A Novel OD Estimation Method Based on Automatic Vehicle Identification Data

With the development and application of Automatic Vehicle Identification (AVI) technologies, a novel high resolution OD estimation method was proposed based on AVI detector information. 4 detected categories (O-x+D-y, O-x/D-y+Path(s), O-x/D-y, Path(s)) were divided at the first step. Then the initial OD matrix was updated using the O-x+D-y sample information considering the AVI detector errors. Referenced by particle filter, the link-path relationship data were revised using the last 3 categories information based on Bayesian inference and the possible trajectory and OD were determined using Monte Carlo random process at last. Finally, according to the current application of video detector in Shanghai, the North-South expressway was selected as the testbed which including 17 OD pairs and 9 AVI detectors. The results show that the calculated average relative error is 12.09% under the constraints that the simulation error is under 15% and the detector error is about 10%. It also shows that this method is highly efficient and can fully using the partial vehicle trajectory which can be satisfied with the dynamic traffic management application in reality.