Long-Term Prediction of Traffic Accident Record From Bus Driver Celeration Behavior

Driver celeration (speed change) behavior of bus drivers measured a number of times was used to predict their culpable accidents over increasing time periods. It was found that predictive power was considerable (>.30 correlation) over 5 years of time with aggregated celeration (mean of repeated measurements) as independent variables, and there were also indications that power reached even further, although too low Ns made these results unreliable. Similarly, there were indications of even stronger correlations with increased aggregation of celeration values. The results were discussed in terms of the methodology needed to bring out such results, and the stability of accident-causing behavior over time.     

Driver celeration behavior and the prediction of traffic accidents.

A study was undertaken to investigate whether driver celeration (overall mean speed change) behavior can predict traffic accident involvement. Also, to test whether acceleration, deceleration or the combined celeration measure was the better predictor. Bus driver celeration behavior was measured repeatedly in real traffic, driving en route, and correlated with accidents for which the drivers were deemed at least partly responsible. Correlations around .20 were found in several samples between celeration behavior and culpable accidents for a 2-year period. The results show that although celeration behavior is only semi-stable over time, it predicts with some accuracy individual accident involvement over 2 years. The predictive power of acceleration and deceleration was slightly lower than the combined measure, in accordance with theory. The correlations found were strong enough to warrant the use of celeration behavior as a predictive variable for transportation companies in their safety work.     

Driver Celeration Behavior and the Prediction of Traffic Accidents

A study was undertaken to investigate whether driver celeration (overall mean speed change) behavior can predict traffic accident involvement. Also, to test whether acceleration, deceleration or the combined celeration measure was the better predictor. Bus driver celeration behavior was measured repeatedly in real traffic, driving en route, and correlated with accidents for which the drivers were deemed at least partly responsible. Correlations around .20 were found in several samples between celeration behavior and culpable accidents for a 2-year period. The results show that although celeration behavior is only semi-stable over time, it predicts with some accuracy individual accident involvement over 2 years. The predictive power of acceleration and deceleration was slightly lower than the combined measure, in accordance with theory. The correlations found were strong enough to warrant the use of celeration behavior as a predictive variable for transportation companies in their safety work.     

Aggregation of driver celeration behavior data: Effects on stability and accident prediction

Predictions about effects of aggregating driver celeration data were tested in a set of data where bus drivers’ behavior had been measured repeatedly over three years in a city environment. For drivers with many measurements, this data was correlated with the drivers’ accident record at various levels of aggregation over measurements. A single measurement (one sample) was seldom a significant predictor, but for each drive added to a mean, the variation explained in accident record was increased by about 1%. Also, correlations between measurements increased when these were aggregated, and the association with number of passengers (a proxy for traffic density) decreased somewhat, all as predicted. These results show that although driver celeration behavior is only semi-stable across time and environments, aggregating measurements increases both stability and predictive power versus accidents considerably. The celeration variable is therefore promising as a tool for identifying dangerous drivers, if these can be measured repeatedly, or, even better, continuously.     

Effects of passengers on bus driver celeration behavior and incident prediction

PROBLEM: Driver celeration (speed change) behavior of bus drivers has previously been found to predict their traffic incident involvement, but it has also been ascertained that the level of celeration is influenced by the number of passengers carried as well as other traffic density variables. This means that the individual level of celeration is not as well estimated as could be the case. Another hypothesized influence of the number of passengers is that of differential quality of measurements, where high passenger density circumstances are supposed to yield better estimates of the individual driver component of celeration behavior. METHOD: Comparisons were made between different variants of the celeration as predictor of traffic incidents of bus drivers. The number of bus passengers was held constant, and cases identified by their number of passengers per kilometer during measurement were excluded (in 12 samples of repeated measurements). RESULTS: After holding passengers constant, the correlations between celeration behavior and incident record increased very slightly. Also, the selective prediction of incident record of those drivers who had had many passengers when measured increased the correlations even more. CONCLUSIONS: The influence of traffic density variables like the number of passengers have little direct influence on the predictive power of celeration behavior, despite the impact upon absolute celeration level. Selective prediction on the other hand increased correlations substantially. This unusual effect was probably due to how the individual propensity for high or low celeration driving was affected by the number of stops made and general traffic density; differences between drivers in this respect were probably enhanced by the denser traffic, thus creating a better estimate of the theoretical celeration behavior parameter C. The new concept of selective prediction was discussed in terms of making estimates of the systematic differences in quality of the individual driver data.     

