快速道路公交和城市轨道交通关键参数比较及相关问题探讨

对快速道路公交和城市轨道交通系统的规划和建设时间、基建费用和运营成本、票费收支比、补贴和投融资、载客量、速度和灵活性、能源消耗等关键参数进行了分析比较.指出快速道路公交在费用、灵活性和建设周期上具有较大优势,轨道交通系统在载客能力、环境景观和服务水平上更有优势,还可以充分利用地下空间.在层次分析法框架下讨论了发展快速公共交通的决策准则.提出了快速道路公交和轨道交通的两种组合模式:快速道路公交作为轨道交通的补充和延伸,提高公共交通的覆盖率和服务水平;快速道路公交作为轨道交通发展的过渡阶段,先发展快速道路公交,培育客流,待轨道交通建成后再将快速道路公交路权返还给社会车辆.     

基于模型视图控制器框架的多功能车辆总线一致性测试的实现

一致性测试是通信设备实现互操作的必要条件.简单介绍了对列车通信网(TCN)进行一致性测试的重要性和模型视图控制器(MVC)框架.重点描写了对多功能车辆总线(MVB)进行一致性测试所包括的内容、测试的方案和步骤,以及如何在MVC这种优秀的框架中实现.在实验室搭建了测试平台,使用的是Duagon公司D114MVB网卡,测试结果真实有效.     

基于有限元分析的城市客车扶手杆结构改进

基于国内城市客车扶手杆应用的现状,对顶置电池城市客车扶手结构进行了有限元分析,为扶手整体结构的强度、刚度设计提供理论依据。     

关于城市快捷路设计的探讨和思考

随着城镇化建设进程的快速推进,城市空间不断拓展,大型都市圈迅速崛起,居民出行距离不断增长,机动车进出交通与长距离快速通行交通之间的矛盾日益凸显,同步制约了都市圈之间经济、人口、交通之间日益密切的互联互通。加之土地资源和空间限制,新的快速通廊无法实现而既有的主干路因红绿灯较多、耗时较长等无法满足都市圈之间快速一体化发展的进程。为此,很多城市开启了新一轮的城市主干路升级改造工程。但受工程投资、周边环境、征地拆迁等因素制约而又难以实施标准化的城市快速路,很多城市提出了城市快捷路的概念。从城市快捷路的提出和功能定位入手,依托长沙市腾飞路工程实例,探讨城市快捷路设立的意义、适用的范围、工程技术标准、横断面布置形式等技术要点,为其他城市主干路升级改造设计提供部分参考。     

宜昌市夜明珠路总体方案研究

结合宜昌BRT(快速公交系统)建设对宜昌市夜明珠路进行改造,受众多因素控制,道路改造难度较高。介绍了工程建设条件及总体设计方案。总体方案结合路线两侧现状地形、控制因素等不同特点,将路线分为沿河线段和合流线段两个典型路段,并进行方案比选,综合各方面因素,得出了推荐方案。     

An adaptive information fusion model to predict the short-term link travel time distribution in dynamic traffic networks

As intelligent transportation systems (ITS) approach the realm of widespread deployment, there is an increasing need to robustly capture the variability of link travel time in real-time to generate reliable predictions of real-time traffic conditions. This study proposes an adaptive information fusion model to predict the short-term link travel time distribution by iteratively combining past information on link travel time on the current day with the real-time link travel time information available at discrete time points. The past link travel time information is represented as a discrete distribution. The real-time link travel time is represented as a range, and is characterized using information quality in terms of information accuracy and time delay. A nonlinear programming formulation is used to specify the adaptive information fusion model to update the short-term link travel time distribution by focusing on information quality. The model adapts good information by weighing it higher while shielding the effects of bad information by reducing its weight. Numerical experiments suggest that the proposed model adequately represents the short-term link travel time distribution in terms of accuracy and robustness, while ensuring consistency with ambient traffic flow conditions. Further, they illustrate that the mean of a representative short-term travel time distribution is not necessarily a good tracking indicator of the actual (ground truth) time-dependent travel time on that link. Parametric sensitivity analysis illustrates that information accuracy significantly influences the model, and dominates the effects of time delay and the consistency constraint parameter. The proposed information fusion model bridges key methodological gaps in the ITS deployment context related to information fusion and the need for short-term travel time distributions.     

