英文摘要 |
This study proposes an iterative dynamic O-D matrices estimation algorithm to effectively capture the traffic behaviors and their arrival distributions under various traffic conditions. The core logic of the proposed algorithm is to combine extended Kalman filtering with cell transmission model to simulate traffic movement behaviors so as to predict the arrival distributions of all O-D pair traffic in various time intervals, and then to estimate dynamic O-D matrices. To validate the performance of the proposed algorithm, a small-scale corridor example with six O-D pairs is tested, in which a set of 90-minute O-D matrices, varying at every six seconds is estimated. For comparison, the Greenshields macroscopic model, which predicts the travel time by assuming that entered traffic will arrive at their destinations within two time intervals, is also tested in the same corridor example. The results show that the proposed algorithm can obtain a relatively accurate estimation result with RMSE value much smaller than the Greenshields model. To further investigate the applicability of the proposed algorithm, two case corridors on Taiwan Freeway No.1: Yangmei Toll Station to Taishan Toll Station and Taichung Interchange to Taipei Interchange are conducted. The results show that the proposed algorithm can obtain satisfactory RMSE values, suggesting the effectiveness and applicability of the proposed algorithm. |