上海市公交站牌的调查与分析

论文分析了上海三种常见公交站牌的优缺点,通过问卷调查的方式和参考网络上市民的意见和建议,了解市民对于现有公交站牌的评价,对公交站牌设计中存在的问题进行总结,并提出了改进建议.     

中途站的合理位置设计与分析

本文重点对中途站的合理位置进行设计与分析,同时根据中途站的具体位置给出中途站样式的建议,希望能够优化中途站设计,不仅将中途站对交通的干扰降为最低,也力争做到以人为本。     

增大高速区电制动力的方法

针对现有电力机车高速区电制动力下降,导致车辆维修费用增加问题,提出了2种解决办法,即在牵引逆变器和电机绕组间串接电阻或电容,来提高电制动力和改善功率因数,并从理论和实践的角度作了充分的论证。对电阻短路时引起的电流和转矩变动进行了试验分析,并提出了解决方法。     

蒙皮粘接技术在大客车上的应用

介绍蒙皮粘接技术在大客车上的应用.     

基于CAN总线数据的LNG公交车能源 消耗分析

为研究公交车辆在正常运营中能源消耗的影响因素,通过CAN总线数据与公交IC 卡数据 的融合,从站点间断面以及站点两个层面对北京市液化天然气（LNG） 公交车辆的能源消耗影响 因素进行了相关分析。首先分析了不同道路等级下的能耗消耗,然后利用SPSS 的相关性分析工 具对能耗的影响因素进行了分析。通过分析发现,公交车辆在公交专用道路段的行驶速度约为非 公交专用道的1.7 倍,能源消耗约为无公交专用道的70%。能源消耗由高到低依次为辅路、匝 道、主干路。同时在站点层面,车辆的能源消耗主要受到停滞时间、车辆的加减速时间、乘客的 上下车人数的影响。期望通过此项研究能够帮助公共交通的运营和规划部门制定相应的政策,以 达到减少能源消耗的同时提高公共交通运行效率的目的。     

含串补电容电气化铁路馈线故障测距算法

含串联补偿电容的电气化铁路牵引电网线路的电抗一距离关系不是单调的，按常规的电抗查表测距法，每个故障点会对应2个或多个定位点．通过对含串补电容馈线故障模型特性的分析，提出了一个新的判别方法．对不同的故障角和过渡电阻的ATP仿真以及MATLAB程序分析结果验证，该方法能够判断出故障与区间串补电容的相对位置．给出了含2个串补电容的电气化铁路馈线故障分段查表测距算法．     

基于VISA技术的高速USB数据采集系统

高速USB数据采集系统的设计严格遵循USB2.0协议,实现了主机和测试设备之间简单、快速、可靠的连接和通信.该文介绍了这种数据采集系统的硬件组成、驱动程序和固件程序的设计以及采用虚拟仪器软件LabWindows/CVI在VISA技术上开发应用程序的设计方法.     

Adaptive control algorithm to provide bus priority with a pre-signal

In urban areas, where road space is limited, it is important to provide efficient public and private transportation systems to maximize person throughput, for example from a signalized intersection. To this end, this research looks at providing bus priority using a dedicated bus lane which is terminated upstream of the intersection, and placing an additional signal at this location, called a pre-signal. Although pre-signals are already implemented in some countries (e.g. UK, Denmark, and Switzerland), an adaptive control algorithm which responds to varying traffic demands has not yet been proposed and analyzed in the literature. This research aims to fill that gap by developing an adaptive control algorithm for pre-signals tailored to real-time private and public transportation demands. The necessary infrastructure to operate an adaptive pre-signal is established, and guidelines for implementation are provided. The relevant parameters regarding the boundary conditions for the adaptive algorithm are first determined, and then quantified for a typical case using a micro-simulation model. It is demonstrated with case studies that, under all considered scenarios, implementing a pre-signal with the proposed adaptive control algorithm will result in the least average person delay at the intersection. The algorithm is expected to function well with a wide range of car demands, bus frequencies, and bus passenger occupancies. Moreover, the algorithm is robust to errors in these input values, so exact information is not required.     

Bus arrival time calculation model based on smart card data

Bus arrival time is usually estimated using the boarding time of the first passenger at each station. However, boarding time data are not recorded in certain double-ticket smart card systems. As many passengers usually swipe the card much before their alighting, the first or the average alighting time cannot represent the actual bus arrival time, either. This lack of data creates difficulties in correcting bus arrival times. This paper focused on developing a model to calculate bus arrival time that combined the alighting swiping time from smart card data with the actual bus arrival time by the manual survey data. The model was built on the basis of the frequency distribution and the regression analysis. The swiping time distribution, the occupancy and the seating capacity were considered as the key factors in creating a method to calculate bus arrival times. With 1011 groups of smart card data and 360 corresponding records from a manual survey of bus arrival times, the research data were divided into two parts stochastically, a training set and a test set. The training set was used for the parameter determination, and the test set was used to verify the model’s precision. Furthermore, the regularity of the time differences between the bus arrival times and the card swiping times was analyzed using the “trend line” of the last swiping time distribution. Results from the test set achieved mean and standard error rate deviations of 0.6% and 3.8%, respectively. The proposed model established in this study can improve bus arrival time calculations and potentially support state prediction and service level evaluations for bus operations.     

Is rail cleaner and greener than bus?

The popular consensus is that urban passenger rail is more environmentally friendly than urban passenger bus. This position is largely associated with the key energy source for each mode, respectively electricity and diesel, where electric vehicle use will typically result in local air quality improvements away from the electricity generation source. Surveys of community perceptions reflect this sentiment; however the relationship between the source of energy and its resultant emissions is not something that citizens fully understand. There is a general lack of awareness of the resource base of much of electricity generation in some countries. Where generation sources are suitably renewable or low-carbon, electricity use will offer greenhouse gas abatement potential. However, in countries which still rely heavily on coal-fired power stations, such as Australia, abatement is not as assured and estimating emission outcomes can require careful assessment. Supporters of alternatives to diesel use can focus on the future supply of fossil-fuels, an argument which has merit; however such arguments are often confounded with environmental qualities related to local air pollution and enhanced greenhouse gas emissions. This paper takes a close look at the greenhouse emissions that are associated with urban rail and bus in Australia. Estimated intensities, when presented in the context of effective service delivery (primarily in terms of emissions per passenger kilometre), raise questions about the distortions that are present in the widespread promotion in Australia (at least) of rail as a more environmentally friendly and hence a sustainable mode of urban passenger transport than bus.