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.     

Overestimation of self-reported driving exposure: Results from the SHRP2 Naturalistic Driving Study

Objectives: The accuracy of self-reported driving exposure has questioned the validity of using self-reported mileage to inform research questions. Studies examining the accuracy of self-reported driving exposure compared to objective measures find low validity, with drivers overestimating and underestimating driving distance. The aims of the current study were to (1) examine the discrepancy between self-reported annual mileage and driving exposure the following year and (2) investigate whether these differences depended on age and annual mileage.

Methods: Two estimates of drivers’ self-reported annual mileage collected during vehicle installation (obtained via prestudy questionnaires) and approximated annual mileage driven (based upon Global Positioning System data) were acquired from 3,323 participants who participated in the Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study.

Results: A Wilcoxon signed rank test showed that there was a significant difference between self-reported and annual driving exposure during participation in SHRP 2, with the majority of self-reported responses overestimating annual mileage the following year, irrespective of whether an ordinal or ratio variable was examined. Over 15% of participants provided self-reported responses with over 100% deviation, which were exclusive to participants underestimating annual mileage. Further, deviations in reporting differed between participants who had low, medium, and high exposure, as well as between participants in different age groups.

Conclusions: These findings indicate that although self-reported annual mileage is heavily relied on for research, such estimates of driving distance may be an overestimate of current or future mileage and can influence the validity of prior research that has utilized estimates of driving exposure.     

Characteristics of ride share services for older adults in the United States

Introduction: Safe and accessible transportation options are important for older adults’ health, safety, mobility, and independence. Ride share services may promote older adult health and well-being. This is the first study that describes ride share services available to older adults (65+ years) in the United States, including factors that may affect use of services. Methods: We analyzed secondary data from two research and administrative databases provided by ITNAmerica, a national non-profit transportation service for older adults: ITNRides, which tracks information on older adults who used ITN in 29 locations across the United States from 1996 to 2019, and Rides in Sight, the largest national data source on ride share services for older adults. We conducted a literature review, and telephone interviews with nine key informants representing ride share services, referral services, and other organizations. We offer a conceptual framework describing factors that may affect older adults’ use of ride share services. Results: This study identified 917 non-profit ride share services and eleven for-profit ride share services available for older adults in the United States as of August 2018. Services varied by corporate structure, location, use of technology, and business model. The majority of non-profit services served primarily older adults, while the for-profit services served primarily younger adults. Riders from one multi-site non-profit service had a median age of 82. Use of ride share services is affected by individual needs and preferences; social conditions; and business and policy factors. Conclusion: Ride share services may offer a promising alternative to driving for older adults and may help to address negative health consequences associated with driving cessation. Practical applications: These findings may help policy makers, practitioners, and other stakeholders understand older adults’ needs related to use of ride share services in order to offer solutions that prioritize public health and safety.     

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.     

Alcohol-impaired motorcyclists versus car drivers: A comparison of crash involvement and legal consequence from adjudication data

Introduction: Driving under the influence (DUI) increases the probability of motor-vehicle collisions, especially for motorcycles with less protections. This study aimed to identify commonalities and differences between criminally DUI offenses (i.e., with a blood alcohol concentration (BAC) of 80 mg/dL or higher) committed by motorcyclists and car drivers. Methods: A total of 10,457 motorcycle DUIs and 8,402 car DUIs were compared using a series of logistic regression models, using data extracted from the documents of adjudication decisions by the courts of Jiangsu, China. Results: The results revealed that offenders from the high-BAC group (i.e., 200 mg/dL or higher) accounted for more than 20% of the total DUI offenses, and were more likely to be involved in a crash and punished with a longer detention. Motorcyclists had a higher likelihood of crash involvement, and were also more likely to be responsible for single-vehicle crashes associated with higher odds of injury sustained, compared to alcohol-impaired car drivers. In the verdict, motorcycle offenders were more likely to receive a less severe penalty. Conclusions: Interventions are clearly required to focus on reducing in the high-BAC group of offenders. For alcohol-impaired motorcyclists, their risks of crash and injury against BAC climb more steeply than the risks for car drivers. The factors including frequent occurrences, uncertainty of detection, and short-term sentences may weaken the deterrence effect of the criminalization of motorcycle DUI. Practical Applications: The traffic-related adjudication data support traffic safety analysis. Strategies such as combating motorcycle violations (e.g., unlicensed operators or driving unsafe vehicles), undertaking education and awareness campaigns, are expected for DUI prevention.     

