三峡坝区河势演变与水流特性的研究

给出了三峡坝区河势演变与水流动力特性变化的试验研究成果     

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已有旅行时间预测方法多是针对高速公路、城市快速路和主干道路的路段,而针对城市一般道路,及路径旅行时间预测的研究则相对不足.本文提出一种基于案例的旅行时间预测算法.算法的基本原理为,在轨迹数据建模的基础上,建立动态更新的、包含多个属性的历史旅行样本数据库,然后根据出行时间及环境信息从案例库查找匹配案例,其结果经过一定修正用于预测路径旅行时间.与基于路段的旅行时间预测方法相比,该算法具有较强的鲁棒性和可移植性,受空间路网和数据样本量的影响较弱;并且在相同数据样本量和路网空间覆盖率的情况下,该算法预测精度高于对比算法.     

铁路站场咽喉区优化设计及平面图自动铺画方法研究

铁路车站咽喉区平面设计在站场计算机辅助设计中占有重要的地位,本文运用图论思想对车站咽喉区结构图型进行数学抽象,提出识别咽喉区结构图型中道岔邻接关系的象限推理方法,建立以缩短咽喉长度为优化目标的数学模型,并依此实现利用计算机推算咽喉区最优岔心位置坐标的算法,最后通过实例对文中提出的模型算法进行验证.     

客车内饰材料燃烧标准分析

针对客车内饰材料燃烧特性标准体系现状,参照国内外相关标准和相关交通、建筑方面的防火阻燃标准,分析现行标准的不足,并提出建议。     

基于案例推理的测试序列生成方法研究

鉴于测试序列生成专家系统知识获取困难以及知识库维护不易等问题,本文提出从案例推理技术的新角度研究CTCS-3级列控系统测试序列的生成.设计了测试序列案例推理流程;提取了现场测试序列特征属性并构建了案例的框架表示结构;为实现案例检索,设计了属性相似度计算方法、确定案例属性权重的层次分析法、案例间相似度计算方法和案例检索过程;给出一个测试序列生成的具体流程.基于案例推理的研究方法为CTCS-3级列控系统测试序列的生成提供了一个新的思路.     

Impact of Everyday Weather on Individual Daily Travel Behaviours in Perspective: A Literature Review

Despite the hundreds of billions of dollars being spent on infrastructure development -- from roads, rail and airports to energy extraction and power networks to the Internet -- surprisingly little reliable knowledge exists about the performance of these investments in terms of actual costs, benefits and risks. This paper presents results from the first statistically significant study of cost performance in transport infrastructure projects. The sample used is the largest of its kind, covering 258 projects in 20 nations worth approximately US$90 billion (constant 1995 prices). The paper shows with overwhelming statistical significance that in terms of costs transport infrastructure projects do not perform as promised. The conclusion is tested for different project types, different geographical regions and different historical periods. Substantial cost escalation is the rule rather than the exception. For rail, average cost escalation is 45% (SD=38), for fixed links (tunnels and bridges) it is 34% (62) and for roads 20% (30). Cost escalation appears a global phenomenon, existing across 20 nations on five continents. Cost estimates have not improved and cost escalation not decreased over the past 70 years. Cost estimates used in decision-making for transport infrastructure development are highly, systematically and significantly misleading. Large cost escalations combined with large standard deviations translate into large financial risks. However, such risks are typically ignored or underplayed in decision-making, to the detriment of social and economic welfare.     

Choosing Public Transport—Incorporating Richer Behavioural Elements in Modal Choice Models

The development of behaviourally richer representations of the role of well-established and increasingly important influences on modal choice, such as trip time reliability and accounting for risk attitude and process rules, has moved forward at a fast pace in the context of automobile travel. In the public transport setting, such contributions have, with rare exception, not been considered. In this paper, we discuss and empirically illustrate the merits of advanced modelling developments aimed at improving our understanding of public transport choice, namely the inclusion of reliability in extended expected utility theoretic forms, to recognize risk attitude and perceptual conditioning, the consideration of passenger crowding and its inclusion in linear additive models, and the role of multiple heuristics in representing attribute processing as a way of conditioning modal choice. We illustrate the mechanics of introducing these behaviourally appealing extensions using a modal choice data set collected in Sydney.     

A State-of-the-Art Review: Developments in Utility Theory,Prospect Theory and Regret Theory to Investigate Travellers' Behaviour in Situations Involving Travel Time Uncertainty

Abstract

Despite the wide use of utility theory to model travellers' behaviour, the interest in non-expected utility theories has increased due to their potential to capture more realistic behaviour. A main question raised is whether travellers are better described as utility maximizers or should be qualified differently.

This paper presents a literature review on the use of expected utility theory (EUT), prospect theory (PT) and regret theory (RT) to model travellers' behaviour. Gaps in the literature are identified and a discussion about advantages and disadvantages of each theory is presented. A case study illustrates the differences between the theories.

Under certain conditions, PT and RT restrict themselves to EUT. Their added value, however, is the possibility of capturing loss aversion, risk aversion and risk-seeking (PT) and regret aversion (RT). On the practical level, the use of EUT is well established, while contributions of PT and RT are marginal. On the theoretical level, however, RT seems to be (marginally) more suitable to model travellers' behaviour, while EUT and PT are equally suitable. This suggests that the large use of EUT is highly influenced by its very tractable framework. We do not claim the superiority of any theory, but propose to compare them through a systematic review.     

Modelling heavy vehicle car‐following behaviour in congested traffic conditions

This study develops a car‐following model in which heavy vehicle behaviour is predicted separately from passenger car. Heavy vehicles have different characteristics and manoeuvrability compared with passenger cars. These differences could create problems in freeway operations and safety under congested traffic conditions (level of service E and F) particularly when there is high proportion of heavy vehicles. With increasing numbers of heavy vehicles in the traffic stream, model estimates of the traffic flow could be degrades because existing car‐following models do not differentiate between these vehicles and passenger cars. This study highlighted some of the differences in car‐following behaviour of heavy vehicle and passenger drivers and developed a model considering heavy vehicles. In this model, the local linear model tree approach was used to incorporate human perceptual imperfections into a car‐following model. Three different real world data sets from a stretch of freeway in USA were used in this study. Two of them were used for the training and testing of the model, and one of them was used for evaluation purpose. The performance of the model was compared with a number of existing car‐following models. The results showed that the model, which considers the heavy vehicle type, could predict car‐following behaviour of drivers better than the existing models. Copyright © 2013 John Wiley & Sons, Ltd.