广西公路项目平交式工程安全评价探讨

文章介绍了公路项目平面交叉口工程安全评价的目的,分析了影响公路项目平面交叉口工程安全的因素,并以广西来马高速马山南互通出口与G210公路平交口项目为工程实例,从平纵线形、视距、交叉口间距、交通工程、施工方案等方面对公路项目平交式工程进行安全评价。     

雾天高速公路交通事故成因分析及管理措施

文章分析了雾天高速公路交通事故的成因与特征,提出了相应的交通管制方式和处置措施,为雾天高速公路的交通管理工作提供思路。     

公路路线设计中运行速度理论检验的方法

我国目前的公路路线设计采用设计速度理论,设计速度是个定值,而多年的实践表明,车辆实际的运行速度总是随公路线形等条件的改变而变化,所以设计速度理论本身存在一定的局限性,需要采用动态的运行速度对公路的路线设计进行安全性检验,以确保行车安全。文章结合设计实例,探讨公路路线设计中运行速度理论检验的方法。     

高速公路石方路堑爆破技术分析

文章结合工程实践,针对爆破开挖的难点问题,提出了微差松动和留碴挤压爆破相结合的爆破新技术,并对该爆破技术方案、施工要点及安全施工措施等进行了介绍。     

宁武高速公路隧道线形设计探讨

线形设计是隧道工程建设和行车安全的基本保障。文章结合宁武高速公路隧道设计实例,介绍隧道洞口及洞内的线形设计方法及注意事项,为隧道线设计提供参考。     

运营公路隧道安全评估

通过对某运营公路隧道的衬砌和路面状况、衬砌厚度与其背后回填状况、衬砌混凝土强度、隧道净空断面、风道吊杆和吊顶板、隧道路面横坡及抗滑性能等的调查与检测,对其安全性进行了评估,结果表明下行隧道病害严重,已达到“2A”级,需要尽早对隧道衬砌背后的空洞、隧道衬砌裂缝和渗漏水等问题进行全面综合整治。文章介绍了该隧道安全评估的检测项目、方法及频率。     

公路除雪及安全技术的研究

文章介绍了西部交通科技建设项目公路除雪及安全技术研究的目的意义、技术成果,为我国寒冷地区冬季道路养护提供了一套经济有效的除雪防滑技术,其研究成果具有推广应用价值。     

基于PHA-LEC-SCL法公路隧道施工安全评价研究

为了制定科学的公路隧道施工安全评价的基本模式,针对公路隧道施工的危险、有害因素的危害程度及特殊工艺,将公路隧道施工系统分为隧道开挖、爆破、施工用电、施工通风、出碴与洞内运输、支护衬砌等6个主要子系统.运用预先危险性分析法(PHA)对公路隧道施工的危险、危害因素进行辨识和定性分析,结合作业条件危险性评价法(LEC)对公路隧道施工系统中各子系统进行危险性评价,定量分析计算PHA中的子系统各个危险因素的危险等级,并采用安全检查表(SCL)对公路隧道施工现场进行安全综合评价,建立了安全评价方法之间的内在联系.PHA-LEC-SCL法确立了公路隧道施工安全评价的基本模式.     

基于ANSYS的公路隧道衬砌结构安全分析

文章基于大型通用软件ANSYS,以深埋条件下隧道为例,采用荷载结构法,对考虑仰拱作用的各级围岩两车道公路隧道衬砌结构进行计算,求解其强度安全系数并进行相关安全分析,所得结论可为工程人员参考。     

Comparative analysis of traveler destination choice models by method of sampling alternatives

In a destination choice model, it is important to introduce alternatives that have been adequately aggregated into traffic analysis zone levels based on spatial similarities and feasibility of analysis, because considering every spatial location possible for the traveler as an elemental alternative is intractable in terms of data management and analysis. In this study, we derive strata for alternative sets through simple random sampling and stratified importance sampling based on the concept of Moran’s I. As a result of comparative analysis, we are able to reduce errors by drawing an adequate number of samples for the destination choice model’s choice alternative sets based on measures of spatial similarity.     

Development of crash prediction models with individual vehicular data

Typical engineering research on traffic safety focuses on identifying either dangerous locations or contributing factors through a post-crash analysis using aggregated traffic flow data and crash records. A recent development of transportation engineering technologies provides ample opportunities to enhance freeway traffic safety using individual vehicular information. However, little research has been conducted regarding methodologies to utilize and link such technologies to traffic safety analysis. Moreover, traffic safety research has not benefited from the use of hurdle-type models that might treat excessive zeros more properly than zero-inflated models.This study developed a new surrogate measure, unsafe following condition (UFC), to estimate traffic crash likelihood by using individual vehicular information and applied it to basic sections of interstate highways in Virginia. Individual vehicular data and crash data were used in the development of statistical crash prediction models including hurdle models. The results showed that an aggregated UFC measure was effective in predicting traffic crash occurrence, and the hurdle Poisson model outperformed other count data models in a certain case.     

