Introducing a multi-variate classification method: Risky driving acceptance among different heterogeneous driver sub-cultures

Introduction: Heterogeneous driving populations with many different origins are likely to have various sub-cultures that comprise of drivers with shared driver characteristics, most likely with dissimilar traffic safety cultures. An innovative methodology in traffic safety research is introduced which is beneficial for large datasets with multiple variables, making it useful for the multi-variate classification of drivers, driving attitudes and/or (risky) driving behaviours. Method: With the application of multidimensional scaling analysis (MDS), this study explores traffic safety culture in the State of Qatar using a questionnaire and investigates the similarity patterns between the questionnaire items, aiming to classify attitudes towards risky driving behaviours into themes. MDS is subsequently applied to classify drivers within a heterogeneous driving sample into sub-cultures with shared driver characteristics and different risky driving attitudes. Results: Results show that acceptance of speeding is highest among the young Arabic students and acceptance of distraction and drivers’ negligence such as phone use and not wearing a seatbelt is highest among male Arab drivers. Acceptance of extreme risk-taking like intoxicated driving and red-light running is highest among South-Asian business drivers. Conclusion: It is important and practical to understand risky behavioural habits among sub-cultures and thereby focussing on groups of drivers instead of individuals, because groups are easier to approach and drivers within sub-cultures are found to influence each other. By indicating which groups of drivers are most likely to perform specific risky driving themes, it is possible to target these groups and effectively emphasise certain subsets of risky driving behaviours during training or traffic safety education. Practical Applications: This study provides guidance for the improvement of driver education and targeted traffic safety awareness campaigns, intending to make changes to attitudes and habits within specific driver sub-cultures with the aim to improve traffic safety on the longer term.     

Identification of aggressive driving from naturalistic data in car-following situations

Introduction: Aggressive driving has been associated as one of the causes for crashes, sometimes with very serious consequences. The objective of this study is to investigate the possibility of identifying aggressive driving in car-following situations on motorways by simple jerk metrics derived from naturalistic data. Method: We investigate two jerk metrics, one for large positive jerk and the other for large negative jerk, when drivers are operating the gas and brake pedal, respectively. Results: The results obtained from naturalistic data from five countries in Europe show that the drivers from different countries have a significantly different number of large positive and large negative jerks. Male drivers operate the vehicle with significantly larger number of negative jerks compared to female drivers. The validation of the jerk metrics in identifying aggressive driving is performed by tailgating (following a leading vehicle in a close proximity) and by a violator/non-violator categorization derived from self-reported questionnaires. Our study shows that the identification of aggressive driving could be reinforced by the number of large negative jerks, given that the drivers are tailgating, or by the number of large positive jerks, given that the drivers are categorized as violators. Practical applications: The possibility of understanding, classifying, and quantifying aggressive driving behavior and driving styles with higher risk for accidents can be used for the development of driver support and coaching programs that promote driver safety and are enabled by the vast collection of driving data from modern in-vehicle monitoring and smartphone technology.     

Are older drivers’ driving patterns during an on-road driving task representative of their real-world driving patterns?

Abstract

Objective: The current study investigated whether older drivers’ driving patterns during a customized on-road driving task were representative of their real-world driving patterns.

Methods: Two hundred and eight participants (male: 68.80%; mean age?=?81.52 years, SD?=?3.37 years, range?=?76.00–96.00 years) completed a customized on-road driving task that commenced from their home and was conducted in their own vehicle. Participants’ real-world driving patterns for the preceding 4-month period were also collected via an in-car recording device (ICRD) that was installed in each participant’s vehicle.

Results: During the 4-month period prior to completing the on-road driving task, participants’ median real-world driving trip distance was 2.66?km (interquartile range [IQR]?=?1.14–5.79?km) and their median on-road driving task trip distance was 4.41?km (IQR?=?2.83–6.35?km). Most participants’ on-road driving task trip distances were classified as representative of their real-world driving trip distances (95.2%, n?=?198).

Conclusions: These findings suggest that most older drivers were able to devise a driving route that was representative of their real-world driving trip distance. Future research will examine whether additional aspects of the on-road driving task (e.g., average speed, proportion of trips in different speed zones) are representative of participants’ real-world driving patterns.     

