MFAM模型在河流水质污染模拟及预测中的应用

文中以时间序列分析为基础，介绍了均值生成函数这一崭新概念，并且经成份因子提取分析推导建立了模拟序列的数字模型（简记为MFAM），经对黄河下游花园口断面的1988-1989年实测水质污染指标溶解氧（DO），氨氧，化学耗氧量（COD），五日生化需氧量（BOD5）等序列模拟，结果表明MFAM模型能较好地模拟河流水质污染指标的变化趋势，拟合平均误差只有5.2-6.4%，MFAM模型应用于预测1990-1991年水质污染指标变化，结果表明预测精度达85%以上，文中最后得出结论：MFAM模型应用于河流污染模拟和预测，是完全可行且十分方便。     

Aggressive behavior while driving as predictor of self-reported car crashes

PROBLEM: In Greece, there is a lack of scientific evidence on the relationship between aggressive behavior while driving and young drivers' involvement in car crashes; this study examined this potential relationship. METHODS: The randomly selected samples of 356 young drivers (18-24 years old) were interviewed through a questionnaire of self-reported car crash involvement, which mainly focused on their behavior on the road and the number of car crashes in which they had been involved. RESULTS: The statistical methods used were principal components analysis (PCA) and multiple regression analysis. Two factors relevant to aggressive driving emerged: (a) driving violations and (b) irritability while driving. The multivariate model suggested that driving just for fun (joyriding) and irritability were predictors of young drivers' involvement in car crashes. It was found that younger age was negatively associated with young drivers' involvement in car crashes. IMPACT ON GOVERNMENT AND INDUSTRY: The findings of this study can contribute in the formation of public policies aiming to prevent young drivers' car crashes. These findings can also be the starting point of some health promotion interventions trying to reduce car crashes and casualties on the road. Finally, the insurance companies may be interested in applying these findings into their field of interest.     

Investigation of seat belt use among the drivers of different education levels

Seat belt use habit has been investigated according to the education level of drivers. Copies of a questionnaire were distributed to 1000 participants of four different education levels. Factors such as seat belt usage habit, restricting factors and crash data have been investigated. Data have been analyzed with SPSS 15.0 software. Increased level of education leads to increased seat belt usage, lower numbers of crashes and crash severities. The factors restricting seat belt use are lack of habit, discomfort and short distance driving. The use of precaution signal and increases in comfort can increase seat belt usage. The primary and high school education on traffic safety and seat belt usage has been serving the purpose.     

Effect on fatality risk of changing from secondary to primary seat belt enforcement

BACKGROUND: Most seat belt use laws originally passed in the United States contained language restricting enforcement to drivers already stopped for some other reason. States that have since removed this secondary enforcement restriction have reported increased seat belt use. The purpose of the present study was to estimate the effect of these law changes on driver fatality rates. METHOD: Trends in passenger vehicle driver death rates per billion miles traveled were compared for 10 states that changed from secondary to primary seat belt enforcement and 14 states that remained with secondary enforcement. RESULTS: After accounting for possible economic effects and other general time trends, the change from secondary to primary enforcement was found to reduce annual passenger vehicle driver death rates by an estimated 7% (95% confidence limits 3.0-10.9). CONCLUSION: The majority of U.S. states still have secondary enforcement laws. If these remaining secondary laws were amended, an estimated 696 deaths per year could be prevented.     

Driving anger among motor vehicle drivers in China: A cross-sectional survey

Objective: Driving anger is a common emotion while driving and has been associated with traffic crashes. This study aimed to investigate situations that increase driving anger among Chinese drivers.

Methods: A cross-sectional study was conducted among 3,101 drivers in southern China. The translated version of the 33-item Driving Anger Scale (DAS) was used to measure driving anger. Data were collected by face-to-face interviews between June 2016 and September 2016.

Results: Confirmatory factor analysis showed that the fit of the original 6-factor model (discourtesy, traffic obstacles, hostile gestures, slow driving, illegal driving, and police presence) was satisfactory, after removing 2 items and allowing 5 error pairs to covary. The model showed satisfactory fit: goodness of fit index (GFI) = 0.90, incremental fit index (IFI) = 0.90, root mean square error of approximation (RMSEA) = 0.06, 90% confidence interval (CI) = 0.061–0.064. Driving anger among Chinese drivers was lower than that in some Western countries. Compared to older and experienced drivers, younger and new drivers were more likely to report driving anger. There was no difference in total reported driving anger between males and females. Additionally, the higher the driver’s anger level was, the more likely he or she was to have had a traffic crash.

Conclusion: Driving anger is a common emotion among Chinese drivers and has a strong correlation with aggressive driving behavior and traffic crashes.     

Characteristics of animal-related motor vehicle crashes in select National Park Service units—United States, 1990–2013

Objectives: Nationally, animal–motor vehicle crashes (AVCs) account for 4.4% of all types of motor vehicle crashes (MVCs). AVCs are a safety risk for drivers and animals and many National Park Service (NPS) units (e.g., national park, national monument, or national parkway) have known AVC risk factors, including rural locations and substantial animal densities. We sought to describe conditions and circumstances involving AVCs to guide traffic and wildlife management for prevention of AVCs in select NPS units.

