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Mie理论的激光雾中传输衰减特性研究

海雾是沿海地区或海上常见天气现象,对激光传输的影响很大.采用雾滴谱指数分布模型,结合能见度与含水量、模式半径的经验关系,应用Mie理论研究激光在海雾中的传输衰减.首先通过Mie衰减模型与其它衰减计算模型的比较,分析说明了其优越性;其次从波长、能见度、温度三个方面对激光衰减的影响作用进行了仿真分析,并得出了海雾衰减的相关结论;最后总结了Mie衰减模型的主要误差来源,提出一种提高模型计算精度的方法,并对其可行性进行了分析.     

雾封层技术在现代公路养护中的应用

介绍雾封层预防性养护技术的原理、适用条件和技术特点,并结合某实际工程,总结了该技术的具体施工工艺和注意要点,指出该技术能够改善路面外观,延长路面使用寿命,降低养护工程造价。     

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.     

雾封层养护措施的路用效果分析

依托多条雾封层养护措施试验路段的施工实践,对雾封层措施的施工艺及养护措施的路用效果进行评价,评价指标主要包括抗滑摆值、路面构造深度及路面渗水系数,结果表明：雾封层措施对这3个指标值都有明显的改善,达到了减少水损害和延长道路寿命的目的,但在施工中,应严格注意针对具体的路段采用合适的雾封层措施中乳化沥青的比例,达到最佳的养护效果。     

论船长在气象导航中的作用

根据船舶气象导航的原理以及影响航线设计因素的原则,为船长、船东和租船人如何正确选择使用气导公司及其提供的资料提供一些参考意见,以期减少船东、租船人之间使用气导的纠纷。