地铁柔性接触网线岔检调标准的制定与应用

根据以往运行经验,结合西安地铁2号线的实际情况,从支柱定位、线岔交叉点、始触区、接触线高度、线岔定位拉出值等方面,对柔性接触网线岔的检调标准进行深入研究、分析并加以明确。将所定标准实际应用在西安地铁渭河车辆段接触网的建设中,顺利通过了接触网的冷滑、热滑试验及实际运行的考验。同时,将所定部分标准与国铁普速接触网线岔检调标准进行对比,以供有关接触网生产和技术人员参考。     

接地变压器在轨道交通电力系统中的应用与分析

介绍接地变压器的原理、工作特点,以及接地变压器在轨道交通供电系统中的实际运用。从保护动作可靠性、系统运行方式调整的灵活性和安全性以及建设成本3个方面,对2种不同接线方式的接地变压器进行了分析比较。并从日常运行维护角度建议接地变压器采用独立的断路器。     

具有碎石基层的半刚性沥青混凝土路面的非线性有限元分析

在充分考虑碎石基层非线性(弹塑性)特性的基础上，采用非线性有限元法分析了吉林通化试验路3种路面结构面层底面及半刚性基层底面弯拉应力的变化规律，并对通化试验路2种具有碎石基层半刚性沥青混凝土路面结构的沥青混凝土面层的抗疲劳寿命进行了预估。     

Time windows in workers' activity patterns: Empirical evidence from the Netherlands

This paper assumes that activities at the home and work location are important determinants of individuals' paths through time and space. Fixed activities at these locations determine to a large extent the duration and timing of time windows – blocks of time available for participation in travel and out-of-home non-work activities. Taking the time spent at home and at the workplace as a starting point, this paper classifies activity patterns on workdays into six groups with distinct home- and work-stay patterns. For this, data are used from the 1998 Netherlands National Travel Survey. The six clusters vary in terms of the duration and timing of time windows and some of the differences can be explained by commute characteristics, types of non-work activities performed, workers' sociodemographic attributes, and their spatiotemporal environment. However, the impact of sociodemographic and spatiotemporal variables on cluster membership is shown to be weak.     

柔性桩与土相互作用非线性分析的增量传递矩阵法

对桩侧土采用非线性荷载传递函数,对桩端土采用线性荷载传递函数,同时考虑桩周土所分担的荷载对单桩荷载传递规律的影响,利用增量荷载传递矩阵法及微分方程的近似解法--子域法,推出了刚性承台下柔性桩与地基非线性相互作用的近似解析算式。为了验证该方法的可行性,通过试验将试验结果与有限元结果及该方法所得结果进行了对比,对比表明:该理论解与现场实测值、有限元计算值都非常接近。     

Spatiotemporal influence of land use and household properties on automobile travel demand

Understanding the patterns of automobile travel demand can help formulate policies to alleviate congestion and pollution. This study focuses on the influence of land use and household properties on automobile travel demand. Car license plate recognition (CLPR) data, point-of-interest (POI) data, and housing information data were utilized to obtain automobile travel demand along with the land use and household properties. A geographically and temporally weighted regression (GTWR) model was adopted to deal with both the spatial and temporal heterogeneity of travel demand. The spatial-temporal patterns of GTWR coefficients were analyzed. Also, comparative analyses were carried out between automobile and total person travel demand, and among travel demand of taxis, heavily-used private cars, and total automobiles. The results show that: (I) The GTWR model has significantly higher accuracy compared with the Ordinary Least Square (OLS) model and the Geographically Weighted Regression (GWR) model, which means the GTWR model can measure both the spatial and temporal heterogeneity with high precision; (II) The influence of built environment and household properties on automobile travel demand varies with space and time. In particular, the temporal distribution of regression coefficients shows significant peak phenomenon; and (III) Comparative analyses indicate that residents’ preference for automobiles over other travel modes varies with their travel purpose and destination. The above findings indicate that the proposed method can not only model spatial-temporal heterogeneous travel demand, but also provide a way to analyze the patterns of automobile travel demand.     