Speed choice versus celeration behavior as traffic accident predictor

INTRODUCTION: The driver celeration behavior theory predicts that this variable is superior to all other variables as a predictor of individual traffic accident involvement, including the ever-important speed parameter. The study was undertaken to test this prediction. Also, it was expected that most variables would associate fairly strongly. METHOD: The use of speed choice as a predictor of individual traffic accident record was discussed, and four different variants of this variable (maximum, net mean, gross mean, and standard deviation of speed) identified. These variables were then compared to celeration behavior as predictors of accident record of bus drivers in the same set of data. RESULTS: Celeration behavior was found to be slightly superior, in accordance with the prediction made from the driver celeration behavior theory, although the differences were not significant. Furthermore, the predictor variables were found to associate fairly strongly between themselves, with the exception of gross mean speed, and to have fair stability over time, especially when aggregated. CONCLUSIONS: These results tentatively confirm some of the predictions made from the driver celeration behavior theory. As the results for accidents were in the expected direction, but not significant, and the maximum speed variable may have suffered from a ceiling effect, the conclusion is provisional. Impact on industry: The correlations found were strong enough to warrant the use of celeration behavior as a predictive variable for transportation companies in their safety work.     

The relation of non-culpable traffic incidents to bus drivers' celeration behavior

PROBLEM: The driver celeration behavior theory predicts that celerations are associated with incidents for which the driver has some responsibility in causing, but not other incidents. METHOD: The hypothesis was tested in 25 samples of repeated measurements of bus drivers' celeration behavior against their incidents for two years. RESULTS: The results confirmed the prediction; in 18 samples, the correlation for culpable incidents only was higher than for all incidents, despite the higher means of the latter. Non-culpable incidents had correlations close to zero with celeration. DISCUSSION: It was pointed out that most individual crash prediction studies have not made this differentiation, and thus probably yielded underestimates of the associations sought, although the effect is not strong, due to non-culpable accident involvements being few (less than a third of the total). The methods for correct identification of culpable incident involvements were discussed.     

Fear of terror and increased job burnout over time: Examining the mediating role of insomnia and the moderating role of work support

While the prevalence of terrorism has increased substantially, there is a paucity of research on the effects of terrorism on employee behavior at work. Building on conservation of resources (COR) theory, and its extension, the conservation of social resources theory, we close gaps in the literature by investigating the effect of fear of terror on increased job burnout over time, the mediating effect of insomnia, and the moderating effect of supervisor and co‐worker support on these relationships. This longitudinal study followed a large sample of Israeli employees (n = 670) across three time measurements over 7 years, in a time period characterized by a high number of terror attacks. The results showed fear of terror to be related to elevated job burnout over time, even during a period in which terror attacks were reduced substantially. Further, insomnia mediated the relationship between fear of terror and increased burnout, while co‐worker support, but not supervisor support, moderated the relationships between fear of terror and increased insomnia and between increased insomnia and increased burnout. The results further support the notion of loss cycles in COR theory, as well as the importance of social resources, which are the cornerstones of conservation of social resources theory. Copyright © 2014 John Wiley & Sons, Ltd.     

低压配电线路剩余电流断路器动作判据的研究

为了改善剩余电流断路器频繁误动作的问题,提出以偶次谐波变化率最小值阈值、工频变化量阈值、剩余电流动作整定值相结合的三重判据.首先,搭建活体触电试验平台,获取活体不同部位的多组触电试验数据,利用S变换提取触电波形谐波特征,并计算出触电时刻偶次谐波变比率最小值阈值和工频变化量阈值.其次,搭建人体触电仿真模型,发现存在相似的...     

Social desirability effects in driver behavior inventories

Problem

The use of lie scales to control for common method variance in driver behavior inventories has been very limited. Given that such questionnaires often use self-reported safety variables as criteria, and have social implications, the risk of artefactual associations is high.

Method

A questionnaire containing scales from several well known driver inventories that have been claimed to predict traffic accident involvement was distributed three times to a group of young drivers in a driver education program, as well as a random group twice. The Driver Impression Management scale (DIM) was used to control for socially desirable responding.

Results

For all behavior scales, the correlation with the DIM scale was substantial. If a scale correlated with self-reported crashes, the amount of predictive power was more than halved when social desirability was controlled for. Results were similar for both samples and all waves. The predictive power of the behavior scales was not increased when values were averaged over questionnaire waves, as should have been the case if the measurement and predictive power were valid. Results were similar for self-reported penalty points. The present results indicate that even the most well-known and accepted psychometric scales used in driver research are susceptible to social desirability bias.

