城市轨道交通网络运营组织协调性研究

分析了城市轨道交通由单线管理向网络化运营转变过程中的实际问题,提出了分析网络运营组织协调关系的必要性.从路网运输能力均衡配置角度,阐述了网络运营协调的主旨,对影响运营组织的多个关键要素做定性分析.采用解释结构模型法,根据推移律特性,建立网络运营协调要素的多级递阶结构,对层次划分结果进行要素间的关联性分析.该结构模型可作为协调准则应用于运营组织过程,为网络列车运行计划的制定提供理论依据.     

活性或惰性掺和料对复合胶凝材料水化性能的影响

采用等温量热法、X射线衍射(XRD)和化学结合水量测定等方法,研究了含有不同比例的粉煤灰或磨细石英粉的复合胶凝材料在不同养护温度条件下的水化过程,观察了水化产物量和水化程度随水化龄期变化情况。在掺量相同时,矿物掺和料的种类变化不会对复合胶凝材料的初期水化过程有明显影响,其反应过程仍由其中所含硅酸盐水泥控制。活性的粉煤灰可延迟复合胶凝材料的水化反应,而惰性的石英粉则不会。热激发作用可显著促进粉煤灰的火山灰反应,但对于硅酸盐水泥的长期水化反应有抑制作用。热养护能促使水化初期生成的高含水率的CSH向低含水率的CSH变化;粉煤灰的火山灰反应生成的也是含水率较低的CSH凝胶。     

太原市交通现状及改善建议

该文阐述了太原市道路网、公共交通及停车场的现状,并对存在问题提出了改善的建议及措施,以缓解城市交通压力。     

污水管网系统节点流量模拟计算

污水管网系统节点流量模拟计算是城市污水管网系统规划设计和运行管理的基础性工作。该文从污水管网系统规划设计和运行管理两个方面阐述了污水管网系统节点流量模拟计算的内涵,并对该领域的未来发展作了展望。     

下一代网络(NGN)与移动IPv6

下一代网络(NGN)是目前网络发展的趋势,是今后通信业务和互联网业务的核心,其核心承载将使用IPv6技术。作为IPv6内在组成部分的移动IPv6技术,对于下一代网络,尤其是对于下一代移动通信网络,有着极其重要的影响。通过移动IPv6技术,可以各种接入方式,将宽带、移动互联网和现有的无线系统等都无缝地集成到IP层,通过一种网络基础设施提供所有通信和信息服务,即是下一代网络发展的方向,也是移动IPv6的核心优势。     

一种基于无人机倾斜摄影的三维路网提取方法

三维路网是重要的基础地理信息数据,为了快速高效地获取包括路网在内的地表三维模型,可以采用无人机倾斜摄影技术,并设计相应的三维路网提取方法。在对无人机倾斜摄影三维模型、道路特性分析的基础上,提出一种基于无人机倾斜摄影的三维路网提取方法。首先,对无人机倾斜摄影和三维建模方法进行了分析,设计了针对三维路网提取的航空摄影策略和数据处理流程。分析了真实三维模型的构成,并结合道路在材质、形态等方面的特殊性提出了可用于道路提取的三维模型特征。然后,以三维模型中的三角面片为处理对象,开展了相关分割方法研究,消除存在混合地物的面片。利用支持向量机方法和面片的多种特征,进行了道路面片识别。最后,设计了道路面片三维连接方法和道路边缘三维修正方法,实现了面片间的连接以及道路边缘的有效修正。此外,还以北京某地区为例开展实际数据采集、三维建模和三维路网提取试验,介绍了倾斜摄影、控制点验证点数据采集以及三维模型的采集和生产过程;利用所提出的方法进行路网提取试验,得到了该区域的三维路网数据成果,并从定性和定量2个角度对成果进行评价。试验结果表明：所提出的方法可以有效地从倾斜摄影三维模型上提取路网信息,其平面和高程的精度均可满足一般导航等应用的要求。     

城市道路网可行性研究中CIVIL 3D应用浅谈

以武汉航空企业总部区域市政配套工程(四期)为例,采用AutoCAD Civil 3D计算道路和场地土石方,并与传统设计软件EICAD进行了比较。对Civil 3D的运用进行了简单的探索。     

Developing an enhanced weight-based topological map-matching algorithm for intelligent transport systems

Map-matching (MM) algorithms integrate positioning data from a Global Positioning System (or a number of other positioning sensors) with a spatial road map with the aim of identifying the road segment on which a user (or a vehicle) is travelling and the location on that segment. Amongst the family of MM algorithms consisting of geometric, topological, probabilistic and advanced, topological MM (tMM) algorithms are relatively simple, easy and quick, enabling them to be implemented in real-time. Therefore, a tMM algorithm is used in many navigation devices manufactured by industry. However, existing tMM algorithms have a number of limitations which affect their performance relative to advanced MM algorithms. This paper demonstrates that it is possible by addressing these issues to significantly improve the performance of a tMM algorithm. This paper describes the development of an enhanced weight-based tMM algorithm in which the weights are determined from real-world field data using an optimisation technique. Two new weights for turn-restriction at junctions and link connectivity are introduced to improve the performance of matching, especially at junctions. A new procedure is developed for the initial map-matching process. Two consistency checks are introduced to minimise mismatches. The enhanced map-matching algorithm was tested using field data from dense urban areas and suburban areas. The algorithm identified 96.8% and 95.93% of the links correctly for positioning data collected in urban areas of central London and Washington, DC, respectively. In case of suburban area, in the west of London, the algorithm succeeded with 96.71% correct link identification with a horizontal accuracy of 9.81 m (2σ). This is superior to most existing topological MM algorithms and has the potential to support the navigation modules of many Intelligent Transport System (ITS) services.     

Using on-board logging devices to study the longer-term impact of an eco-driving course

In this paper the long-term impact of an eco-driving training course is evaluated by monitoring driving behavior and fuel consumption for several months before and after the course. Cars were equipped with an on-board logging device that records the position and speed of the vehicle using GPS tracking as well as real time as electronic engine data extracted from the controller area network. The data includes mileage, number of revolutions per minute, position of the accelerator pedal, and instantaneous fuel consumption. It was gathered over a period of 10 months for 10 drivers during real-life conditions thus enabling an individual drive style analysis. The average fuel consumption four months after the course fell by 5.8%. Most drivers showed an immediate improvement in fuel consumption that was stable over time, but some tended to fall back into their original driving habits.     

Vulnerability analysis for large-scale and congested road networks with demand uncertainty

To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.