富水区隧道环向盲管间距优化分析北大核心CSCD

富水区隧道涌水遵循“以堵为主、防排结合”的处置原则,其中排水体系构建的合理性是隧道安全施工与良好运营的关键因素。首先分析隧道排水体系,揭示其工作原理,然后利用FLAC 3D有限差分软件,对鸿图特长隧道富水断层区设置的不同环向盲管间距进行三维流固耦合模拟,通过分析渗水压力、锚杆受力及涌水量,揭示塑性区体积及分布区域特征。研究结果表明:沿隧道轴向,支护结构孔隙水压力大致呈周期性分布,其周期近似等于环向盲管纵向间距;加密环向盲管,在降低支护结构受力并减小塑性区体积的同时,会增加隧道排水量;随环向盲管间距的增大,注浆加固圈塑性区首先出现在围岩好的区域,断层区出现塑性区最晚;断层区锚杆加固效果较差,可通过减小钢拱架环向间距以提高结构刚度,使注浆加固圈沿轴向受力更合理。综合考虑各种因素,建议在建工程断层区环向盲管间距设置为3 m,断层附近区间距为4 m。     

Estimating traffic volumes on intercity road locations using roadway attributes,socioeconomic features and other work-related activity characteristics

Traffic volume data are key inputs to many applications in highway design and planning. But these data are collected in only a limited number of road locations due to the cost involved. This paper presents an approach for estimating daily and hourly traffic volumes on intercity road locations combining clustering and regression modelling techniques. With the aim of applying the procedure to any road location, it proposes the use of roadway attributes and socioeconomic characteristics of nearby cities as explanatory variables, together with a set of previously discovered patterns with the hourly traffic percent distribution. Test results show that the proposed approach significantly produces accurate estimates of daily volumes for most locations. The accuracy at hourly level is a bit more reduced but, for periods when traffic is significant, more than half of the estimates are within 20% of absolute percentage error. Moreover, the main peak period is approximately identified for most cases. These findings together with its great applicability make this approach attractive for planners when no traffic data are available and an estimate is helpful.     

Transport in developing and emerging nations

One perspective on the allocation of transport investments by public authorities is offered by the so‐called ‘pork barrel’ model, whereby politicians and political parties allocate public investment spatially in such a way as to gain electoral support from localities so benefited. The paper introduces this model and discusses its attractions and problems in the case of the transport sector. A review of the modest number of published examples of this approach is offered before a detailed case study considers the case of railway investment in Nelson, New Zealand.     

Short‐term traffic forecasting: Overview of objectives and methods

In the last two decades, the growing need for short‐term prediction of traffic parameters embedded in a real‐time intelligent transportation systems environment has led to the development of a vast number of forecasting algorithms. Despite this, there is still not a clear view about the various requirements involved in modelling. This field of research was examined by disaggregating the process of developing short‐term traffic forecasting algorithms into three essential clusters: the determination of the scope, the conceptual process of specifying the output and the process of modelling, which includes several decisions concerning the selection of the proper methodological approach, the type of input and output data used, and the quality of the data. A critical discussion clarifies several interactions between the above and results in a logical flow that can be used as a framework for developing short‐term traffic forecasting models.     

Practical safety considerations for short headway automated transit systems

Continued interest in Personal Rapid Transit (PRT) systems as one solution to urban traffic congestion emphasizes the need for careful consideration of the safety of short headway automated transit systems. Current approaches to the determination of safe headways are reviewed. The reduction in headway which could be achieved by improved braking and signaling hardware is outlined. Improved design of emergency brakes is the most important single factor in the reduction of safe headways.

Very short headway systems are reviewed from a safety standpoint. Such systems might be safely operated if operation at intermediate headways (separations on the order of the stopping distance) can be avoided.     

Gender inequality in mobility and mode choice in Pakistan

Using the nationally representative dataset of the 2007 Pakistan Time-Use Survey, this paper examines gender differences in daily trip rate, mode choice, travel duration, and purpose of travel, which are previously unreported because of limited data availability. Wide gender mobility gaps are observed in the country, where women are less likely to travel, are half as mobile as men and may rely heavily on walking. The particular social and cultural context of the country, that renders women as private, secluded and family honor, seems influential in shaping their mobility and choice of activities. Demographic factors such as age, household income, and marital status significantly decrease female mobility levels. Hence, these findings call for a gender-based culturally responsive transportation policy in the country.     

