Airport capacity increase via the use of braking profiles

Many airports are encountering the problem of insufficient capacity, which is particularly severe in periods of increased traffic. A large number of elements influence airport capacity, but one of the most important is runway occupancy time. This time depends on many factors, including how the landing roll procedure is performed. The procedure usually does not include the objective to minimize the runway occupancy time. This paper presents an analysis which shows that the way of braking during landing roll has an essential impact on runway throughput and thus on airport capacity. For this purpose, the landing roll simulator (named ACPENSIM) was created. It uses Petri nets and is a convenient tool for dynamic analysis of aircraft movement on the runway with given input parameters and a predetermined runway exit. Simulation experiments allowed to create a set of nominal braking profiles that have different objective functions: minimizing the runway occupancy time, minimizing noise, minimizing tire wear, maximizing passenger comfort and maximizing airport capacity as a whole. The experiments show that there is great potential to increase airport capacity by optimizing the braking procedure. It has been shown that by using the proposed braking profiles it is possible to reduce the runway occupancy time even by 50%.     

Heteroscedastic Gaussian processes for uncertainty modeling in large-scale crowdsourced traffic data

Accurately modeling traffic speeds is a fundamental part of efficient intelligent transportation systems. Nowadays, with the widespread deployment of GPS-enabled devices, it has become possible to crowdsource the collection of speed information to road users (e.g. through mobile applications or dedicated in-vehicle devices). Despite its rather wide spatial coverage, crowdsourced speed data also brings very important challenges, such as the highly variable measurement noise in the data due to a variety of driving behaviors and sample sizes. When not properly accounted for, this noise can severely compromise any application that relies on accurate traffic data. In this article, we propose the use of heteroscedastic Gaussian processes (HGP) to model the time-varying uncertainty in large-scale crowdsourced traffic data. Furthermore, we develop a HGP conditioned on sample size and traffic regime (SSRC-HGP), which makes use of sample size information (probe vehicles per minute) as well as previous observed speeds, in order to more accurately model the uncertainty in observed speeds. Using 6 months of crowdsourced traffic data from Copenhagen, we empirically show that the proposed heteroscedastic models produce significantly better predictive distributions when compared to current state-of-the-art methods for both speed imputation and short-term forecasting tasks.     

Vehicle electrification in a developing country: Status and issue,from a well-to-wheel perspective

The increase of public attention, scientific research and political interest in environmental problems associated with transportation has provided the motivation for re-invention of electric vehicles. However the usage of grid-dependent EVs with a high-carbon electricity grid might produce more damage to the environment. This study aims to provide an environmental impact comparison of ICEVs, HEVs and EVs during their usage cycle, by modeling their energy consumption (electricity or fuel) and the supply chains of the supplied energy, (well-to-wheel) based on a life cycle assessment. The results show that running EVs with the existing mixed sources of electrical energy produce larger impacts on the environment 60% of the time; when compared to HEVs. When compared to ICEVs, EVs produce a larger environmental impact on 7 out of 15 environmental impact categories. Overall the environmental impacts of EVs are substantial based on the well-to-wheel analysis. It will continue to be so if no change is made to the methods of electricity generation in the near future. Given that the environmental profile of EVs is linked with the existing national electricity generation mix, the national electricity supply must be made cleaner before the electrification of the urban transport system.     

