Evaluating the Effect of Multiple Data Types on a Large Scale Static Origin–Destination Matrix Estimation, Case Study of Tehran, Iran

The purpose of this study is to estimate the Origin–Destination Matrix (ODM) of Tehran city which is a large scale network, using three types of field data of count links, partial paths flows, and the difference in incoming and outgoing flows to/from the central traffic area. The data was collected from 482 Automatic Number Plate Recognition cameras on two cordon lines and 1957 inductive loop detectors at signalized intersections. A bi-level iterative model is used to estimate the static ODM. The upper level minimized an error term based on the multiple field measurements and the lower level formulates a user equilibrium traffic assignment. The results showed that the R-squared value of the fitted line, which regressed the observed and estimated values of the field data, was increased from 0.5 before an ODM estimation to 0.74 afterwards. The value of the PRMSE after estimating the ODM decreased by 37% compared to the before scenario. These results indicate that the estimated ODM is significantly better than the base ODM. In conclusion, this study demonstrated an efficient approach to estimate the ODM in a large scale network and successfully estimated the ODM of Tehran city.