The determinants of car ownership in England and Wales from anonymous 2001 census data

Within the transportation research literature, the attempt to understand and predict the level of car ownership is probably one of the most popular areas of study. The primary reason for this is understandable, having access to a vehicle increases an individual’s (or their household’s) travel options, leading to greater mobility. Secondary reasons for this scrutiny include the need to predict future transport investment in road infrastructure and the commercial demand for new vehicles. This paper attempts to predict the level of household car ownership as a function of the characteristics of the household and the individuals that make up the household. The primary data source for this study comes from the 2001 United Kingdom Census and the analysis methods used are from the discipline of data mining. The results of this study are in line with those from previous research but show a potential to predict the higher levels of household car ownership with greater accuracy than other similar studies.     

A gradient boosting logit model to investigate driver’s stop-or-run behavior at signalized intersections using high-resolution traffic data

Driver’s stop-or-run behavior at signalized intersection has become a major concern for the intersection safety. While many studies were undertaken to model and predict drivers’ stop-or-run (SoR) behaviors including Yellow-Light-Running (YLR) and Red-Light-Running (RLR) using traditional statistical regression models, a critical problem for these models is that the relative influences of predictor variables on driver’s SoR behavior could not be evaluated. To address this challenge, this research proposes a new approach which applies a recently developed data mining approach called gradient boosting logit model to handle different types of predictor variables, fit complex nonlinear relationships among variables, and automatically disentangle interaction effects between influential factors using high-resolution traffic and signal event data collected from loop detectors. Particularly, this research will first identify a series of related influential factors including signal timing information, surrounding traffic information, and surrounding drivers’ behaviors using thousands drivers’ decision events including YLR, RLR, and first-to-stop (FSTP) extracted from high-resolution loop detector data from three intersections. Then the research applies the proposed data mining approach to search for the optimal prediction model for each intersection. Furthermore, a comparison was conducted to compare the proposed new method with the traditional statistical regression model. The results show that the gradient boosting logit model has superior performance in terms of prediction accuracy. In contrast to other machine learning methods which usually apply ‘black-box’ procedures, the gradient boosting logit model can identify and rank the relative importance of influential factors on driver’s stop-or-run behavior prediction. This study brings great potential for future practical applications since loops have been widely implemented in many intersections and can collect data in real time. This research is expected to contribute to the improvement of intersection safety significantly.     

道路运输达标车辆核查数据挖掘应用探索

道路运输达标车辆核查系统作为车辆核查信息化手段,有效地提高了道路运输达标车辆核查效率。本文首先选取达标客车核查数据进行了统计分析,探索利用数据关联规则算法试验研究数据规律,最后对核查数据质量管理提出了一些建议,对更科学合理地管理道路运输车辆生产和核查具有重要的意义,也为完善相关法律法规提供决策支持。     

How big data enriches maritime research – a critical review of Automatic Identification System (AIS) data applications

ABSTRACT

The information-rich vessel movement data provided by the Automatic Identification System (AIS) has gained much popularity over the past decade, during which the employment of satellite-based receivers has enabled wide coverage and improved data quality. The application of AIS data has developed from simply navigation-oriented research to now include trade flow estimation, emission accounting, and vessel performance monitoring. The AIS now provides high frequency, real-time positioning and sailing patterns for almost the whole world's commercial fleet, and therefore, in combination with supplementary databases and analyses, AIS data has arguably kickstarted the era of digitisation in the shipping industry. In this study, we conduct a comprehensive review of the literature regarding AIS applications by dividing it into three development stages, namely, basic application, extended application, and advanced application. Each stage contains two to three application fields, and in total we identified seven application fields, including (1) AIS data mining, (2) navigation safety, (3) ship behaviour analysis, (4) environmental evaluation, (5) trade analysis, (6) ship and port performance, and (7) Arctic shipping. We found that the original application of AIS data to navigation safety has, with the improvement of data accessibility, evolved into diverse applications in various directions. Moreover, we summarised the major methodologies in the literature into four categories, these being (1) data processing and mining, (2) index measurement, (3) causality analysis, and (4) operational research. Undoubtedly, the applications of AIS data will be further expanded in the foreseeable future. This will not only provide a more comprehensive understanding of voyage performance and allow researchers to examine shipping market dynamics from the micro level, but also the abundance of AIS data may also open up the rather opaque aspect of how shipping companies release information to external authorities, including the International Maritime Organization, port states, scientists and researchers. It is expected that more multi-disciplinary AIS studies will emerge in the coming years. We believe that this study will shed further light on the future development of AIS studies.     

某钢桁架桥基于静力数据的有限元模型修正

在既有桥梁的工作状态和使用安全评估中,需要建立能够精确模拟结构目前工作状态的有限元模型。文章以一座既有钢桁架桥为例,在参数灵敏度分析的基础上,以结构设计参数为修正参数,借助ANSYS的优化设计模块对该桥的有限元模型进行了基于静力数据的有限元模型修正。修正后的有限元模型的静力特性更加接近于该桥的实际结构,可以用于对全桥工作性能的评定和加固方案的设计。