Effectiveness of travel time reliability indicators in the light of the assessment of dynamic managed lane strategy

ABSTRACT

The aim of traffic management is to ensure a high quality of service for a maximum number of users by decreasing congestion and increasing safety. Uncertainty of travel times decreases the quality of service and leads end users to modify their plans regardless of the average travel time. Indicators describing travel time reliability are being developed and should be used in the future both for the optimization and for the assessment of active traffic management operations. This article discusses the efficiency of certain reliability indicators in an ex-post assessment of a traffic management strategy. Ex-post assessment is based on an observational before–after study. As some factors other than the studied management strategy may intervene between the two periods, and as most reliability indicators require knowledge of the full travel time distribution and not only its average, a methodology is developed for the identification of the impact of these exogenous factors on the whole distribution. Many reliability indicators are split into different parts allowing the identification of the part due to the management strategy impact. The methodology is tested numerically on a managed lane operation consisting of Hard Shoulder Running (HSR) at rush hour on a section of a French motorway. The variation of some reliability indicators appears misleading, whereas the splitting of the indicators increases our understanding of the strategy and highlights its impact. The paper gives the reliability assessment of the HSR field test and discusses different reliability indicators to identify their potential performances and shortcomings.     

我国商业银行信息化建设研究综述

我国商业银行信息化建设已走过近20年的路程,在取得巨大业绩的同时也存在若干不足之处．文章在总结我国商业银行信息化建设经验的基础上,对其信息化建设的现状进行了深入的分析,同时指出了我国商业银行信息化建设的总体规划方向,以期大幅度提高我国商业银行的信息化建设绩效。     

公路生态系统服务功能分析及评估

文章探讨了公路生态系统的生态服务功能,提出价值评估指标体系及定量评估方法,为公路生态系统的恢复或重建提供理论依据,对全面、正确评价公路生态系统有积极意义。     

厦门地铁2号线钻探工程海上通航安全评估

依据港口通航现状、港口发展规划、附近海域船舶交通现况,分析通航安全形势,预测厦门轨道交通2号线跨海路段施工期间,船舶交通流可能的变化和通航环境、通航秩序的适应能力,论证在施工期间存在的通航安全风险、主要问题及通航安全保障能力,并提出保障通航安全的可行性建议和措施.     

基于名义应力法的动车组车体净水箱吊装部件疲劳强度分析

针对高速运行动车组车体悬挂设备振动疲劳损伤问题,以某型动车组车顶净水箱吊装结构为研究对象,采用名义应力法对吊装结构的焊缝部位进行疲劳强度评估.根据EN 12663标准确定净水箱的工作载荷工况,采用有限元法计算了各工况下结构的振动响应,并基于BS标准计算了焊缝疲劳评估点的寿命.假定各载荷工况出现频率相同的情况下,构造了工作载荷历程,采用Fe-safe软件对焊缝的疲劳寿命进行了仿真分析.两种方法分析结果均表明:焊缝1与焊缝2寿命最低,是结构最易发生疲劳破坏的位置;焊缝位于筋板表面的焊趾寿命低于位于主支撑板表面的焊趾寿命.     

一种适用于虚拟惯量优化控制研究的风电场等值建模方法

大型风电场的建模分析是研究风电参与电力系统频率调控的前提。风电场内机组众多且运行方式各异,根据风电机组的整体结构及虚拟惯量控制策略的基本原理,在直驱式风电机组单机详细模型的基础上进行简化,然后按典型风速将风电场内全部机组分为三群,同群机组采用聚合方法得到等值机组,从而形成最终的风电场多机并网等值模型。考虑风速扰动和负荷扰动两种情况,通过Matlab/Simulink软件对比校验所建模型,仿真结果显示了该建模方法的有效性。     

基于参数化船型的阻力优化研究

船型几何模型的参数化表达,是船型多学科设计优化的基础。其作用是为各学科分析和优化提供一个统一的几何模型,并根据各学科分析结果自动修改调整船体型线。文中尝试使用Friendship进行船体完全参数化建模,并使用该软件中的feature编程功能编程实现shipflow型值数据的提取;通过改变一系列重要的船型参数实现变换船型几何模型,以获得满足性能需求的船型。最后利用该软件的优化框架,采用切线搜索法 (Tangent Search, TSearch) 完成1300TEU集装箱船的兴波阻力优化,优化球首和前体船体曲面。结果表明,该参数化方法在改进船型水动力性能方面有很好的效果。