Discussion

As social desirability is only one of a number of common method variance mechanisms that can create artefactual associations, and the great popularity of the self-report methodology, the problem for traffic research is grave.

Impact on industry

Organizations that fund traffic safety research need to re-evaluate their policies regarding what methods are acceptable. The use of self-reported independent and dependent variables can lead to directly misleading results, with negative effects on traffic safety.     

蠕变-渗流耦合作用下水力冲孔周围煤体渗透率时空演化规律

为了研究水力冲孔周围煤体瓦斯运移规律,研究了水力冲孔周围煤体的应力、体积应变和孔径变化规律,建立了蠕变-渗流耦合作用下的水力冲孔周围煤体渗透率动态演化模型,揭示了水力冲孔周围煤体渗透率的时空演化规律,阐明了蠕变变形和基质收缩对渗透率的控制作用机理。研究结果表明:水力冲孔措施可以大幅度提高钻孔周围煤体的渗透率,在空间上煤体渗透率随距离呈负幂函数关系迅速降低（K=2×10-16 r -2.4）;在时间上煤体渗透率随抽采时间的延长而逐渐增大,但是增加梯度会逐渐降低;水力冲孔周围煤体渗透率的增加主要受到煤的蠕变变形控制,基质收缩效应虽然有利于渗透率的增加,但对渗透率的贡献远小于煤体的蠕变变形;钻孔由于蠕变变形会产生缩孔现象,很容易堵塞抽采通道,此时即使渗透率大幅度的提高,也很难保证抽采效果,因此迫切需要制定相应的防堵孔措施。     

基于改进Apriori算法的电力通信设备缺陷关联性分析*

为了保障大规模电力通信设备接入电网的稳定运行,首先分析通信设备的物理模型,然后分析电力通信设备缺陷的影响因素和缺陷特征及两者之间的映射关系,接着对Apriori算法进行改进,降低算法的时间复杂度和内存空间,导入电力通信设备缺陷数据模型并结合关联规则,提出基于改进Apriori算法的电力通信设备缺陷关联性分析方法。结果表明:电力通信设备存在缺陷频繁项集,并与影响因素之间存在强关联关系,最后以实际电力通信设备缺陷数据仿真算例对本文方法的有效性进行验证,为通信检修策略的制定提供支持。     

Experimental study on thermal runaway risk of 18650 lithium ion battery under side-heating condition

To simulate the heat transfer process between lithium-ion batteries (LIBs), an electric heater with the same size and shape as LIB in this work is used to trigger thermal runaway event. The effect of state of charge (SOC), the power of heater, the cell spacing on thermal behavior of LIB was investigated as well the amount of transferred heat between the heater and LIB was calculated. The results indicate that 50% SOC is an unstable state for LIB, that a stronger jet flame becomes more likely when the SOC of LIB is higher than 50%. Additionally, the increased spacing, lower heating power and SOC can contribute to mitigate the severity of thermal runaway behavior. Further, the dominant path of heat transfer between the heater and LIB will also vary with operating conditions. The heat conduction through air is the main heat transfer path in tests with lower heating power. However, heat radiation will replace heat conduction as the primary heat transfer mode when there is a large temperature difference between the heater and LIB in tests with higher heating power. Understanding the leading heat transfer path between LIBs can provide valuable guidelines for the safety design of lithium-ion battery modules.     

2类礼貌属性消防安全标语的眼动行为规律研究

为研究不同礼貌属性消防安全标语的眼动行为规律,采用眼动技术对个体在阅读标语过程中的眼动行为进行记录,并对实验数据进行统计分析。研究结果表明:在注视次数和总注视时间上,不礼貌属性标语大于礼貌属性标语,在首次注视时间上2者未存在显著差异;在阅读路径上,不礼貌属性标语的路径更长且回视现象更多;在关键词方面,结果导向关键词的注视时间和次数大于行为指导类关键词,其中恶性结果导向关键词最大。     

Oregon's habitual traffic offender program: An evaluation of the effectiveness of license revocation

This report presents the results of a study of the effectiveness of license revocation for habitual offenders. Drivers whose licenses were revoked were compared with a similar group of drivers whose licenses were not revoked. All revoked drivers had significantly fewer nonmajor violations than did the control drivers. Revoked drivers who received the revocation notice (47%) also had significantly fewer accidents and major violations. Moreover, revoked drivers demonstrated a significant change in the pattern of violation types after revocation. It was concluded that: (a) revocation seems to be an effective way to deter habitual traffic offenders, because habitual offenders whose licenses are revoked have fewer traffic involvements than would be expected if they were not revoked; (b) license revocation would be more effective if the rate of delivery of the revocation notice was higher; and (c) even though many habitual offenders drive illegally after revocation, there is evidence that improved driving behavior, as well as reduced exposure, contributes to the effectiveness of the program.     

