Participation and desire: leisure activities among Canadian adults with disabilities

As a signatory of the Convention on the Rights of Persons with Disabilities, Canada has assumed the obligation to foster the fundamental right of individuals with impairments to participate in all normal activities and relationships of society. Currently, however, relatively little is known about the extent to which Canadians with disabilities are able to exercise of this right. Previous research has investigated the employment status and commute distance of persons with disabilities in Canada. In this paper, we use the 2006 Participation and Activity Limitation Survey to investigate, from the perspective of Canadian adults with disabilities, the factors that influence (1) their frequency of participation in various leisure and recreation activities; (2) the role of transportation in activity participation; and (3) the desire for more leisure and recreation activities during spare time. The latter question is closely associated to the experience of exclusion. The results of the analysis indicate that some of the very factors that tend to reduce participation also relate to a desire for more leisure and recreation activities.     

An empirical analysis of freight transport traffic modes in Brazil, 1996–2012

This paper analyses the performance of freight transportation modes in Brazil – namely air, water, rail and road – from February 1996 to August 2012 by investigating their long memory properties using fractional integration and autoregressive models on monthly tonnage data. Two important features are analysed: the degree of dependence of transportation traffic across time and its seasonal structure over the period. Furthermore, the stability of parameters across the sample period is investigated, incorporating potential structural breaks in the data, which describe discontinuity in freight transportation traffic. Some policy implications are derived.     

Bayesian committee of neural networks to predict travel times with confidence intervals

Short-term prediction of travel time is one of the central topics in current transportation research and practice. Among the more successful travel time prediction approaches are neural networks and combined prediction models (a ‘committee’). However, both approaches have disadvantages. Usually many candidate neural networks are trained and the best performing one is selected. However, it is difficult and arbitrary to select the optimal network. In committee approaches a principled and mathematically sound framework to combine travel time predictions is lacking. This paper overcomes the drawbacks of both approaches by combining neural networks in a committee using Bayesian inference theory. An ‘evidence’ factor can be calculated for each model, which can be used as a stopping criterion during training, and as a tool to select and combine different neural networks. Along with higher prediction accuracy, this approach allows for accurate estimation of confidence intervals for the predictions. When comparing the committee predictions to single neural network predictions on the A12 motorway in the Netherlands it is concluded that the approach indeed leads to improved travel time prediction accuracy.     

Hybridation of generation propagation models and SPH model to study severe sea states in Galician Coast

The Atlantic and Cantabrian coasts of the Iberian Peninsula suffer the periodic passage of storms which give rise to severe sea states. Standard generation- propagation models (WAM, WAVEWATCH, SWAN) are commonly used for operational oceanography purposes with satisfactory results both in the open ocean and in near shore areas but they do not provide information about the possibility of flooding in coastal areas. A 2D HV version of SPH (Smoothed Particle Hydrodynamics) model is considered to propagate the signal provided by generation- propagation models to the coast and to analyze the nature of coastal structures overtopping as a tool to create maps of risk. SPH is shown to provide valuable information about overtopping (maximum water height and water velocity) under the stormy conditions suffered by the Galician coast on February 17, 2006.     

Driver response to variable message signs: a stated preference investigation

This paper uses a Stated Preference approach to undertake a detailed assessment of the effect on drivers’ route choice of information provided by variable message signs (VMS). Although drivers’ response to VMS information will vary according to the availability of alternative routes and the extent to which they are close substitutes, our findings show that route choice can be strongly influenced by the provision of information about traffic conditions ahead. This has important implications for the use of VMS systems as part of comprehensive traffic management and control systems. The principal findings are that the impact of VMS information depends on: the content of the message, such as the cause of delay and its extent; local circumstances, such as relative journey times in normal conditions; and drivers’ characteristics, such as their age, sex and previous network knowledge. The impact of qualitative indicators, visible queues and delays were examined. It was found that not only is delay time more highly valued than normal travel time, which is to be expected, but that drivers become more sensitive to delay time as delay times increased across the range presented.     

潮湿路面滑水现象及抗滑力模型

滑水及抗滑力的衰减是潮湿条件下影响道路及机场跑道交通安全的两个重要因素。模拟潮湿路面抗滑力是一个相对复杂的问题。笔者采用理论研究方法,提出了一个分析计算模型,用来模拟车轮滑移速度增加时,潮湿路面的滑水现象及抗滑力的衰减情况。该理论公式及三维有限元模型的理论基础是固体力学及流体动力学。通过NASA滑水速度方程,对模型计算的滑水速度进行分析验证。     

Situation and prospects of shipboard integrated power system reconfiguration technology北大核心CSCD

当前,船舶综合电力系统(IPS)正朝着复杂化、模块化、自动化方向发展,研究快速、稳定、能够应对各种突发状况的船舶综合电力系统重构技术对保障船舶安全和可靠航行具有重要意义。首先,综述当前国内外在船舶综合电力系统重构技术方面的研究进展,讨论集中式重构和分布式重构的特点,并对数学优化算法、启发式算法、人工智能算法等进行归纳总结;然后,分析面对多重并发故障时重构技术所面临的困难与挑战,提出需重点关注混杂系统建模和分层分布式重构框架的建立;最后,从重构模型建立、算法优化、分布式架构等方面对未来船舶综合电力系统重构的发展提出设想和建议。     

A randomized controlled trial in travel demand management

Transportation - This paper presents a trial aimed at reducing parking demand at a large urban employer through an informational campaign and monetary incentives. A 6-week randomized controlled...     

Information impact on quality of multimodal travel choices: conceptualizations and empirical analyses

This paper investigates the impact of a variety of travel information types on the quality of travel choices. Choice quality is measured by comparing observed choices made under conditions of incomplete knowledge with predicted choice probabilities under complete knowledge. Furthermore, the potential impact of travel information is considered along multiple attribute-dimensions of alternatives, rather than in terms of travel time reductions only. Data is obtained from a choice experiment in a multimodal travel simulator in combination with a web-based mode-choice experiment. A Structural Equation Model is estimated to test a series of hypothesized direct and indirect relations between a traveler’s knowledge levels, information acquisition behavior and the resulting travel-choice quality. The estimation results support the hypothesized relations, which provides evidence of validity and applicability of the developed measure of travel-choice quality. Furthermore, found relations in general provide some careful support for the often expected impact of information on the quality of travel choices. The effects are largest for information services that generate previously unknown alternatives, and lowest for services that provide warnings in case of high travel times only.

Influence of the weather on mode choice in corridors with time-varying congestion: a mixed data study

Studies that link human behaviour to the influence of weather have historically been conducted in such fields as tourism, marketing and leisure. In most studies that jointly examine weather and the mode of transport, only open-air transportation has been considered (for example, bicycle, motorcycle or walking). This focus, together with the habitual use of data collected with automatic devices and a lack of studies that analyse this issue using stated preference data, are the main reasons motivating this paper. This paper aims to analyse the influence of weather and the density of traffic on the choice of transport mode. A case study is conducted in an access/egress corridor located in the city of Barcelona (Spain). Two data sources were used: revealed preference and stated preference data. Modelling techniques using mixed data enabled the stronger features from both data sources to be captured. Finally, we discuss how the selection of different alternative specific constants in models estimated using mixed data could generate unrealistic forecasting results if environmental changes are expected in the actual market.