Flash point of biodiesel/glycerol/alcohol mixtures for safe processing and storage

Mixtures of biodiesel, glycerol, and ethanol/methanol are commonly processed and stored in biodiesel production. In this work, non-ideal models are used to calculate the Flash Points (FPs) of binary and ternary mixtures, using data available from different feedstocks. Despite the fact that biodiesel is considered safer than common diesel fuels, results show a synergistic effect of biodiesel/methanol and biodiesel/ethanol mixtures, resulting in a reduction of the flash point of mixtures to values lower than the ones of pure compounds. Most soluble ternary mixtures were found flammable, the only exception being mixtures with a relatively lower alcohol content (45% mol. ethanol or 42% methanol) at temperature lower than 303 K. Accidental increase in temperature can cause domino effect, due to the higher solubility and the formation of new flammable ternary mixtures.     

大气14CO2的时空分异特征及其在化石源CO2示踪中的应用

大气CO₂中放射性碳同位素(¹⁴C)的水平可以反映化石源CO₂的影响程度,这对于评估我国目前化石源CO₂的排放状况和制定节能减排政策具有重要的指导意义。本文在概述大气¹⁴CO₂采样和分析方法的基础上,简要介绍了大气¹⁴CO₂观测的起源和主要的源汇过程,重点论述了大气¹⁴CO₂的时空分异特征及其驱动因素;阐述了化石源CO₂浓度的估算方法及¹⁴CO₂在国内外化石源CO₂示踪中的应用现状,并对大气¹⁴CO₂观测在我国化石源CO₂示踪中的应用前景进行了展望;旨在为我国正确地开展大气¹⁴CO₂的观测研究,深刻地理解特定区域大气¹⁴CO₂的时空分异特征和化石源CO₂的分布状况提供参考。     

Community structure and elevational diversity patterns of soil Acidobacteria

Acidobacteria is one of the most dominant and abundant phyla in soil,and was believed to have a wide range of metabolic and genetic functions. Relatively little is known about its community structure and elevational diversity patterns. We selected four elevation gradients from 1000 to 2800 m with typical vegetation types of the northern slope of Shennongjia Mountain in central China. The vegetation types were evergreen broadleaved forest,deciduous broadleaved forest,coniferous forest and sub-alpine shrubs. We analyzed the soil acidobacterial community composition,elevational patterns and the relationship between Acidobacteria subdivisions and soil enzyme activities by using the 16 S rRNA meta-sequencing technique and multivariate statistical analysis. The result found that 19 known subdivisions as well as an unclassified phylotype were presented in these forest sites,and Subdivision 6 has the highest number of detectable operational taxonomic units(OTUs). A significant single peak distribution pattern(P 0.05) between the OTU number and the elevation was observed. The Jaccard and Bray–Curtis index analysis showed that the soil Acidobacteria compositional similarity significantly decreased(P 0.01) with the increase in elevation distance. Mantel test analysis showed the most of the soil Acidobacteria subdivisions had the significant relationship(P 0.01) with different soil enzymes. Therefore,soil Acidobacteria may be involved in different ecosystem functions in global elemental cycles. Partial Mantel tests and CCA analysis showed that soil pH,soil temperature and plant diversity may be the key factors in shaping the soil Acidobacterial community structure.     

武汉城市圈土地利用变化系统仿真模拟与驱动力分析

土地利用变化是全球环境变化与可持续研究的重要内容,驱动力研究是土地利用变化研究中的核心问题。现有土地利用变化驱动力研究多针对单一的城市区域展开,无法解释城市群地区,城市一体化战略指导下城市交互作用对土地利用变化的影响。运用系统动力学(SD)方法,综合考虑经济、人口、城市化、政策等主要人文因素,并将城市交互作用因素引入SD,以武汉城市圈为例,构建土地利用变化系统SD模型,运用1997~2006年的历史数据进行检验,并对武汉城市圈2010~2020年不同情景下的土地利用变化进行模拟。结果表明,建立的SD模型是有效的,两种情景下土地利用变化表现出差异性,说明城市交互作用是除经济、人口城市化等社会经济因素外,土地利用变化的又一重要影响因素。     

上喷式矿井排风热回收装置内液滴运动模型及其优化计算

为了减小常见下喷式装置风吹水损失大的问题,设计了上喷式矿井排风热回收装置.通过液滴受力及运动分析,将上喷式液滴的运动划分为2个阶段.根据牛顿第二定律,建立了简化的液滴动量方程;在该方程的基础上,结合运动阶段划分,得到临界条件下的力平衡关系式;利用该式,在10个不同相对速度下,得到了上喷式与下喷式的保证液滴不被吹飞的临界直径.应用变量替换,将液滴动量方程变换为液滴运动距离的微分式;继而,根据液滴及空气之间的雷诺数组合,导出了液滴最大上升高度的5个积分计算式.应用这些积分式,数值计算了不同迎面风速、液滴粒径及液滴初速度下,上喷式中液滴最大上升高度、下喷式中液滴最大下降高度.对比计算结果,相比下喷式,上喷式具有节水、液滴选择范围宽和低耗高效的优势.