Abstract
The accuracy of transit assignment plays an important role in the successful design and operation of a transit system. The majority of previous studies on validating transit assignment models has used limited survey data or has lacked a large-scale multimodal and high quality dataset. Considering the advantages of smart card [automatic fare collection (AFC)] systems, the aims of this study are to put forward a methodological framework to validate existing transit assignment models and to quantify the performance of these models. Our study combines data from three sources: the General Transit Feed Specification, an AFC system, and a strategic transport model from a large-scale multimodal public transport network, namely the South-East Queensland (SEQ) network in Australia. The AFC system in SEQ has provided a very large and highly accurate dataset on passenger boardings and alightings for the three transit modes of bus, rail and ferry. Following a data analysis, an origin–destination trip matrix is estimated for the AM peak period using AFC data as an input to the transit assignment model. Then, the results of the transit assignment model are compared with the actual passengers’ route choices over the same period, at different levels of aggregation. The model performance is quantified by each route (and direction), by each segment of each route (and direction), and by each stop. The results indicate that relatively tighter thresholds are required to validate the transit assignment at the segment level than at the stop level. Furthermore, the validation results indicate that the greatest error is realized for the bus mode, while the level of accuracy in the rail mode is the best. The results suggest a segment-level analysis should be used as the most useful level of aggregation for future calibration and validation of transit assignment models.
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Acknowledgements
The authors would like to acknowledge TransLink for providing the AFC data for this research. We would also like to acknowledge the Queensland Department of Transport and Main Roads (DTMR), Transport Strategy and Planning Branch, for providing access to the South East Queensland Strategic Transport Model (SEQSTM). This work is partially supported by the Transport Academic Partnership between DTMR and the University of Queensland, and by the Australian Research Council through a DECRA Grant (Grant number: DE2015002743).
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Tavassoli, A., Mesbah, M. & Hickman, M. Application of smart card data in validating a large-scale multi-modal transit assignment model. Public Transp 10, 1–21 (2018). https://doi.org/10.1007/s12469-017-0171-1
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DOI: https://doi.org/10.1007/s12469-017-0171-1