膨胀土路基的胀缩变形模型试验

为了研究不同气候条件下膨胀土路基的胀缩变形规律,通过8组膨胀土路基模型试验,对广西南友路宁明地段中等膨胀土和湖南常张路慈利地段弱膨胀土,在压实度为90%和不同排水边界条件下,模拟路基分别处于积水、阴天、日照、降雨4种条件,研究膨胀土路基中各位置测点的胀缩变形大小及变化规律等,获得了这两种膨胀土路基的竖向和水平方向的胀缩变形量与变化规律。研究结果对膨胀土路基的设计和施工,保护路基、路面及路基中的构造物具有重要的理论和工程实际意义。     

冰雪、大雾天气下交通安全保障设施应用研究

文章分析了冰雪、大雾天气的特点及其对道路行车安全的影响,探讨了冰雪、大雾天气下的交通安全保障措施,并对各种交通安全保障设施的设置进行了优化研究,为不良气候条件下的道路交通安全设计、评价提供技术依据。     

单幅雾霾天气交通监控图像去雾处理技术

针对交通视频监控系统在恶劣雾霾天气下获取的图片质量受损,无法正确识别车辆信息的 问题,首先总结了已有图像除雾技术的研究成果,对比分析了全局直方图去雾处理法、同态滤波 去雾处理法、多尺度Retinex(MSR)去雾处理法3 种算法。然后,采用这3 种方法对雾霾交通图片 进行处理,并根据图像纹理特征统计量对处理后的图像效果进行了客观评价。仿真结果表明,3 种算法中,采用多尺度Retinex(MSR)处理法最能提高雾霾图像的质量,能有效地恢复和增强图像 信息,使图像的近景和远景得到均衡。最后,基于Matlab 设计了GUI图像去雾系统,逐一验证了 3 种算法的处理效果,结果表明该系统能够有效地提高交通视频监控系统图像的清晰度,可在一 定程度上优化雾霾天气下的交通图像质量。     

高温季节桥上CRTSⅡ型板式无砟轨道温度分布试验研究

为研究高温季节高速铁路桥上CRTSⅡ型板式无砟轨道的温度分布规律,制作CRTSⅡ型板式无砟轨道-预应力混凝土简支箱梁1:4缩尺试验模型.通过开展夏季典型高温天气的温度试验,分析高速铁路桥上CRTSⅡ型板式无砟轨道结构的温度分布变化规律,研究无砟轨道横、竖向温度分布型式.结果表明:在非阳光直射条件下,高速铁路桥上C RT...     

基于RBF神经网络的不利天气道路通行能力计算

不利天气下影响城市道路通行能力的各种因素都具有随机的、非线性,采用常态条件下修正理论通行能力的计算方法是不适合的.文章结合RBF神经网络模型方法能够良好地分析出随机的、非线性的特点,对路网组成单元进行重新划分,选定不利天气下道路通行能力的影响因素,建立了道路通行能力计算的RBF神经网络模型.并依据哈尔滨市暴雨天气下道路的实际情况进行了算例分析,计算的道路通行能力与实测数据最大误差为-1.16%,验证了模型的可行性和有效性.     

Utilizing naturalistic driving data for in-depth analysis of driver lane-keeping behavior in rain: Non-parametric MARS and parametric logistic regression modeling approaches

It is known that adverse weather conditions can affect driver performance due to reduction in visibility and slippery surface conditions. Lane keeping is one of the main factors that might be affected by weather conditions. Most of the previous studies on lane keeping have investigated driver lane-keeping performance from driver inattention perspective. In addition, the majority of previous lane-keeping studies have been conducted in controlled environments such as driving simulators. Therefore, there is a lack of studies that investigate driver lane-keeping ability considering adverse weather conditions in naturalistic settings. In this study, the relationship between weather conditions and driver lane-keeping performance was investigated using the SHRP2 naturalistic driving data for 141 drivers between 19 and 89 years of age. Moreover, a threshold was introduced to differentiate lane keeping and lane changing in naturalistic driving data. Two lane-keeping models were developed using the logistic regression and multivariate adaptive regression splines (MARS) to better understand factors affecting driver lane-keeping ability considering adverse weather conditions. The results revealed that heavy rain can significantly increase the standard deviation of lane position (SDLP), which is a very widely used method for analyzing lane-keeping ability. It was also found that traffic conditions, driver age and experience, and posted speed limits have significant effects on driver lane-keeping ability. An interesting finding of this study is that drivers have a better lane-keeping ability in roadways with higher posted speed limits. The results from this study might provide better insights into understanding the complex effect of adverse weather conditions on driver behavior.     

空间天气对导航卫星的影响

简要介绍了空间天气的基本概念,对灾害性空间天气可能对导航卫星所产生的主要影响进行了探索;进而着重分析了电离层电子密度、电离层暴、电离层突然骚扰等空间天气要素对卫星导航定位系统的影响。     

A probabilistic framework for weather-based rerouting and delay estimations within an Airspace Planning model

In this paper, we develop a novel severe weather-modeling paradigm to be applied within the context of a large-scale Airspace Planning and collaborative decision-making model in order to reroute flights with respect to a specified probability threshold of encountering severe weather, subject to collision safety, airline equity, and sector workload considerations. This approach serves as an alternative to the current practice adopted by the Federal Aviation Administration (FAA) of adjusting flight routes in accordance with the guidelines specified in the National Playbook. Our innovative contributions in this paper include (a) the concept of “Probability-Nets” and the development of discretized representations of various weather phenomena that affect aviation operations; (b) the integration of readily accessible severe weather probabilities from existing weather forecast data provided by the National Weather Service; (c) the generation of flight plans that circumvent severe weather phenomena with specified probability threshold levels, and (d) a probabilistic delay assessment methodology for evaluating planned flight routes that might encounter potentially disruptive weather along its trajectory. Additionally, we conduct an economic benefit analysis using a k-means clustering mechanism in concert with our delay assessment methodology in order to evaluate delay costs and system disruptions associated with variations in probability-net refinement-based information. Computational results and insights are presented based on flight test cases derived from the Enhanced Traffic Management System data provided by the FAA and using weather scenarios derived from the Model Output Statistics forecast data provided by the National Weather Service.     

基于天气因素的城市轨道交通接驳客流预测改进模型

本文从当前城市轨道交通车站接驳工作中存在的问题入手,阐明了接驳客流预测工作的重要性,并着重抓住天气因素对接驳客流预测的影响,结合现实调查数据,找出了晴天和雨天的各种接驳交通方式客流分担率变化规律;在此基础之上借助于经典的Logit模型构建了城市轨道交通接驳客流预测的改进模型,指出各种接驳方式的设施需根据不同天气条件下客流需求的最大值进行配置.     

大风浪天气情况下船舶供油作业风险控制研究

大风浪天气情况下的船舶供油作业对港口安全生产和海洋环境保护有着重要影响.创新风险理论分析,加强风险要素控制,增强船舶供油作业特别是大风浪天气下作业风险辨识,对于确保大风浪天气情况下供油作业风险有着重要意义.