Fuel price elasticities in the U.S. combination trucking sector

This paper estimates fuel price elasticities of combination trucking operations in the United States between 1970 and 2012. We evaluate trucking operations in terms of vehicle miles traveled and fuel consumption for combination trucks. Our explanatory variables include measures of economic activity, energy prices, and indicator variables that account for important regulatory shifts and changes in data collection and reporting in national transportation datasets. Our results suggest that fuel price elasticities in the United States’ trucking sector have shifted from an elastic environment in the 1970s to a relatively inelastic environment today. We discuss the importance of these results for policymakers in light of new policies that aim to limit energy consumption and reduce greenhouse gas emissions from heavy-duty vehicles.     

Prediction of arrival times of freight traffic on US railroads using support vector regression

Variability of travel times on the United States freight rail network is high due to large network demands relative to infrastructure capacity, especially when traffic is heterogeneous. Variable runtimes pose significant operational challenges if the nature of runtime variability is not predictable. To address this issue, this article proposes a data-driven approach to predict estimated times of arrival (ETAs) of individual freight trains, based on the properties of the train, the properties of the network, and the properties of potentially conflicting traffic on the network. The ETA prediction problem from an origin to a destination is posed as a machine learning regression problem and solved using support vector regression trained and cross validated on over two years of detailed historical data for a 140 mile section of track located primarily in Tennessee, USA. The article presents the data used in this problem and details on feature engineering and construction for predictions made across the full route. It also highlights findings on the dominant sources of runtime variability and the most predictive factors for ETA. Improvement results for ETA exceed 21% over a baseline prediction method at some locations and average 14% across the study area.     

Classifying the purpose of stopped truck events: An application of entropy to GPS data

This paper applies the concept of entropy to mine large volumes of global positioning system (GPS) data in order to determine the purpose of stopped truck events. Typical GPS data does not provide detailed activity information for a given stop or vehicle movement. We categorize stop events into two types: (1) primary stops where goods are transferred and (2) secondary stops where vehicle and driver needs are met, such as rest stations. The proposed entropy technique measures the diversity of truck carriers with trucks that dwell for 15 min or longer at a given location. Larger entropy arises from a greater variety of carriers and an even distribution of stop events among these carriers. An analysis confirms our initial hypothesis that the stop locations used for secondary purposes such as fuel refills and rest breaks tend to have higher entropy, reflecting the diversity of trucks and carriers that use these facilities. Conversely, primary shipping depots and other locations where goods are transferred tend to have lower entropy due to the lower variety of carriers that utilize such locations.     

Economic valuation of Well-To-Wheel CO2 emissions from freight transport along the main transalpine corridors

CO₂ emissions are one of the main externalities related to freight transport. Their evaluation is extremely difficult, due to the presence of several scientific and economic uncertainties. This paper discusses the approaches currently adopted by literature to deal with CO₂, proposing a methodology based on a Well-To-Wheel quantification and an economic valuation deriving from a meta-regression. A freight transport analysis is then provided for one of the most critical areas of Europe, the Alps. Here, the different approaches adopted by the single nations determine divergent results in terms of modal shift towards rail and, consequently, CO₂ emissions. An integrated and transnational strategy could lead to better results, avoiding detoured traffic and increasing the share of railway traffic. To this aim, the carbon impacts of three specific alpine-wide measures are evaluated: namely, Alpine Crossing Exchange, Emissions Trading and Differentiated Toll System. In comparison with business-as-usual scenario, the case study reveals a potential CO₂ saving up to more than 600,000 tons and 38 M€ for the year 2030, thus providing policy makers with an integrative transnational tool able to evaluate the long-term carbon impact of their transport decisions.     

北京新机场线服务标准研究

北京新机场线是连接首都第二国际机场与中心城的轨道交通专线,其服务对象、功能需求、运营目标与普通地铁线路差异巨大。基于对公交系统运营要素的认识,站在城市轨道交通运营设计的角度,以落实运营需求及标准为目标,对新机场线应具备的服务标准予以探讨,重点落实速度标准、舒适度标准以及发车间隔、可靠性等指标分析。     

建设现代铁路物流中心的探讨

分析建设铁路物流中心的必要性和可行性,提出铁路物流中心应该向一体化、专业化、信息化、规模化、现代化和自动化的方向发展。阐述铁路物流中心应具备承运和交付、储存、配送等核心功能,装卸搬运、多式联运、生活服务等辅助功能,以及包装和流通加工、结算等可选功能。     

基于多层复杂网络的中欧班列运输网络关键节点识别研究

若运输网络中的重要节点发生故障,中欧班列的运输效率和货物流动会受到严重制约。 本文提出一种基于改进TOPSIS(Technique for Order Preference by Similarity to an Ideal Solution) 法及灰色关联分析的多层网络节点重要性评价方法。首先,以中欧班列运输网络结构特征为基础,构建中欧班列多层网络;其次,选取度中心性、介数中心性及接近中心性等多个评价指标,运用改进TOPSIS法计算节点单层网络重要度评价值,采取灰色关联分析融合得到节点综合重要度评价值;最后,利用多层网络SIR(Susceptible Infected Recovered Model)模型验证方法的有效性。 结果表明：本文识别出的关键节点包含中欧班列主要线路的起讫城市、境内外重要口岸和中欧班列集结中心,结果与实际情况较为契合;采用排序前10%重要节点作为初始感染节点,SIR网络感染率在 20 次迭代后达到 97.8%,本文提出方法的网络节点感染率及传播速率均高于 BC (Betweenness Centrality)算法、DC(Degree Centrality)算法和PageRank算法等传统单一网络排序方法,即识别的关键节点对全局网络的影响更为普遍和高效。此外,根据排序结果从国家层面提出相应的政策建议,有助于提高中欧班列运输网络的鲁棒性。     

加强铁路货运安全的研究

针对货运安全面临的新形势,分析了货物自身特点、货运技术、人员、运输设备、运输环境及安全管理等因素对铁路货运安全的影响,结合实际提出在理论研究和实践两方面进行攻关,推广采用先进技术,加强管理,不断创新,以提高货运安全管理水平。     

加强直达运输组织全力推进铁路大客户战略的贯彻实施

介绍济南铁路局管内两家大客户的情况,分析提高大客户直达运输比重的必要性和可行性,以及需要解决的问题和困难,总结了健全制度保障、优化运输环节、实施运力倾斜等提高大客户物资运输直达比重的措施。并回顾了大客户战略的实施效果,提出了2006年进一步推进铁路大客户战略的初步设想。     

新型货车转向架螺旋弹簧三维有限元分析与疲劳寿命估算

基于三维有限元法建模,对转向架弹簧的刚度和支撑圈接触条件下的应力进行计算分析.结果表明分析结果与静应力测试结果相近,转K2外簧静强度满足设计要求;支撑圈与相邻工作圈接触不仅使弹簧的最大应力有所增大,而且在加载过程中接触应力和最大应力随着支撑圈接触面积的变化而变化,因此在制造过程中应控制支撑圈的间隙.采用有限元法可快速获得弹簧的刚度和弹性特性曲线,克服了以往通过试验测试弹簧刚度所带来的周期长、费用高等缺点.弹簧疲劳寿命初步估算表明不考虑弹簧强化处理的影响,弹簧的疲劳寿命约为2.55×106次;采用喷丸等强化处理工艺并在提高弹簧20%的疲劳强度情况下,弹簧的疲劳寿命为8.9×106次.