Design and Practice of Cloud Computing Platform for TBM Operation Information北大核心CSCD

The problems of TBM construction data loss, information barriers and absence of data mining have con⁃ strained the advancement of basic technologies in TBM field. Aimed at building a cloud computation platform for TBM operation information, a new concept of 3B, i. e. Born by digit, Born in format and Born to the cloud, was pre⁃ sented, the issues of information acquisition, transmission and storage during TBM operation were solved, and massive heterogeneous information intelligent transmission system and big data warehouse of TBM group were established. A structure model of cloud computation platform was designed by taking Hadoop system as ecosphere, and a cloud computation platform was built to deploy related algorithm, realizing on-line monitoring and data sharing, further⁃ more the data law mining of interaction of rock mass versus TBM machine was conducted based on big data tech⁃ nique, exploring the development direction of the information platform. © 2018, Editorial Office of "Modern Tunnelling Technology". All right reserved.     

An integrated framework for embedding large-scale dynamic traffic assignment models in advanced traveler information systems

In recent years, increasing attention has been drawn to the development of various applications of intelligent transportation systems (ITS), which are credited with the amelioration of traffic conditions in urban and regional environments. Advanced traveler information systems (ATIS) constitute an important element of ITS by providing potential travelers with information on the network's current performance both en-route and pre-trip. In order to tackle the complexity of such systems, derived from the difficulty of providing real-time estimations of current as well as forecasts of future traffic conditions, a series of models and algorithms have been initiated. This paper proposes the development of an integrated framework for real-time ATIS and presents its application on a large-scale network, that of Thessaloniki, Greece, concluding with a discussion on development and implementation challenges as well as on the advantages and limitations of such an effort.     

Estimation of origin-destination matrices from link counts and sporadic routing data

Estimation of origin-destination (OD) matrices from link count data is a challenging problem because of the highly indeterminate relationship between the observations and the latent route flows. Conversely, estimation is straightforward if we observe the path taken by each vehicle. We consider an intermediate problem of increasing practical importance, in which link count data is supplemented by routing information for a fraction of vehicles on the network. We develop a statistical model for these combined data sources and derive some tractable normal approximations thereof. We examine likelihood-based inference for these normal models under the assumption that the probability of vehicle tracking is known. We show that the likelihood theory can be non-standard because of boundary effects, and provide conditions under which such irregular behaviour will be observed in practice. For regular cases we outline connections with existing generalised least squares methods. We then consider estimation of OD matrices under estimated and/or misspecified models for the probability of vehicle tracking. Theoretical developments are complemented by simulation experiments and an illustrative example using a section of road network from the English city of Leicester.     

Sharing costs in Swedish road ownership associations

Usually transport systems, and roads in particular, are viewed as public goods. However, this is not always the case. In Sweden a large part of the road system is privately owned. Most of these privately owned roads are rural roads used by farmers and summer cottage owners, or used for forest transport. These roads are mainly provided by ownership associations.An important difference between public roads and these privately owned roads is that all investments- and maintenance decisions are made by the users themselves, who also have to pay the costs, whereas the usual case is that the owners/providers of a road-system are different agents than the users. Here the question is not how to charge the roads but how to split the costs of the roads among the users in an efficient and “fair” way.The motivation of this paper is the practical problem of how such an ownership association can divide the costs for the road network among the members in an efficient and “fair” way. The problem is treated from a game theoretical point of view, making use of the Shapley value. This means that the problem is associated with a game - a mathematical representation of the conflict situation. The Shapley value is a very important solution concept for cooperative games, like the game in this case. For games corresponding to this specific type of problems, it is shown that the Shapley value has excellent properties, such as beeing an element of the core, and beeing very easy to compute.     

