Classification of Livebus arrivals user behavior

With the increasing use of Intelligent Transport Systems, large amounts of data are created. Innovative information services are introduced and new forms of data are available, which could be used to understand the behavior of travelers and the dynamics of people flows. This work analyzes the requests for real-time arrivals of bus routes at stops in London made by travelers using Transport for London's LiveBus Arrivals system. The available dataset consists of about one million requests for real-time arrivals for each of the 28 days under observation. These data are analyzed for different purposes. LiveBus Arrivals users are classified based on a set of features and using K-Means, Expectation Maximization, Logistic regression, One-level decision tree, Decision Tree, Random Forest, and Support Vector Machine (SVM) by Sequential Minimal Optimization (SMO). The results of the study indicate that the LiveBus Arrivals requests can be classified into six main behaviors. It was found that the classification-based approaches produce better results than the clustering-based ones. The most accurate results were obtained with the SVM-SMO methodology (Precision of 97%). Furthermore, the behavior within the six classes of users is analyzed to better understand how users take advantage of the LiveBus Arrivals service. It was found that the 37% of users can be classified as interchange users. This classification could form the basis of a more personalized LiveBus Arrivals application in future, which could support management and planning by revealing how public transport and related services are actually used or update information on commuters.     

Suspension system state estimation using adaptive Kalman filtering based on road classification

This paper provides a new method to solve the problem of suspension system state estimation using a Kalman Filter (KF) under various road conditions. Due to the fact that practical road conditions are complex and uncertain, the influence of the system process noise variance and measurement noise covariance on the estimation accuracy of the KF is first analysed. To accurately estimate the road condition, a new road classification method through the vertical acceleration of sprung mass is proposed, and different road process variances are obtained to tune the system’s variance for the application of the KF. Then, road classification and KF are combined to form an Adaptive Kalman Filter (AKF) that takes into account the relationship of different road process noise variances and measurement noise covariances under various road conditions. Simulation results show that the proposed AKF algorithm can obtain a high accuracy of state estimation for a suspension system under varying International Standards Organisation road excitation levels.     

Fault classification method for the driving safety of electrified vehicles

A fault classification method is proposed which has been applied to an electric vehicle. Potential faults in the different subsystems that can affect the vehicle directional stability were collected in a failure mode and effect analysis. Similar driveline faults were grouped together if they resembled each other with respect to their influence on the vehicle dynamic behaviour. The faults were physically modelled in a simulation environment before they were induced in a detailed vehicle model under normal driving conditions. A special focus was placed on faults in the driveline of electric vehicles employing in-wheel motors of the permanent magnet type. Several failures caused by mechanical and other faults were analysed as well. The fault classification method consists of a controllability ranking developed according to the functional safety standard ISO 26262. The controllability of a fault was determined with three parameters covering the influence of the longitudinal, lateral and yaw motion of the vehicle. The simulation results were analysed and the faults were classified according to their controllability using the proposed method. It was shown that the controllability decreased specifically with increasing lateral acceleration and increasing speed. The results for the electric driveline faults show that this trend cannot be generalised for all the faults, as the controllability deteriorated for some faults during manoeuvres with low lateral acceleration and low speed. The proposed method is generic and can be applied to various other types of road vehicles and faults.     

高分辨率罗兰C天波延迟估计新技术

提出了一种基于特征分解的多信号分类算法估计罗兰C接收机天波延迟的信号处理新技术。它为接收机基准点的实时设置提供了一种新方法。常规接收机为了防止天波干扰，将基准点设置在一个固定位置上，导致基准点处信噪比受包络限制而较低，从而大大增加了对准基准点的时间。利用这项技术，我们在低信噪比条件下分离出了地波和天波的到达时刻。这就使得接收机能根据天波延迟变化实时选择基准点最佳位置，并能利用地波到达时刻进行周期选择。由于此法有助于增加基准点处的信噪比，减少对准基准点的时间，因而能极大地提高现有罗兰C接收机的性能。还显示了新方法较IFFF方法有更高的分辨率。     

