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Title: Improving the Efficiency of Dynamic Traffic Assignment Through Computational Methods Based on Combinatorial Algorithm
Accession Number: 01373741
Record Type: Component
Abstract: A new combinatorial dynamic traffic assignment (CDTA) algorithm for multi-destination transportation networks is developed. The algorithm, stated on a discrete space-time network, uses the cell transmission model (CTM) to propagate traffic, thereby ensuring that traffic dynamics such as queue evolution, link spill-over, and shockwave propagation are adequately captured. The CDTA algorithm assigns vehicles to optimal time-dependent shortest paths in one shot by finding connectivity between origin-destination pairs in the time-expanded CTM network. The CDTA algorithm runs in polynomial time and is guaranteed to find a user optimal assignment in single-destination networks. However, vehicular trajectories could potentially violate first–in first–out (FIFO) condition in a multi–destination network (thereby yielding an optimal though infeasible solution). FIFO flows are achieved by simulating the vehicular trajectories using a simulation-based dynamic traffic assignment (DTA) model. These flows in turn serve as an initial feasible DTA solution – this method is called “warm starting” a simulation-based DTA model. The algorithm has been tested for the Anaheim and Winnipeg networks for varying demand levels. The warm started DTA models performed better than the non-warm started models in terms of equilibrium convergence metrics. In particular, for solutions involving small path sets, the DTA model warm started using the CDTA algorithm provided better solutions than the purely simulation-based model. In addition to the “warm start” approach, parallel computing was also applied to the CDTA model to gain computational efficiency. The results are encouraging, and showed improved run times using multiple processors. Larger networks are better at realizing the full benefit of high number of processors.
Supplemental Notes: This paper was sponsored by TRB committee ADB30 Transportation Network Modeling
Monograph Title: Monograph Accession #: 01362476
Report/Paper Numbers: 12-4040
Language: English
Corporate Authors: Transportation Research Board 500 Fifth Street, NW Authors: Nezamuddin, NWaller, S TravisPagination: 15p
Publication Date: 2012
Conference:
Transportation Research Board 91st Annual Meeting
Location:
Washington DC, United States Media Type: Digital/other
Features: Figures; References
TRT Terms: Uncontrolled Terms: Subject Areas: Highways; Planning and Forecasting; I72: Traffic and Transport Planning
Source Data: Transportation Research Board Annual Meeting 2012 Paper #12-4040
Files: TRIS, TRB
Created Date: Feb 8 2012 5:21PM
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