Data dependent input control for origin–destination demand estimation using observability analysis

• We study network observability in O–D estimation problems.
• Both network topological and operational relationships are incorporated.
• We develop an approach for input selection to ensure observability and estimation quality.
• We analyze error bounds of the estimation.

In this paper, we address the observability issue of static O–D estimation based on link counts. Unlike most classic observability analyses that relied only on network topological relationships, our analysis incorporates the actual values of input parameters, thus including network operational relations as well. We first analyze possible mathematical properties of an O–D estimation problem with different data input. We then propose a modeling approach based on mixed-integer program for selecting model input that ensures observability and estimation quality. Through establishing a stronger connection between observability analysis and the corresponding estimation problem, the proposed method aims to improve estimation quality while reducing reliance on erroneous data.