A Novel Method for Estimation of Dynamic OD Flow. (2016)

• Record Type: Journal Article
• Authors: Ying, Li; Zhu, Jiang; Huiyan, Wang; Zhenyu, Lei
• Is Part Of: Procedia engineering. Volume 137(2016)
• Page Start: 94
• Page End: 102
• Publication Date: 2016
• Subjects: Kalman filtering -- polynomial trend -- OD matrix estimation -- deviations; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Conference proceedings; Periodicals; 620.005
• DOI: 10.1016/j.proeng.2016.01.238
• Languages: English
• ISSNs: 1877-7058

Abstract

Abstract: To more accurately describe the evolution process of traffic flow, a novel method was proposed on the basis of the polynomial trend model and the Kalman filtering theory in the paper. The state variables were defined as the deviations of the actual OD flow from the historical values. These deviations were presented as a stochastic evolution process with a sliding trend. Furthermore, the dynamic OD matrix was estimated and predicated by establishing a polynomial trend filtering model. A large number of simulation results prove that the performance of the algorithm proposed in this paper is better than the traditional method, and this algorithm can acquire more accurate estimation and prediction information for OD matrix.