An Unlicensed Taxi Identification Model Based on Big Data Analysis

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	An Unlicensed Taxi Identification Model Based on Big Data Analysis
	Yuan, W ; Deng, P ; Taleb, T ; Wan, JF ; Bi, CF
刊名	IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
	2016
卷号	17 期号:6 页码:1703-1713
关键词	Big data intelligent transportation systems machine learning data-driven ITS unlicensed taxi
ISSN号	1524-9050
中文摘要	Social networks and mobile networks are exposing human beings to a big data era. With the support of big data analytics, conventional intelligent transportation systems (ITS) are gradually changing into data-driven ITS ((DITS)-I-2). Along with traffic growth, (DITS)-I-2 need to solve more real-life problems, including the issue of unlicensed taxis and their identification, which potentially disrupts the taxi business sector and endangers society safety. As a remedy to this issue, a smart model is proposed in this paper to identify unlicensed taxis. The proposed model consists of two submodel components, namely, candidate selection model and candidate refined model. The former is used to screen out a coarse-grained suspected unlicensed taxi candidate list. The list is taken as an input for the candidate refined model, which is based on machine learning to get a fine-grained list of suspected unlicensed taxis. The proposed model is evaluated using real-life data, and the obtained results are encouraging, demonstrating its efficiency and accuracy in identifying unlicensed taxis, helping governments to better regulate the traffic operation and reduce associated costs.
英文摘要	Social networks and mobile networks are exposing human beings to a big data era. With the support of big data analytics, conventional intelligent transportation systems (ITS) are gradually changing into data-driven ITS ((DITS)-I-2). Along with traffic growth, (DITS)-I-2 need to solve more real-life problems, including the issue of unlicensed taxis and their identification, which potentially disrupts the taxi business sector and endangers society safety. As a remedy to this issue, a smart model is proposed in this paper to identify unlicensed taxis. The proposed model consists of two submodel components, namely, candidate selection model and candidate refined model. The former is used to screen out a coarse-grained suspected unlicensed taxi candidate list. The list is taken as an input for the candidate refined model, which is based on machine learning to get a fine-grained list of suspected unlicensed taxis. The proposed model is evaluated using real-life data, and the obtained results are encouraging, demonstrating its efficiency and accuracy in identifying unlicensed taxis, helping governments to better regulate the traffic operation and reduce associated costs.
收录类别	SCI
语种	英语
WOS记录号	WOS:000377457200019
公开日期	2016-12-09
内容类型	期刊论文
源URL	[http://ir.iscas.ac.cn/handle/311060/17326]
专题	软件研究所_软件所图书馆_期刊论文
推荐引用方式 GB/T 7714	Yuan, W,Deng, P,Taleb, T,et al. An Unlicensed Taxi Identification Model Based on Big Data Analysis[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2016,17(6):1703-1713.
APA	Yuan, W,Deng, P,Taleb, T,Wan, JF,&Bi, CF.(2016).An Unlicensed Taxi Identification Model Based on Big Data Analysis.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,17(6),1703-1713.
MLA	Yuan, W,et al."An Unlicensed Taxi Identification Model Based on Big Data Analysis".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 17.6(2016):1703-1713.