Understanding members' carsharing (activity) persistency by using econometric model

Carsharing is an innovative travel alternative that has recently experienced considerable growth and become part of sustainable transportation initiatives. Although carsharing is becoming increasingly a popular alternative transportation mode in North America, it is still an under‐researched area. Current research is aimed at better understanding of the behavior of carsharing users. For every member, a two‐stage approach microsimulates the probability of being active in any month using a binary probit model and given that a particular member is active during a month, the probability of that member using the service multiple times using a random utility‐based model. The model is estimated using empirical data from one of the largest carsharing companies in North America. The model estimates reveal that the activity persistency of members is positively linked to previous behaviors for up to 4 months, and that the influence of previous months weakens over time. It also shows that some attributes of the traveler (gender, age, and language spoken at home) impact his or her behaviors. Copyright © 2010 John Wiley & Sons, Ltd.     

Understanding the impacts of a combination of service improvement strategies on bus running time and passenger’s perception

Transit agencies implement many strategies in order to provide an attractive transportation service. This article aims to evaluate the impacts of implementing a combination of strategies, designed to improve the bus transit service, on running time and passenger satisfaction. These strategies include using smart card fare collection, introducing limited-stop bus service, implementing reserved bus lanes, using articulated buses, and implementing transit signal priority (TSP). This study uses stop-level data collected from the Société de transport de Montréal (STM)’s automatic vehicle location (AVL) and automatic passenger count (APC) systems, in Montréal, Canada. The combination of these strategies has lead to a 10.5% decline in running time along the limited stop service compared to the regular service. The regular route running time has increased by 1% on average compared to the initial time period. The study also shows that riders are generally satisfied with the service improvements. They tend to overestimate the savings associated with the implementation of this combination of strategies by 3.5-6.0 min and by 2.5-4.1 min for both the regular route and the limited stop service, respectively. This study helps transit planners and policy makers to better understand the effects of implementing a combination of strategies to improve running time and passenger’s perception of these changes in service.     

The determinants of long distance travel in Great Britain

This study analyses of the determinants of long distance travel in Great Britain using data from the 1995-2006 National Travel Surveys (NTSs). The main objective is to determine the effects of socio-economic, demographic and geographic factors on long distance travel. The estimated models express the distance travelled for long distance journeys as a function of income, gender, age, employment status, household characteristics, area of residence, size of municipality, type of residence and length of time living in the area. A time trend is also included to capture common changes in long distance travel over time not included in the explanatory variables. Separate models are estimated for total travel, travel by each of four modes (car, rail, coach and air), travel by five purposes (business, commuting, leisure, holiday and visiting friends and relatives (VFRs)) and two journey lengths (<150 miles and 150+ miles one way), as well as the 35 mode-purpose-distance combinations.The results show that long distance travel is strongly related to income: air is most income-elastic, followed by rail, car and finally coach. This is the case for most journey purposes and distance bands. Notable is the substantial difference in income elasticities for rail for business/commuting as opposed to holiday/leisure/VFR. In addition, the income elasticity for coach travel is very low, and zero for the majority of purpose-distance bands, suggesting coach travel to be an inferior mode in comparison to car, rail and air. Regarding journey distance, we find that longer distance journeys are more income elastic than shorter journeys.For total long distance travel, the study indicates that women travel less than men, the elderly less than younger people, the employed and students more than others, those in one adult households more than those in larger households and those in households with children less than those without. Long distance travel is also lowest for individuals living in London and greatest for those in the South West, and increases as the size of the municipality declines.     

On the income elasticity of the value of travel time

Transport infrastructure is long-term and in appraisal it is necessary to value travel time savings for future years. This requires knowing how the value of time (VTT) will develop over time as incomes grow. This paper investigates if the cross-sectional income elasticity of the VTT is equal to inter-temporal income elasticity. The study is based on two identical stated choice experiments conducted with a 13 year interval. Results indicate that the relationship between income and the VTT in the cross-section has remained unchanged over time. As a consequence, the inter-temporal income elasticity of the VTT can be predicted based on cross-sectional income elasticity. However, the income elasticity of the VTT is not a constant but increases with income. For this reason, the average income elasticity of the VTT in the cross-sections has increased between the two survey years and can be expected to increase further over time.