The determinants of long distance travel in Great Britain

This study analyses of the determinants of long distance travel in Great Britain using data from the 1995-2006 National Travel Surveys (NTSs). The main objective is to determine the effects of socio-economic, demographic and geographic factors on long distance travel. The estimated models express the distance travelled for long distance journeys as a function of income, gender, age, employment status, household characteristics, area of residence, size of municipality, type of residence and length of time living in the area. A time trend is also included to capture common changes in long distance travel over time not included in the explanatory variables. Separate models are estimated for total travel, travel by each of four modes (car, rail, coach and air), travel by five purposes (business, commuting, leisure, holiday and visiting friends and relatives (VFRs)) and two journey lengths (<150 miles and 150+ miles one way), as well as the 35 mode-purpose-distance combinations.The results show that long distance travel is strongly related to income: air is most income-elastic, followed by rail, car and finally coach. This is the case for most journey purposes and distance bands. Notable is the substantial difference in income elasticities for rail for business/commuting as opposed to holiday/leisure/VFR. In addition, the income elasticity for coach travel is very low, and zero for the majority of purpose-distance bands, suggesting coach travel to be an inferior mode in comparison to car, rail and air. Regarding journey distance, we find that longer distance journeys are more income elastic than shorter journeys.For total long distance travel, the study indicates that women travel less than men, the elderly less than younger people, the employed and students more than others, those in one adult households more than those in larger households and those in households with children less than those without. Long distance travel is also lowest for individuals living in London and greatest for those in the South West, and increases as the size of the municipality declines.     

Vulnerability analysis for large-scale and congested road networks with demand uncertainty

To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.     

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.     

VMT, energy consumption, and GHG emissions forecasting for passenger transportation

Globalization, greenhouse gas emissions and energy concerns, emerging vehicle technologies, and improved statistical modeling capabilities make the present moment an opportune time to revisit aggregate vehicle miles traveled (VMT), energy consumption, and greenhouse gas (GHG) emissions forecasting for passenger transportation. Using panel data for the 48 continental states during the period 1998-2008, the authors develop simultaneous equation models for predicting VMT on different road functional classes and examine how different technological solutions and changes in fuel prices can affect passenger VMT. Moreover, a random coefficient panel data model is developed to estimate the influence of various factors (such as demographics, socioeconomic variables, fuel tax, and capacity) on the total amount of passenger VMT in the United States. To assess the influence of each significant factor on VMT, elasticities are estimated. Further, the authors investigate the effect of different policies governing fuel tax and population density on future energy consumption and GHG emissions. The presented methodology and estimation results can assist transportation planners and policy-makers in determining future energy and transportation infrastructure investment needs.     

The accuracy of proxy responses in a stated choice setting: A re-examination and some controversial conclusions

Data is typically gathered from an individual respondent who represents the group or the household. This individual is often identified as the “primary decision maker” and is asked to provide responses as a proxy for the group given that the cost of interviewing each member individually is impractical and/or expensive. The collection of joint preferences is rarely undertaken, with the use of proxy responses not uncommon in travel behaviour research. Under such a framework, there exists an assumption that the primary decision maker has perfect knowledge of other group member preferences, and bargaining behaviour, and is able to synthesise this information when providing a response on their behalf. The validity of such an assumption however remains an open question, with recent research calling the reliability of proxy responses into account (Bateman and Munro, 2009). In this paper, using three models estimated in willingness to pay space, we examine the accuracy of proxy responses in a stated choice experiment. We find that there is overlap between a proxy response and the own preferences of the individual providing the proxy choice, but while the proxy responses fail to represent the full preference heterogeneity that exists in the actual choices made by individuals, the proxy responses in aggregate provide a suitable replacement for actual data, subject to a number of caveats.     

预制中隔墙施工技术在轨交区间隧道内的应用

轨交区间隧道中隔墙采用预制与现浇结合的方式进行施工,在国内尚属首例。以上海轨交16号线南段工程为实例,阐述了在施工过程中如何在小空间范围内进行拼装中隔墙、临时支撑的安装及浇筑等工艺,可为今后类似工程施工提供借鉴。     

穿越古滑坡川主寺隧道围岩破坏特征及稳定性研究

文章以川主寺隧道所处的工程地质条件为基础,通过现场调研分析了隧道围岩变形破坏形式主要为坍塌、掉块以及剥落.围岩稳定性三维有限元数值模拟结果显示,碎裂围岩自稳能力差,围岩变形以弹塑性变形、松弛变形为主;H型钢拱架支护结构对碎裂围岩稳定性起到积极的作用,并通过典型洞段现场位移监测数据分析结果得以证实.     

轴对称解对隧道衬砌水压力计算的适用性研究

文章根据渗流理论推导了隧道衬砌水压力的轴对称解,并利用数值分析方法研究了轴对称解对不同形状隧道断面与浅埋隧道的适用性.研究结果表明:轴对称解适用于非圆形隧道断面衬砌水压力的估算;隧道断面形状对衬砌水压力折减系数的影响较小,可以忽略不计,其影响大小主要由衬砌与围岩的渗透系数比值决定.对于浅埋低水头隧道,用轴对称解计算的毛洞流量Qm与数值解比较,其误差较大,最大误差为36.5％;但用来计算衬砌水压力p1以及衬砌后水流量Q1时,误差相对较小,最大误差为6.3％,特别是利用轴对称解得出的衬砌水压力值与利用数值解得出的衬砌水压力特征值最大误差仅为3.4％.     

宁波轨道交通1号线车站深基坑设计与施工监测的对比分析

本文对宁波市轨道交通1号线东门口站所进行的土层性质分析、设计方案的优化、设计计算结果与实际施工监测数据的对比分析,对于宁波地区轨道交通车站深基坑设计具有积极意义,使设计与施工能互为印证、互为比较、互为参考,为后续地下三层车站的设计和施工提供了宝贵的实践经验。     

Surface street traffic volume and single-family house price

This study investigates the relationship between surface street traffic volume and single-family house prices in a relatively small city in the US. Hedonic price models are estimated using data from 9670 transactions that occurred between January 1998 and March 2011. It is discovered that parcels fronting or adjacent to a high-traffic street sell, on average, at an 8.1% discount compared to similar parcels that are not so situated. Restricting the analysis to parcels on or adjacent to a high-traffic street, house price and traffic volume are found to be negatively related; a doubling of volume from any particular traffic count, ceteris paribus, reduces selling price by an average of 2.1%.