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基于大规模定位数据的出行方式模糊判别研究
引用本文:张德欣,刘小明,孙立光,刘杰,冉斌.基于大规模定位数据的出行方式模糊判别研究[J].交通与计算机,2011,29(2):1-4.
作者姓名:张德欣  刘小明  孙立光  刘杰  冉斌
作者单位:1. 北京工业大学建工学院,北京,100124
2. 上海美慧软件有限公司,上海,200081
3. 美国威斯康星大学麦迪逊分校,麦迪逊53706
摘    要:交通需求信息对于从战略上解决交通拥堵问题是非常重要的。从无线通信网络和GPS系统中可以获得大规模的定位数据。从定位数据中可以挖掘出完整的出行轨迹信息和有价值的出行需求特征信息。文中提出了以各种出行方式的先验知识为依据的出行方式模糊判别方法。该方法以从出行轨迹信息中提取的出行属性数据为输入,采用模糊推理机制实现机动车、自行车、步行等3种出行方式的良好区分。该方法可为交通规划工作提供出行方式划分方面的数据,并具有比传统交通调查方法更低的成本和更短的数据更新周期。

关 键 词:模糊逻辑  模糊推理  出行方式分类  大规模定位数据  无线通信网络

Fuzzy Classification of Trip Mode Based on Large Scale Location Data
ZHANG Dexin,LIU Xiaoming,SUN Liguang,LIU Jie,RAN Bin.Fuzzy Classification of Trip Mode Based on Large Scale Location Data[J].Computer and Communications,2011,29(2):1-4.
Authors:ZHANG Dexin  LIU Xiaoming  SUN Liguang  LIU Jie  RAN Bin
Institution:(College of Architecture and Engimeering,Beijing University of Technology,Beijing 100124,China)1(Shanghai Meihui Software Co.Ltd.,Shanghai 200081,China)2(University of Wisconsin Madison,Madison 53706,USA)3
Abstract:Traffic demand data are important to strategically solve the traffic congestion problem.Large scale location data can be extracted from Wireless Communication Network and GPS system.These data can provide entire trip trajectory and valuable traffic demand related information.This paper proposes a fuzzy classification method to identify trip mode based on prior knowledge of general traffic modes.The input of this method is trip properties extracted from trip trajectory data.This Method adopts Fuzzy Reasoning Method to archive satisfactory distinction of three trip modes including automobile,biking and walking.This Method can provide trip mode identification results for the transportation planning practices,and has lower cost and shorter update cycle than the traditional traffic survey methods.
Keywords:fuzzy logic  fuzzy reasoning  classification of trip mode  large scale location data  wireless communications network
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