走廊层面交通小区划分方法的优化

基于公交客运走廊划分的交通小区，可为走廊公交线网优化提供更为符合公交乘客出行特征的需求分析和预测基础.本研究针对公交客运走廊特点，将走廊划分为直接影响区和间接影响区，提出分层次的交通小区划分理论.针对走廊不同影响区在需求预测和分析中对结果精度要求的不同，基于大数据选取更加适合公交走廊交通小区划分的聚类指标，提出直接影响区细分和间接影响区合并的划分方法，并通过引入聚类因子初步确定聚类数目和交通小区中心对传统聚类方法进行改进，克服了传统聚类方法随机选取聚类数目和中心而影响聚类精度的不足.最后，基于多源异构大数据对广渠路走廊进行实例验证，结果表明，本研究提出的分层次小区划分方法较传统方法在适用于公交客运走廊需求分析和预测划分精度方面更优.     

无接触网有轨电车车地无线传输系统研究

针对无接触网有轨电车设计了一套基于大数据分析技术及物联网技术的车地无线传输系统。介绍了该系统的系统架构、系统功能及设计要点。该系统能够显著提升列车车地数据传输的安全性、高效性及便捷性,提高了无接触网有轨电车车地传输技术和智能化应用水平。同时,该系统具有良好的可扩展性,可满足各类城市轨道交通车辆车载设备调试、维护以及数据传输的应用需求。     

浅谈鲁南高铁CSD瞬时干扰率优化工作

在鲁南高铁曲阜东至日照段联调联试中.日照西站附近总是出现CSD瞬时干扰问题.为此对网络、设备进行研究,分析A和Abis接口监测数据码流,查看有关参数设置是否匹配.找出问题所在,修改设备参数后解决了问题。     

Exploring the role of social capital influence variables on travel behaviour

This paper explores the potential role of individual trip characteristics and social capital network variables in the choice of transport mode. A sample of around 100 individuals living or working in one suburb of Madrid (i.e. Las Rosas district of Madrid) participated in a smartphone short panel survey, entering travel data for an entire working week. A Mixed Logit model was estimated with this data to analyze shifts to metro as a consequence of the opening of two new stations in the area. Apart from classical explanatory variables, such as travel time and cost, gender, license and car ownership, the model incorporated two “social capital network” variables: participation in voluntary activities and receiving help for various tasks (i.e. child care, housekeeping, etc.). Both variables improved the capacity of the model to explain transport mode shifts. Further, our results confirm that the shift towards metro was higher in the case of people “helped” and lower for those participating in some voluntary activities.     

双后桥平衡悬架骑马螺栓的布置分析

分析了双后桥车型底盘平衡悬架板簧连接骑马螺栓竖直布置与内八斜拉布置2种布置形式对平衡悬架系统的性能的影响,并通过CAE软件完成了相应骑马螺栓的受力及变形分析。通过分析可知,骑马螺栓内八字斜拉布置应力分布优于竖直布置结构,该布置可增加板簧的有效作用长度。     

浅谈GPS在高等级公路测量中的应用和发展前景

叙述GPS的组成,GPS系统在公路测量中与传统的测量设备对比的优点,GPS测量在高速公路中的应用及发展前景。     

Using smartphones as a very low-cost tool for road inventories

Road inventories are a key component in the planning of road networks as they allow for efficient management and a better return on the investment. Current techniques for carrying out road inventories are expensive and entail long planning processes and data postprocessing. Furthermore, these inventories are only useful to those parties interested in designing and building road networks. This study presents a new method for create road inventories based on the use of the latest generation cellular phones, also called smartphones. This paper describes the use of several mobile apps developed for this project that were implemented during the different stages of road inventory process. The results indicate that the data processing speed, its low cost, and the ease of implementation from any type of vehicle validate the proposed procedure as an invaluable tool (1) to do inventories of all types of road networks that are not accessible to cars; (2) to manage the routine maintenance of small road networks; and (3) as a basis for future research projects on road design and outline.     

A cell-based logit-opportunity taxi customer-search model

This paper proposes a cell-based model to predict local customer-search movements of vacant taxi drivers, which incorporates the modeling principles of the logit-based search model and the intervening opportunity model. The local customer-search movements were extracted from the global positioning system data of 460 Hong Kong urban taxis and inputted into a cell-based taxi operating network to calibrate the model and validate the modeling concepts. The model results reveal that the taxi drivers’ local search decisions are significantly affected by the (cumulative) probability of successfully picking up a customer along the search route, and that the drivers do not search their customers under the random walk principle. The proposed model helps predict the effects of the implementation of the policies in adjusting the taxi fleet size and the changes in passenger demand on the customer-search distance and time of taxi drivers.     

An integrated analysis of workers’ physically active activity and active travel choice behavior

Using Texas add-on sample data from the 2009 National Household Travel Survey, this study examines adult workers’ daily active choice decisions in the context of physical activity and attendant health benefits. The study looked at workers’ two choice behaviors: active activity and active travel. The first choice behavior, active activity, is developed as an ordered-response model based on the number of physically active recreational activities pursued during the workday. The second choice behavior, active travel, is developed as a binary-response model that examines workers’ active travel choices—whether or not the worker used any active mode of travel during the same workday. The study improves the understanding and knowledge of observed factors influencing workers’ physically active activity-travel behavior. The study also provides several observations regarding the role (and constraints) of employment in individuals’ active choices. Using a flexible copula modeling methodology, we explore the true correlation (or dependence) between the two behavior choices that could occur due to the presence of unobserved factors, suggesting a simultaneously low or simultaneously high propensity for being physically active across workers. The study findings suggest that transportation and public health policy makers can mutually benefit from encouraging workers to be physically active (from an activity and/or travel perspective). Overall, the study draws attention to the integrated nature of the public health and transportation fields, thereby providing a distinct view of active/inactive choice behavior. To our knowledge, this is the first study exploring a rich variety of components for workers’ active activity-travel behavior through a robust copula approach.