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Journal of Advanced Transportation
Volume 2017, Article ID 4341532, 18 pages
Research Article

Origin-Destination Estimation Using Probe Vehicle Trajectory and Link Counts

1Department of Civil, Construction & Environmental Engineering, San Diego State University, San Diego, CA, USA
2Baidu Online Network Technology Co., Ltd., Beijing, China
3University Transportation Research Center, City College of New York, New York, NY, USA

Correspondence should be addressed to Xianfeng Yang; ude.usds.liam@gnayx

Received 23 June 2016; Revised 13 October 2016; Accepted 14 November 2016; Published 23 January 2017

Academic Editor: Dongjoo Park

Copyright © 2017 Xianfeng Yang 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.


This paper presents two origin-destination flow estimation models using sampled GPS positions of probe vehicles and link flow counts. The first model, named as SPP model (scaled probe OD as prior OD), uses scaled probe vehicle OD matrix as prior OD matrix and applies conventional generalized least squares (GLS) framework to conduct OD correction using link counts; the second model, PRA model (probe ratio assignment), is an extension of SPP in which the observed link probe ratios are also included as additional information in the OD estimation process. For both models, the study explored a new way to construct assignment matrices directly from sampled probe trajectories to avoid sophisticated traffic assignment process. Then, for performance evaluation, a comprehensive numerical experiment was conducted using simulation dataset. The results showed that when the distribution of probe vehicle ratios is homogeneous among different OD pairs, both proposed models achieved similar degree of improvement compared with the prior OD pattern. However, under the case that the distribution of probe vehicle ratios is heterogeneous across different OD pairs, PRA model achieved more significant reduction on OD flow estimations compared with SPP model. Grounded on both theoretical derivations and empirical tests, the study provided in-depth discussions regarding the strengths and challenges of probe vehicle based OD estimation models.