重载交通沥青路面设计指标研究

重载交通地区车辆超载严重，路面质量下降迅速，严重影响了车辆的行驶速度和运行安全。沥青路面结构设计重点考虑沥青面层的疲劳开裂、半刚性基层的开裂和车辙三个方面的临界破坏情况。采用ANSYS有限元软件进行路面结构力学响应分析和常用沥青路面结构应力应变分析。     

A programmable calculation procedure for number of traffic conflict points at highway intersections

Traffic movement conflict points at intersections are the points at which traffic movements intersect (including crossing, merging, and diverging). Numbers and distribution of different types of conflict points are used to evaluate intersection access management designs and safety performance. Traditionally, the determination of the numbers of conflict points for different traffic movements is based on manual methods, which causes the difficulty for computerized procedures to evaluate safety performance of different access management designs. Sometimes, a programmable calculation procedure may provide more effective solutions as compared with manual methods. This paper presents a programmable calculation procedure for the determination of the numbers of conflict points, which could be used as a basis for a computerized procedure. Concepts of virtual movement lanes and intersection quadrants are introduced to specify types of intersections, traffic lane configurations, and traffic movement regulations. Calculation models, based on such concepts, for traffic movement conflict points at signalized and unsignalized intersections can be obtained. In support of the procedure, case studies are presented in the paper. The procedure presented in the paper can be programmed into a computer program for the purpose of a computerized evaluation of intersection safety and design performance of different access management or control approaches. Copyright © 2012 John Wiley & Sons, Ltd.     

基于DD6119K60客车流水槽优化设计

对近年来国内客车流水槽的结构、材料及造型方面存在的问题进行了分析，并给出了具体的设计方案。     

重庆市两江新区疏唐互通立交方案设计浅析

重庆市两江新区基础设施快速建设,港口、码头、铁路、公路、城市道路之间相互交叉影响,以疏唐互通立交为例,浅述如何解决各项基础设施建设之间的矛盾,确保项目的顺利实施。     

铁路延伸客服系统设计方案研究

随着客运专线铁路及电子商务的兴起，延伸铁路客运服务信息系统将为旅客提供更加便捷高效的服务，介绍了延伸旅客服务信息系统的总体方案及设计。     

基于ANP和粗糙集计算权重的绿色铁路客站评估

建设满足"节能环保"要求的绿色铁路客站,是我国铁路发展的趋势所在,因此铁路客站的绿色等级评估是极有必要的。通过建立绿色铁路客站"四节一环保"评价指标体系,以网络层次分析法(ANP)确定指标主观权重,经典粗糙集理论确定指标客观权重,再通过最小相对熵原理对二者进行优化结合,最后用得出的指标综合权重对银川新铁路客站进行绿色星级评估。结果表明:该权重确定方法既克服了因未考虑各指标之间的依存反馈关系而使主观权重不够准确的弊端,又利用相对熵原理优化并减小了主、客观权重结合的偏差,得出科学合理的组合权重,体现本文指标权重确定方法的有效性和优越性,为更加准确地评估铁路客站的绿色等级提供参考。     

高速公路左侧路肩设置必要性研究

尽管<公路工程技术标准>(JTG B01-2003)中规定八车道的高速公路应当设置2.5 m的左侧硬路肩,但国内几条刚刚改建完成的八车道高速公路中没有一条设置了左侧硬路肩,甚至没有宽于0.75 m的路缘带.研究运用可接受间隙理论计算了不同流量和车道数条件下车辆从最内侧车道穿插变道停驶到右侧路肩这一过程的概率和所需距离,并通过交通事故数据调研,分析了左侧路肩设置对提高交通安全的影响,从运行效率和交通安全两个方面定性和定量分析了左侧路肩设置的必要性.     

A theoretical foundation for the relationship between generalized origin–destination matrix and flow matrix based on ordinal graph trajectories

This paper shows the relationship between flow, generalized origin–destination (OD), and alternative route flow from a set of ordinal graph trajectories. In contrast to traffic assignment methods that employ OD matrix to produce flow matrix, we use ordinal trajectory on a network graph as input and produce both the generalized OD matrix and the flow matrix, with the alternative and substitute route flow matrices as additional outputs. By using linear algebra‐like operations on matrix sets, the relationship between network utilization (in terms of flow, generalized OD, alternative route flow, and desire line) and network structure (in terms of distance matrix and adjacency matrix) are derived. Copyright © 2012 John Wiley & Sons, Ltd.     

Options for reducing noise from roads and railway lines

The fundamental noise generation mechanisms of road and rail vehicles are discussed with attention to noise abatement measures. Based on an evaluation of publicly available tire noise data and the European road traffic noise emission model CNOSSOS, it is shown that on the road side there is a significant noise reduction potential in the usage of low-noise tires. From a three months measurement campaign a noise model was derived to predict the maximal sound pressure level of heavy duty vehicles during a pass-by in 7.5 m distance with the parameters vehicle speed and number of axles. With help of recently published information about external costs caused by heavy duty vehicles and the noise prediction tool, a model was developed to derive a money equivalent that can be used as a bonus/malus in a heavy duty vehicle fee. As a measure at the infrastructure, the installation of low-noise pavements is an effective, durable and economically attractive measure. Recent experiences with different technologies from all over the world are compiled and evaluated. On the rail side, an overview of the possible noise reduction strategies is given, followed by a discussion of the current policy and legislation in the EU and on the national level of different European countries.     

Short-term speed predictions exploiting big data on large urban road networks

Big data from floating cars supply a frequent, ubiquitous sampling of traffic conditions on the road network and provide great opportunities for enhanced short-term traffic predictions based on real-time information on the whole network. Two network-based machine learning models, a Bayesian network and a neural network, are formulated with a double star framework that reflects time and space correlation among traffic variables and because of its modular structure is suitable for an automatic implementation on large road networks. Among different mono-dimensional time-series models, a seasonal autoregressive moving average model (SARMA) is selected for comparison. The time-series model is also used in a hybrid modeling framework to provide the Bayesian network with an a priori estimation of the predicted speed, which is then corrected exploiting the information collected on other links. A large floating car data set on a sub-area of the road network of Rome is used for validation. To account for the variable accuracy of the speed estimated from floating car data, a new error indicator is introduced that relates accuracy of prediction to accuracy of measure. Validation results highlighted that the spatial architecture of the Bayesian network is advantageous in standard conditions, where a priori knowledge is more significant, while mono-dimensional time series revealed to be more valuable in the few cases of non-recurrent congestion conditions observed in the data set. The results obtained suggested introducing a supervisor framework that selects the most suitable prediction depending on the detected traffic regimes.