Cause Analysis of Traffic Accidents on Mountain Expressway Based on Multistage Microscope Technology
Traffic accidents are generally considered to be affected by a combination of factors such as driver characteristics, vehicle characteristics, roadway characteristics, and environmental factors. In order to analyze the contributing factors affecting traffic accident frequency and severity, this research develop multilevel logistic regression models using 1338 traffic accidents collected from 20 road segment on mountainous freeway in China. A series of new confocal microscopes have been successfully developed and put into use, such as video confocal laser scanning microscopy, two-photon microscopy, 4Pi microscopy, fluorescence lifetime imaging microscopy and so on. Compared with traditional confocal microscopes, they have their own unique advantages. Understanding their basic properties and characteristics is helpful for their wider and deeper applications in the field of biology. A two-level logistic regression model was developed including one outcome variable (severity), five level-1 explanatory variables (lighting, weather, visibility, driving experience and vehicle type) and one level-2 explanatory variable (Fatal accidents site classification). The results showed this model fits the data much better than the null model or the random intercept only model; three level-1 explanatory variables (i.e., experience, visibility and vehicle_type) have statistically significant effects on the dichotomous variable fatal_accident.