首页> 外文会议>Annual transportation research forum >Creating a Statewide Commodity Flow Forecast from National FAF2 Data
【24h】

Creating a Statewide Commodity Flow Forecast from National FAF2 Data

机译:从国家FAF2数据创建州所有商品流量预测

获取原文

摘要

As part of the planning effort leading up to the development of a statewide Freight Plan, the Oregon Department of Transportation (ODOT) developed a statewide commodity flow forecast. The methodology used to create this Oregon Commodity Flow Forecast (Oregon CFF), aimed to address the limitations of existing forecasts – inconsistent and separate databases for different modes, lack of transparency in data and assumptions, and data gaps – in a consistent methodology based on national and local data sources, and be able to meet the tight timelines. This paper will document the work done by the consulting team and the agency to create a statewide forecast that addressed these limitations. The project team decided to build on the Federal Highway Administration (FHWA) Freight Analysis Framework (FAF2) national commodity flow forecast. The FAF2 commodity flow forecast was chosen because FAF2 is national in scope, highly regarded in terms of capturing interstate and international flows, uses a relatively recent base year (2002), and provided a quick way to complete a forecast in time for the Oregon Freight Plan work. FAF2 provides freight flows in tons or dollar value between 130 FAF2 regions encompassing the US for the year 2002 plus forecasts from 2010 to 2035 in five year increments. The desired final product for the Oregon CFF was a county-county level flow forecast for truck, rail, marine, air, and pipeline modes. In order to transform the coarse FAF2 zone flows (2 zones cover Oregon) into counties within Oregon, the data was disaggregated. Since the FAF2 dataset contains the whole United States, flows with at least one trip ends within Oregon were disaggregated from FAF2 zones to Oregon counties. Each of the freight modes was disaggregated separately. In the case of truck flows, this was done based on county employment and IMPLAN inter-industry coefficients of what commodities are made and used by each industry. For rail flows, the FAF2 flows were compared to the Surface Transportation Board‘s Rail Carload Waybill data set which contains county level detail of origin and destinations. The overall numbers were found to be comparable, so the Waybill data for 2002 was used as the base, and the FAF2 ii growth rates were applied to forecast the future years. The other modes relied on local data to allocate FAF2 flows to specific Oregon facilities (rail stations, airports, marine ports, or pipeline terminals), including US Corps of Engineers Waterborne Commerce data and the Oregon Energy Report. Zones outside of Oregon were aggregated from FAF2 zones to ―Other Domestic‖ and ―Other International‖ categories. Special consideration was made for air mail and fish commodities using the knowledge of industry experts. Using the Rail Waybill data and other sources required a conversion in commodity categories, because FAF2 uses the Standard Classification of Transported Goods (SCTG)TG and other sources used the Standard Transportation Commodity Code classification. Once the data was disaggregated to represent county-county commodity flows, the FAF2 future year forecast numbers were adjusted down to account for the economic downturn that occurred after the forecast was prepared. One of the challenges of working with the FAF2 data is the inability to adjust or quantify the FAF2 underlying economic forecasts, particularly the optimistic economic conditions and low fuel price assumptions. These poses some limitations that must be taken into account. The Oregon CFF 2002 to 2035 forecast provides a basis for understanding the primary freight movements today and in the future under existing conditions. In several instances circumstances are likely to change, and the detail and transparency provided in Oregon CFF can provide a starting point for evaluating such changes.
机译:作为规划努力的一部分,导致州际运输计划的发展,俄勒冈州交通部(奥特别徒)制定了全州商品流预测。用于创建此俄勒冈商品流量预测(俄勒冈CFF)的方法,旨在解决现有预测的局限性 - 对于不同模式,数据和假设缺乏透明度,以及数据差距 - 基于一致的方法国家和地方数据来源,能够满足紧张的时间表。本文将记录咨询团队和原子能机构的工作,以创建解决这些限制的全州预测。该项目团队决定建立联邦公路管理局(FHWA)货运分析框架(FAF2)国家商品流量预测。选择FAF2商品流量预测,因为FAF2是国家范围的,备受捕获州际和国际流量的备受尊重,采用了一个相对较近的基准年(2002年),并提供了一种快速的方式来完成俄勒冈州俄勒冈州的预测计划工作。 FAF2在2002年增加了130个FAF2地区的吨或美元价值之间提供货流量,从2010年到2035年增加了2002年的预测。俄勒冈州CFF的预期最终产品是卡车,轨道,海洋,空气和管道模式的县县级水平。为了将粗糙FAF2区域流(2区覆盖副)转换为俄勒冈州的县,数据被分解。由于FAF2数据集包含整个美国,因此俄勒冈州至少有一段行程的流程从FAF2区分解给俄勒冈州。每个货运模式分别分类。在卡车流动的情况下,这是基于县就业,并植入各行业制造和使用商品的行业间系数。对于轨道流动,将FAF2流与地表运输板的轨道卡载货单片数据集进行比较,其中包含县级的起源和目的地细节。发现总体数量是可比的,因此2002年的Waybill数据被用作基础,并申请FAF2 II增长率来预测未来几年。其他模式依赖于本地数据,将FAF2流到特定的俄勒冈州设施(火车站,机场,海港港口或管道终端),包括美国工程师水运商业数据和俄勒冈州能源报告。俄勒冈州以外的区域从FAF2区汇总到 - 其他家庭,以及其他国际‖类别。利用行业专家的知识,为空中邮件和鱼类商品进行了特殊考虑。使用铁路地板数据和其他消息来源所需的转换在商品类别中,因为FAF2使用运输货物的标准分类(SCTG)TG和其他来源使用标准运输商品代码分类。一旦数据分解以代表县县商品流动,FAF2未来年度预测数量被调整下来,以考虑预测准备后发生的经济衰退。使用FAF2数据的挑战之一是无法调整或量化FAF2的潜在经济预测,特别是乐观的经济条件和低燃料价格假设。这些构成了必须考虑的一些限制。俄勒冈州CFF 2002至2035年预测为在现有条件下,在今天和将来的未来提供了理解的基础。在几个情况下,情况可能会改变,俄勒冈州CFF中提供的细节和透明度可以提供评估此类变化的起点。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号