Origin-Destination Estimation Using Probe Vehicle Trajectory and Link Counts

This paper presents two origin-destination flow estimation models using sampled GPS positions of probe vehicles and link flow counts. The first model, named as SPP model (scaled probe OD as prior OD), uses scaled probe vehicle OD matrix as prior OD matrix and applies conventional generalized least squares (GLS) framework to conduct OD correction using link counts; the second model, PRA model (probe ratio assignment), is an extension of SPP in which the observed link probe ratios are also included as additional information in the OD estimation process. For both models, the study explored a new way to construct assignment matrices directly from sampled probe trajectories to avoid sophisticated traffic assignment process. Then, for performance evaluation, a comprehensive numerical experiment was conducted using simulation dataset. The results showed that when the distribution of probe vehicle ratios is homogeneous among different OD pairs, both proposed models achieved similar degree of improvement compared with the prior OD pattern. However, under the case that the distribution of probe vehicle ratios is heterogeneous across different OD pairs, PRA model achieved more significant reduction on OD flow estimations compared with SPP model. Grounded on both theoretical derivations and empirical tests, the study provided in-depth discussions regarding the strengths and challenges of probe vehicle based OD estimation models.

The Application of Fluid Analogy Method for Estimating Transit Route ODs Using IC Card On-Off Passenger Data

Transit route ODs are important reference data for transit network planning and operation management. However, it has the difficulties in data collection, and is of high expense and survey error by means of manual investigation method. It is easy to collect the passenger boarding-alighting counts. The method of fluid analogy method (FAM) is presented for transit passenger OD estimation. It uses the concept of pipe flow, transit route and passengers are regarded as the pipe and fluid, generate bus route OD matrix based upon passenger boarding and alighting counts. The accuracy of route OD estimates generated from boarding-alighting data is tested against actual transit integrated circuit cards (IC cards) OD based on Beijing transit route. It is shown that error index for OD at AM peak hours, PM peak hours and all day is 0.79, 0.80 and 0.83, the result shows that it has a good performance. While the correlation coefficient for actual traveled stops and estimated at AM peak hours, PM peak hours and all day is 0.98, 0.98 and 0.99, which further validate the accuracy and reliability of FAM method in estimating transit route ODs. Compared with traditional equalization algorithms and other analytical model, the method is simple, efficient and able to get a unique solution OD. It has a high practical value in real-time scheduling of intelligent public transport.