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.     

Who you are is how you travel: A framework for transportation mode detection using individual and environmental characteristics

With the increasing prevalence of geo-enabled mobile phone applications, researchers can collect mobility data at a relatively high spatial and temporal resolution. Such data, however, lack semantic information such as the interaction of individuals with the transportation modes available. On the other hand, traditional mobility surveys provide detailed snapshots of the relation between socio-demographic characteristics and choice of transportation modes. Transportation mode detection is currently approached using features such as speed, acceleration and direction either on their own or in combination with GIS data. Combining such information with socio-demographic characteristics of travellers has the potential of offering a richer modelling framework that could facilitate better transportation mode detection using variables such as age and disability. In this paper, we explore the possibility to include both elements of the environment and individual characteristics of travellers in the task of transportation mode detection. Using dynamic Bayesian Networks, we model the transition matrix to account for such auxiliary data by using an informative Dirichlet prior constructed using data from traditional mobility surveys. Results have shown that it is possible to achieve comparable accuracy with the most widely used classification algorithms while having a rich modelling framework, even in the case of sparse mobility data.     

无核密度仪在沥青路面工程质量控制中的应用技术研究

无核密度仪是一种可实现大样本、高效、实时、无损、安全测定沥青面层压实度和非均匀性的新型检测仪器.根据无核密度仪检测方法的基本原理,分析该法测值精确度的影响因素,并提出现场检测时的操作建议及注意事项.阐述无核密度仪在沥青路面压实过程中的压实控制、压实效果评价、压实方案和工艺比选,提出改善沥青面层压实效果的措施,并探讨无核密度仪在沥青面层非均匀性检测中的应用技术.     

乙二醇型汽车发动机冷却液的检测和正确使用

发动机的正常运转与发动机冷却液密不可分,本文主要探讨了乙二醇型汽车发动机冷却液的科学检测和正确使用。发动机冷却液,俗称防冻液,是发动机正常运转不可缺少的散热介质,能保持发动机在最有利的工作温度范围内运行,避免因发动机温度过高或过低带来的不良后果。根据发动机运行的情况对冷却液进行科学的检测、正确的使用和更换会直接影响发动机的使用寿命。     

基于视频检测的交通冲突判别方法和模型

为了克服交通冲突传统人工判别方法的缺陷,提出了基于视频检测的交通冲突发生判别的基本流程,将交通冲突发生的判别划分为交通参数的视频检测、坐标变换和交通冲突判别3个阶段。在借助OpenCV和Matlab标定工具箱进行交通实体检测和坐标变换的基础上,建立了以冲突角度、速度和距离等指标为核心的交通冲突综合判别模型,并通过现实场景验证该模型的有效性。     

碎石桩在高填方机场软基处理中的试验研究

在试验段软基处理中采用了碎石桩加固法,并通过室内土工试验、载荷试验、动探试验对地基处理效果进行了检测分析,结果表明:碎石桩处理地基后对地基内水分的排除、地基深部的加固以及地基土承载力的提高均有显著效果,采用碎石桩处理地基的方法可行。     

PHC管桩基础在住宅小区工程中的应用

以廊坊华元和庭小区PHC管桩基础施工应用为依托,分析管桩基础施工过程中的一些方法措施及检测结果。采用PHC管桩基础,在工程质量、环境、经济、施工工期等方面都是城区地基处理的一种好方法。     

隧道火灾后结构物快速检测评估及处治设计分析

以京珠高速公路大宝山隧道火灾后结构物损伤为研究对象,重点分析隧道内发生火灾后,对隧道损伤部分进行快速检测的内容及其方法。根据检测结果,科学合理评估火灾烧损等级,制定快速又合理的加固设计方案,并结合营运3年的检查情况,认为处治设计方案科学合理,达到了预期的加固效果。     

基于图像分析技术的混凝土表面色差检测及评定

混凝土色差是混凝土结构外观质量检测与评定时的重要参数之一。目前,混凝土色差的评定主要依据检测人员的经验对混凝土表面颜色的均一性进行直观定性判断,其结果难以客观评定混凝土的外观质量。基于图像分析技术的应用,提出采用数码相机现场采集混凝土结构表面图像,对图像进行灰度转换,计算灰度图像的标准差,考虑人类视觉识别特征和拍摄环境的影响,建立混凝土表面色差的定量评价体系和方法。基于所提方法,对一混凝土结构的表面进行了对比试验,结果表明：该方法能有效检测与评定混凝土表面色差缺陷。     

Adhesion estimation at the wheel–rail interface using advanced model-based filtering

The railway industry in the UK is currently expanding the use of condition monitoring of railway vehicles. These systems can be used to improve maintenance procedures or could potentially be used to monitor current vehicle running conditions without the use of cost prohibitive sensors. This paper looks at a novel method for the online detection of areas of low adhesion in the wheel/rail contact that cause significant disruption to the running of a network, particularly in the autumn season. The proposed method uses a Kalman–Bucy filter to estimate the creep forces in the wheel–rail contact area; post-processing is then applied to provide information indicative of the actual adhesion level. The algorithm uses data that, in practice, would be available from a set of modest cost inertial sensors mounted on the vehicle bogie and wheel-sets. The efficacy of the approach is demonstrated using simulation data from a nonlinear dynamic model of the vehicle and its track interface.