Journal
TRANSPORTATION RESEARCH RECORD
Volume -, Issue 2667, Pages 96-107Publisher
SAGE PUBLICATIONS INC
DOI: 10.3141/2667-10
Keywords
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Funding
- National Research Foundation, Prime Minister's Office, Singapore, under its CREATE program
- Singapore-Massachusetts Institute of Technology Alliance for Research and Technology Future Urban Mobility Interdisciplinary Research Group
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Effective real-time traffic management strategies often require dynamic traffic assignment systems that are calibrated online. But the computationally intensive nature of online calibration limits their application to smaller networks. This paper presents a dimensionality reduction of the online calibration problem that is based on principal components to overcome this limitation. To demonstrate this approach, the origin-destination flow estimation problem is formulated in relation to its principal components. The efficacy of the procedure was tested with real data on the Singapore Expressway network in an open-loop framework. A reduction in the problem dimension by a factor of 50 was observed with only a 2% loss in estimation accuracy. Further, the computational times were reduced by an order of 100. The procedure led to better predictions, as the principal components captured the structural spatial relationships. This work has the potential to make the online calibration problem more scalable.
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