驾驶员接管自动驾驶车辆的眼动特性和行为分析

为探究接管自动驾驶车辆期间驾驶员的视觉特性,分析眼动与接管反应操控行为的关系,开展驾驶模拟试验收集驾驶行为及眼动数据。运用统计学方法,分析驾驶员感知不同接管场景的视觉特性,探究接管请求(TOR)前后眼动指标的变化规律;并基于视觉分配和瞳孔变化特性分析驾驶行为,揭示眼动特性与接管反应及驾驶操纵策略的内在联系。结果表明:TOR前,相较于静态场景,驾驶员感知动态场景诱发元素扫视更频繁且平均注视时间更短;此时驾驶员的视觉分配特性与其接管反应行为存在显著相关性。TOR后,驾驶员的注视时间增加,眨眼频率降低,瞳孔直径扩张,眼跳幅度增大;不同场景下驾驶员的瞳孔差异表明其应对动态场景时具备更好的警戒水平和更平稳的操纵策略。     

基于YOLOv3的电网作业人员安全帽佩戴检测

为了有效监测电网作业人员不规范佩戴安全帽行为,提出1种基于YOLOv3的电网作业现场安全帽佩戴检测方法.针对安全帽佩戴规范性问题,构建正确佩戴、不正确佩戴和未佩戴安全帽3种情况下的图像样本库;并利用该数据库对YOLOv3模型进行训练与测试,结合模型参数、样本比例及算法对比分析,开展电网作业人员安全帽佩戴检测算例.结果表...     

Work status and organizational citizenship behavior: a field study of restaurant employees

This survey‐based field study of 257 service employees developed and tested a model of differences in the organizational citizenship behavior of full‐time and part‐time employees based on social exchange theory. Questionnaire data from matched pairs of employees and their supervisors demonstrated that part‐time employees exhibited less helping organizational citizenship behavior than full‐time employees, but there was no difference in their voice behavior. We also predicted that both preferred work status (an individual factor) and organizational culture (a contextual factor) would moderate the relationships between work status and citizenship. For helping, results demonstrated that preferred status mattered more to part‐time workers than to full‐time. For voice, preferred work status was equally important to part‐time and full‐time workers, such that voice was high only when actual status matched preferred status. Contrary to our expectations, work status made more of a difference in both helping and voice in less bureaucratic organizations. We discuss the implications of work status for social exchange relationships, differences in the social exchange costs and benefits of helping compared to voice, and ramifications of our findings for future research. Copyright © 2001 John Wiley & Sons, Ltd.     

基于ai智能图像的工控火电现场爆炸风险评估

对工控火电现场爆炸风险进行评估时,若采用人工识别现场图片信息的方法,容易导致现场图片特征信息采集不准确,存在评估耗时长、评估效率低和评估结果不准确的问题。针对该问题,提出1种基于ai智能图像的工控火电现场爆炸风险评估方法;通过自适应融合方法提取工控火电现场ai智能图像中的特征信息,根据特征信息对工控火电现场ai智能图像进行识别;结合层次分析法和问卷调查法,选取工控火电现场爆炸风险评估指标;在图像识别结果的基础上,通过风险等级集合、评估指标权重,建立工控火电现场爆炸风险评估模型,并与另外2种工控火电现场爆炸风险评估方法进行了对比。研究结果表明:所建方法能够缩短评估时间,且评估效率较高、评估结果准确率较高。     

Dynamic modeling and bifurcation analysis for the methyl isocyanate hydrolysis reaction

The aim of this work was to characterize the methyl isocyanate hydrolysis reaction and to identify its operational criteria. The parametric sensitivity and dynamic stability methodologies were performed at the Bhopal disaster circumstances, over the relevant operating parameter space. Stable and unstable conditions, bifurcations points, turning points and oscillatory behavior were determined. The combined methodology give useful guidance on the operative conditions selection and the appropriate strategy to overcome hazardous situations. The obtained results demonstrated high sensitivity to small perturbations (thermal runaway) and prevalent oscillatory behavior. Moreover, the following critical parameters for the studied dynamic system were defined: the inverse residence time of 1.5700103 and the heat transfer coefficient of 752.394.