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.     

循环载荷下煤裂隙演化试验研究

为了研究循环载荷下的煤体裂隙演化特征,在不同应力水平和不同频率条件下分别进行煤样破坏力学及声发射试验。结果表明:应力-应变曲线呈疏-密-疏的变化特征,对应的振铃数柱状图呈U型;上限应力点的应变值、累积能量、撞击计数均随循环次数增加而上升,曲线呈倒S型;煤裂隙演化经历了原始裂隙闭合、新生裂隙稳定发育和裂纹贯穿破坏等3个不同阶段;循环载荷的应力水平和加载频率对煤体疲劳寿命的影响具有差异性,对煤体裂隙演化和破坏模式均有明显影响。     

基于情感思维的安全管理模式研究

为促进安全管理,提高效率与效果,对基于情感思维的安全管理进行研究,将情感思维融于安全管理,基于情感思维的定义、内涵及功能,具体分析安全管理中情感思维的功能及其功能综合作用,建立安全管理中情感思维功能作用理论模型;根据该理论模型分析情感思维驱动力及强化作用及其对安全目标实现的影响;建立基于情感思维的安全管理设计模式,最后提出优化安全管理的措施与方法,以促进安全管理的实施。研究表明:基于情感思维的安全管理研究,能较好地体现安全管理人本原理,发挥情感的能动作用,将理性融入其中与情感进行平衡,实现安全管理的优化。     

Technological innovation paths toward green industry in China

With the environmental carrying capacity reaching its limits and the decreasing margin benefits of traditional production factors, the green transformation and green development through technological innovations has been a major direction for the future development of Chinese industries. However, the characteristics and heterogeneities of various types of industries call for different approaches regarding technological innovations. How to choose the most effective mode of technological innovation according to the characteristics of a certain industry has been a key issue. This paper measures the green total factor productivity of 32 industrial trades using the Slacks Based Measure(SBM)-DDF method. The effects of three innovation modes in the green transformation of industrial industry, including the independent innovation(Ⅱ), the technology introduction(TI), and the government support(GS), are empirically analyzed based on industry heterogeneity. Results indicate that the green total factor productivities of different industries show significant differences if taking into account the energy input and the undesirable output of pollutant emissions. The green total factor productivities of traditional high input,high pollution, and high energy consumption industrial trades were significantly lower than those with obvious green features. The year of 2009 is a leap year for the industrial green transformation in China. For resource-intensive industries, the II and the GS are the important ways to achieve green transformation. For labor-intensive industries, the TI is the best path to achieve green transformation, while for technology-intensive industries, the II is the primary driving force for the promotion of green developments. In addition, the innovation-compensating effect of the current Chinese environmental regulations to the resource-intensive industries has been revealed. Improving the overall scale and the industrial concentration of the industries is also beneficial for the green transformation of the industries.     

秦皇岛市天然矿泉水水质特征及开发利用前景研究

秦皇岛市天然矿泉水主要赋存在早太古代的花岗岩和变质岩的构造裂隙与风化裂隙之中,有锶、偏硅酸、锶及偏硅酸、锶溴及偏硅酸等4种类型。矿泉水水源地数量较多,水质优良,但开采程度较低,开发利用前景广阔。     

生态脆弱区乡村旅游开发模式研究——以沂蒙山区为例

乡村旅游在实践中正从边缘化向系列化发展。沂蒙山区是全国水土流失重点治理区,针对沂蒙山区乡村旅游资源状况,分析了沂蒙山区发展乡村旅游的市场条件,认为生态脆弱区发展乡村旅游应遵循经济多元复合化发展与内源发展的原则,建构纵向深化与横向附加开发模式,具体提出乡村旅游开发途径,即旅游内容特色化、耦合化,旅游服务网络化、规范化的深化途径与附加旅游教育和旅游养生内容等途径。     

城市水业PPP项目的风险分担研究

公私合伙制（即PPP）模式在城市水业项目中已经得到广泛的应用,公私双方的合作方式和风险分担是PPP项目成功的关键。在不同的合作关系中,公私双方所承担的风险种类和程度都有所不同。因此,只有理顺PPP项目合作方式与风险分担的对应关系,公共部门才能正确选择PPP项目的合作方式和私营合作方。