Correction of Time-Dependent Origin-Destination Demand in Dynamic Traffic Assignment, M.Sc. Thesis Sharif University of Technology ; Zakaei Ashtiani, Hedayat (Supervisor)
Abstract
Time-dependent origin-destination demand is a key input in dynamic traffic assignment in advanced traffic management systems, and the result of dynamic traffic assignment is dependent on the accuracy of this information. One method to achieve time dependent demand matrices is using a primary demand matrix and volume traffic counts in some links of network. In this thesis a bi-level model is used to correct the demand matrix and the extended gradient method is suggested to solve the problem. The extended gradient is an iterative method that in each iteration, corrects the demand matrix in a way that the estimated traffic flow be close to the observed traffic flow. Execution of this method in...
Cataloging briefCorrection of Time-Dependent Origin-Destination Demand in Dynamic Traffic Assignment, M.Sc. Thesis Sharif University of Technology ; Zakaei Ashtiani, Hedayat (Supervisor)
Abstract
Time-dependent origin-destination demand is a key input in dynamic traffic assignment in advanced traffic management systems, and the result of dynamic traffic assignment is dependent on the accuracy of this information. One method to achieve time dependent demand matrices is using a primary demand matrix and volume traffic counts in some links of network. In this thesis a bi-level model is used to correct the demand matrix and the extended gradient method is suggested to solve the problem. The extended gradient is an iterative method that in each iteration, corrects the demand matrix in a way that the estimated traffic flow be close to the observed traffic flow. Execution of this method in...
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