[1]

Kepaptsoglou K, Karlaftis MG. 2009. The bus bridging problem in metro operations: conceptual framework, models and algorithms. Public Transport 1:275−97

doi: 10.1007/s12469-010-0017-6
[2]

China Association of Metros. 2019. China urban rail transit statistical report in 2018. China Academic Journal Electronic Publishing House 4(5):16−34

doi: 10.14052/j.cnki.china.metros.2019.04.005
[3]

Kyriakidis M, Hirsch R, Majumdar A. 2012. Metro railway safety: an analysis of accident precursors. Safety Science 50:1535−48

doi: 10.1016/j.ssci.2012.03.004
[4]

Zhang Q, Han B, Li D. 2008. Modeling and simulation of passenger alighting and boarding movement in Beijing metro stations. Transportation Research Part C: Emerging Technologies 16:635−49

doi: 10.1016/j.trc.2007.12.001
[5]

Almeida JE, Rosseti RJF, Coelho AL. 2013. Crowd simulation modeling applied to emergency and evacuation simulations using multi-agent systems. ArXiv Preprint:93−104

doi: abs/1303.4692
[6]

Parisi DR, Dorso CO. 2005. Microscopic dynamics of pedestrian evacuation. Physica A: Statistical Mechanics and Its Applications 354:606−18

doi: 10.1016/j.physa.2005.02.040
[7]

Sun L, Luo W, Yao L, Qiu S, Rong J. 2017. A comparative study of funnel shape bottlenecks in subway stations. Transportation Research Part A: Policy and Practice 98:14−27

doi: 10.1016/j.tra.2017.01.021
[8]

Rahman K, Abdul Ghani N, Kamil AA, Mustafa A, Chowdhury MAK. 2015. An M/M/c/K state-dependent model for pedestrian flow control and design of facilities. PLoS One 10:e0133229

doi: 10.1371/journal.pone.0133229
[9]

Hu L, Jiang Y, Zhu J, Chen Y. 2015. A PH/PH(n)/C/C state-dependent queuing model for metro station corridor width design. European Journal of Operational Research 240:109−26

doi: 10.1016/j.ejor.2014.06.010
[10]

Long ZQ, Li Y, He G. 2010. Research on electromagnet fault diagnosis technology of suspension control system of maglev train. Control and Decision (in Chinese) 25(7):1004−9
[11]

Fu Z, Jia Q, Chen J, Ma J, Han K, et al. 2018. A fine discrete field cellular automaton for pedestrian dynamics integrating pedestrian heterogeneity, anisotropy, and time-dependent characteristics. Transportation Research Part C: Emerging Technologies 91:37−61

doi: 10.1016/j.trc.2018.03.022
[12]

Heliövaara S, Kuusinen JM, Rinne T, Korhonen T, Ehtamo H. 2012. Pedestrian behavior and exit selection in evacuation of a corridor–An experimental study. Safety Science 50:221−27

doi: 10.1016/j.ssci.2011.08.020
[13]

Desmet A, Gelenbe E. Capacity based evacuation with dynamic exit signs. 2014 IEEE International Conference on Pervasive Computing and Communication Workshops. Budapest, Hungary, 24-28 March 2014. USA: IEEE. pp. 332−27. https://doi.org/10.1109/PerComW.2014.6815227
[14]

Dias C, Sarvi M, Shiwakoti N, Ejtemai O, Burd M. 2013. Investigating collective escape behaviours in complex situations. Safety Science 60:87−94

doi: 10.1016/j.ssci.2013.07.005
[15]

Shiwakoti N, Sarvi M, Burd M. 2014. Using non-human biological entities to understand pedestrian crowd behaviour under emergency conditions. Safety Science 66:1−8

doi: 10.1016/j.ssci.2014.01.010
[16]

Zhang J, Klingsch W, Rupprecht T, Schadschneider A, Seyfried A. 2011. Empirical study of turning and merging of pedestrian streams in T-junction. arXiv1112.5299

doi: 10.48550/arXiv.1112.5299
[17]

Guo R. 2014. Simulation of spatial and temporal separation of pedestrian counter flow through a bottleneck. Physica A: Statistical Mechanics and Its Applications 415:428−39

doi: 10.1016/j.physa.2014.08.036
[18]

Hoogendoorn SP, Daamen W. 2005. Pedestrian behavior at bottlenecks. Transportation Science 39:147−59

doi: 10.1287/trsc.1040.0102
[19]

Nagai R, Fukamachi M, Nagatani T. 2006. Evacuation of crawlers and walkers from corridor through an exit. Physica A: Statistical Mechanics and Its Applications 367:449−60

doi: 10.1016/j.physa.2005.11.031
[20]

Liao W, Tordeux A, Seyfried A, Chraibi M, Drzycimski K, et al. 2016. Measuring the steady state of pedestrian flow in bottleneck experiments. Physica A: Statistical Mechanics and Its Applications 461:248−61

doi: 10.1016/j.physa.2016.05.051
[21]

Rahman K, Ghani NA, Kamil AA, Mustafa A, Kabir Chowdhury MA. 2013. Modelling pedestrian travel time and the design of facilities: A queuing approach. PLoS One 8:e63503

doi: 10.1371/journal.pone.0063503
[22]

Vermuyten H, Beliën J, de Boeck L, Reniers G, Wauters T. 2016. A review of optimisation models for pedestrian evacuation and design problems. Safety Science 87:167−78

doi: 10.1016/j.ssci.2016.04.001
[23]

Li D, Han B. 2015. Behavioral effect on pedestrian evacuation simulation using cellular automata. Safety Science 80:41−55

doi: 10.1016/j.ssci.2015.07.003
[24]

D’Ariano A, Pacciarelli D, Pranzo M. 2008. Assessment of flexible timetables in real-time traffic management of a railway bottleneck. Transportation Research Part C: Emerging Technologies 16:232−45

doi: 10.1016/j.trc.2007.07.006
[25]

Yuhaski SJ, Smith JM. 1989. Modeling circulation systems in buildings using state dependent queueing models. Queueing Systems 4:319−38

doi: 10.1007/BF01159471
[26]

Gosavi HD, Smith JM. 1997. An algorithm for sub-optimal routeing in series-parallel queueing networks. International Journal of Production Research 35:1413−30

doi: 10.1080/002075497195399
[27]

Kerbachea L, MacGregor Smith J. 1987. The generalized expansion method for open finite queueing networks. European Journal of Operational Research 32:448−61

doi: 10.1016/s0377-2217(87)80012-7
[28]

Osorio C, Bierlaire M. 2009. An analytic finite capacity queueing network model capturing the propagation of congestion and blocking. European Journal of Operational Research 196:996−1007

doi: 10.1016/j.ejor.2008.04.035
[29]

Hoogendoorn SP, Daamen W, Bovy PHL. 2003. Microscopic pedestrian traffic data collection and analysis by walking experiments. Pedestrian and evacuation dynamics 2003, Greenwich, London, 20-22 Aug 2003. London: CMS Press. pp. 89–100.
[30]

Liang M, Xu J, Jia L, Qin Y. 2020. An improved model of passenger merging in a Y-shaped passage. Physica A: Statistical Mechanics and Its Applications 540:123233

doi: 10.1016/j.physa.2019.123233