A novel dynamic OD estimation approach based on automatic vehicle identification data

Based on the new information which was detected through automatic vehicle identification (AVI) technology, an approach for dynamic OD estimation by using the AVI information is put forward. Partial trajectory, dynamic travel time and detector measurability were introduced into this approach with a reference to the particle filter. First the selection scope and the probability were reduced and collected by Bayesian estimation. Then the absented trajectory of any vehicles was determined by Monte Carlo stochastic simulation and the initial corrected OD matrix was obtained by correcting the individual vehicles trajectory. At last, the initial OD matrix was corrected by the path-link flow function based on the AVI volume information. Finally, an analysis was made of the accuracy of dynamic OD estimation on different coverage of AVI and different accuracy of prior information based on the Shanghai North-South expressway. The analysis result shows that the accuracy of OD estimation is high when the coverage is 60% and the relative error is 28.87% in 50% coverage and 60% accuracy of prior information. This approach can be used with low accuracy prior information which can better overcome the defect that the current OD information precision is low in China.