Prediction of travel time variability for cost-benefit analysis

Unreliable travel times cause substantial costs to travelers. Nevertheless, they are often not taken into account in cost-benefit analyses (CBA), or only in very rough ways. This paper aims at providing simple rules to predict variability, based on travel time data from Dutch highways. Two different concepts of travel time variability are used, which differ in their assumptions on information availability to drivers. The first measure is based on the assumption that, for a given road link and given time of day, the expected travel time is constant across all working days (rough information: RI). In the second case, expected travel times are assumed to reflect day-specific factors such as weather conditions or weekdays (fine information: FI). For both definitions of variability, we find that the mean travel time is a good predictor. On average, longer delays are associated with higher variability. However, the derivative of variability with respect to delays is decreasing in delays. It can be shown that this result relates to differences in the relative shares of observed traffic ‘regimes’ (free-flow, congested, hyper-congested) in the mean delay. For most CBAs, no information on the relative shares of the traffic regimes is available. A non-linear model based on mean travel times can then be used as an approximation.     

基于蚁群算法和群决策理论的动态路径优化研究

文章针对城市交通信号控制中的动态路径优化问题,综合考虑相邻交叉口间距和路段交通饱和度两个参数的影响,提出了一种基于蚁群算法和群决策理论的动态路径优化算法模型,并通过仿真实验,对比分析了该算法模型的有效性。     

养护施工总承包模式下业主与承包商的博弈分析

文章以博弈论为理论基础,分析了养护施工总承包模式下业主与总承包商的博弈关系,提出了引导双方采用合理的策略以获得最大利益及保证工程产品达到较高质量水平的博弈对策,为养护施工总承包工程的管理和施工提供方法借鉴。     

城市交通系统通行性影响因素及计算理论

文章分析了震后城市交通系统通行性的影响因素,提出了包含路段单元通行概率、路段连通概率及路网连通概率的城市交通系统通行性计算理论,为城市路网的连通可靠性评价提供参考。     

地下工程平衡稳定理论再研究

目前,地下工程结构在计算分析方面主要采用传统松弛荷载理论（类似荷载结构法）和数值分析法;在合理结构构造、施工工法等方面主要采用岩承理论（类似地层结构法）,这些已有理论或方法隐含“变形协调控制”假定,实际应用中往往将这些假定忽视,因而需进一步发展新的理论方法以适应实际应用的需求。在大量工程实践和试验的基础上,揭示地下工程有效承载结构层与围岩荷载转移规律之间的关联性,建立地下工程平衡稳定理论,此理论既能反映传统“松弛荷载理论”和现代“岩承理论”的基本内容,又能拓宽平衡稳定性等内容,是地下工程平衡稳定性的新认识、新理念; 同时提出能量控制技术、预支护技术、受力独立性综合技术、变形协调控制技术4项关键技术。将这些技术合理地运用到实际工程施工中,将便于利用已有或新成果分类预防和控制地下工程质量和安全,为解决新型地下工程问题提供新的依据。     

Identifying optimal data aggregation interval sizes for link and corridor travel time estimation and forecasting

With the recent increase in the deployment of ITS technologies in urban areas throughout the world, traffic management centers have the ability to obtain and archive large amounts of data on the traffic system. These data can be used to estimate current conditions and predict future conditions on the roadway network. A general solution methodology for identifying the optimal aggregation interval sizes for four scenarios is proposed in this article: (1) link travel time estimation, (2) corridor/route travel time estimation, (3) link travel time forecasting, and (4) corridor/route travel time forecasting. The methodology explicitly considers traffic dynamics and frequency of observations. A formulation based on mean square error (MSE) is developed for each of the scenarios and interpreted from a traffic flow perspective. The methodology for estimating the optimal aggregation size is based on (1) the tradeoff between the estimated mean square error of prediction and the variance of the predictor, (2) the differences between estimation and forecasting, and (3) the direct consideration of the correlation between link travel time for corridor/route estimation and forecasting. The proposed methods are demonstrated using travel time data from Houston, Texas, that were collected as part of the automatic vehicle identification (AVI) system of the Houston Transtar system. It was found that the optimal aggregation size is a function of the application and traffic condition.