A critical overview of driver recording tools

Introduction: Technological advancements during recent decades have led to the development of a wide array of tools and methods in order to record driving behavior and measure various aspects of driving performance. The aim of the present study is to present and comparatively assess the various driver recording tools that researchers have at their disposal. Method: In order to achieve this aim, a multitude of published studies from the international literature have been examined based on the driver recording methodologies that have been implemented. An examination of more traditional survey methods (questionnaires, police reports, and direct observer methods) is initially conducted, followed by investigating issues pertinent to the use of driving simulators. Afterwards, an extensive section is provided for naturalistic driving data tools, including the utilization of on-board diagnostics (OBD) and in-vehicle data recorders (IVDRs). Lastly, in-depth incident analysis and the exploitation of smartphone data are discussed. Results: A critical synthesis of the results is conducted, providing the advantages and disadvantages of utilizing each tool and including additional knowledge regarding ease of experimental implementation, data handling issues, impacts on subsequent analyses, as well as the respective cost parameters. Conclusions: New technologies provide undeniably powerful tools that allow for seamless data handling, storage, and analysis, such as smartphones and in-vehicle data recorders. However, this sometimes comes at considerable costs (which may or may not pay off at a later stage), while legacy driver recording methods still have their own niches to fill in research. Practical Applications: The present research supports researchers when designing driver behavior monitoring studies. The present work enables better scheduling and pacing of research activities, but can also provide insights for the distribution of research funds.     

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.     

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.     

基于VOSviewer的2010-2020年安全疏散研究进展分析

为给安全疏散研究提供综合性的参考,从CNKI和Web of Science收录的2010-2020年核心期刊中整理出关于安全疏散的研究文献,应用VOSviewer软件分别对国内外研究文献的发表数量、关键词、作者等进行了计量分析,并类比其他应用此方法的研究来验证结果的有效性.结果表明:国内针对安全疏散的相关文献年度发表数...     

Leaching of styrene and other aromatic compounds in drinking water from PS bottles

Bottled water may not be safer, or healthier, than tap water. The present studies have proved that styrene and some other aromatic compounds leach continuously from polystyrene （PS） bottles used locally for packaging. Water sapmles in contact with PS were extracted by a preconcentration technique called as ＂purge and trap＂ and analysed by gas chromatograph-mass spectrometer （GC/MS）. Eleven aromatic compounds were identified in these studies. Maximum concentration of styrene in PS bottles was 29.5 μg/L. Apart from styrene, ethyl benzene, toluene and benzene were also quantified but their concentrations were much less than WHO guide line values. All other compounds were in traces. Quality of plastic and storage time were the major factor in leaching of styrene. Concentration of styrene was increased to 69.53 μg/L after one-year storage. In Styrofoam and PS cups studies, hot water was found to be contaminated with styrene and other aromatic compounds. It was observed that temperature played a major role in the leaching of styrene monomer from Styrofoam cups. Paper cups were found to be safe for hot drinks.     

江苏苏中3市的沿江岸线资源开发利用变化及驱动因素

长江是我国重要的黄金水道,其岸线资源有着丰富的开发利用价值。近年来,苏中地区长江岸线资源利用发展迅速。因此,选取苏中扬州、泰州、南通3市为研究对象,基于2002年和2008年的长江岸线利用状况数据,对比分析了3市岸线发展变化的规律。研究表明:2002年以来,苏中3市的岸线利用率大幅提高;新增岸线中工业岸线占比最大,港口岸线和生活服务岸线次之;工业岸线和生活服务岸线的增幅最为显著;各类型岸线的增加主要来源于未利用岸线,已有岸线类型的转换主要流向工业岸线和未利用岸线。港口建设需求、沿江基础工业化进程加快、港产城融合发展、规划和政策引导等是岸线利用变化的重要驱动力。     

南京市2000~2014年城市建设用地变化及驱动因子研究

基于土地利用模型测度2000~2014年南京市城市建设用地的动态变化,再运用典型相关分析、主成分分析及逐步回归分析组合的偏最小二乘回归法对南京市城市建设用地的驱动因子进行分析。结果表明：（1）2000~2014年南京市城市建设用地面积总体上呈上升趋势,年均增长率为11.73%;（2）南京市用地结构信息熵呈波动下降趋势,城市建设用地系统结构性增强,但是用地扩展的综合效益趋降;（3）人口增长、道路扩展、投资水平提高及文化产业发展等能够较好的解释南京市城市建设用地的增长,这4类因子对城市建设用地变化具有正向作用;（4）逐步线性回归结果表明,园林绿地面积的增加相对其他因子对南京市建设用地规模增长的作用最大,其次是道路长度和公路里程。     

