This paper examines the impact of applying dynamic traffic assignment (DTA) and quasi-dynamic traffic assignment (QDTA) models, which apply different route choice approaches (shortest paths based on current travel times, User Equilibrium: UE, and system optimum: SO), on the accuracy of the solution of the offline dynamic demand estimation problem. The evaluation scheme is based on the adoption of a bilevel approach, where the upper level consists of the adjustment of a starting demand using traffic measures and the lower level of the solution of the traffic network assignment problem. The SPSA AD-PI (Simultaneous Perturbation Stochastic Approximation Asymmetric Design Polynomial Interpolation) is adopted as a solution algorithm. A comparative analysis is conducted on a test network and the results highlight the importance of route choicemodel and information for the stability and the quality of the offline dynamic demand estimations.

Nigro, M., Abdelfatah, A., Cipriani, E., Colombaroni, C., Fusco, G., Gemma, A. (2018). Dynamic O-D demand estimation: Application of SPSA AD-PI method in conjunction with different assignment strategies. JOURNAL OF ADVANCED TRANSPORTATION, 2018, 1-18 [10.1155/2018/2085625].

Dynamic O-D demand estimation: Application of SPSA AD-PI method in conjunction with different assignment strategies

Nigro, Marialisa
;
Cipriani, Ernesto;Gemma, Andrea
2018-01-01

Abstract

This paper examines the impact of applying dynamic traffic assignment (DTA) and quasi-dynamic traffic assignment (QDTA) models, which apply different route choice approaches (shortest paths based on current travel times, User Equilibrium: UE, and system optimum: SO), on the accuracy of the solution of the offline dynamic demand estimation problem. The evaluation scheme is based on the adoption of a bilevel approach, where the upper level consists of the adjustment of a starting demand using traffic measures and the lower level of the solution of the traffic network assignment problem. The SPSA AD-PI (Simultaneous Perturbation Stochastic Approximation Asymmetric Design Polynomial Interpolation) is adopted as a solution algorithm. A comparative analysis is conducted on a test network and the results highlight the importance of route choicemodel and information for the stability and the quality of the offline dynamic demand estimations.
2018
Nigro, M., Abdelfatah, A., Cipriani, E., Colombaroni, C., Fusco, G., Gemma, A. (2018). Dynamic O-D demand estimation: Application of SPSA AD-PI method in conjunction with different assignment strategies. JOURNAL OF ADVANCED TRANSPORTATION, 2018, 1-18 [10.1155/2018/2085625].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/339398
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