基于多源公交数据和车时成本优化的公交运营时段划分方法

现有公交运营时段划分方法均基于单一参数（乘客需求或行程时间）的相似性,忽略了乘客需求与行程时间对时段划分方案的协同作用。针对传统方法的缺陷,利用多源公交数据,提出一种新的基于最小化车队运营时间成本的时段划分方法。首先,利用逆差函数模型计算时间窗内完成班次任务所需要的最小车队规模,进而利用滑动时间窗模型,计算全天各时间窗所需的理论最小车队规模。然后,以时段划分方案的时间分割点为决策变量,以最小化全天累计车队运营时间成本为目标建立优化模型,采用遗传算法对运营时段划分方案进行寻优。最后,以广州市87路公交线路实际数据为例进行验证,并对模型参数进行敏感性分析。研究结果表明：与传统方法相比,所提方法能更好地实现运力与运量相匹配,并有效降低车时成本;与以往基于断面客流和基于行程时间的划分方案相比,所提方案的车时成本分别降低25 veh·h和45.33 veh·h。     

我国隧道及地下工程的历史机遇、发展困局及若干建议

改革开放40年来,我国隧道及地下工程建设取得了令世人瞩目的成就,但隧道及地下工程建设项目存在的问题同样突出,重视和解决当下的隧道及地下工程困局已经到了刻不容缓的地步。首先,从国家基本建设的发展态势及隧道与地下工程的优势分析,得出我国隧道及地下工程发展有着良好的历史机遇。通过实例说明目前隧道的发展困局主要是隧道工程巨额亏损。然后,从工程理念、技术运用、管理体制和实务操作等方面分析导致我国隧道及地下工程发展困局的原因： 1）处于主导地位的理念措施造成专业领域建设指导思想的混乱,包括低造价“王者称霸”、“狂躁症”害人害己、旧思维难以生新; 2）在技术方面,主要是工法运用不当带来的严重后果; 3）隧道工程建设管理体制失调和管理实务操作失控,造成的不良后果明显。最后,从事业和产业进步的角度出发,提出对我国隧道及地下工程发展的建议： 1）改革建设管理体制; 2）加大对生态环境保护的投入; 3)走机械化、自动化、智能化之路; 4）培养和造就隧道建设专业队伍; 5）重视和提倡工程经济学研究。     

Cost escalations in the front-end of projects – empirical evidence from Norwegian road projects

This paper investigates an issue largely ignored in the transport literature on cost overruns, namely, cost increases in the early project phase, long before the decision to build is made. This is the phase of project planning that is referred to as the front-end phase in the literature. The rationale of the study is that unless cost estimates during the front-end phase are relatively accurate, the wrong projects may be selected for further development. We first argue for why it is important to address cost escalation during the front-end phase of project planning. We then use Norwegian data to demonstrate the magnitude of cost escalations during the front-end phase of projects and in comparison to the implementation phase. We find that even in a sample of projects with relatively small cost overruns as in the case of Norway, there are substantial cost increases before the formal decision to build was made. This raises the issue of whether decisions and priorities taken at the early stages of project development are based on false information and whether this may lead to the wrong project concepts being selected.     

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。