title: A Two-Stage Algorithm for Origin-Destination Matrices Estimation Considering Dynamic Dispersion Parameter for Route Choice.
abstract: This paper proposes a two-stage algorithm to simultaneously estimate origin-destination (OD) matrix, link choice proportion, and dispersion parameter using partial traffic counts in a congested network. A non-linear optimization model is developed which incorporates a dynamic dispersion parameter, followed by a two-stage algorithm in which Generalized Least Squares (GLS) estimation and a Stochastic User Equilibrium (SUE) assignment model are iteratively applied until the convergence is reached. To evaluate the performance of the algorithm, the proposed approach is implemented in a hypothetical network using input data with high error, and tested under a range of variation coefficients. The root mean squared error (RMSE) of the estimated OD demand and link flows are used to evaluate the model estimation results. The results indicate that the estimated dispersion parameter theta is insensitive to the choice of variation coefficients. The proposed approach is shown to outperform two established OD estimation methods and produce parameter estimates that are close to the ground truth. In addition, the proposed approach is applied to an empirical network in Seattle, WA to validate the robustness and practicality of this methodology. In summary, this study proposes and evaluates an innovative computational approach to accurately estimate OD matrices using link-level traffic flow data, and provides useful insight for optimal parameter selection in modeling travelers' route choice behavior.
authors.affiliation: School of Management, Chongqing Jiaotong University, Chongqing, China.|Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, United States of America.
authors.forename: Yong
authors.initials: Y
authors.lastname: Wang
authors.affiliation: School of Transportation Science and Engineering, Beijing Key Laboratory for Cooperative Vehicle Infrastructure, Systems, and Safety Control, Beihang University, Beijing, China.|Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, SiPaiLou #2, Nanjing, Jiangsu, China.
authors.forename: Xiaolei
authors.initials: X
authors.lastname: Ma
authors.affiliation: School of Management, Chongqing Jiaotong University, Chongqing, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Liu
authors.affiliation: School of Management, Chongqing Jiaotong University, Chongqing, China.
authors.forename: Ke
authors.initials: K
authors.lastname: Gong
authors.forename: Kristian C
authors.initials: KC
authors.lastname: Henrickson
authors.affiliation: Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, United States of America.
authors.forename: Kristian C
authors.initials: KC
authors.lastname: Henricakson
authors.affiliation: School of Management, Chongqing Jiaotong University, Chongqing, China.
authors.forename: Maozeng
authors.initials: M
authors.lastname: Xu
authors.affiliation: Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, United States of America.
authors.forename: Yinhai
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D002755:Choice Behavior; D008962:Models, Theoretical; D009716:Numerical Analysis, Computer-Assisted; D013997:Time Factors; D014195:Travel; D014861:Washington