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.     

广州市在用机动车排气抽检工作若干问题探讨

介绍了广州市在用机动车抽检工作情况和程序,分析了排气抽检工作中存在的问题,提出了解决问题的建议和方法。     

高速公路交通流实时安全性评价

根据多条高速公路近3年的事故数据及实时交通流数据,分析了高速公路运营安全性的相关影响因素,在此基础上提出了车速变异系数指标及其分级标准,建立了考虑交通流量、平均车速、车速变异系数、天气条件等多因素的高速公路交通流运行风险预测多元模型,并提出了高速公路交通流实时行车风险指数TRI指标,制定了交通流状态实时安全性评价标准,最后给出了高速公路交通流混合交通状态下的实时安全风险评价流程。通过西攀高速公路的交通流实时数据,验证了模型的有效性。     

The Real-World Safety Potential of Connected Vehicle Technology

Objective: This article estimates the safety potential of a current commercially available connected vehicle technology in real-world crashes.

Method: Data from the Centre for Automotive Safety Research's at-scene in-depth crash investigations in South Australia were used to simulate the circumstances of real-world crashes. A total of 89 crashes were selected for inclusion in the study. The crashes were selected as representative of the most prevalent crash types for injury or fatal crashes and had potential to be mitigated by connected vehicle technology. The trajectory, speeds, braking, and impact configuration of the selected in-depth cases were replicated in a software package and converted to a file format allowing “replay” of the scenario in real time as input to 2 Cohda Wireless MK2 onboard units. The Cohda Wireless onboard units are a mature connected vehicle technology that has been used in both the German simTD field trial and the U.S. Department of Transport's Safety Pilot project and have been tuned for low false alarm rates when used in the real world. The crash replay was achieved by replacing each of the onboard unit Global Positioning System (GPS) inputs with the simulated data of each of the involved vehicles. The time at which the Cohda Wireless threat detection software issued an elevated warning was used to calculate a new impact speed using 3 different reaction scenarios and 2 levels of braking.

Results: It was found that between 37 and 86% of the simulated crashes could be avoided, with highest percentage due a fully autonomous system braking at 0.7 g. The same system also reduced the impact speed relative to the actual crash in all cases. Even when a human reaction time of 1.2 s and moderate braking of 0.4 g was assumed, the impact speed was reduced in 78% of the crashes. Crash types that proved difficult for the threat detection engine were head-on crashes where the approach angle was low and right turn–opposite crashes.

Conclusions: These results indicate that connected vehicle technology can be greatly beneficial in real-world crash scenarios and that this benefit would be maximized by having the vehicle intervene autonomously with heavy braking. The crash types that proved difficult for the connected vehicle technology could be better addressed if controller area network (CAN) information is available, such as steering wheel angle, so that driver intent can be inferred sooner. More accurate positioning in the real world (e.g., combining satellite positioning and accelerometer data) would allow the technology to be more effective for near-collinear head-on and rear-end crashes, because the low approach angles that are common in such crashes are currently ignored in order to minimize false alarms due to positioning uncertainty.     

基于无人机高光谱遥感在太湖蓝藻水华监测中的一次应用

采用机载高光谱视频相机,在4个季节对太湖蓝藻进行7次、18个架次的有效拍摄。对拍摄到的高光谱影像进行辐射定标、几何拼接等预处理后,提取不同浓度蓝藻和水草等其他物体的高光谱数据,发现不同浓度的蓝藻光谱在680 nm后表现出较大差异。采用主成分分析（PCA）对高光谱数据降维后,结合k-近邻（kNN）分类算法,可实现对蓝藻的精准定位。定性识别结果经光谱预处理后,采用连续投影算法（SPA）进行特征波段提取,发现蓝藻光谱的季节差异主要表现在450 nm~570 nm和760 nm~910 nm波段。     

基于无人机影像的城市植被精细分类

针对传统植被资源调查方法工作量大、成本高、效率低的问题,利用高分辨率无人机遥感影像,联合地物光谱-纹理-空间信息,构建了一种适用于描述城市不同植被种类的多维特征空间,在此基础上对三种应用广泛的分类算法(基于像素的、面向对象的支持向量机及深度学习Mobile-Unet语义分割模型)开展了对比分析研究.结果表明:本文提出的联合地物光谱-纹理-空间信息的特征空间构建方法能够有效地描述城市不同类型植被的特征差异,提升影像分割、植被分类的精度;在分类精度上,基于像素和面向对象的支持向量机分类结果的总体精度均超过90%,深度学习方法的总体分类精度为84%;在算法效率上,传统机器学习方法也优于深度学习方法.因此,得出结论针对城市小区域、小样本的植被精细分类,传统机器学习分类方法比深度学习方法效果更好.     

汽车整车腐蚀试验主观评价方法的探讨

本本文介绍汽车整车道路腐蚀试验、整车腐蚀试验中评价方法的选择,主要探讨整车腐蚀评价体系中主观评价的几大要素。     

30MHz以下电动车辆电磁兼容测试方法研究

本文深入研究SAE J551-5:2012,剖析30MHz以下电动车辆的电场辐射发射、磁场辐射发射和传导发射的测试布置、最大发射工况选择、测试过程、场分量和检波器组合、限值等方面;对比SAE J551-5:2004,针对GB/T18387-2008,提出若干修订建议,以提高其实用性和可操作性。     

Sorption‐desorption kinetics of some organochlorine insecticides in silt‐water suspensions

Kinetic (batch) sorption and desorption experiments for some organochlorine insecticides in silt‐water suspensions are described. The effect of possible experimental artifacts on the results is examined. The influence of the silt/water ratio on the linear sorption coefficient and on the “nonextractable”; solute fraction is determined. The sorption process is described in terms of some kinetic models.     

未铺装道路扬尘排放特征研究

在未铺装道路下风向不同高度测量PM10浓度和风速风向,同时测量上风向PM10浓度,采用暴露高度浓度剖面法计算未铺装道路的扬尘排放量,同时现场记录通过车辆的类型、车速、车轮个数等信息,计算未铺装道路扬尘PM10排放因子。分别分析车辆类型、车辆重量、车轮个数、路面粉土含量、车辆行驶速度对排放因子的影响。结果表明,大货车的排放因子最大,为362 g(/km.辆),其次为小客车、小货车和机动三轮车,分别为112、105和67 g(/km.辆);随着车辆重量的增加排放因子增大并呈线形相关性;随着车辆平均车轮个数的增加排放因子增大并呈线形相关性;分别研究了大货车、小客车和小货车排放因子与车速的关系,随着车速的增加,3种类型车辆的排放因子都增大,并有较好的线形相关性;路面尘土中粉土含量增大,道路扬尘排放因子也增大,路面尘土湿度增加排放因子减小。