温度梯度模式对一座变截面连续箱梁桥主应力的影响分析

箱形截面整体性好,结构刚度大,能承受正负弯矩,且抗扭能力强,是一种经济合理的截面形式,近年来得到广泛应用,但建成后通过一定时间的运营,发现箱梁简支端附近腹板开裂较严重,结合一座预应力混凝土变截面连续箱梁桥实例,采用空间有限元分析仿真计算,结果表明温度梯度模式对箱梁腹板的主拉应力影响较大。     

《交通微观仿真分析指南》概要

近年来,交通规划软件所使用的方法从对交通量的宏观分配转变为对单个车辆的微观仿真.这一方法论的改变意味着需要对委任交通工程项目、项目管理以及对其结果进行解释等的职能部门的指导方针进行更新,以便能反映微观仿真的独特能力.与之前的模型相比,微型仿真能够更完整和详细地反映道路交通状况的内在变化.位于苏格兰的SIAS交通规划咨询公司就此编写了《微观仿真最佳咨询项目指南》和《交通微观仿真分析指南》,以帮助交通从业人员从事微观仿真项目和解释其结果.这些指导方针是基于该公司进行项目咨询和开发S-Paramics微观仿真软件的经验基础上编写而成的.     

The evaluation of the spatial integration of station areas via the node place model; an application to subway station areas in Tehran

Urban planners usually consider the transportation system and land use systems in different ways. The node place model is an analytical tool that explores the interaction between the transportation and land use systems in station areas in an urban region. The essential issue with the node place model is spatial. To address this issue, spatial indices are added to the model. Another purpose of this paper is to provide a procedure to identify the most effective transportation and land use dynamics in station areas. In this respect, canonical correlation analysis was conducted on data concerning Tehran’s subway stations. The resulting spatial indices have a fairly logical relationship with other transportation and land use indices, and it is useful to incorporate these indices in the node place model. The case studies demonstrated that a well-integrated, continuous and dense spatial configuration of the street network in station areas is associated with an increase in the variety and intensity of activities, an increase in the workforce and better accessibility for the station by attracting greater pedestrian movement. Additionally, these case studies indicated that to sustain a station area, the streets that exist in a station area and the streets that are connected to a station should be connected to the streets that locally benefit from well-integrated areas within fewer steps.     

A framework to analyze the vulnerability of European road networks due to Sea-Level Rise (SLR) and sea storm surges

This study proposes a framework to explore the concepts of exposure, vulnerability and connectivity in EU road network and to assess the potential transportation infrastructure sensitivities towards Sea-Level Rise (SLR) and storm surges. The magnitude and significance of impacts were determined and knowledge of network robustness was built up based on existing climate data and on future trends. Various spatial databases were integrated and a four-stage transport model was used to explore the likely impacts of network degradation. The pattern of the network was assessed via both node- and link-based measurements, where different road databases, namely TRANS-TOOLS and Tele Atlas/TomTom, were employed in order to analyze the impact of spatial resolution within network connectivity analyses. This general framework developed for European Union, was tested on a specific and articulated case study area; namely, the north-east coastal region of Spain. The research conducted, yielded useful methods for the analysis of network vulnerability, where impacts are more significant in regional accessibility patterns. Accessibility indicators at the regional level changed drastically, with some regions showing up to a 26% decrease. According to the results of network connectivity indicators, the changes in network topology have reduced the number of alternative routes and placed more pressure on the transport system. The implementation of this framework and quantitative assessment methodologies outlined in this paper could be employed to assist policy makers to recognize the opportunities that may arise or diminish the adverse effects.     

Marginal cost congestion pricing based on the network fundamental diagram

Congestion pricing schemes have been traditionally derived based on analytical representations of travel demand and traffic flows, such as in bottleneck models. A major limitation of these models, especially when applied to urban networks, is the inconsistency with traffic dynamics and related phenomena such as hysteresis and the capacity drop. In this study we propose a new method to derive time-varying tolling schemes using the concept of the Network Fundamental Diagram (NFD). The adopted method is based on marginal cost pricing, while it also enables to account realistically for the dynamics of large and heterogeneous traffic networks. We derive two alternative cordon tolls using network-aggregated traffic flow conditions: a step toll that neglects the spatial distribution of traffic by simply associating the marginal costs of any decrease in production within the NFD to the surplus of traffic; and a step toll that explicitly accounts for how network performance is also influenced by the spatial variance in a 3D-NFD. This pricing framework is implemented in the agent-based simulation model MATSim and applied to a case study of the city of Zurich. The tolling schemes are compared with a uniform toll, and they highlight how the inhomogeneous distribution of traffic may compromise the effectiveness of cordon tolls.     

