Objective: The present research relies on 2 main objectives. The first is to investigate whether latent model analysis through a structural equation model can be implemented on driving simulator data in order to define an unobserved driving performance variable. Subsequently, the second objective is to investigate and quantify the effect of several risk factors including distraction sources, driver characteristics, and road and traffic environment on the overall driving performance and not in independent driving performance measures.
Methods: For the scope of the present research, 95 participants from all age groups were asked to drive under different types of distraction (conversation with passenger, cell phone use) in urban and rural road environments with low and high traffic volume in a driving simulator experiment. Then, in the framework of the statistical analysis, a correlation table is presented investigating any of a broad class of statistical relationships between driving simulator measures and a structural equation model is developed in which overall driving performance is estimated as a latent variable based on several individual driving simulator measures.
Results: Results confirm the suitability of the structural equation model and indicate that the selection of the specific performance measures that define overall performance should be guided by a rule of representativeness between the selected variables. Moreover, results indicate that conversation with the passenger was not found to have a statistically significant effect, indicating that drivers do not change their performance while conversing with a passenger compared to undistracted driving. On the other hand, results support the hypothesis that cell phone use has a negative effect on driving performance. Furthermore, regarding driver characteristics, age, gender, and experience all have a significant effect on driving performance, indicating that driver-related characteristics play the most crucial role in overall driving performance.
Conclusions: The findings of this study allow a new approach to the investigation of driving behavior in driving simulator experiments and in general. By the successful implementation of the structural equation model, driving behavior can be assessed in terms of overall performance and not through individual performance measures, which allows an important scientific step forward from piecemeal analyses to a sound combined analysis of the interrelationship between several risk factors and overall driving performance. 相似文献
To analyze the factors affecting US public concern about the threat of climate change between January 2002 and December 2013, data from 74 separate surveys are used to construct quarterly measures of public concern over global climate change. Five factors should account for changes in levels of concern: extreme weather events, public access to accurate scientific information, media coverage, elite cues, and movement/countermovement advocacy. Structural equation modeling indicates that elite cues, movement advocacy efforts, weather, and structural economic factors influence the level of public concern about climate change. While media coverage exerts an important influence, it is itself largely a function of elite cues and economic factors. Promulgation to the public of scientific information on climate change has no effect. Information-based science advocacy has had only a minor effect on public concern, while political mobilization by elites and advocacy groups is critical in influencing climate change concern. 相似文献
Gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM) and particulate bound mercury (PBM) were measured on the University of Mississippi campus from July 2011 to June 2012. It is believed to be the first time that concentrations of atmospheric mercury species have been documented in northern Mississippi, and at a location with relatively large and sudden swings in population. The mean concentration (±1SD) of GEM was 1.54 ± 0.32 ng m−3; levels were lower and generally more stable during the winter (1.48 ± 0.22) and spring (1.46 ± 0.27) compared with the summer (1.56 ± 0.32) and fall (1.63 ± 0.42). Mean concentrations for GOM and PBM were 3.87 pg m−3 and 4.58 pg m−3, respectively; levels tended to be highest in the afternoon and lowest in the early morning hours. During the fall and spring academic semesters concentrations and variability of GOM and PBM both increased, possibly from vehicle exhaust. There were moderate negative correlations with wind speed (all species) and humidity (GOM and PBM). Backward air mass trajectory modeling for the ten highest peaks for each mercury species revealed that the majority of these events occurred from air masses that passed through the northern continental US region. Overall, this study illustrates the complexity of temporal fluctuations of airborne mercury species, even in a small town environment. 相似文献