Evaluation of Overcrowded Mass Transit Demand-Supply Interaction Considering the Fail to Board Probability and Waiting Time Increase
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-46874-2_28
Reference21 articles.
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3. Darsena D, Gelli G, Iudice I, Verde F (2022) Sensing technologies for crowd management, adaptation, and information dissemination in public transportation systems: a review. IEEE Sens J 23(1):68–87. https://doi.org/10.1109/JSEN.2022.3223297
4. Ponkratov D, Davidich Y, Kopytkov D et al (2023) Public transit crowding estimation indicators: comparative analysis, conditions of application, interaction. In: Arsenyeva O et al (eds) Smart technologies in urban engineering. STUE 2022. LNNS, vol 536. Springer, Cham, pp 764–774. https://doi.org/10.1007/978-3-031-20141-7_68
5. Shao M, Xie C, Li T, Sun L (2022) Influence of in-vehicle crowding on passenger travel time value: insights from bus transit in Shanghai, China. Int J Transp Sci Technol 11(4):665–677. https://doi.org/10.1016/j.ijtst.2021.09.001
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