出砖入史——闽南红砖中的地方记忆与空间转型

建筑是文化的重要组成部分,其技术发展、材料运用与社会文化变迁直接相关,其象征、仪式、居俗是空间策略的反映。砖是重要的建筑材料,闽南建筑的砖瓦作尤为独树一帜。闽南地区在墙面、屋顶、地板多处大量使用当地烧制的红砖,色彩强烈,与中国传统的帝王宫殿近似,因此漫长的历史中,身处"红砖文化区"的泉州民众一直试图解释自身的"僭越"之举。此外,泉州红砖运用方式的变迁也反映海外贸易与文化交流对地方建筑的影响。     

A discrete choice framework for modeling and forecasting the adoption and diffusion of new transportation services

Major technological and infrastructural changes over the next decades, such as the introduction of autonomous vehicles, implementation of mileage-based fees, carsharing and ridesharing are expected to have a profound impact on lifestyles and travel behavior. Current travel demand models are unable to predict long-range trends in travel behavior as they do not entail a mechanism that projects membership and market share of new modes of transport (Uber, Lyft, etc.). We propose integrating discrete choice and technology adoption models to address the aforementioned issue. In order to do so, we build on the formulation of discrete mixture models and specifically Latent Class Choice Models (LCCMs), which were integrated with a network effect model. The network effect model quantifies the impact of the spatial/network effect of the new technology on the utility of adoption. We adopted a confirmatory approach to estimating our dynamic LCCM based on findings from the technology diffusion literature that focus on defining two distinct types of adopters: innovator/early adopters and imitators. LCCMs allow for heterogeneity in the utility of adoption for the various market segments i.e. innovators/early adopters, imitators and non-adopters. We make use of revealed preference (RP) time series data from a one-way carsharing system in a major city in the United States to estimate model parameters. The data entails a complete set of member enrollment for the carsharing service for a time period of 2.5 years after being launched. Consistent with the technology diffusion literature, our model identifies three latent classes whose utility of adoption have a well-defined set of preferences that are significant and behaviorally consistent. The technology adoption model predicts the probability that a certain individual will adopt the service at a certain time period, and is explained by social influences, network effect, socio-demographics and level-of-service attributes. Finally, the model was calibrated and then used to forecast adoption of the carsharing system for potential investment strategy scenarios. A couple of takeaways from the adoption forecasts were: (1) placing a new station/pod for the carsharing system outside a major technology firm induces the highest expected increase in the monthly number of adopters; and (2) no significant difference in the expected number of monthly adopters for the downtown region will exist between having a station or on-street parking.     

Where are the dangerous intersections for pedestrians and cyclists: A colocation-based approach

Pedestrians and cyclists are vulnerable road users. They are at greater risk for being killed in a crash than other road users. The percentage of fatal crashes that involve a pedestrian or cyclist is higher than the overall percentage of total trips taken by both modes. Because of this risk, finding ways to minimize problematic street environments is critical. Understanding traffic safety spatial patterns and identifying dangerous locations with significantly high crash risks for pedestrians and cyclists is essential in order to design possible countermeasures to improve road safety. This research develops two indicators for examining spatial correlation patterns between elements of the built environment (intersections) and crashes (pedestrian- or cyclist-involved). The global colocation quotient detects the overall connection in an area while the local colocation quotient identifies the locations of high-risk intersections. To illustrate our approach, we applied the methods to inspect the colocation patterns between pedestrian- or cyclist-vehicle crashes and intersections in Houston, Texas and we identified among many intersections the ones that significantly attract crashes. We also scrutinized those intersections, discussed possible attributes leading to high colocation of crashes, and proposed corresponding countermeasures.     

Impacts of information technology and urbanization on less-than-truckload freight flows in China: An analysis considering spatial effects

Understanding the relationship between socioeconomic factors and the Less-than-Truckload (LTL) freight flows is important for transportation planners and policy makers. This paper explores the impacts of information technology, urbanization on LTL freight flows by using a spatial autocorrelation model with freight flow data from a leading LTL company in China. The results show that all IT variables and urbanization variables have positive effects on freight flows. Distance, as expected, is negatively correlated with the freight flow volume. The application of the spatial autocorrelation model further shows that origin dependence, destination dependence and OD dependence are all significant, justifying the consideration of spatial interdependence. Finally, policy implications are discussed based on the estimated results. These findings shed light on the impacts of internet and urbanization on freight transportation, and contribute to the design of freight policies and the development of the LTL industry.     

高速铁路CP0框架控制网GAMIT解算结果与IGS站的选取研究

针对高速铁路CP0框架控制网数据解算时IGS基准站的选取问题,以沿江城际铁路CP0框架控制网作为研究对象,用试验的方法讨论使用GAMIT软件处理高速铁路CP0框架网时,选择IGS基准站的空间分布和数量分布对基线解算的影响。结果表明,在CP0框架网数据处理时必须选取IGS站提供参考框架,但可不必选择位于南半球的IGS站;选取的IGS站空间分布要均匀,数量上选择4～5个即可。