Autonomous cars: The tension between occupant experience and intersection capacity

Systems that enable high levels of vehicle-automation are now beginning to enter the commercial marketplace. Road vehicles capable of operating independently of real-time human control under an increasing set of circumstances will likely become more widely available in the near future. Such vehicles are expected to bring a variety of benefits. Two such anticipated advantages (relative to human-driver vehicle control) are said to be increased road network capacity and the freeing up of the driver-occupant’s time to engage in their choice of leisurely or economically-productive (non-driving) tasks.In this study we investigate the implications for intersection capacity and level-of-service of providing occupants of automated (without real-time human control), autonomously-operating (without vehicle-to-X communication) cars with ride quality that is equivalent (in terms of maximum rates of longitudinal and lateral acceleration) to two types of rail systems: [urban] light rail transit and [inter-urban] high-speed rail. The literature suggests that car passengers start experiencing discomfort at lower rates of acceleration than car drivers; it is therefore plausible that occupants of an autonomously-operating vehicle may wish to instruct their vehicle to maneuver in a way that provides them greater ride comfort than if the vehicle-control algorithm simply mimicked human-driving-operation.On the basis of traffic microsimulation analysis, we found that restricting the dynamics of autonomous cars to the acceleration/deceleration characteristics of both rail systems leads to reductions in a signalized intersection’s vehicle-processing capacity and increases in delay. The impacts were found to be larger when constraining the autonomous cars’ dynamics to the more-restrictive acceleration/deceleration profile of high-speed rail. The scenarios we analyzed must be viewed as boundary conditions, because autonomous cars’ dynamics were by definition never allowed to exceed the acceleration/deceleration constraints of the rail systems. Appropriate evidence regarding motorists’ preferences does not exist at present; establishing these preferences is an important item for the future research agenda.This paper concludes with a brief discussion of research needs to advance this line of inquiry.     

Hierarchal assessment of noise pollution in urban areas – A case study

Noise pollution in urban areas has many harmful effects on the citizens. There are varieties of noise generation sources of which the traffic noise could be a major source. The point which is perhaps less noticed is that sound level is not the only parameter to indicate the extent and intensity of noise pollution. Situation of urban land uses, distribution of population centers and types of passages can deeply affect the concern on this environmental issue but not with a similar ratio. This article presents an overlaying technique to define noise prone areas using all different factors involved. A case study was carried out in the District 14 of Tehran Metropolitan City where there are busy streets and highways. For this purpose, the share of each criterion in noise pollution intensity was determined using Analytical Hierarchy Process (AHP). Afterwards, the map layers were overlaid based upon the relative importance of the criteria to get the final map on which the noise prone areas are specified. The developed method could be used as a tool for indirect estimation of noise pollution by which instead of direct measurement of the equivalent sound level, it would be possible to predict noise susceptible areas considering the most important influential factors.     

桥梁模板施工技术应用性研究

桥梁模板是桥梁施工中的重要工具。通过搜集国内外桥梁模板资料,研究总结并提出解决模板工程在桥梁施工中存在各种问题的办法,将对提高工程质量、加快施工速度、提高劳动生产率、降低工程成本和实现桥梁工程的文明施工起到一定的推动作用。     

Travel analytics: Understanding how destination choice and business clusters are connected based on social media data

Understanding how destination choice and business clusters are connected is of great importance for designing sustainable cities, fostering flourishing business clusters, and building livable communities. As sharing locations and activities on social media platforms becomes increasingly popular, such data can reveal destination choice and activity space which can shed light on human-environment relationships. To this end, this research models the relationship between characteristics of business clusters and check-in activities from Los Angeles County, California. Business clusters are analyzed via two lenses: the supply side (employment data by industry) and the demand side (on-line check-in data). Spatial and statistical analyses are performed to understand how land use and transportation network features affect the popularity of the identified clusters and their relationships. Our results suggest that a cluster with more employment opportunities and more types of employment is associated with more check-ins. A business cluster that has access to parks or recreational services is also more popular. A business cluster with a longer road network and better connectivity of roads is associated with more check-ins. The visualization of the common visitors between clusters reveals that there are a few clusters with outstanding strong ties, while most have modest ties with each other. Our findings have implications on the influence of urban design on the popularity of business clusters.