城市轨道交通中无线局域网的应用

信息技术已经成为当今社会的主流技术.及时、准确地得到需要的信息是很多客户的要求.无线局域网(WLAN)是相当便利的数据民用通信传输系统.随着WLAN技术的普及,如何将其融合到城市轨道交通环境中去,更好地为乘客信息系统、乘客个人终端服务,已经成为一个新的课题.车地通信的实现是WLAN能够在城市轨道交通中成功应用的关键.针对不同的模式对WLAN的应用进行了阐述,以寻找最适合上海轨道交通系统的应用方案.     

地铁车站乘客导向标志设计要点分析

车站乘客导向标志的设计,应科学严谨、规范统一,体现人性化的特征和理念.分析了目前我国地铁车站乘客导向标志设计和实施过程中存在的主要问题.从一个地铁乘客的角度,对地铁站内乘客基本交通行为的信息流传播过程进行了模型化,进而论证了无缝连接的导向标志的重要性.基于信息流传播理论,从设计和实施的角度给出了以人为本的地铁车站乘客导向标志的设计及实施具体建议.     

船体分段制造质量信息追溯及软件实现

针对船舶企业在质量管控过程中对船体分段制造质量信息追溯的实际需求,提出质量信息追溯的技术方案和解决方案,并阐述船体分段制造质量信息追溯软件的设计思路和功能.该软件通过对原材料及相关证书信息、组件信息、焊缝及焊接实名记录信息的管理,完成原材料信息和焊缝信息追溯,并提供其他人性化的查看和快捷导出、下载等功能,方便其他系统对...     

网络环境下高职院校教师信息素质调查与分析

在信息时代,高职教师的信息素质已成为影响职业教育信息化的关键因素。文中通过对问卷调查获得的数据,分析了本院教师信息素质现状,并就如何提高教师的信息素质进行了探讨。     

考虑出行者行为的多重网络拥堵风险传播模型

城市道路交通拥堵风险传播过程受拥堵预警信息、出行者行为特性及居民出行流量分布等诸多因素影响.本文提出包括道路子网、信息子网和出行子网的多重网络模型,应用改进的UAU-SIR(Unaware-Aware-Unaware-Susceptible-Infective-Recovered)模型,探讨多重网络预警信息下的城市道路...     

信息化战争要求国防交通必须强化五种能力

根据信息化战争的特点,论述了国防交通应努力强化应急保障、机动保障、立体保障、生存防卫和组织指挥等五种能力。     

IFC标准下隧道智能管理系统建立与应用

建筑信息模型(BIM)是一种有效的复杂工程信息综合管理方法,为了实现隧道类岩土工程信息在BIM模型中进行清晰、规范表达的目的,将IFC标准文件针对隧道领域进行相应拓展,实现了不同平台之间信息无损交互传递.通过参数化族建模方式创建隧道构件族库,采用坐标定位的形式拼装隧道工程模型,并将所建立的模型参照IFC拓展标准进行实体...     

Determinants of full and partial household evacuation decision making in hurricane matthew

This paper adds partial household evacuation to the traditional binary evacuate/stay decision. Based on data from a survey of Jacksonville, FL residents after Hurricane Matthew, multinomial (MNL) and random parameter MNL models were developed to determine the influential factors and whether some variables’ effects are more nuanced than prior literature suggests. The random parameter model was preferred to the fixed parameters model. Variables significant in this model included injury concern, certainty about hurricane impact location, age, marital status, family cohesion, and living in mobile or detached homes. Greater injury concern results in lower likelihood of none of the household evacuating and greater likelihood of partial evacuation, but lower likelihood of full household evacuation. Similarly, greater certainty about hurricane impact increased the probability of partial household evacuation but decreased the probability of full evacuation. Respondent age had heterogenous effects; for 85.54% of respondents, additional years of age increased the likelihood of the household staying. Married households had a higher likelihood of staying or evacuating together. Similarly, greater family cohesion was associated with the household remaining together. Living in mobile homes decreased the likelihood that all of the household stays or evacuates and increased the probability of partial household evacuation. Living in a single-family detached home was associated with lower likelihood of all of the household staying or evacuating and a greater likelihood of a partial household evacuation. These findings can inform strategies that influence full or partial household evacuations, material requirements based on these decisions, and ways to reduce family risk.     

Identifying optimal data aggregation interval sizes for link and corridor travel time estimation and forecasting

With the recent increase in the deployment of ITS technologies in urban areas throughout the world, traffic management centers have the ability to obtain and archive large amounts of data on the traffic system. These data can be used to estimate current conditions and predict future conditions on the roadway network. A general solution methodology for identifying the optimal aggregation interval sizes for four scenarios is proposed in this article: (1) link travel time estimation, (2) corridor/route travel time estimation, (3) link travel time forecasting, and (4) corridor/route travel time forecasting. The methodology explicitly considers traffic dynamics and frequency of observations. A formulation based on mean square error (MSE) is developed for each of the scenarios and interpreted from a traffic flow perspective. The methodology for estimating the optimal aggregation size is based on (1) the tradeoff between the estimated mean square error of prediction and the variance of the predictor, (2) the differences between estimation and forecasting, and (3) the direct consideration of the correlation between link travel time for corridor/route estimation and forecasting. The proposed methods are demonstrated using travel time data from Houston, Texas, that were collected as part of the automatic vehicle identification (AVI) system of the Houston Transtar system. It was found that the optimal aggregation size is a function of the application and traffic condition.

Estimation of origin-destination matrices from link counts and sporadic routing data

Estimation of origin-destination (OD) matrices from link count data is a challenging problem because of the highly indeterminate relationship between the observations and the latent route flows. Conversely, estimation is straightforward if we observe the path taken by each vehicle. We consider an intermediate problem of increasing practical importance, in which link count data is supplemented by routing information for a fraction of vehicles on the network. We develop a statistical model for these combined data sources and derive some tractable normal approximations thereof. We examine likelihood-based inference for these normal models under the assumption that the probability of vehicle tracking is known. We show that the likelihood theory can be non-standard because of boundary effects, and provide conditions under which such irregular behaviour will be observed in practice. For regular cases we outline connections with existing generalised least squares methods. We then consider estimation of OD matrices under estimated and/or misspecified models for the probability of vehicle tracking. Theoretical developments are complemented by simulation experiments and an illustrative example using a section of road network from the English city of Leicester.