Dynamic charging infrastructure deployment for plug-in hybrid electric trucks

Inspired by the rapid development of charging-while-driving (CWD) technology, plans are ongoing in government agencies worldwide for the development of electrified road freight transportation systems through the deployment of dynamic charging lanes. This en route method for the charging of plug-in hybrid electric trucks is expected to supplement the more conventional charging technique, thus enabling significant reduction in fossil fuel consumption and pollutant emission from road freight transportation. In this study, we investigated the optimal deployment of dynamic charging lanes for plug-in hybrid electric trucks. First, we developed a multi-class multi-criteria user equilibrium model of the route choice behaviors of truck and passenger car drivers and the resultant equilibrium flow distributions. Considering that the developed user equilibrium model may have non-unique flow distributions, a robust deployment of dynamic charging lanes that optimizes the system performance under the worst-case flow distributions was targeted. The problem was formulated as a generalized semi-infinite min-max program, and a heuristic algorithm for solving it was proposed. This paper includes numerical examples that were used to demonstrate the application of the developed models and solution algorithms.     

Transition to a cyclable city: Latent variables affecting bicycle commuting

An understanding of the key factors influencing bicycle commuting is essential for developing effective policies towards a cyclable city. This paper contributes to this line of research by proposing a methodology for including cycling-related indicators in mobility surveys based on the Theory of Planned Behaviour (TPB), and applying an exploratory factor analysis (EFA) to evaluate the structure of latent variables associated with bicycle commuting. The EFA identified six cycling latent variables: Lifestyle, Safety and comfort, Awareness, Direct disadvantages, Subjective norm, and Individual capabilities. These were complemented with a latent variable related to habit: Non-commuting cycling habit. Statistical differences and regression analysis were applied with the cycling latent variables. The study also includes the relationship between objective factors and bicycle commuting, which reveals minor associations. This methodology was applied to the “starter cycling city” of Vitoria-Gasteiz (Spain). The results confirm that in this context – in transition to a cyclable city – safety and comfort issues are not the main barriers for all commuters, although more progress needs to be made to normalise cycling. A set of customised policy initiatives is recommended in the light of the research findings, including marketing campaigns to encourage non-commuting cycling trips, bicycle measures to target social groups as opposed to individuals, bicycle-specific programs such as “Bike-to-work Days”, and cycling courses.     

考虑损伤下的汽车吸能盒轴向压缩特性研究

用有限元软件ABAQUS对钢质、铝合金质吸能盒的吸能特性进行对比研究,采用不同的损伤模型模拟材料的变形行为,比较了两种吸能盒轴向压缩距离、变形模式、评价指标的变化特性。结果表明,数值模拟下吸能盒的轴向压缩距离和变形模式与试验结果吻合。在冲击速度为10 m/s的低速碰撞下,铝合金质吸能盒吸收的能量与钢质吸能盒相比减少了6%;钢质吸能盒的吸能效率为35.5 kJ/mm,比铝合金质吸能盒高。铝合金质吸能盒相较于钢质吸能盒在压缩过程中形成了明显的折叠褶皱,边缘处材料失效,单元被移除。吸能盒的评价指标中铝合金质吸能盒的比吸能 （SEA）、峰值碰撞力 （PCF） 均比钢质吸能盒更优,钢质吸能盒的吸能量 （EA）、平均碰撞力 （MCF） 比铝合金质吸能盒更优。铝合金相比钢更适合作为中低速碰撞时车用吸能盒的材料。     

基于态度-行为模型的低收入通勤者出行方式选择

为了分析城市低收入通勤者交通方式选择行为,揭示个体社会经济属性、活动 属性和潜在态度变量对出行者出行方式选择的影响,基于抚顺市居民一日出行调查数 据,采用态度-行为模型探究低收入通勤者出行方式选择机理.首先基于多指标多原因模 型分析影响态度变量的外在因素,结果表明性别、驾照拥有情况和年龄对态度变量的构 成影响较大.然后,分别建立含潜变量和不含潜变量的多项Logit 模型,发现含潜变量的选 择模型更能解释出行行为,社会经济属性、活动属性和态度变量对低收入通勤者出行方 式选择影响存在一定差异.     

