As one kind of highest hierarchy node on the network, the transfer scheme of high-speed railway hub timetable should be studied at priority. After defining the problem that optimizing transfer scheme of timetable at high-speed railway hub, this paper proposes time adjusting strategy and platform adjusting strategy to optimize the problem, of which the first strategy introduces a FUZZY set of reasonable time range to reduce the possible train conflicts at adjacent stations on the network, and the second strategy helps to use different transfer time to match the arrival and departure of trains. Then, an optimization model of timetable based on passenger transfer is established with the minimized invalid transfer waiting time for passenger and train conflicts at adjacent stations as the objective function. The model is solved by the above two strategies in MATLAB software. Finally, the rationality and effectiveness of this model are verified, taking Shanghai Hongqiao Station as an example.
GoverdeR.M.P., Synchronization Control of Scheduled Train Services to Minimize Passenger Waiting Times, Ms. D. Dissertation, December 1998.
2.
ZhouP.F., HanB.M. and ZhangQ., High-Speed Railway Passenger Node Classification Method and Train Stops Scheme, Applied Mechanics and Materials505 (2014), 632–636.
3.
ZhangX., LiL., Le VineS. and LiuX., An integrated pricing/planning strategy to optimize passenger rail service with uncertain demand, Journal of Intelligent & Fuzzy Systems36 (2019), 435–448.
4.
ChenC., XiangB., LiuY. and WangK., A Secure Authentication Protocol for Internet of Vehicles, IEEE Access7 (2019), 12047–12057.
5.
TerrinJ.-J., High speed railway hubs in European medium-sized cities: The case of the ENTER. HUB network, The Open Transportation Journal10 (2016).
6.
ChenD., LvM. and NiS., Optimization model and algorithm for departure time domain of passenger trains based on conflicts detecting and node important degree, Advanced Science Letters11 (2012), 722–725.
7.
ChenD., NiS., XuC.’a. and JiangX., Optimizing the draft passenger train timetable based on node importance in a railway network, Transportation Letters11 (2019), 20–32.
8.
SmetsM., Transfers, nodes, hubs and places: Different forms of intermodal exchange. In Huburbs Seminar, 2011.
9.
FleurentC., LessardR. and SéguinL., Transit Timetable Synchronization: Evaluation and Optimization 2004.
10.
HuangQ., Research on Optimization of Passenger Train Connection Scheme in Large Transfer Station, Ms.D. Dissertation, Southwest Jiaotong University, 2018.
11.
ParkM.-K., Traffic regulation algorithm for metro lines with time interval deviations, Journal of Intelligent & Fuzzy Systems31 (2016), 1001–1008.
12.
RappM.H. and GehnerC.D., Innovations in transportation system planning, National Academy of Sciences, Washington, 1976.
13.
CederA., HadasY., McIvorM. and AngA., Transfer Synchronization of Public Transport Networks, Transportation Research Record2350 (2013), 9–16.
14.
WongR.C.W., YuenT.W.Y., FungK.W. and LeungJ.M.Y., Optimizing Timetable Synchronization for Rail Mass Transit, Transportation Science42 (2008), 57–69.
15.
LiebchenC., Periodic Timetable Optimization in Public Transport. In Operations Research Proceedings 2006, K.-H. Waldmann and U.M. Stocker, eds. Springer Berlin Heidelberg, Berlin, Heidelberg (2007), 29–36.
16.
WuY., TangJ., YuY. and PanZ., A stochastic optimization model for transit network timetable design to mitigate the randomness of traveling time by adding slack time, Transportation Research Part C: Emerging Technologies52 (2015), 15–31.
17.
GuoX., SunH., WuJ., JinJ., ZhouJ. and GaoZ., Multiperiod-based timetable optimization for metro transit networks, Transportation Research Part B: Methodological96 (2017), 46–67.
18.
SunB., WeiM., YangC. and CederA., Solving demand-responsive feeder transit service design with fuzzy travel demand: A collaborative ant colony algorithm approach, Journal of Intelligent & Fuzzy Systems37 (2019), 3555–3563.
19.
ParboJ., NielsenO.A. and PratoC.G., User perspectives in public transport timetable optimization, Transportation Research Part C: Emerging Technologies48 (2014), 269–284.
20.
SchollS., Customer-oriented line planning, Ms.D. Dissertation, Technology University of Kaiserslautern, 2005.
NachtigallK. and VogetS., Minimizing waiting times in integrated fixed interval timetables by upgrading railway tracks, European Journal of Operational Research103 (1997), 610–627.
23.
ShiF., ZhouZ., YaoJ. and HuangH., Incorporating transfer reliability into equilibrium analysis of railway passenger flow, European Journal of Operational Research220 (2012), 378–385.
24.
KnoppersP. and MullerT., Optimized Transfer Opportunities in Public Transport, Transportation Science29 (1995), 101–105.
25.
VansteenwegenP. and van OudheusdenD., Developing railway timetables which guarantee a better service, European Journal of Operational Research173 (2006), 337–350.
26.
VansteenwegenP. and van OudheusdenD., Decreasing the passenger waiting time for an intercity rail network, Transportation Research Part B: Methodological41 (2007), 478–492.
27.
ChenD., NiS., XuC.’a., LvH. and WangS., High-Speed Train Stop-Schedule Optimization Based on Passenger Travel Convenience, Mathematical Problems in Engineering2016 (2016).
28.
FanB., RobertsC. and WestonP., A comparison of algorithms for minimising delay costs in disturbed railway traffic scenarios, Journal of Rail Transport Planning & Management2 (2012), 23–33.
29.
GoverdeR.M.P., Improving Punctuality and Transfer Reliability by Railway Timetable Optimization, December 1999.
