標題: Dynamic origin-destination demand flow estimation under congested traffic conditions
作者: Lu, Chung-Cheng
Zhou, Xuesong
Zhang, Kuilin
運輸與物流管理系 註:原交通所+運管所
Department of Transportation and Logistics Management
關鍵字: OD demand estimation;Path flow estimator;Lagrangian relaxation;Newell's simplified kinematic wave theory
公開日期: 1-九月-2013
摘要: This paper presents a single-level nonlinear optimization model to estimate dynamic origin destination (OD) demand. The model is a path flow-based optimization model, which incorporates heterogeneous sources of traffic measurements and does not require explicit dynamic link-path incidences. The objective is to minimize (i) the deviation between observed and estimated traffic states and (ii) the deviation between aggregated path flows and target OD flows, subject to the dynamic user equilibrium (DUE) constraint represented by a gap-function-based reformulation. A Lagrangian relaxation-based algorithm which dualizes the difficult DUE constraint to the objective function is proposed to solve the model. This algorithm integrates a gradient-projection-based path flow adjustment method within a column generation-based framework. Additionally, a dynamic network loading (DNL) model, based on Newell's simplified kinematic wave theory, is employed in the DUE assignment process to realistically capture congestion phenomena and shock wave propagation. This research also derives analytical gradient formulas for the changes in link flow and density due to the unit change of time-dependent path inflow in a general network under congestion conditions. Numerical experiments conducted on three different networks illustrate the effectiveness and shed some light on the properties of the proposed OD demand estimation method. (C) 2013 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/j.trc.2013.05.006
http://hdl.handle.net/11536/22104
ISSN: 0968-090X
DOI: 10.1016/j.trc.2013.05.006
期刊: TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
Volume: 34
Issue: 
起始頁: 16
結束頁: 37
顯示於類別:期刊論文


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