Abstract298)      PDF(pc) (1149KB)(1509)       Save
Based on traffic accidents and meteorological observation data from December 2015 to November 2018 in Hebei Province, the quantitative relationship between highway traffic accidents and meteorological conditions was analyzed. The highway traffic accidents happened more in summer and autumn than in spring and winter, and they happened more in the daytime than during nighttime. The peak value appeared in August and October, and it appeared during 09:00-11:00 and 14:00-17:00. Highway traffic accidents in Gaocheng of Shijiazhuang and Fengnan of Tangshan occurred most. Take the case of Shijiazhuang area, the response of the relative risk RR of highway traffic accidents to different meteorological elements was analyzed using the Spearman rank correlation and curve fitting method, it was found that there was a significant threshold effect of temperature on the frequency of highway traffic accidents, and the threshold of daily average temperature, the daily maximum temperature and daily minimum temperature  were 20 ℃, 25 ℃ and 15 ℃, respectively. When the daily minimum relative humidity exceeded 80%, the relative risk of accident increased by 3.77% for every 1% increase of relative humidity. When the maximum rain intensity increased 10 mm·h-1, the accident risk increased by 18.8%. When the visibility was less than 1000 meters, the risk of highway traffic accident decreased by 4.14% with the increase of 100 meters in the visibility.


Related Articles | Metrics
An Approaching Prediction Method of Road Surface Temperature of Winter Olympic Highway Demonstration Station Based on METRo Model 
QU Xiaoli, QI Yuchao, YOU Qi, WANG Yuefeng, WU Dan, LI Meiqi
Journal of Arid Meteorology    2020, 38 (03): 497-503.  
Abstract251)      PDF(pc) (1805KB)(1399)       Save
The method of road surface temperature prediction for 2022 winter Olympic demonstration station (Beijing Huilongguan station) was discussed based on the METRo model. The artificial thermal parameters of iterative training fitting with a large number of sample data were added to the METRo model as the leading parameters in order to reduce the systematic error of the METRo model and the influence of human production and life on road surface temperature prediction. The results are as follows: (1) After introduction of artificial heat parameters, the simulation ability of the METRo model was improved significantly , especially at night, the root mean square error of road surface temperature prediction could be controlled at about 1 ℃. (2) The effect of artificial heat on road surface temperature presented negative feedback during daytime and positive feedback at night. (3) The simulated road surface temperature still had some errors due to influence of limitation of radiation prediction ability of meteorological models. In the mass, it was feasible to simulate the road surface temperature, especially for low temperature of road surface at the winter Olympic expressway demonstration station by using the METRo model with pre-set anthropogenic thermal parameters, which could support the prediction and early warning ability of highway road surface temperature and road icing in winter.
Related Articles | Metrics
Forecasting Method on Integrated Risk Level of Traffic Condition Based on Weather Conditions for Highway of Hebei Province
QU Xiaoli, ZHANG Di, GUO Rui, QI Yuchao, ZHAO Zengbao, WU Dan
Journal of Arid Meteorology    2019, 37 (2): 345-350.   DOI: 10.11755/j.issn.1006-7639(2019)-02-0345
Abstract482)      PDF(pc) (450KB)(2135)       Save
Based on the meteorological observation data at traffic weather stations along the highways of Hebei Province and the highway traffic accidents and closed-control data caused by the meteorological conditions during 2012-2017, the influence factors of the intensity of high impact weather, durations, risk zoning levels, single traffic flow, topography and occurrence period, etc. on the highway traffic passing were selected, firstly. Then the risk level forecast models of fog, road icing and heavy rainfall disasters were established by using the multifactor weighted method. And on this basis, the integrated risk level forecast model of highway traffic based on three weather conditions was built, and the grade standards were defined with the discrimination index of highway closed-control time caused by fog, road icing and heavy rainfall. Through testing, the accuracy rate of the forecast products of highway traffic integrated risk level model based on the meteorological conditions was 76.7%, which can meet the demand of daily traffic meteorological service.
Related Articles | Metrics