Development of driving cycles for electric vehicles in the context of the city of Florence

Strong efforts are spent in automotive engineering for the creation of so called Driving Cycles (DCs). Vehicle DC development has been a topic under research over the last thirty years, since it is a key activity both from an authority and from an industrial research point of view. Considering the innovative characteristics of Electric Vehicles (EVs) and their diffusion on certain contexts (e.g. city centers), the demand for tailored cycles arises. A proposal for driving data analysis and synthesis has been developed through the review and the selection of known literature experiences, having as a goal the application on a EVs focused case study. The measurement campaign has been conducted in the city of Florence, which includes limited traffic areas accessible to EVs. A fleet of EVs has been monitored through a non-invasive data logging system. After data acquisition, time-speed data series have been processed for filtering and grouping. The main product of the activity is a set of DCs obtained by pseudo-randomized selection of original data. The similarity of synthetic DCs to acquired data has been verified through the validation of cycle parameters. Finally, the new DCs and a selection of existing ones are compared on the basis of relevant kinematic parameters and expected energy consumption. The method followed for the creation of DCs has been implemented in a software package. It can be used to generate cycles and, under certain boundary conditions, to get a filtered access to the measured data and provide integration within simulation environment.     

我国天然胶期货市场有效性实证分析

以上海期货交易所天然橡胶7月合约的每日收盘价为研究对象,采用的方法是单位根检验和方差比检验相结合,通过检验期货价格序列是否服从随机步游过程,来判断市场是否具有弱式有效性。实证检验结果表明,在第一、第二、第四和第五阶段,市场是弱式有效的,但在第三阶段市场并不具有弱式有效性,检验结果与近年来我国天然胶期货市场的实际发展情况基本吻合。     

慢行交通系统发展经验及对厦门的启示

在城市化、机动化快速发展的今天,慢行交通系统的发展因其生态环保、灵活方便、健康活力等特点而日益受到人们的关注。本文在分析慢行交通系统概念及特性的基础上,总结了国内外慢行交通系统发展先进理念及经验．提出了厦门发展慢行交通系统的几点启示。     

陀螺角度随机游走误差对旋转惯导系统的影响

采用旋转调制技术可以抑制惯导系统误差随时间发散的趋势,然而,随机误差是限制旋转惯导系统精度继续提高的因素之一。对于高精度应用领域,陀螺角度随机游走误差也是惯导系统设计时考虑的因素。本文从对准和导航2个过程出发,研究陀螺角度随机游走误差对惯导系统的影响,结合激光陀螺实测数据进行艾伦方差分析,并利用实测结果进行仿真验证。结果表明,陀螺角度随机游走引起惯导系统振荡误差,0.0005°/√h的角度随机游走导航7天引起的位置误差大约1.3 nm。     

船体分段下胎封固支撑位置优化算法的研究

分段下胎封固是分段建造过程中的一个工艺环节,它关系到分段后续装配过程的精度控制。文章在船体分段下胎封固的一般工艺原则指导下,对分段下胎封固的支撑点设计进行了研究,通过计算分段在下胎封固之后的变形,以结构变形量最小为优化目标,采用随机行走法对封固方案进行了优化。以某一双层底分段为例,对优化之后的分段变形量进行了分析,结果符合预期,表明该优化算法可以用于分段的下胎封固支撑点优化设计。同时,文章利用MATLAB开发了针对下胎封固工艺方案设计的可视化界面。     

一类格子上有限维不可约随机游动常返性的证明

格子上的随机游动是随机过程理论中的一类比较特殊的随机游动.而常返性和非常返性则是这一类随机游动所讨论的一条重要性质,对于一维格子上(E1ξ=0)的随机游动是常返的,对于二维格子上的不可约随机游动也是常返的,而对于维数大于或等于3的情形和一维和二维的并不一样,文章主要证明了其是非常返的.这个结论又解决了一类随机游动的一个常返性问题.     

社区步行通达性对独栋住宅房价的效益评估--美国德克萨斯州奥斯丁市空间特征分析

通过分析美国德克萨斯州奥斯丁市2010—2012年独栋住宅的销售价格,以街道智慧步行指数(Street Smart Walk Score)和人行道密度(Sidewalk Density)作为衡量指标,研究社区步行通达性对房价的影响。使用Cliff-Ord空间特征模型(即广义空间模型,General Spatial Model,或者SAC)控制空间自相关影响。结果表明：在依赖小汽车的社区通过增加设施可达性来提升步行通达性的举措并不能提高房价;增加人行道也只能最小限度地提高房价。投资社区便利设施和人行道对适宜步行社区的房价提升效果比依赖小汽车的社区显著。     

Efficient Search in P2P File Sharing System

A new routing algorithm of peer-to-peer file sharing system with routing indices was proposed, in which a node forwards a query to neighbors that are more likely to have answers based on its statistics. The proposed algorithm was tested by creating a P2P simulator and varying the input parameters, and was compared to the search algorithms using flooding （FLD） and random walk （RW）. The result shows that with the proposed design, the queries are muted effectively, the network flows are reduced remarkably, and the peer-to-peer file sharing system gains a good expansibility.     

Caching Scheme Based on Power-Law Characteristic in Unstructured P2P Networks

In order to reduce the traffic load and improve the availability of the shared resources in unstructured P2P networks, a caching scheme combining alternative index and adaptive replication (AIAR) is presented. AIAR uses random walk mechanism to disperse the caching information of resources in the network based on its power-law characteristic, and dynamically adjusts replicas according to the visit frequency on resources and the degree information of peers. Subsequent experimental results show that the proposed AIAR scheme is beneficial to improve the search performance of success rate and respond speed. In addition, compared to some existing caching scheme, AIAR can perform much better in success rate, especially in a dynamic environment.     

Estimation of bus dwell time using univariate time series models

A significant proportion of bus travel time is contributed by dwell time for passenger boarding and alighting. More accurate estimation of bus dwell time (BDT) can enhance efficiency and reliability of public transportation system. Regression and probabilistic models are commonly used in literatures where a set of independent variables are used to define the statistical relationship between BDT and its contributing factors. However, due to technical and monetary constraints, it is not always feasible to collect all the data required for the models to work. More importantly, the contributing factors may vary from one bus route to another. Time series based methods can be of great interest as they require only historical time series data, which can be collected using a facility known as automatic vehicle location (AVL) system. This paper assesses four different time series based methods namely random walk, exponential smoothing, moving average (MA), and autoregressive integrated moving average to model and estimate BDT based on AVL data collected from Auckland. The performances of the proposed methods are ranked based on three important factors namely prediction accuracy, simplicity, and robustness. The models showed promising results and performed differently for central business district (CBD) and non‐CBD bus stops. For CBD bus stops, MA model performed the best, whereas for non‐CBD bus stops, ARIMA model performed the best compared with other time series based models. Copyright © 2014 John Wiley & Sons, Ltd.