Transit passenger origin–destination flow estimation: Efficiently combining onboard survey and large automatic passenger count datasets

As transit agencies increasingly adopt the use of Automatic Passenger Count (APC) technologies, a large amount of boarding and alighting data are being amassed on an ongoing basis. These datasets offer opportunities to infer good estimates of passenger origin–destination (OD) flows. In this study, a method is proposed to estimate transit route passenger OD flow matrices for time-of-day periods based on OD flow information derived from labor-intensive onboard surveys and the large quantities of APC data that are becoming available. The computational feasibility of the proposed method is established and its accuracy is empirically evaluated using differences between the estimated OD flows and ground-truth observations on an operational bus route. To interpret the empirical differences from the ground-truth estimates, differences are also computed when using the state-of-the-practice Iterative Proportional Fitting (IPF) method to estimate the OD flows. The empirical results show that when using sufficient quantities of boarding and alighting data that can be readily obtained from APC-equipped buses, the estimates determined by the proposed method are better than those determined by the IPF method when no or a small sample sized onboard OD flow survey dataset is available and of similar quality to those determined by the IPF method when a large sample sized onboard OD flow survey dataset is available. Therefore, the proposed method offers the opportunity to forgo conducting costly onboard surveys for the purpose of OD flow estimation