静力作用下沉管隧道三维数值模拟

沉管隧道纵断面结构计算常采用弹性地基梁或弹性地基板法,但这些方法较难真实模拟沉管隧道的受力情况,特别是接头的受力情况。文章以三维实体单元出发,引入适当的假设,对沉管隧道静力作用下的受力、位移,特别是接头受力情况进行了详细的模拟分析,对沉管隧道结构纵向计算做了有益的探索,对类似工程有较强的指导意义。     

Impacts of Information and Communication Technologies (ICT) on time use and travel behavior: a structural equations analysis

The objective of this paper is to contribute an empirical study to the literature on transportation impacts of Information and Communications Technologies (ICT). The structural equation model (SEM) is employed to analyze the impacts of ICT usage on time use and travel behavior. The sample is derived from the travel characteristic survey conducted in Hong Kong in 2002. The usage of ICT is defined as the experience of using e-mail, Internet service, video conferencing and videophone for either business or personal purposes. The results show that the use of ICT generates additional time use for out-of-home recreation activities and travel and increases trip-making propensity. Individuals at younger age or with higher household income are found to be more likely ICT users. The findings of this study provide further evidence on the complementarity effects of ICT on travel, suggesting that the wide application of ICT probably leads to more, not less, travel. The study also demonstrates the importance of considering the interactions between activity and travel for better understanding of the nature and magnitude of the impacts of ICT on time use and trip making behavior.     

双车道公路超车两难区域研究

基于超车行为分析,提出了双车道公路超车行为的两难区域概念,在该区域内超车车辆既无法完成超车动作又不能在避免与对向车辆相撞前安全避让。应用运动学理论建立了下游车队规模、车速、设计车速与两难区域范围以及安全超车视距之间的关系,发现与超越单车的视距要求相比,超越车队所需的安全视距较大,且随着设计车速、下游车队规模以及车速的增大而增大。并发现当流量或车速较大时,两难区域出现的概率较大,且因驾驶者错误估计引发交通事故的机会增多。最后给出了不同下游车队规模条件下安全超车的速度限制及视距要求,为制定安全行车策略以及道路安全管理提供了理论依据。     

太行山隧道膏溶角砾岩工程特性试验研究

膏溶角砾岩具有强度低、土质不均、局部压缩性高的特点，属于复杂的特殊软岩，以太行山隧道Z5标段的膏溶角砾地质特征为依托，对膏溶角砾岩的地质背景、成因、工程特性等进行了分析研究，并着重介绍了膏溶角砾岩的工程性能现场试验分析结果。     

城市中心区路内停车调查分析——以南京为例

在路内停车调查的基础上,对比路外停车相关研究成果,分析了路内停车特征和停放行为特性,得到路内停车时间短、对步行距离要求高、路内停车场利用率较高且与周边用地属性有很大关系;简单分析了当前城市路内停车存在的问题以及利用停车收费调整停车需求的有效性。最后,指出路内停车场的设置除了考虑其对道路交通流的影响,还要考虑区域路外停车的供应量、服务的土地利用类型以及停车者对步行距离的要求。     

Representing mental maps and cognitive learning in micro-simulation models of activity-travel choice dynamics

This paper develops a model, based on Bayesian beliefs networks, for representing mental maps and cognitive learning into micro-simulation models of activity-travel behavior. Mental maps can be used to address the problem that choice sets in models of travel demand are often ad hoc specified. The theory underlying the model is discussed, a specification is derived and numerical simulation is used to illustrate the properties of the model.     

Rural mobility and mode choice: Evidence from the 2001 National Household Travel Survey

This article uses data from the 2001 National Household Travel Survey (NHTS) to compare travel behavior in rural and urban areas of the U.S. As expected, the car is the overwhelmingly dominant mode of travel. Over 97% of rural households own at least one car vs. 92% of urban households; 91% of trips are made by car in rural areas vs. 86% in urban areas. Regardless of age, income, and race, almost everyone in rural areas relies on the private car for most travel needs. Mobility levels in rural areas are generally higher than in urban areas. That results from the more dispersed residences and activity sites in rural areas, which increase trip distances and force reliance on the car. Somewhat surprisingly, the rural elderly and poor are considerably more mobile than their urban counterparts, and their mobility deficit compared to the rural population average is strikingly less than for the urban elderly and poor compared to the urban average. Data limitations prevented a measurement of accessibility, however, and it seems likely that rural areas, by their very nature, are less accessible than urban areas, especially for the small percentage of car-less poor and elderly households.     

基于驾驶员特征的汽车自适应巡航控制研究

汽车自适应巡航控制系统(ACC)是当前汽车驾驶员辅助系统研究中的热点课题之一。在介绍ACC原理和对驾驶员行为特征进行分析的基础上，建立了2自由度ACC控制模型，并对模型跟随前车和前车切入情况进行了模拟分析。     

Exploring the propensity to perform social activities: a social network approach

Conceptual and empirical models of the propensity to perform social activity–travel behavior are described, which incorporate the influence of individuals’ social context, namely their social networks. More explicitly, the conceptual model develops the concepts of egocentric social networks, social activities, and social episodes, and defines the three sets of aspects that influence the propensity to perform social activities: individuals’ personal attributes, social network composition, and information and communication technology interaction with social network members. Using the structural equation modeling (SEM) technique and data recently collected in Toronto, the empirical model tests the effect of these three aspects on the propensity to perform social activities. Results suggest that the social networks framework provides useful insights into the role of physical space, social activity types, communication and information technology use, and the importance of “with whom” the activity was performed with. Overall, explicitly incorporating social networks into the activity–travel behavior modeling framework provides a promising framework to understand social activities and key aspects of the underlying behavioral process. Juan Antonio Carrasco a PhD candidate in Civil Engineering at the University of Toronto, holds a MSc degree in Transportation Engineering from the Pontificia Universidad Católica de Chile. His doctoral research explores the relationships between social networks, activity–travel behavior, and ICTs. His research interests also include microsimulation, land use-transportation, and econometric modeling. Eric J. Miller is Bahen-Tanenbaum Professor of Civil Engineering at the University of Toronto where he is also Director of the Joint Program in Transportation. His research interests include integrated land-use/transportation modeling, activity-based travel modeling, microsimulation and sustainable transportation planning.     

An empirical investigation on the dynamic processes of activity scheduling and trip chaining

Investigation of the dynamic processes of activity scheduling and trip chaining has been an interest of transportation researchers over the past decade because of its relevance to the effectiveness of congestion management and intelligent transportation systems. To empirically examine the processes, a computerized survey instrument is developed to collect household activity scheduling data. The instrument is unique in that it records the evolution of activity schedules from intentions to final outcomes for a weekly period. This paper summarizes the investigation on the dynamic processes of activity scheduling and trip chaining based on data collected from a pilot study of the instrument. With the data, ordered logit models are applied to identify factors that are pertinent to the scheduling horizon of activities. Results of the empirical analysis show that a daily schedule often starts with certain activities occupying a portion of the schedule and other activities are then arranged around these pre-occupants. Activities of shorter duration are more likely to be opportunistically inserted in a schedule already anchored by their longer duration counterparts. Persons with children often expect more constraining activities than those with no children. The analysis also shows that female respondents tend to be more structured in terms of how the week is planned. Additionally, analysis of travel patterns reveals that many trip-chains are formed opportunistically. Travel time required to reach an activity is positively related to the scheduling horizon for the activity, with more distant stops being planned earlier than closer locations.