Application of a simulation-based dynamic traffic assignment model
The evaluation of on-line intelligent transportation system (ITS) measures, such as adaptive route-guidance and traffic management systems, depends heavily on the use of faster than real time traffic simulation models. Off-line applications, such as the testing of ITS strategies and planning studies...
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| Published in | European journal of operational research Vol. 189; no. 3; pp. 1381 - 1392 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Amsterdam
Elsevier B.V
16.09.2008
Elsevier Elsevier Sequoia S.A |
| Series | European Journal of Operational Research |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0377-2217 1872-6860 |
| DOI | 10.1016/j.ejor.2006.07.054 |
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| Abstract | The evaluation of on-line intelligent transportation system (ITS) measures, such as adaptive route-guidance and traffic management systems, depends heavily on the use of faster than real time traffic simulation models. Off-line applications, such as the testing of ITS strategies and planning studies, are also best served by fast-running traffic models due to the repetitive or iterative nature of such investigations. This paper describes a simulation-based, iterative dynamic equilibrium traffic assignment model. The determination of time-dependent path flows is modeled as a master problem that is solved using the method of successive averages (MSA). The determination of path travel times for a given set of path flows is the network-loading sub-problem, which is solved using the space-time queuing approach of Mahut. This loading method has been shown to provide reasonably accurate results with very little computational effort. The model was applied to the Stockholm road network, which consists of 2100 links, 1191 nodes, 228 zones, representing and 4964 turns. The results show that this model is applicable to medium-size networks with a very reasonable computation time. |
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| AbstractList | The evaluation of on-line intelligent transportation system (ITS) measures, such as adaptive route-guidance and traffic management systems, depends heavily on the use of faster than real time traffic simulation models. Off-line applications, such as the testing of ITS strategies and planning studies, are also best served by fast-running traffic models due to the repetitive or iterative nature of such investigations. This paper describes a simulation-based, iterative dynamic equilibrium traffic assignment model. The determination of time-dependent path flows is modeled as a master problem that is solved using the method of successive averages (MSA). The determination of path travel times for a given set of path flows is the network-loading sub-problem, which is solved using the space-time queuing approach of Mahut. This loading method has been shown to provide reasonably accurate results with very little computational effort. The model was applied to the Stockholm road network, which consists of 2100 links, 1191 nodes, 228 zones, representing and 4964 turns. The results show that this model is applicable to medium-size networks with a very reasonable computation time. The evaluation of on-line intelligent transportation system (ITS) measures, such as adaptive route-guidance and traffic management systems, depends heavily on the use of faster than real time traffic simulation models. Off-line applications, such as the testing of ITS strategies and planning studies, are also best served by fast-running traffic models due to the repetitive or iterative nature of such investigations. This paper describes a simulation-based, iterative dynamic equilibrium traffic assignment model. The determination of time-dependent path flows is modeled as a master problem that is solved using the method of successive averages (MSA). The determination of path travel times for a given set of path flows is the network-loading sub-problem, which is solved using the space-time queuing approach of Mahut. This loading method has been shown to provide reasonably accurate results with very little computational effort. The model was applied to the Stockholm road network, which consists of 2100 links, 1191 nodes, 228 zones, representing and 4964 turns. The results show that this model is applicable to medium-size networks with a very reasonable computation time. [PUBLICATION ABSTRACT] |
| Author | Mahut, Michael Florian, Michael Tremblay, Nicolas |
| Author_xml | – sequence: 1 givenname: Michael surname: Florian fullname: Florian, Michael email: mike@inro.ca – sequence: 2 givenname: Michael surname: Mahut fullname: Mahut, Michael email: michaelm@inro.ca – sequence: 3 givenname: Nicolas surname: Tremblay fullname: Tremblay, Nicolas email: nicolas@inro.ca |
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| Cites_doi | 10.1287/opre.41.1.179 10.1051/jp1:1992277 10.1016/0191-2615(90)90041-V 10.3141/1771-23 10.3141/1876-11 10.1098/rspa.1955.0088 10.1287/opre.4.1.42 |
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| Keywords | Traffic simulation Queuing models Dynamic traffic assignment Method of successive averages |
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Universitat Politecnica de Catalunya. See also – reference: Ben-Akiva, M., Koutsopoulos, H.N., Mishalani, R., 1998. DYNAMIT: A simulation-based system for traffic prediction. Paper presented at the DACCORD Short Term Forecasting Workshop, Delft, The Netherlands. See also – reference: Ben-Akiva, M., Koutsopoulis, H., Toledo, T., 2000. MITSIMLab: Recent developments and applications. Presented at the Spring meeting of INFORMS, Salt Lake City, USA, May 7–10. – reference: Barceló, J., 2000. The role of traffic simulation in advanced traffic management systems. Presented at the Spring meeting of INFORMS, Salt Lake City, USA, May 7–10. – reference: Mahut, M., 2001. A multi-lane extension of the space-time queue model of traffic dynamics. In: Fourth Triennial Symposium on Transportation Analysis (TRISTAN IV). Preprints, vol. 2, 303–308. – reference: Leonard, D.R., Gower, P., Taylor, N.B., 1989. CONTRAM: Structure of the model. Transport and Road Research Laboratory (TRRL) Research Report 178. Department of Transport, Crowthorne. See also – reference: Mahmassani, H.S., Abdelghany, A.F., Huynh, N., Zhou, X., Chiu, Y.C., 2001. Abdelghany KF. DYNASMART-P (version 0.926) user’s guide. Technical Report STO67-85-PIII, Center for Transportation Research, University of Texas at Austin. – reference: Yang, Q., 1997. A simulation laboratory for evaluation of dynamic traffic management systems. Ph.D. Thesis, Massachusetts Institute of Technology. See also – volume: 24 start-page: 471 year: 1990 end-page: 495 ident: bib17 article-title: Dynamic modelling, assignment and route guidance in traffic networks publication-title: Transportation Research B – reference: Mahut, M., 2000. Discrete flow model for dynamic network loading. Ph.D. Thesis, Département d’informatique et de recherche opérationnelle, Université de Montréal. 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| Title | Application of a simulation-based dynamic traffic assignment model |
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