@article{discovery10103792,
       publisher = {Hindawi Limited},
            note = {'is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited https://creativecommons.org/licenses/by/4.0/},
           title = {Identifying Crowding Impact on Departure Time Choice of Commuters in Urban Rail Transit},
         journal = {Journal of Advanced Transportation},
          volume = {2020},
           month = {June},
            year = {2020},
          author = {Cheng, Y and Ye, X and Fujiyama, T},
             url = {https://doi.org/10.1155/2020/8850565},
        abstract = {Crowding in urban rail transit is an inevitable issue for most of the high-density cities across the world, especially during peak
time. For commuters who have considerably fixed destination arrival times, departure time choice is an important tool to adjust
their trips. 'e ignorance of crowding impact on commuters' departure time choice in urban rail transit may cause errors in
forecasting dynamic passenger flow during peak time in urban rail transit. 'e paper develops a mixed logit model to identify how
crowding impacts the departure time choice of commuters and their taste variation. Arrival time value was firstly measured in a
submodel by applying the reference point approach and then integrated to the main model. Considering the characteristics of
human perception, we divided crowding into five grades with distinct circumstances. All parameter distributions were assumed
based on their empirical distributions revealed through resampling. 'e data from Shanghai Metro used for estimation were
collected by a specifically designed survey, which combines revealed preference questions and stated preference experiments to
investigate the willingness and extent of changing departure time choice of passengers who experienced various grades and
duration of crowding in the most crowded part. 'e result shows that an asymmetric valuation model with preferred arrival time
as the only reference point best captured commuters' responses to arrival time. 'e departure time choice model clearly identified
that only crowding ranging from Grades 3 to 5 had an impact on commuters' departure time choice. 'e parameters of crowding
costs can be assumed to follow transformed lognormal distributions. It is found that the higher the grade of crowding is, the bigger
the impact each unit of crowding cost has on commuters' departure time choice, while commuters' tastes get more concentrated
when crowded situation upgrades. 'e model in this paper can help policymakers better understand the interaction between
commuters' departure time choice and crowding alleviation.}
}