Structural equation model analysis for the evaluation of overall driving performance: A driving simulator study focusing on driver distraction

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.     

矿工心理因素、工作压力反应和不安全行为关系研究

为研究在巨大工作压力下，矿工的心理因素与工作压力反应和不安全行为的关系，以问卷的形式调查陕西省2家具代表性煤矿的工人，分别以矿工的心理因素、工作压力反应和作业过程中的不安全行为作为外生变量、中介变量和内生变量，构建心理因素、压力反应和不安全行为的结构方程模型。通过对调研数据处理与分析，得出如下结论:本研究中的4项心理因素，性格因素、心理素质、注意力和工作态度显著影响不安全行为的发生；性格因素、心理素质和注意力对压力反应有显著影响；工作态度与煤矿工人的压力反应的关系不显著；性格因素、心理素质、注意力和工作态度通过影响矿工的压力反应，间接影响矿工的不安全行为。     

基于支持向量回归机的南黄海浒苔分布面积预测模型

绿潮作为一种新型的海洋灾害,已经引起了各个国家的重视.依据2012年南黄海海域浒苔遥感监测分布面积数据,选取了温度、天气状况、风向、风力、浪高5种影响浒苔扩散的气候因子,建立了基于SVR的浒苔分布面积预测模型,并与经典的最近邻点插值模型、线性插值模型、3次样条函数插值模型和分段3次Hermite插值模型进行了回归效果的对比.分析结果表明,基于SVR的浒苔分布面积预测模型能够为浒苔遥感数据的插补提供一种方法,且回归效果优于传统的回归方法,为浒苔的防治提供辅助决策信息.     

火灾发生率空间分异及影响因素研究

为了探究我国火灾空间聚集特征与影响因素的空间异质性，采用全局莫兰指数、局部莫兰指数、逐步回归模型、地理加权回归模型、地理探测器方法对我国地级市单元进行研究。研究结果表明:我国火灾发生率具有显著的聚集性；我国火灾发生率较低的“冷点”区域有1个，火灾发生率较高的“热点”区域有4个；人均GDP、城镇居民人均可支配收入、人口密度、年平均气温4 个因素的影响效应具有空间异质性。人均GDP与火灾发生率为正相关，另外3影响因素对火灾发生率的作用表现出正负2种相关关系；2因素交互作用要比单因素作用于火灾发生率时影响力更显著，各影响因素的交互作用类型有非线性增强型和双因子增强型2种。     

不同类型压力对飞行员安全绩效的影响规律研究

为探究各类型压力对飞行员安全绩效的影响规律，为飞行员日常工作管理提供依据，选取某航空公司200名飞行员进行压力测试，并调取其近6 a的飞机品质(QAR)数据，通过相关性分析和线性回归分析将飞行员压力数据与其QAR数据进行对比分析，探究飞行员压力对飞行安全绩效的影响规律。研究结果表明:工作负荷压力、家庭压力、人际关系压力和组织管理压力会显著负向影响飞行员安全绩效；角色压力和专业发展压力会显著正向影响飞行员安全绩效。     

Spatial and Seasonal Response of Municipal Water Use to Weather across the Contiguous U.S.

Weather variability has the potential to influence municipal water use, particularly in dry regions such as the western United States (U.S.). Outdoor water use can account for more than half of annual household water use and may be particularly responsive to weather, but little is known about how the expected magnitude of these responses varies across the U.S. This nationwide study identified the response of municipal water use to monthly weather (i.e., temperature, precipitation, evapotranspiration [ET]) using monthly water deliveries for 229 cities in the contiguous U.S. Using city‐specific multiple regression and region‐specific models with city fixed effects, we investigated what portion of the variability in municipal water use was explained by weather across cities, and also estimated responses to weather across seasons and climate regions. Our findings indicated municipal water use was generally well‐explained by weather, with median adjusted R² ranging from 63% to 95% across climate regions. Weather was more predictive of water use in dry climates compared to wet, and temperature had more explanatory power than precipitation or ET. In response to a 1°C increase in monthly maximum temperature, municipal water use was shown to increase by 3.2% and 3.9% in dry cities in winter and summer, respectively, with smaller changes in wet cities. Quantifying these responses allows urban water managers to plan for weather‐driven variability in water use.     

农地整治权属调整中农户认知对行为响应的作用机制--基于改进TPB及多群组SEM

农地整治权属调整是实现农业规模化和现代化的重要手段,而农户有效参与是推动权属调整的内在动力,研究农地整治权属调整中农户认知对其行为响应的作用机制,有助于高效引导农户参与权属调整,并为制定农地整治权属调整的政策提供科学依据。基于改进计划行为理论和湖北省11个县(市、区)1044份农户抽样调查数据,采用多群组结构方程模型探究了农地整治权属调整中不同类型农户认知对其行为响应的作用机制。结果表明:农地整治权属调整中农户行为逻辑符合改进计划行为理论,农户的行为态度、主观规范、知觉行为控制交互影响行为意愿,进而转换为行为响应,政府支持在行为意愿和行为响应之间起到部分中介作用。总体上,农户行为响应是"自发性""诱发性"和"约束性"三重行动逻辑的结合,且"自发性"占主导地位。多群组结构方程估计结果表明,纯农型与兼业Ⅰ型农户的行为响应受到"自发性""诱发性"和"约束性"三重影响,兼业Ⅱ型农户受到"自发性"和"诱发性"双重影响,非农型农户仅受到"诱发性"单一影响。因此,为引导农户积极参与农地整治权属调整,应该分别针对各类农户相应地提高其参与的"自发性"和"诱发性",降低"约束性",充分发挥农村社会经济组织的作用,将四种不同类型农户的利益需求统筹考虑,降低权属调整过程中利益协调难度。     

Factors associated with driving under the influence of alcohol

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.     

Estimate on spillover effect of environmental pollution between peripheral areas

ABSTRACT

Interaction of environmental pollution between peripheral areas has become a central topic in the field of resources and environment but little is known about the actual impact on peripheral areas in the current literature. This paper sets out a simultaneous equation model to investigate the spillover effect of environmental pollution between China’s peripheral areas utilizing the panel data of 218 cities in China. Making use of indicators for measuring the impact on environmental pollution, it identifies that environmental pollution between cities of China has a significant two-way spillover effect. After standardization of variables, it is found that the spillover effect of peripheral areas on urban environmental pollution cannot be neglected. Nearly, a third of the environmental pollution level in a city is induced by the environmental pollution in peripheral areas. If the indicator of environmental pollution in peripheral areas is missing, wrong conclusions will be drawn. Therefore, government should shift the emphasis of environmental regulation from local to global, and improve the overall environmental quality through coordinated management of regional environment.     

示踪技术用于气体泄漏扩散模拟的多元线性回归分析

采用江苏工业学院油气储运安全综合实验模型平台,利用示踪技术(以CO2为示踪剂),模拟了有害气体瞬时泄漏扩散的整个过程.并结合多元线性回归分析的基本方法,定量分析了气体泄漏扩散过程,建立了多元线性回归模型,初步确定了泄漏气体浓度与相关物理量的变化关系,在此基础上得到了2个定量评价指标:确定性系数R=0.991,相关系数r=0.995.研究表明,在实验室建立的试验模型能较好地反映现实情况,模型仿真度较高,数据拟合效果较好.研究可为评价模型的相似性提供理论参考,对有害气体泄漏扩散事故应急救援、实施有效的现场控制,具有一定的科学参考价值.