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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 763469, 8 pages
Research Article

Robust Missing Traffic Flow Imputation Considering Nonnegativity and Road Capacity

1Department of Transportation Engineering, Beijing Institute of Technology, Beijing 100081, China
2Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI, USA

Received 18 December 2013; Accepted 13 February 2014; Published 18 March 2014

Academic Editor: Huimin Niu

Copyright © 2014 Huachun Tan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


There are increasing concerns about missing traffic data in recent years. In this paper, a robust missing traffic flow data imputation approach based on matrix completion is proposed. In the proposed method, the similarity of traffic flow from day to day is exploited to impute missing data by the low-rank hypothesis of constructed traffic flow matrix. And the physical limitation of road capacity and nonnegativity is also considered through the optimization process, which avoids the possibility of producing negative and overcapacity values. Moreover, the proposed algorithm can impute missing data and recover outlier in a unify framework. The experiment results show that the proposed method is more accurate, stable, and reasonable.