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Processing Commercial Global Positioning System Data to Develop a Web-Based Truck Performance Measures Program

卡车 运输工程 全球定位系统 地理编码 目的地 TRIPS体系结构 自动车辆定位 计算机科学 数据收集 地理信息系统 流量网络 出租车 Web应用程序 车队管理 工程类 数据处理 数据库 汽车工程 电信 旅游 统计 数学优化 地质学 遥感 法学 数学 政治学
作者
Xiaolei Ma,Edward McCormack,Yinhai Wang
出处
期刊:Transportation Research Record [SAGE Publishing]
卷期号:2246 (1): 92-100 被引量:37
标识
DOI:10.3141/2246-12
摘要

Although trucks move larger volumes of goods than other modes of transportation, public agencies know little about their travel patterns and how the roadway network performs for trucks. Trucking companies use data from the Global Positioning System (GPS) provided by commercial vendors to dispatch and track their equipment. This research collected GPS data from approximately 2,500 trucks in the Puget Sound, Washington, region and evaluated the feasibility of processing these data to support a statewide network performance measures program. The program monitors truck travel time and system reliability and will guide freight investment decisions by public agencies. While other studies have used a limited number of project-specific GPS devices to collect frequent location readings, which permit a fine-grained analysis of specific roadway segments, this study used data that involved less frequent readings but that were collected from a larger number of trucks for more than a year. Automated processing was used to clean and format the data, which encompassed millions of data points. Because a performance measurement program ultimately monitored trips generated by trucks as they travel between origins and destinations, an algorithm was developed to extract this information and geocode each truck's location to the roadway network and to traffic analysis zones. Measures were developed to quantify truck travel characteristics and performance between zones. To simplify the process and provide a better communications platform for the analysis, the researchers developed a Google Maps–based online system to compute the measures and show the trucks’ routes graphically.
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