UTN-Model-Based Traffic Flow Prediction for Parallel-Transportation Management Systems

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 平行智能技术与系统团队

	UTN-Model-Based Traffic Flow Prediction for Parallel-Transportation Management Systems
	Kong, Qing-Jie1 ; Xu, Yanyan 2; Lin, Shu 2; Wen, Ding 3; Zhu, Fenghua1 ; Liu, Yuncai 2
发表期刊	IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
	2013-09-01
卷号	14 期号:3 页码:1541-1547
文章类型	Article
摘要	Aiming to comply with the requirement of parallel-transportation management systems (PtMS), this paper presents a short-term traffic flow prediction method for signal-controlled urban traffic networks (UTNs) based on the macroscopic UTN model. In contrast with other time-series-based or spatio-temporal correlation methods, the proposed method focuses more on using the substantial mechanism of traffic transmission in road networks and the topology model of the entire UTN. Furthermore, this approach employs a speed-density model based on the fundamental diagram (FD) to obtain more accurate travel times in links. In the comparison experiment, the microscopic traffic simulation software CORSIM is adopted to simulate the real urban traffic. The experiment results fully verify the outstanding performances of the proposed prediction method.
关键词	Corsim Fundamental Diagram (Fd) Parallel-transportation Management Systems (Ptms) Short-term Traffic Flow Prediction Urban Traffic Network (Utn) Model
WOS标题词	Science & Technology ; Technology
关键词[WOS]	VOLUME ; NETWORKS
收录类别	SCI
语种	英语
WOS研究方向	Engineering ; Transportation
WOS类目	Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS记录号	WOS:000324336100046
引用统计	被引频次：21[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/3643
专题	多模态人工智能系统全国重点实验室_平行智能技术与系统团队
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China 3.Natl Univ Def Technol, Ctr Mil Computat Expt & Parallel Syst Technol, Changsha 410073, Hunan, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Kong, Qing-Jie,Xu, Yanyan,Lin, Shu,et al. UTN-Model-Based Traffic Flow Prediction for Parallel-Transportation Management Systems[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2013,14(3):1541-1547.
APA	Kong, Qing-Jie,Xu, Yanyan,Lin, Shu,Wen, Ding,Zhu, Fenghua,&Liu, Yuncai.(2013).UTN-Model-Based Traffic Flow Prediction for Parallel-Transportation Management Systems.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,14(3),1541-1547.
MLA	Kong, Qing-Jie,et al."UTN-Model-Based Traffic Flow Prediction for Parallel-Transportation Management Systems".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 14.3(2013):1541-1547.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
06490058.pdf（607KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览下载