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https://doi.org/10.1002/atr.149
Title: | A computational model for the probit-based dynamic stochastic user optimal traffic assignment problem | Authors: | Meng, Q. Khoo, H.L. |
Keywords: | transportation networks | Issue Date: | Jan-2012 | Citation: | Meng, Q., Khoo, H.L. (2012-01). A computational model for the probit-based dynamic stochastic user optimal traffic assignment problem. Journal of Advanced Transportation 46 (1) : 80-94. ScholarBank@NUS Repository. https://doi.org/10.1002/atr.149 | Abstract: | This paper focuses on computational model development for the probit-based dynamic stochastic user optimal (P-DSUO) traffic assignment problem. We first examine a general fixed-point formulation for the P-DSUO traffic assignment problem, and subsequently propose a computational model that can find an approximated solution of the interest problem. The computational model includes four components: a strategy to determine a set of the prevailing routes between each origin-destination pair, a method to estimate the covariance of perceived travel time for any two prevailing routes, a cell transmission model-based traffic performance model to calculate the actual route travel time used by the probit-based dynamic stochastic network loading procedure, and an iterative solution algorithm solving the customized fixed-point model. The Ishikawa algorithm is proposed to solve the computational model. A comparison study is carried out to investigate the efficiency and accuracy of the proposed algorithm with the method of successive averages. Two numerical examples are used to assess the computational model and the algorithm proposed. Results show that Ishikawa algorithm has better accuracy for smaller network despite requiring longer computational time. Nevertheless, it could not converge for larger network. Copyright © 2010 John Wiley & Sons, Ltd. | Source Title: | Journal of Advanced Transportation | URI: | http://scholarbank.nus.edu.sg/handle/10635/54007 | ISSN: | 01976729 | DOI: | 10.1002/atr.149 |
Appears in Collections: | Staff Publications |
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