Using structural equations modeling to unravel the influence of land use patterns on travel behavior of workers in Montreal

This paper addresses the relations between travel behavior and land use patterns using a Structural Equations Modeling (SEM) framework. The proposed model structure draws on two earlier models developed for Lisbon and Seattle which show significant effects of land use patterns on travel behavior. The travel behavior variables included here are multifaceted including commuting distance, car ownership, the amount of mobility by mode (car, transit and non-motorized modes), both in terms of total kilometers travelled and number of trips. The model also includes a travel scheduling variable, which is the total time spent between the first and last trips to reflect daily constraints in time allocation and travel.The modeled land use variables measure the levels of urban concentration and density, diversity, both in terms of types of uses and the mix between jobs and inhabitants/residents, the transport supply levels, transit and road infrastructure, and accessibility indicators. The land use patterns are described both at the residence and employment zones of each individual included in the model by using a factor analysis technique as a data reduction and multicollinearity elimination technique. In order to explicitly account for self selection bias the land use variables are explicitly modeled as functions of socioeconomic attributes of individuals and their households.The results obtained show that people with different socioeconomic characteristics tend to work and live in places of substantially different urban environments. But besides these socioeconomic self-selection effects, land use variables significantly affect travel behavior. More precisely the effects of land use are in great part passed thru variables describing long term decisions like commuting distance, and car ownership. These results point to similar conclusions from the models developed for Lisbon and Seattle and thus give weight to the use of land use policies as tools for changing travel behavior.     

A household-level activity pattern generation model with an application for Southern California

This paper develops and estimates a multiple discrete continuous extreme value model of household activity generation that jointly predicts the activity participation decisions of all individuals in a household by activity purpose and the precise combination of individuals participating. The model is estimated on a sample obtained from the post census regional household travel survey conducted by the South California Association of Governments in the year 2000. A host of household, individual, and residential neighborhood accessibility measures are used as explanatory variables. The results reveal that, in addition to household and individual demographics, the built environment of the home zone also impacts the activity participation levels and durations of households. A validation exercise is undertaken to evaluate the ability of the proposed model to predict participation levels and durations. In addition to providing richness in behavioral detail, the model can be easily embedded in an activity-based microsimulation framework and is computationally efficient as it obviates the need for several hierarchical sub-models typically used in extant activity-based systems to generate activity patterns.     

Commercially managed road funds: managing roads like a business,not like a bureaucracy

Nearly all countries are seriously short of revenues for investment and maintenance of roads. Improving utilization of the existing road budget has helped to narrow, but not eliminate, this financing gap. Requests for additional resources from the government's budget have fallen on deaf ears, because the road sector has grown too large to be fully-financed through general tax revenues. Government tax systems were not designed to finance major economic sectors like roads. Faced with an acute shortage of funds, many road agencies have introduced tolls on high-volume roads and have invited the private sector to build and operate such roads under concession agreements. Although this has narrowed the financing gap, tolling is only economic on a small part of the road network. Tolls have thus had a relatively small impact on the financing gap. Against this background, and mindful of the fact that roads are now 'big business' on the scale of the Fortune Global 500, a growing number of countries have started to 'bring roads into the market place, put them on a fee-for-service basis and manage them like a business.' The fee-for-service concept, though superficially like the user-pay principle and the associated road funds which became popular during the 1950s, differs from user-pay in a number of important respects. The key differences are that: (i) only road user charges go into the road fund (i.e., there are no earmarked taxes); (ii) the fund is managed by a representative board with half or more members representing road users and the business community; (iii) members are nominated by the constituencies they represent and there is an independent chairperson; (iv) financing arrangements are designed to ensure that money is not diverted from other sectors; (v) funds are managed pro-actively by a small secretariat; (vi) there are published financial regulations governing the way funds are managed; (vii) charges are adjusted regularly to meet agreed expenditure targets; and (viii) there are regular technical and financial audits. Other important characteristics are that most commercially managed road funds are managed through a separate road fund administration, funds are channeled to all roads (sometimes even to unclassified roads) and they are introduced as part of a wider agenda to commercialize road management. Some of these road funds have been set up as road public utilities under a board with powers to set their own tariffs.     

Automated detection of lane-blocking freeway incidents using artificial neural networks

A major source of urban freeway delay in the U.S. is non-recurring congestion caused by incidents. The automated detection of incidents is an important function of a freeway traffic management center. A number of incident detection algorithms, using inductive loop data as input, have been developed over the past several decades, and a few of them are being deployed at urban freeway systems in major cities. These algorithms have shown varying degrees of success in their detection performance. In this paper, we present a new incident detection technique based on artificial neural networks (ANNs). Three types of neural network models, namely the multi-layer feedforward (MLF), the self-organizing feature map (SOFM) and adaptive resonance theory 2 (ART2), were developed to classify traffic surveillance data obtained from loop detectors, with the objective of using the classified output to detect lane-blocking freeway incidents. The models were developed with simulation data from a study site and tested with both simulation and field data at the same site. The MLF was found to have the highest potential, among the three ANNs, to achieve a better incident detection performance. The MLF was also tested with limited field data collected from three other freeway locations to explore its transferability. Our results and analyzes with data from the study site as well as the three test sites have shown that the MLF consistently detected most of the lane-blocking incidents and typically gave a false alarm rate lower than the California, McMaster and Minnesota algorithms currently in use.