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Optimal Traffic Sensor Location for Origin-Destination Estimation Using a Compressed Sensing Framework | |
Ye, Peijun1,2![]() | |
发表期刊 | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
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ISSN | 1524-9050 |
2017-07-01 | |
卷号 | 18期号:7页码:1857-1866 |
文章类型 | Article |
摘要 | A series of flow estimation problems, especially origin-destination estimation, involves optimally locating sensors on a transportation network to measure traffic counts. As compressed sensing (CS) provides a new method to solve the estimation problem, its sensor location strategy needs to be researched in order to facilitate the reconstruction. This paper first points out that the accurate flow recovery is difficult by introducing a necessary condition, and then categorizes the location determination into two cases: sensor number with restriction and without restriction. For both cases, we elucidate their theoretical foundations of locating methods and propose an algorithm based on column coherence minimization, which optimally facilitates the reconstruction for CS framework. Numerical experiments indicate that the selected sensor locations fit the flow recovery and the proposed algorithm, compared with other methods, can lead to a slightly better result under certain observations. |
关键词 | Traffic Sensor Location Traffic Flow Estimation Compressed Sensing |
WOS标题词 | Science & Technology ; Technology |
DOI | 10.1109/TITS.2016.2614828 |
关键词[WOS] | LINK FLOW INFERENCE ; MATRIX ESTIMATION ; SELECTION ; NETWORKS ; MODEL ; OBSERVABILITY ; OPTIMIZATION ; QUALITY ; COUNTS |
收录类别 | SCI |
语种 | 英语 |
项目资助者 | National Natural Science Foundation of China(61603381) |
WOS研究方向 | Engineering ; Transportation |
WOS类目 | Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology |
WOS记录号 | WOS:000404370500017 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/15225 |
专题 | 多模态人工智能系统全国重点实验室_复杂系统智能机理与平行控制团队 |
通讯作者 | Ye, Peijun |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Qingdao Acad Intelligent Ind, Qingdao 266000, Peoples R China 3.Natl Univ Def & Technol, Mil Computat Expt & Parallel Syst Res Ctr, Changsha 410073, Hunan, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Ye, Peijun,Wen, Ding. Optimal Traffic Sensor Location for Origin-Destination Estimation Using a Compressed Sensing Framework[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2017,18(7):1857-1866. |
APA | Ye, Peijun,&Wen, Ding.(2017).Optimal Traffic Sensor Location for Origin-Destination Estimation Using a Compressed Sensing Framework.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,18(7),1857-1866. |
MLA | Ye, Peijun,et al."Optimal Traffic Sensor Location for Origin-Destination Estimation Using a Compressed Sensing Framework".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 18.7(2017):1857-1866. |
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