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This study proposes a framework to estimate alighting locations from Smart Card Data (SCD) that are absent information on entry-only public transport systems such as buses and trams. The proposed method uses the characteristics of SCD to (i) determine boarding locations from SCD and GPS-bus data based on exact match and time windows using common attributes, (ii) infer individuals' home locations and user types from multimodal SCD, (iii) estimate alighting locations using inferred information with different scenarios such as with and without home locations based on the type of users. Reliable results are obtained once home locations are identified with high confidence for all user types. The proposed framework is applied to Shenzhen, China as a case study to validate the proposed model's effectiveness. The study offers valuable insight into aligning location estimation from user types to optimise the quality of public transport planning and services.
Aslam et al. (Wed,) studied this question.