Methods: We conducted an analysis using NPS law enforcement MVC data. An MVC is a collision involving an in-transit motor vehicle that occurred or began on a public roadway. An AVC is characterized as a collision between a motor vehicle and an animal. A non-AVC is a crash between a motor vehicle and any object other than an animal or noncollision event (e.g., rollover crash). The final data for analysis included 54,068 records from 51 NPS units during 1990–2013. Counts and proportions were calculated for categorical variables and medians and ranges were calculated for continuous variables. We used Pearson’s chi-square to compare circumstances of AVCs and non-AVCs. Data were compiled at the park regional level; NPS parks are assigned to 1 of 7 regions based on the park’s location.

Results: AVCs accounted for 10.4% (5,643 of 54,068) of all MVCs from 51 NPS units. The Northeast (2,021 of 5,643; 35.8%) and Intermountain (1,180 of 5,643; 20.9%) regions had the largest percentage of the total AVC burden. November was the peak month for AVCs across all regions (881 of 5,643; 15.6%); however, seasonality varied by park geographic regions. The highest counts of AVCs were reported during fall for the National Capital, Northeast/Southeast, and Northeast regions; winter for the Southeast region; and summer for Intermountain and Pacific West regions.

Conclusions: AVCs represent a public health and wildlife safety concern for NPS units. AVCs in select NPS units were approximately 2-fold higher than the national percentage for AVCs. The peak season for AVCs varied by NPS region. Knowledge of region-specific seasonality patterns for AVCs can help NPS staff develop mitigation strategies for use primarily during peak AVC months. Improving AVC data collection might provide NPS with a more complete understanding of risk factors and seasonal trends for specific NPS units. By collecting information concerning the animal species hit, park managers can better understand the impacts of AVC to wildlife population health.     

Effectiveness of lowering the blood alcohol concentration (BAC) limit for driving from 0.10 to 0.08 grams per deciliter in the United States

Objective: The current study evaluates of the effects of lowering the blood alcohol concentration (BAC) limit from 0.10 to 0.08?g/dL across all 50 states in the United States. Our objectives were to (1) estimate the effects of the 0.08?g/dL BAC limit on drinking driver fatal crash rates; (2) compare the effects from early-adopting states to the effects of late-adopting states; (3) determine the effects on drivers with low BACs (0.01–0.07?g/dL) and high BACs (0.08+ g/dL); and (4) estimate the lives saved since 1983 due to the adoption of 0.08?g/dL BAC laws.

Methods: Our study examined annual data from the Fatality Analysis Reporting System (FARS) for each jurisdiction from 1982 through 2014. Our basic outcome measure was the ratio of drinking drivers (BAC ≥0.01?g/dL) to nondrinking drivers (BAC?=?0.00?g/dL). Covariates included 0.10 BAC laws, administrative license revocation (ALR) laws, seat belt laws, minimum legal drinking age (MLDA) laws, and unemployment rates. We utilized autoregressive integrated moving average (ARIMA) models for each state, where the implementation date of the law was modeled as a zero-order transfer function in the series, in addition to any extant trends that may have been occurring simultaneously. Before determining the specific impact of the implementation of 0.08?g/dL BAC laws, we conducted a time series analysis for each state. We tested for between-state mediating factors relating to our covariates.

Results: A total of 38 of the 51 jurisdictions showed that lowering the BAC limit was associated with reduced drinking driver fatal crash ratios, with 20 of those reductions being significant. The total effects showed a 10.4% reduction in annual drinking driver fatal crash rates, which is estimated to have saved an average of 1,736 lives each year between 1983 and 2014 and 24,868 lives in total. Implementing a BAC limit of 0.08?g/dL had significant impacts on both high- and low-BAC fatal crash ratios. Though early-adopting jurisdictions (1983–1999) demonstrated a larger decrease in fatal drinking driver crash ratios than did late-adopting jurisdictions (2000–2005), the results were not statistically significant (P?>?.05).

Conclusions: Our study of the effects of lowering the BAC from 0.10 to 0.08?g/dL in the United States from 1982 to 2014 showed an overall effect of 10.4% on annual drinking driver fatal crash rates, in line with other multistate studies. This research provides strong evidence of the relationship between lowering the BAC limit for driving and the general deterrent effect on impaired-driving fatal crash rates.     

Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model

Introduction: Reducing the severity of crashes is a top priority for safety researchers due to its impact on saving human lives. Because of safety concerns posed by large trucks and the high rate of fatal large truck-involved crashes, an exploration into large truck-involved crashes could help determine factors that are influential in crash severity. The current study focuses on large truck-involved crashes to predict influencing factors on crash injury severity. Method: Two techniques have been utilized: Random Parameter Binary Logit (RPBL) and Support Vector Machine (SVM). Models have been developed to estimate: (1) multivehicle (MV) truck-involved crashes, in which large truck drivers are at fault, (2) MV track-involved crashes, in which large truck drivers are not at fault and (3) and single-vehicle (SV) large truck crashes. Results: Fatigue and deviation to the left were found as the most important contributing factors that lead to fatal crashes when the large truck-driver is at fault. Outcomes show that there are differences among significant factors between RPBL and SVM. For instance, unsafe lane-changing was significant in all three categories in RPBL, but only SV large truck crashes in SVM. Conclusions: The outcomes showed the importance of the complementary approaches to incorporate both parametric RPBL and non-parametric SVM to identify the main contributing factors affecting the severity of large truck-involved crashes. Also, the results highlighted the importance of categorization based on the at-fault party. Practical Applications: Unrealistic schedules and expectations of trucking companies can cause excessive stress for the large truck drivers, which could leads to further neglect of their fatigue. Enacting and enforcing comprehensive regulations regarding large truck drivers’ working schedules and direct and constant surveillance by authorities would significantly decrease large truck-involved crashes.