Subway Timetable Adjusting Method Research of Bi-directional Trains Arriving at a Station Asynchronously

Metro transmits, as the backbone of urban public transit, plays an important role in alleviating congested traffic and shaping low-carbon and comfortable trip mode. With the rapid development of urban rail transit, the traffic of the city cannot be separated from the subway; however, large passenger flow triggers heavy traffic accident easily and reduces the degree of comfort greatly, especially when up and down trains arriving at the same station simultaneously. To implement urban railway transit system optimization and to achieve the goal of up and down trains arrive at a station asynchronously, situations of trains arriving at the platform are studied, and a quantitative analysis of different time periods and different types of platforms are completed. The definition of the train conflict time of arriving at a station simultaneously is given. Through the derivation and calculation of the total use of the subway conflict time, to identify the key variables that affect the conflict time, a solution of using greedy algorithm to adjust conflict time is proposed. Simulation through Visual C++ platform demonstrates that the algorithm can provide optimal railway timetables while satisfying operational constraints. Comparative analysis of the results showed that: if passenger flow is considered, departure time, interval time and dwell time are invariant, only adjusting the morning peak-hours is 19.76 % superior than the unadjusted state, while adjusting the morning and evening peak-hours is 34.85 % prior. The models can be further expanded to develop models and algorithms for estimating the conflict time of up and down trains and reduce the conflict time.

[1]  Kyung min Kim,et al.  A Mathematical Approach for Reducing the Maximum Traction Energy: The Case of Korean MRT Trains , 2010 .

[3]  Leo G. Kroon,et al.  A Variable Trip Time Model for Cyclic Railway Timetabling , 2003, Transp. Sci..

[4]  Roberto Cordone,et al.  Optimizing the demand captured by a railway system with a regular timetable , 2011 .

[5]  Michiel A. Odijk,et al.  A CONSTRAINT GENERATION ALGORITHM FOR THE CONSTRUCTION OF PERIODIC RAILWAY TIMETABLES , 1996 .

[6]  T Albrecht REDUCING POWER PEAKS AND ENERGY CONSUMPTION IN RAIL TRANSIT SYSTEMS BY SIMULTANEOUS TRAIN RUNNING TIME CONTROL , 2004 .

[7]  K. Nachtigall,et al.  Periodic Network Optimization with Different Arc Frequencies , 1996, Discret. Appl. Math..

[8]  Walter Ukovich,et al.  A Mathematical Model for Periodic Scheduling Problems , 1989, SIAM J. Discret. Math..

[9]  P. Toint On sparse and symmetric matrix updating subject to a linear equation , 1977 .

[10]  R.-L. Lin,et al.  Optimization of an MRT train schedule: reducing maximum traction power by using genetic algorithms , 2005, IEEE Transactions on Power Systems.

[11]  Keun-Ho Lee,et al.  An exhaustive method for characterizing the interconnect capacitance considering the floating dummy-fills by employing an efficient field solving algorithm , 2000, 2000 International Conference on Simulation Semiconductor Processes and Devices (Cat. No.00TH8502).

[12]  Xuesong Zhou,et al.  Stochastic Optimization Model and Solution Algorithm for Robust Double-Track Train-Timetabling Problem , 2010, IEEE Transactions on Intelligent Transportation Systems.

[13]  Hans van Maaren,et al.  Generation of classes of robust periodic railway timetables , 2006, Comput. Oper. Res..

[14]  Z. He,et al.  Research on Greedy Train Rescheduling Algorithm , 2009 .

[15]  Leon W P Peeters,et al.  Cyclic Railway Timetable Optimization , 2003 .

[16]  Zhenhuan He Research on Improved Greedy Algorithm for Train Rescheduling , 2011, 2011 Seventh International Conference on Computational Intelligence and Security.

[17]  Rommert Dekker,et al.  Stochastic Improvement of Cyclic Railway Timetables , 2006 .