船用微机监测系统的故障诊断与排除

由于船用微机监测系统工作条件的特殊性,系统运行过程中经常出现故障。文章根据监测系统的组成及工作特点,论述了监测系统的故障分类,讨论了分析故障的一般方法,并分析监测系统常见故障的原因及对策。     

铁路轨枕现状及发展

研究目的:本文对轨枕的主要功能和分类方法加以论述,同时简述我国铁路轨枕的发展过程及存在的问题。研究方法:通过搜集资料了解我国铁路轨枕及城市轨道交通轨枕的发展历程;总结轨枕分类方法;介绍木枕、混凝土枕及城轨交通用特殊轨枕的主要特点,并调查研究了各类轨枕在设计、制造、使用、养护维修中存在的问题。研究结果:提供了先进国家适用于高速铁路轨枕的发展动态,以及我国已运营4年的秦沈客运专线用轨道板和正处于设计招标阶段的京津城际轨道交通用轨道板等信息。研究结论:我国铁路轨枕及城市轨道交通轨枕的发展应遵循:增加混凝土枕类型以满足不同铺设条件的需要;提高混凝土枕的使用寿命,并开发研制轨枕新品种,适应我国铁路高速、重载以及城市轨道交通迅猛发展的需求。     

山区双车道公路路线设计车型分类标准

为研究建立公路路线设计标准车型,通过对西部山区双车道公路的实地交通调查,并结合我国在用车型统计,建立了各类营运车辆车型参数数据库;在详细统计分析现有车型的尺寸、载质量和功率质量比分布规律的基础上,以满足85%的车型外廓尺寸和载质量为标准,采用双因素聚类分析方法对各种车型的功率质量比进行聚类分层计算,根据外廓尺寸相近的原则进行归并后,提出了山区公路路线设计车型的小型车、大型车外廓尺寸分类标准。在此分类基础上,研究了用于公路纵断面设计的载重汽车动力性能标准,通过大量实地观测资料和统计分析,提出了载重汽车上坡动力性能曲线,建立了速度折减量与坡度、坡长之间的关系曲线,以速度折减量作为公路纵坡和坡长的设计关键指标。     

郑万高铁大断面岩质隧道掌子面稳定性评价及控制措施

为建立施工阶段大断面隧道掌子面稳定性评价方法,结合郑万高铁大型机械化特点,对郑万高铁湖北段隧道掌子面地质信息进行统计分析,将掌子面稳定性分为A整体稳定、B局部掉块、C上半断面不稳定和D全断面不稳定4个级别,并建立以岩石坚硬程度、岩体完整程度和地下水状态3个指标的掌子面稳定性定性分级方法,得出围岩级别与掌子面稳定性的对应关系。研究结果表明： 1）岩石坚硬程度、岩体完整程度和地下水状态是围岩分级指标中使用率最高的3个指标; 2）Ⅰ、Ⅱ、Ⅲ级围岩的掌子面稳定性为A级。     

郑万高铁隧道大断面机械化施工关键技术研究

为实现大断面隧道机械化施工,针对郑万高速铁路湖北段隧道机械化施工所面临的掌子面稳定性控制、支护结构参数优化、机械化施工工法及施工工艺参数选取等主要问题,采取现场试验、资料调研、理论分析等手段,提出掌子面稳定性综合分级方法及稳定性控制措施,并对超前支护、洞身支护参数进行优化。郑万高速铁路采用全断面法和微台阶法2种工法进行施工,同时,对高压劈裂注浆、低预应力锚杆、超挖控制、高标号初喷混凝土等施工工艺进行探索和应用; 在信息化项目管理平台的基础上,建立基于施工动态管理的隧道作业面分类管理方法。研究成果在郑万高速铁路的成功应用将极大提高隧道建设的机械化水平,为隧道机械化施工提供参考。     

软件缺陷分类及其度量技术研究

研究了软件缺陷管理的理论和方法，并在对各种软件缺陷分类方法进行深入分析和研究的基础上，针对目前软件工程管理中强调的软件过程改进方法，提出一种针对软件过程的软件分类方法；接着针对缺陷定量分析的需要，提出了一组缺陷度量公式；建立了基于过程的缺陷管理模型。