Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.
Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).
Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.
Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy. 相似文献
Vertical and temporal distributions of N and P in soil solution in aquatic-terrestrial ecotone (ATE) of Taihu Lake were investigated, and the relations among N, P, ORP (oxidation reduction potential), TOC, root system biomass and microorganism were studied. As a whole, significant declines in TN, NO3^--N, DON (dissolved organic nitrogen) and TP concentration in soil solution have occurred with increase of the depth, and reached their minima at 60 cm depth, except for NH4^+-N, which increased with depth. The concentration of TP increased gradually from spring to winter in the topsoil, the maximum 0.08 mg/L presented in the winter while the minimum 0.03 mg/L in spring. In the deeper layer, the concentration value of TP fluctuated little. As for the NO3^--N, its seasonal variation was significant at 20 cm depth, its concentration increased gradually from spring to autumn, and decreased markedly in winter. Vertical and temporal distribution of DON is contrary to that of NO3^--N. The results also show that the variation of N and P in the percolate between adjacent layers is obviously different. The vertical variation ofTN, TP, NO3^--N, NH4^+-N and DON is significant, of which the variation coefficient of NO3^--N along the depth reaches 100.23%, the highest; while the variation coefficient of DON is 41.14%, the smallest. The results of correlation analysis show that the concentration of nitrogen and phosphorus correlate significantly with TOC, ORP, root biomass and counts of nitrifying bacteria. Most nutrients altered much from 20 to 40 cm along the depth. However, DON changed more between 60 and 80 cm. Results show that soil of 0-60 cm depth is active rhizoplane, with strong capability to remove the nitrogen and phosphorus in ATE. It may suggest that there exists the optimum ecological efficiency in the depth of above 60 cm in reed wetland. This will be very significant for ecological restoration and reestablishment. 相似文献