Coordinated scheduling model for intermodal transit hubs based on GI/M^K/1 queuing system

Abstract

Coordinated scheduling of multimode plays a pivotal role in the rapid gathering and dissipating of passengers in transport hubs. Based on the survey data, the whole-day reaching time distribution at transfer points of passengers from the dominant mode to the connecting mode was achieved. A GI/M^K/1 bulk service queuing system was constituted by putting the passengers’ reaching time distribution as the input and the connecting mode as the service institution. Through queuing theory, the relationship between average queuing length under steady-state and headway of the connecting mode was achieved. By putting the minimum total cost of system as optimization objective, the headway as decision variable, a coordinated scheduling model of multimode in intermodal transit hubs was established. At last, a dynamic scheduling strategy was generated to cope with the unexpected changes of the dominant mode. The instance analysis indicates that this model can significantly reduce passengers’ queuing time by approximately 17% with no apparently increase in departure frequency, which provides a useful solution for the coordinated scheduling of different transport modes in hubs.

Keywords

traffic engineering / coordinated scheduling / queuing theory / intermodal transit hub / headway

References

[1] BookbinderJ H, DesiletsA. Transfer optimization in a transit network [J]. Transportation Science, 1992, 26(2): 106-118

[2] EberleinX J, WilsonN H M, BernsteinD. The holding problem with real-time information available [J]. Transportation Science, 2001, 35(1): 1-18

[3] CederA, GolanyB, TalO. Creating bus timetables with maximal synchronization [J]. Transportation Research Part A: Policy and Practice, 2001, 35(10): 913-928

[4] NgamchaiS, LovellD J. Optimal time transfer in bus transit route network design using a genetic algorithm [J]. Journal of Transportation Engineering, 2003, 129(5): 510-521

[5] HickmanM D. An analytic stochastic model for the transit vehicle holding problem [J]. Transportation Science, 2001, 35(3): 215-237

[6] ChungE H, ShalabyA. Development of control strategy for intermodal connection protection of timed-transfer transit routes [J]. Transportation Research Record: Journal of the Transportation Research Board, 2007, 2006(1): 3-10

[7] HadasY, CederA. Optimal coordination of public-transit vehicles using operational tactics examined by simulation [J]. Transportation Research Part C: Emerging Technologies, 2010, 18(6): 879-895

[8] WangMengAnalysis of passenger-flow organization model of comprehensive passenger hubs [D], 2011BeijingBeijing Jiaotong University

[9] LeeK K T, SchonfeldP. Optimal slack time for timed transfers at a transit terminal [J]. Journal of Advanced Transportation, 1991, 25(3): 281-308

[10] SivakumaranK, LiY-w, CassidyM J, MadanatA. Cost-saving properties of schedule coordination in a simple trunk-and-feeder transit system [J]. Transportation Research Part A: Policy and Practice, 2012, 46(1): 131-139

[11] ChowhuryM S, ChienS I J. Joint optimization of bus size, headway, and slack time for efficient timed transfer [J]. Transportation Research Record: Journal of the Transportation Research Board, 2011, 2218(1): 48-58

[12] DessoukyM, HallR, NowrooziA, MourikasK. Bus dispatching at timed transfer transit stations using bus tracking technology [J]. Transportation Research Part C: Emerging Technologies, 1999, 7(4): 187-208

[13] DessoukyM, HallR, ZhangL, SinghA. Real-time control of buses for schedule coordination at a terminal [J]. Transportation Research Part A: Policy and Practice, 2003, 37(2): 145-164

[14] ChungE H. Transfer coordination model and real-time strategy for inter-modal transit services [D]. Toronto: University of Toronto, 2009

[15] CluettC, JenqJ H, SaitoB M. Utah transit authority’s connection protection system: Perceptions of riders and operators [J]. Journal of Public Transportation, 2005, 8(3): 73

[16] MedhiJStochastic models in queueing theory [M], 2002Salt Lake CityAcademic Press

[17] CohenJ WThe single server queue [M], 2012AmsterdamElsevier