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Approximate Solution Procedure for Dynamic Traffic Assignment
This paper proposes an approximate dynamic traffic assignment algorithm for the analysis of traffic conditions in large-scale road networks over several days. The time-dependent origin-destination trips are assumed to be known. A case study for evacuation of the New Orleans metropolitan area prior to the landfall of Hurricane Katrina is presented to test the efficiency and effectiveness of the proposed procedure. The model results are compared to the traffic counts collected during the evacuation and then further tested by the mesoscopic simulation-based model, DynusT. The study shows that the traffic pattern produced by the proposed procedure is a good approximation to traffic count data and that the algorithm provides a good approximation to the computations performed by DynusT.
Approximate Solution Procedure for Dynamic Traffic Assignment
This paper proposes an approximate dynamic traffic assignment algorithm for the analysis of traffic conditions in large-scale road networks over several days. The time-dependent origin-destination trips are assumed to be known. A case study for evacuation of the New Orleans metropolitan area prior to the landfall of Hurricane Katrina is presented to test the efficiency and effectiveness of the proposed procedure. The model results are compared to the traffic counts collected during the evacuation and then further tested by the mesoscopic simulation-based model, DynusT. The study shows that the traffic pattern produced by the proposed procedure is a good approximation to traffic count data and that the algorithm provides a good approximation to the computations performed by DynusT.
Approximate Solution Procedure for Dynamic Traffic Assignment
Li, Anna C. Y. (author) / Nozick, Linda (author) / Davidson, Rachel (author) / Brown, Nathanael (author) / Jones, Dean A. (author) / Wolshon, Brian (author)
Journal of Transportation Engineering ; 139 ; 822-832
2012-11-03
112013-01-01 pages
Article (Journal)
Electronic Resource
English
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