公路交通经济增长中的制度因素分析

在总结传统的经济增长理论(资本决定论、技术进步论、人力资本论、专业化的人力资本和特殊知识积累论)的基础上,采用新制度经济学的分析方法,对建国以来中国公路交通的制度变迁和经济绩效及其相互关系进行了实证分析,指出了制度在公路交通发展中的极端重要性;提出了"生产要素的制度性边界"这一概念,指出制度边界具有随经济、技术等因素变化而不断变化的特性,在此基础上建立了新的经济增长分析框架和模型;为打破制度的"低度均衡",扩展生产要素的制度边界,最后提出了关于加快制度创新的建议。     

收费公路计重定价理论模型

为了遏制超限运输,解决公路通行费征收中的不公平问题,必须改变目前按车型收费的计费模式,实施计重收费。建立计重收费的定价理论模型是推动这种收费方式健康发展的关键。在提出计重收费定义和类型的基础上,根据公路的准公共产品特性,分析了各种价格结构管制定价模式的特点,提出公路收费宜采用非线性的"两部定价"理论模型。结合收费公路费用分摊的具体方法,给出了收费公路计重定价理论模型,并对相关参数进行了标定。该模型已在江苏省和青海省计重收费标准制定中使用。     

Performance Evaluation of Hybrid-Drive Buses and Potential Fuel Savings in Brazilian Urban Transit

Transporting more than 55 million passengers per day, buses are the main transit mode in Brazil. Most of these vehicles use diesel oil and this situation causes dependence on oil, extensive greenhouse gas emissions and increasing air pollution in urban areas. In order to improve this situation the options for Brazilian cities include the use of alternative fuels and new propulsion technologies, such as hybrid vehicles. This article proposes a procedure for evaluating the performance of a recently developed Brazilian hybrid-drive technology. A simple procedure is presented to compare hybrid-drive buses with conventional diesel buses in urban operation focusing on fuel economy and the potential for reducing diesel oil consumption through the use of hybrid-drive buses. Field tests carried out by the authors indicate that fuel consumption improvement through the use of hybrid-drive buses would certainly exceed 20%, resulting in lower fuel costs and reduced carbon dioxide (CO₂) emissions.     

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。     

电动汽车充电桩安全管理研究

随着国家对环境保护和能源节约的重视以及新能源政策的实施,电动汽车行业迎来了快速发展。充电基础设施的建设,是加快电动汽车推广的重要需要。电动汽车充电基础设施建设和运营业务发展的机会也极大,随之而来的安全管理工作要求也越来越高。本文依据充电桩建设和运营的特点,剖析其中面临的安全风险,并提出加强安全管理工作的措施,为充电桩企业安全管理运营提供参考和借鉴。     

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.     

基于生长曲线函数的货车运营环节碳达峰研究

货车是我国大气环境污染的重要来源之一，也是影响我国碳达峰总体目标实现的重要因 素。本文从货车运营环节入手，在运用生长曲线函数对货车保有量进行预测的基础上，对不同类 型货车的保有量和单车碳排放变化进行研究，并从货车节能技术发展、新能源货车推广和应用进 程两方面入手，分3种情景对货车运营环节中产生的碳排放总量趋势进行预判，推演货车运营环 节的碳达峰时间。研究结果表明，只有同时加快货车节能技术发展以及新能源货车推广和应用 进程，货车运营环节中产生的碳排放总量规模才能得到有效抑制并逐渐减少。若到 2030 年货 车单车燃料消耗水平较 2019 年降低 20%以上，新能源货车在货车整体保有量中的占比达到 20%，到 2060 年货车单车燃料消耗水平较 2019 年降低 50%，新能源货车占比达到 50%，则货车 运营环节碳达峰时间将缩短至2030年左右实现，2030年后货车运营环节产生的碳排放总量规 模将逐渐减少。     

新城区轨道交通线路规划关键问题研究

对国内外主城与新城衔接的新城区(郊区)轨道线特征及交通功能等因素进行总结分析，并结合武汉市及国内外典型城市新城区轨道交通规划建设经验，对新城区轨道交通线路规划关键问题做深入研究。提出对新城区轨道交通线路规划中与其他不同层次轨道线网功能及技术标准的衔接关系；与新城区发展应注重以轨道交通引领新城区协同发展，与城市空间结构高度契合关系；新城区轨道线路走向应沿预测主要客流走廊，串联新城区商业、交通枢纽等大型客流集散点，以缓解开通初期普遍面临客流量增长缓慢，客运强度偏低的问题。