Off-line calibration of Dynamic Traffic Assignment models

Advances in Intelligent Transportation Systems (ITS) have resulted in the deployment of surveillance systems that automatically collect and store extensive network-wide traffic data. Dynamic Traffic Assignment (DTA) models have also been developed for a variety of dynamic traffic management applications. Such models are designed to estimate and predict the evolution of congestion through detailed models and algorithms that capture travel demand, network supply and their complex interactions. The availability of rich time-varying traffic data spanning multiple days thus provides the opportunity to calibrate a DTA model's many inputs and parameters, so that its outputs reflect field conditions. The current state of the art of DTA model calibration is a sequential approach, in which supply model calibration (assuming known demand inputs) is followed by demand calibration with fixed supply parameters. In this thesis, we develop an off-line DTA model calibration methodology for the simultaneous estimation of all demand and supply inputs and parameters, using sensor data. We adopt a minimization formulation that can use any general traffic data, and present approaches to solve the complex, non-linear, stochastic optimization problem.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2006

Author dc:creator

• Balakrishna, Ramachandran, 1978-

Advisor dc:contributor.advisor

• Moshe E. Ben-Akiva and Haris N. Koutsopoulos.

• Civil and Environmental Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/35120
• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Identifier URI

http://dspace.mit.edu/handle/1721.1/35120

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/35120