城轨虚拟编组关键性能指标及技术探讨

列车虚拟编组技术能够实现车辆资源的高效灵活利用,是解决轨道交通客流时空分布不均衡问题的有效方法,已成为国内外的研究热点。既有研究借鉴了汽车编队追踪的思路,主要关注于列车稳定追踪的相关方法,未能完全适应轨道交通的实际需求。针对城市轨道交通(简称“城轨”)虚拟编组研究的需要,深入分析城轨列车运行的特征,在此基础上总结提出包括站台停车时间差等在内的城轨列车虚拟编组应符合的技术性能指标;其次,针对虚拟编组的技术特征,提出包括大小交路和Y型线路等适合列车虚拟编组的潜在应用场景,并对实现虚拟编组的关键技术及其原理进行介绍,可为城轨列车虚拟编组研究提供参考。     

基于智能手机图像采集方法的沥青路面表面离析评价指标优选

为优选沥青路面表面离析评价指标,室内成型了3种不同级配类型的沥青混合料车辙板试件;采用智能手机,提出了一种图像采集方法,获取了沥青混合料表面图像;基于盒子分形维数和多重分形谱算法计算试件表面二值图像的分形维数和多重分形谱指标,依托Image-Pro Plus图像处理软件提取二值图像凹形分布百分数和宏观构造宽度指标,采用室内铺砂法测试表面构造深度,计算平均构造深度来评价沥青混合料表面离析;分析了不同级配组成沥青混合料表面凹形区域分布特征,研究了沥青混合料表面离析评价指标间灰关联熵。研究结果表明：基于智能手机来获取二值图像的可靠性分析误差率不超过3%,说明基于智能手机获取试件表面图像方法具有较高可重复性;沥青混合料表面凹形构造具有显著分形特征,集料颗粒粒径越大,表面构造分形越复杂;基于图像处理方法的沥青路面表面离析评价指标与平均构造深度指标间存在线性相关性,但相关程度不一;同一级配沥青混合料表面分形特征指标计算误差范围较大,而凹形分布百分数指标误差范围最小,仅为±1.89%,且其与平均构造深度指标的熵关联度最高,为0.996 2,其次分别是多重分形谱、分型维数和宏观构造宽度指标;综合考虑推荐沥青混合料表面凹形分布百分数可作为可靠的表面离析评价指标。     

Model uncertainty and the management of a system of infrastructure facilities

The network-level infrastructure management problem involves selecting and scheduling maintenance, repair, and rehabilitation (MR&R) activities on networks of infrastructure facilities so as to maintain the level of service provided by the network in a cost-effective manner. This problem is frequently formulated as a Markov decision problem (MDP) solved via linear programming (LP). The conditions of facilities are represented by elements of discrete condition rating sets, and transition probabilities are employed to describe deterioration processes. Epistemic and parametric uncertainties not considered within the standard MDP/LP framework are associated with the transition probabilities used in infrastructure management optimization routines. This paper contrasts the expected costs incurred when model uncertainty is ignored with those incurred when this uncertainty is explicitly considered using robust optimization. A case study involving a network-level pavement management MDP/LP problem demonstrates how explicitly considering uncertainty may limit worst-case MR&R expenditures. The methods and results can also be used to identify the costs of uncertainty in transition probability matrices used in infrastructure management systems.     

企业财务状况指标分析

以某企业报告期财务报表数据为基础,分析企业负债能力和长期偿债能力等财务指标,计算销售利润率、销售毛利率、销售费用率、销售成本率等盈利能力指标。同时进行直接材料、直接人工、制造费用等成本和期间费用分析,可为企业财务分析工作提供一定参考。