Estimating Bus Passenger Origin-Destination Flow via Passenger Reidentification Using Video Images

The estimation of bus passenger origin-destination (OD) flow is crucial for bus operation and management. Although many existing studies have made efforts to reconstruct OD flow from passenger counts at each station, few of them tracked individual passengers because it is still infeasible in practice to monitor all onboard passengers throughout their entire journeys. This study proposes a passenger reidentification method for estimating route-level bus passenger OD flow using video images at bus doors. All boarding and alighting passengers are identified and their appearance features are extracted from video images. Boarding passengers at upstream stations and alighting passengers at downstream stations are matched considering not only the similarities of their appearance features but also historical alighting probabilities. Reliable passenger matches are filtered out by a matching probability threshold. The corresponding accurate OD samples, together with the boarding and alighting counts at each station, are utilized to estimate OD flow between bus stations. A comprehensive case study was carried out on an operational bus route in Shanghai, China during morning and evening peak hours over 15 weekdays. Results of the case study showed that the proposed method is capable of generating accurate OD estimates, with cosine similarities remaining above 0.9, root mean square errors within 0.5 person, and mean absolute percentage errors of approximately 12%. The error metrics were decreased by nearly half compared to the traditional method that only uses the boarding and alighting counts.