The effects of federal transit subsidy policy on investment decisions: The case of San Francisco's Geary Corridor

In the United States, federal funding for public transit often accounts for a large proportion of a local agency's budget, especially for capital investments. For this reason, local governments can be expected to plan a portfolio of projects that maximize federal contributions. This study examines the financial effects of federal transit subsidy policy on local transit investment decisions. Data from a System Planning Study for the Geary Corridor in San Francisco are used as an illustration. It is found that federal transit subsidy policy provides financial incentives for local decision-makers to select capital-intensive investment options that may not be efficient or effective. While federal financial incentives are not the only factor influencing local investment decisions, some reform of the current subsidy policy may be necessary to reduce the incentive for ineffective use of public resources.     

高压喷射注浆技术在基坑管涌处理中的运用

高压喷射注浆法是在注浆法的基础上，应用高压喷射技术而发展起来的一项新的地基加固方法。本文针对武汉市泰合广场基坑在开挖过程中形成管涌或流上而致使附近建筑物遭受严重破坏的问题，采用高压喷射注浆法施工工艺方法，杜绝了基坑壁管涌或流立现象，使基坑开挖和基础施工得以安全进行。     

治理公路超载超限运输的长效机制和对策研究

为建立治理超载超限运输的长效机制,首先建立了运输企业收入的计量模型,分析了企业利润与运输价格、运输成本、超载罚款等变量之间的互动关系及企业获得最大利润的条件。在此基础上,针对中国道路货运市场结构的特点,从理性经济人的角度,对运输企业在“惩罚博弈”下可能的行为选择进行了研究;其次结合美国治理超载超限运输的经验,分析了不同执法强度和执法密度组合的执法策略及其适用条件、执法效果等,对中国治理超载超限运输提出了解决方案和具体的政策建议,对中国治理超载超限运输具有指导意义。     

西部公路发展策略研究

采用SWOT分析法作为西部公路发展策略的制定方法,在对西部公路交通系统的内外部环境影响因素归纳、剖析的基础上,给出了西部公路内外部环境分析与评价的方法,按重要性确定了西部公路发展环境的优势(S)与劣势(W)、机会(O)和威胁(T)因素,并采用定量与定性方法相结合提出了西部公路发展的建议策略,为西部公路发展在策略层面提供了理论指导。     

基于交易费用的物流运作模式研究

从交易费用理论及物流运作模式着手,探讨了市场采购、物流自营,物流外包与物流内包的适应环境及运作对象。即:对于一般的物流活动应该从市场上进行采购,对于集成化的物流服务应该采用外部外包,当第三方物流市场走向垄断时,要积极寻求物流内包。     

辽阳出口路现场热再生简析

重点介绍了辽阳出口路现场热再生沥青混合料的级配设计和施工工艺及施工过程中的质量控制要点。     

关于山区高速外业勘察中若干问题的探讨

近几年来,我国山区高速建设里程日益增加.因受复杂地形、地质条件的限制,山区高速的外业勘察具有其独有的关键技术难点,应在普通建设条件下的作业内容、作业方式的基础上,采取针对性的对策措施,确保外勘资料满足设计需求.     

Customizing driving cycles to support vehicle purchase and use decisions: Fuel economy estimation for alternative fuel vehicle users

Wider deployment of alternative fuel vehicles (AFVs) can help with increasing energy security and transitioning to clean vehicles. Ideally, adopters of AFVs are able to maintain the same level of mobility as users of conventional vehicles while reducing energy use and emissions. Greater knowledge of AFV benefits can support consumers’ vehicle purchase and use choices. The Environmental Protection Agency’s fuel economy ratings are a key source of potential benefits of using AFVs. However, the ratings are based on pre-designed and fixed driving cycles applied in laboratory conditions, neglecting the attributes of drivers and vehicle types. While the EPA ratings using pre-designed and fixed driving cycles may be unbiased they are not necessarily precise, owning to large variations in real-life driving. Thus, to better predict fuel economy for individual consumers targeting specific types of vehicles, it is important to find driving cycles that can better represent consumers’ real-world driving practices instead of using pre-designed standard driving cycles. This paper presents a methodology for customizing driving cycles to provide convincing fuel economy predictions that are based on drivers’ characteristics and contemporary real-world driving, along with validation efforts. The methodology takes into account current micro-driving practices in terms of maintaining speed, acceleration, braking, idling, etc., on trips. Specifically, using a large-scale driving data collected by in-vehicle Global Positioning System as part of a travel survey, a micro-trips (building block) library for California drivers is created using 54 million seconds of vehicle trajectories on more than 60,000 trips, made by 3000 drivers. To generate customized driving cycles, a new tool, known as Case Based System for Driving Cycle Design, is developed. These customized cycles can predict fuel economy more precisely for conventional vehicles vis-à-vis AFVs. This is based on a consumer’s similarity in terms of their own and geographical characteristics, with a sample of micro-trips from the case library. The AFV driving cycles, created from real-world driving data, show significant differences from conventional driving cycles currently in use. This further highlights the need to enhance current fuel economy estimations by using customized driving cycles, helping consumers make more informed vehicle purchase and use decisions.     

基于需求弹性的城市公交票价优化方法及实证分析

城市公交票价是公交系统健康发展的重要因素，票价制定需兼顾公交企业的市场性和公益性双重属性，在保证服务质量的同时，考虑运营成本和最大限度吸引公交需求，实现经济效益和社会效益的双赢.在本文中，根据用户均衡理论，构建了城市多方式交通出行的需求分析模型，采用灵敏度分析方法给出了城市公交价格-需求弹性的计算方法.在此基础上，充分考虑了各种方式的交通特征、公交需求弹性、公交运营成本及政府限价等因素，提出了城市公交票价优化的数学规划模型，并给出了求解算法.最后，以国内某城市居民出行调查及公交运营数据为基础，分析了不同条件下公交客运需求的变化规律及城市公交票价的优化策略.