Distributed algorithm for empty vehicles management in personal rapid transit (PRT) network

In this paper, an original heuristic algorithm of empty vehicles management in personal rapid transit network is presented. The algorithm is used for the delivery of empty vehicles for waiting passengers, for balancing the distribution of empty vehicles within the network, and for providing an empty space for vehicles approaching a station. Each of these tasks involves a decision on the trip that has to be done by a selected empty vehicle from its actual location to some determined destination. The decisions are based on a multi‐parameter function involving a set of factors and thresholds. An important feature of the algorithm is that it does not use any central database of passenger input (demand) and locations of free vehicles. Instead, it is based on the local exchange of data between stations: on their states and on the vehicles they expect. Therefore, it seems well‐tailored for a distributed implementation. The algorithm is uniform, meaning that the same basic procedure is used for multiple tasks using a task‐specific set of parameters. Copyright © 2016 John Wiley & Sons, Ltd.     

广州地铁线路及车站管理归属划分的研究

针对目前广州地铁的管理模式,通过分析线路和车站的特点,提出线网线路以及车站管理归属的划分原则。通过建立参数和模型,提出了广州地铁线网线路管理归属的3个方案,并运用各种分析方法进行分析比较,最终确定了合适的方案,为完善线网管理体系奠定基础。     

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近年来，一些大城市通过修建大量的道路来缓解交通拥堵的压力，但这种做法却导致更多的车辆使用道路，从而加剧了交通拥堵，造成空气质量下降，资源浪费严重。为解决这些问题，一些城市已经开始或者计划构建以轨道交通主体，轻轨交通或者其他交通方式为补充的交通体系，以增强路网的流动性和可达性。本文从城市流动性和可持续发展的角度，对已有的和新型的轻型交通系统做综述。旨在为交通规划人员进行可持续发展交通运输系统的规划等工作提供参考。     

车道分隔方式对驾驶换道行为的影响

为探索不同车道分隔方式对驾驶换道行为的影响，在分析机动车驾驶换道决策机理与换道决策属性的基础上，改进双车道元胞自动机(STCA)的换道规则模型，提出了基于层次分析法(AHP)的多属性换道决策模型.在同向 3车道上设置不同车道分隔方式，运行模型以获得每种分隔方式在不同空间占有率情况下的换道动机概率、换道成功概率分布规律.分析发现：平均换道动机概率直接与交通流内部状态属性有关，平均换道成功概率则由交通流内部状态属性与车道隔离方式共同决定；通过对不同分隔方式下的换道规律分析，表明模型能较好诠释不同车道分隔方式的交通管理法规涵义.该换道决策模型构造方法上具有同时处理多个外部决策属性的能力，具有较强的通用性.     

The development of a decision making framework for evaluating the trade-off solutions of cleaner seaborne transportation

The general rise in marine fuel prices in combination with ever-more stringent environmental regulations resulting from IMO conventions and EU Directives have become the main industry drivers for seaborne transportation to become cleaner and more energy efficient. Compliance with existing and soon-to-be-enacted regulations requires evaluating the trade-off between often-conflicting options to select the best available technology or fuel source. Although the traditional way of dealing with this issue has been to apply a cost benefit analysis, this kind of analysis does not adequately consider the complexities of the problem, such as incorporating linguistic preferences or interrelations amongst attributes, experts and their preferences.The challenge in such an analysis corresponds to that of a multiple attribute decision-making problem in which a finite number of alternatives are assessed with regards to a finite number of attributes and experts and ranked from the best to the worst.In this paper, a comprehensive and holistic decision-making framework is proposed to overcome the barriers of cost-benefit analysis techniques, facilitating the inclusion of all possible combinations of decision-making parameters and their discrete values, which will eventually help the industry achieve cleaner seaborne transportation.To demonstrate the applicability of the proposed framework, this paper focuses on a real-life study case involving an environmental compliance problem in the Port of Copenhagen, Denmark, in relation to a particular EU Directive. In conclusion, the proposed framework can be applied as a generalised decision-making model to similar compliance issues encountered within other modes of transportation such as rail and road.     

记名提单物权属性的理论研究与司法实践

记名提单作为物权凭证,通过各项物权功能的发挥维系着海上货物运输合同关系的稳定并促成相关商业价值的实现。本文分析论证了记名提单作为物权凭证的权利内涵及其物权属性的具体表现；最后从司法实践角度,考察了世界主要航运国家基于肯定记名提单物权属性而在实践中坚持凭单放货原则的统一化趋势。     

多属性权衡理论在舰船优化设计中的应用研究

探讨多属性权衡理论在舰船优化设计中的应用方式,并以舰船推进装置和电站方案的权衡分析为例,在舰船设计综合模型的基础上,得出了衡量方案优劣的属性值,采用权衡分析的方式,为舰船方案的优化提供了一种实用的手段。     

基于属性块的AutoCAD与Access数据库的连接方法

介绍以属性图块为基础、应用VBA编程实现AutoCAD与Access数据库连接的方法,为进一步实现PDM奠定基础.     

Prospect Theory for joint time and money consequences in risk and ambiguity

Transport users face complex decisions. Not only are the consequences of their choices uncertain, but they generally involve several attributes, such as time and money. Time-money tradeoffs have been studied in depth in transport economics, and research is now paying increasing attention to the role of uncertainty and information in transport decisions. This paper aims to measure the impact of uncertainty and information on multi-attribute decisions using Prospect Theory. In doing so, the study makes two contributions to transportation literature: one methodological and the other empirical. First, we propose a fast and tractable method for measuring Prospect Theory parameters that capture attitudes towards probabilities (probability weighting function) and attitudes towards losses (loss aversion). The elicitation method does not require the elicitation of the utility function. This makes it particularly suitable in complex multi-attribute decisions where the shape of the utility function is unknown. Second, we present the results of an experiment that uses the proposed method to measure, at the individual level, probability weighting in decisions involving joint time and money consequences in two decision contexts: risk (where probabilities are given) and ambiguity (where the probability distribution is unknown). An experimental setup that exposes subjects to real gains and losses for money and time has been built for this purpose. We observe inverse S-shaped probability weighting and loss aversion for risk. Probability weighting is even more pronounced in ambiguity, where subjects do not have precise information about the probability distribution. We explain how these results and the analysis of ambiguity attitudes in general can offer a better understanding of travelers’ route or transport mode choices.     

Specification issues in a generalised random parameters attribute nonattendance model

An extensive literature has recognised that when travel choices are made, only a subset of the attributes of the choice alternatives may be considered or attended to by each decision maker. Numerous econometric approaches have been employed to identify attribute nonattendance (ANA), with the most prevalent in the literature being an adaptation of the latent class model. However, the two latent class structures so far employed either incur a potentially very high parametric cost, or rely on an assumption that nonattendance is independent across all attributes. We present a generalised model that allows for an arbitrary degree of correlation of nonattendance across attributes. In the presented stated choice study investigating short haul flights, this generalised model outperforms the existing approaches. Like two recent papers, the model handles both ANA and preference heterogeneity by combining continuously distributed random parameters with latent classes. However, we present recommendations regarding a number of identification issues stemming from the combination of these two forms of random parameters not covered in those papers. Further, covariates can be introduced into our generalised model to allow insights to be gained into ANA behaviour. We investigate stated ANA as a covariate, and find inferred ANA rates to be more aligned with stated ANA responses than alternative methods.