Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures

Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.     

Impact of regional population density on walking behavior

Land use can influence walking (measured by the number of steps) and so the health of people. This paper presents the result of empirical research on the impact of regional population densities (inhabitants per inhabitable area) on the number of steps (all steps, both outdoors and indoors). With data collected from almost 11,000 respondents in 148 Japanese regions, we estimate polynomial regression models, the total number of steps being the dependent variable and densities being the main independent variable. Regional population density significantly affects the number of steps after controlling for individual and household attributes. The estimated population density that maximizes the number of steps is around 11,000?persons/km². Increasing densities, up to levels of around 11,000?inhabitants/km², could increase walking and consequently the health of inhabitants. The population density elasticity of the number of steps is 0.046–0.049 in a simple log linear regression model without a peak.     

基于BIM设计的道岔设备建模方法研究

为了解决站场BIM设计中道岔与岔线建模繁琐、定位捕捉困难等问题,基于最新的OpenRail软件环境,对MicroStation直接建模和道岔设备抽象化线性建模两种思路进行比较分析。经研究,线性建模方法更适合站场BIM设计。针对线性建模手段,将道岔的主要设备及尺寸信息转化为标准化道岔库元素和标记,然后按抽象化的道岔元素及标记信息进行xml文件编程,得到了较好的应用体验。     

Fueling for contingencies: The hidden cost of unpredictability in the air transportation system

The aviation community is increasing its attention on the concept of predictability when conducting aviation service quality assessments. Reduced fuel consumption and the related cost is one of the various benefits that could be achieved through improved flight predictability. A lack of predictability may cause airline dispatchers to load more fuel onto aircraft before they depart; the flights would then in turn consume extra fuel just to carry excess fuel loaded. In this study, we employ a large dataset with flight-level fuel loading and consumption information from a major US airline. With these data, we estimate the relationship between the amount of loaded fuel and flight predictability performance using a statistical model. The impact of loaded fuel is translated into fuel consumption and, ultimately, fuel cost and environmental impact for US domestic operations. We find that a one-minute increase in the standard deviation of airborne time leads to a 0.88 min increase in loaded contingency fuel and 1.66 min in loaded contingency and alternate fuel. If there were no unpredictability in the aviation system, captured in our model by eliminating standard deviation in flight time, the reduction in the loaded fuel would between 6.12 and 11.28 min per flight. Given a range of fuel prices, this ultimately would translate into cost savings for US domestic airlines on the order of $120–$452 million per year.     

拱墩降温对大跨桥上连续式无砟轨道竖向位移影响分析

受季节和日照的影响,高墩大跨拱桥混凝土结构会出现膨胀现象,从而引起桥墩顶部竖向位移的变化。为了研究拱墩降温对高墩大跨拱桥上连续式无砟轨道竖向位移和高低不平顺的影响,根据桥上连续式无砟轨道的结构和受力特征,参考国内某大跨度上承式钢筋混凝土拱桥的实际参数,利用有限元方法,建立线-桥-墩一体化模型,分析拱墩降温对大跨拱桥上连续式无砟轨道的竖向位移和高低不平顺的影响。结果表明:拱墩降温引起的大跨桥上线路竖向位移较明显,设计时不可忽略;拱墩降温会引起线路高低不平顺,且对长波不平顺影响最严重;线路高低不平顺随降温幅度增加而增大,在年温差较大的地区目前不建议高墩大跨拱桥与连续式无砟轨道配合设计使用。     

真空预压软基处理工程监测

介绍真空预压软基处理工程中一些常用的监测手段及监测方法.结合工程实例,通过综合运用表层沉降监测、孔隙水压力监测、分层沉降监测、地下水位观测等手段,分析真空预压软土地基处理方法的加固效果,可供软土地基处理设计与施工参考.     

洋山港建设时期海域通道冲淤变化特征分析

洋山深水港区是由大、小洋山南、北两支岛链组成,形成东窄西宽面向杭州湾开口的喇叭状水域,文章结合洋山港建设以来现场实测水文、地形资料,分析了1998～2007年洋山海域通道内地形冲淤演变情况,将洋山港通道内地形变化特征概括为:随着边界的变化,地形冲淤调整迅速;南北格局呈现出"南淤北冲"的规律;长时间尺度来看,近期地形总体趋于相对平衡,略有冲刷;短时间上看,年内冲淤变化大。为洋山港港区进一步的规划方案论证提供基本依据。     

大型船舶企业组织管理的柔性控制

介绍了上海船厂船舶有限公司实施企业组织管理柔性控制的背景、主要内容、具体方法,以及取得的初步效果。     

综合物探技术在石油平台场址灾害调查中的应用

海洋物探技术是海洋调查的主要作业手段,在海洋石油平台的安全施工需要方面发挥重要作用.通过实例,介绍石油平台场址调查的主要作业范围、使用设备、以及主要结论,包括描述与分析预定平台位置及周围的、与平台就位、预定管线路由铺设施工有关的工程地质现象.     

基于神经网络的道路通行能力与交通需求匹配度判别研究

交通的供需是否匹配关系到城市和枢纽的发展前景。文中在探讨道路通行能力与需求匹配特性的基础上,用BP神经网络理论建立一种交通匹配预测模型。该模型发挥神经网络的优势,对数据并行处理和分布存储,通过训练、学习产生一个非线性映射,自适应地对数据进行预测。通过相关数据实验证明,该神经网络模型有较高的精度,并有较好的适用性。