Weather variability and travel behaviour – what we know and what we do not know

Given that severe weather conditions are becoming more frequent, it is important to understand the influence of weather on an individual’s daily activity-travel pattern. While some previously rare events are becoming more common, such as heavy rain, unpredicted snow, higher temperatures, it is still largely unknown how individuals will change and adapt their travel patterns in future climate conditions. Because of this concern, the number of research studies on weather and travel behaviour has increased in recent decades. Most of these empirical studies, however, have not used a cost–benefit analysis (CBA) framework, which serves as the the main tool for policy evaluation and project selection by stakeholders. This study summarises the existing findings regarding relationships between weather variability and travel behaviour, and critically assesses the methodological issues in these studies. Several further research directions are suggested to bridge the gap between empirical evidence and current practices in CBA.     

Reducing average comprehensive travel cost by rationally allocating trips to different travel modes

To study the effect of different transport policies on reducing the average comprehensive travel cost (CTC) of all travel modes, by increasing public transport modal share and decreasing car trips, an optimization model is developed based on travel cost utility. A nested logit model is applied to analyze trip modal split. A Genetic Algorithm is then used to determine the implementation of optimal solutions in which various transport policies are applied in order to reduce average CTC. The central urban region of Beijing is selected as the study area in this research. Different policies are analyzed for comparison, focusing on their optimal impacts on minimizing the average CTC utility of all travel modes by rationally allocating trips to different travel modes in the study area. It is found that the proposed optimization model provides a reasonable indication of the effect of policies applied.     

基于代价函数的无人驾驶汽车局部路径规划算法

局部路径规划层作为无人驾驶汽车软件层的重要组成分布,如何有效、安全地到达目的地是当前研究的热点。针对结构化道路信息,充分考虑车道线的约束,在使用Frenet坐标系理论的基础上,提出一种考虑到车道线曲率和障碍物模型信息,得到不同车道上其他道路参与者的位置信息,以便计算其他障碍物模型对本车危险程度,综合算法实时性、轨迹平顺性等要素的最小代价局部路径规划算法。在局部路径规划过程中,沿着参考线（Frenet坐标系下X轴上一段路径）选取多个路径分割点,Frenet坐标系下在每个分割点处沿Y轴进行控制点离散,每个路径分割点处选取1个控制点构成路径控制点集合,使用一元三次方程对每种排列组合路径进行拟合,从而使用代价函数对每种排列组合路径进行评估,代价函数值最小为最优的局部路径。代价函数考虑拟合轨迹到障碍物的危险程度、轨迹平顺性、轨迹到当前参考线（实时在全局路径规划层上根据车速得到一条当前需要跟踪的理想轨迹）的偏离程度、拟合轨迹行驶方向的改变程度、无人驾驶汽车最小转弯半径。研究结果表明：在不同试验场景下,所提出基于代价函数的局部路径规划算法,能规划出一条不与障碍物发生碰撞的最优路径,并能保证无人驾驶汽车行驶轨迹平顺性和路径规划层实时性的要求。     

第三方物流企业作业成本控制研究

第三方物流企业竞争日趋激烈,准确核算和有效控制成本成为第三方物流企业提高管理水平、增强市场竞争优势的关键。本文探讨了作业成本法在第三方物流企业成本控制中的应用,研究企业如何根据未来物流服务的需求,确定未来期间最优的约定作业能力水平,从而为企业的经营管理决策提供科学的依据。     

高速公路沥青路面基层类型选择

通过对不同类型基层结构的敏感性分析,结合对典型柔性基层路面结构的力学分析和功能区域划分,分析所得中下面层结构设计不同于传统设计的理念,有助于总结出重栽交通环境下。沥青稳定类基层值得推广的结论。     

浅谈采用热用密封胶开槽灌缝方法处理高速公路路面裂缝问题

采用热用密封胶开槽灌缝方法修补路面裂缝,综合投资少,使用寿命长,效果明显,是一种值得大力发展的新技术．应引起公路养护工作人员的足够重视。     

关于公路、铁路协调发展评价指标的探讨

公路和铁路运输是我国综合运输系统中的两种重要陆路交通运输方式,因此在对我国陆路运输系统进行现状分析研究的基础上。针对构建衡量公路和铁路协调发展程度的评价指标以厦这些指标的具体计算方法进行探讨,可为公路、铁路的协调发展提供理论依据。     

试论高校教育成本核算

随着市场经济的不断发展。高等教育办学的投资体制已经呈现多元化的趋势,教育市场正在逐步形成,但是传统教育成本已经不能满足市场化和多元化的要求,那么要使高等教育可持续发展,就应该建立科学的高校人才培养成本的核算制度,合理使用资金和优化配置教育资源,使高校的经济效益和社会效益、教育成本与教育收益达到统一、协调发展。     

浅谈公路工程施工项目的成本管理

通过对工程项目成本构成的深入分析,提出了成本预测、成本控制及降低工程成本的有效途径。     

船体结构件中常见焊缝的优化布置

为提高船体制造的焊接效率和质量,根据焊缝布置的基本要求,从合理布置焊缝出发,对部分船体结构件焊缝提出了一系列的优化布置方案.依据生产一线的实际加工经验,提出了焊缝布置应便于钢板加工和避开应力集中区域、焊缝的位置应尽量可能的左右对称布置的观点;另外对焊缝与构件交错等应用中的实际问题也提出了一些解决方法,从而更好地发挥了设...