Development of Algorithms to Convert Large Streams of Truck GPS Data into Truck Trips
Development of Algorithms to Convert Large Streams of Truck GPS Data into Truck Trips
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开发将大量卡车 GPS 数据转换为卡车行程的算法
DOI：
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发表时间：
2015
期刊：
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通讯作者：
S. Tabatabaee
中科院分区：
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作者：
Aayush Thakur;A. Pinjari;Akbar Bakhshi Zanjani;J. Short;Vidya Mysore;S. Tabatabaee
本文记录了算法和程序的开发和验证，这些算法和程序用于将美国运输研究所提供的大量原始 GPS 数据转换为卡车行程数据库，用于全州货运卡车行程的分析和建模。还介绍了将佛罗里达州 4 个月的原始 GPS 数据（总计超过 1.45 亿条 GPS 记录）转换为包含佛罗里达州内、进出佛罗里达州的超过 120 万次卡车行程的数据库的结果。本文描述的程序和实施细节将有助于交通规划机构将原始 GPS 数据流转换为更可用的卡车行程数据库，以便在全州和大区域级别进行卡车流量建模和分析。
This paper documents the development and validation of the algorithms and procedures used to convert large streams of raw GPS data available from the American Transportation Research Institute into a database of truck trips for use in analysis and modeling of statewide freight truck travel. Also presented are the results from the conversion of 4 months of raw GPS data from Florida, totaling more than 145 million GPS records, into a database of more than 1.2 million truck trips within, into, and out of Florida. The procedures and implementation details described in this paper will be useful to transportation planning agencies in converting raw GPS data streams into more usable truck trip databases for truck flow modeling and analysis at statewide and megaregional levels.