家庭部门生活能源消费碳排放:测度与驱动因素研究

本文运用IPCC的二氧化碳排放量测算方法,在省际层面测度了我国家庭部门直接能源消费碳排放,并基于扩展的STIRPAT和Kaya模型,构建家庭部门直接能源消费碳排放影响因子动态面板数据模型,对我国2003-2012年分省面板数据样本及城乡子样本进行系统GMM估计。本文研究表明,第一,我国城乡家庭部门碳排放总量和人均碳排放在近十年都呈快速上升趋势,家庭部门碳排放的空间分布具有明显的地域差异特征,高碳排放地区主要集中在东、中部地区,西部地区的碳排放水平较低;第二,城乡家庭部门生活能源消费的上期碳排放量对本期碳排放产生重要的正向影响,这反映出我国家庭部门碳排放具有显著的惯性特征和路径依赖性,是一种动态自适应机制;人口规模、居民消费水平、能源消费结构、碳排放强度、能源消费强度和城镇化因素,都对我国居民能源消费碳排放总量及人均碳排放具有显著的影响,城乡之间的家庭能源消费碳排放驱动因素存在差异。本文研究得到如下启示及政策含义:家庭部门碳减排将是一个有步骤、分区域的渐进过程,我国碳减排政策应当兼顾消费升级和碳排放的双重目标,努力构建分层次碳减排的适应性预期机制。具体而言,一方面应着眼于引导和激励居民低碳消费,缓解人口规模增加、消费水平提升和城镇化对家庭部门碳减排的压力;另一方面要通过能源价格改革、财政政策和环境规制政策等优化我国能源消费结构,不断降低煤炭消费比重,提高清洁能源的消费。同时,通过技术创新、设备改造等科技手段提高煤炭利用效率,降低碳排放强度,这些政策将更有利于城镇家庭部门碳减排。     

南方丘陵地区河谷城市用地时空演变与驱动分析——以上饶市城区为例

以揭示中国南方丘陵地区河谷城市的空间演变过程和特征为目的,以上饶市城区为例,在遥感与GIS技术的支持下,对1988~2013年间上饶市城区城市用地的时空演变过程、特征及驱动影响因素进行了研究。结果表明,1988~2013年的25 a间,上饶市城区城市用地呈现出快速增长的态势,城市形态的演变具有明显的时空特征:时间序列上,不论扩展幅度还是扩展速度,2001~2013年间的值均高于1988~2001年间的值,前后两个时段的扩展特征呈现出明显的差异性;空间格局上,上饶市城区以老城区的中心广场为中心向四周扩展,先后经历了放射性扩展、组团式分散扩展两个阶段,同时呈现出明显的方向分异性,西南和西为其主要扩展方向,而其东南方向的扩展速度最为缓慢。自然环境中的地貌对上饶市城区城市用地的扩展起到很大的限制作用,经济社会的发展、政策规划等因素成为城市用地扩张与时空演化的外在驱动因素。     

模拟车用工况下5kW燃料电池尾气净化系统

模拟了车用工况下燃料电池发动机脉冲式排氢的特点,设计开发了一套质子交换膜燃料电池的尾气净化系统,并以5 kW燃料电池的尾气排放为例,研究其净化效果。研究了电池阳极排放氢气缓冲前后尾气中氢气浓度的变化,以及不同空速条件下氢气的去除效果。结果表明：电堆阳极排放氢气经过缓冲处理后,尾气中氢气浓度趋于平稳,大部分工况下处在2%以下,达到了安全处理的要求;尾气中氢气的去除效果与空速密切相关。对自制的整体式催化剂而言,当空速低于20000 h^-1时,氢气的去除率能达到约95%,而当空速达到39270 h^-1时,氢气的去除率仅为10.9%。鉴于这一问题,提出通过采用尾排空气的分流手段调整催化燃烧反应器对空速的要求,以提高尾气中氢气的去除率。