Abstract
It might be assumed that a train should run as fast as possible to finish its trip on railway section in the shortest time. However, because of the complex operation constraints, such as speed limits, slopes, and interactions among trains, it is a difficult work to determine an optimal speed profile for a train under the consideration of saving time. This paper develops an efficient algorithm to generate the train speed profile with the minimum section trip time. Moreover, a discrete event model-based simulation approach is proposed to observe the traffic flow on single-track railways with speed limits and slopes in the moving block mode system. Extensive case studies are implemented to demonstrate the effectiveness of the proposed approach and investigate the influence that time headway and dwelling time bring to energy consumption and line clear time.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Albrecht AR, Howlett PG, Pudney PJ and Vu X (2013). Energy-efficient train control: From local convexity to global optimization and uniqueness. Automatica 49(10): 3072–3078.
Dorfman MJ and Medanic J (2004). Scheduling trains on a railway network using a discrete event model of railway traffic. Transportation Research Part B: Methodological 38(1): 81–98.
Howlett PG (1996). Optimal strategies for the control of a train. Automatica 32(4): 519–532.
Howlett PG and Cheng J (1997). Optimal driving strategies for a train on a track with continuously varying gradient. The Journal of the Australian Mathematical Society. Series B. Applied Mathematics 38: 388–410.
Howlett PG and Pudney PJ (1995). Energy-efficient train control. Springer Press: London.
Howlett PG, Pudney PJ and Vu X (2009). Local energy minimization in optimal train control. Automatica 45: 2692–2698.
Ishikawa K (1968). Application of optimization theory for bounded state variable problems to the operation of trains. Bulletin of JSME 11(47): 857–865.
Ke BR, Chen MC and Lin CL (2009). Block-layout design using MAX-MIN ant system for saving energy on mass rapid transit systems. IEEE Transactions on Intelligent Transportation Systems 10(2): 226–235.
Li KP and Fan HQ (2010). The relationship between energy consumption and train delay in railway traffic. Chinese Physics B 19(10): 100511.
Li KP and Guan LJ (2009). Simulating train movement in railway traffic using a car-following model. Chinese Physics B 18(6): 2200–2204.
Li F, Gao ZY, Li KP and Yang LX (2008). Efficient scheduling of railway traffic based on global information of train. Transportation Research Part B: Methodological 42(10): 1008–1030.
Su S, Li X, Tang T and Gao ZY (2013). A subway train timetable optimization approach based on energy-efficient operation strategy. IEEE Transactions on Intelligent Transportation Systems 14(2): 883–893.
Xu XM, Li KP and Yang LX (2014a). Discrete event model-based simulation for train movement on a single-line railway. Chinese Physics B 23(8): 080205.
Xu XM, Li KP, Yang LX and Ye JJ (2014b). Balanced train timetabling on a single-line railway with optimized velocity. Applied Mathematical Modelling 38(3): 894–909.
Xu XM, Li KP and Li X (2015). Research on passenger flow and energy consumption in a subway system with fuzzy passenger arrival rates. Journal of Rail and Rapid Transit 229(8): 863–874.
Yang LX, Li F, Gao ZY and Li KP (2010). Discrete-time movement model of a group of trains on a rail line with stochastic disturbance. Chinese Physics B 19(20): 100510.
Yang LX, Li KP, Gao ZY and Li X (2012). Optimizing trains movement on a railway network. Omega: The International Journal of Management Science 40: 619–633.
Yang LX, Zhou XS and Gao ZY (2014). Credibility-based rescheduling model in a double-track railway network: A fuzzy reliable optimization approach. Omega: The International Journal of Management Science 48: 75–93.
Yang LX, Qi JG, Li SK and Gao Y (2016). Collaborative optimization for train scheduling and train stop planning on high-speed railways. Omega: The International Journal of Management Science 64: 57–76.
Yang X, Li X, Gao ZY, Wang HW and Tang T (2013). A cooperation scheduling model for timetable optimization in subway systems. IEEE Transactions on Intelligent Transportation Systems 14(1): 438–447.
Yang X, Li X, Ning B and Tang T (2016). A survey on energy-efficient train operation for urban rail transit. IEEE Transactions on Intelligent Transportation Systems 17(1): 2–13.
Yang X, Ning B, Li X and Tang T (2014). A two-objective timetable optimization model in subway systems. IEEE Transactions on Intelligent Transportation Systems 15(5): 1913–1921.
Ye JJ and Li KP (2013). Simulation optimization for train movement on a single-track railway. Chinese Physics B 22(5): 050205.
Ye JJ, Li KP and ** XM (2013). Simulating train movement in an urban railway based on an improved car-following model. Chinese Physics B 22(12): 120206.
Acknowledgments
The authors appreciate the valuable comments and suggestions of the referees and Editors. This research is supported by the National Natural Science Foundation of China (Nos. 71401008, 71301042, 71431003, 71571002), the Fundamental Research Funds for the Central Universities, Postdoctoral fund Project (Nos. 2013M530295, 2014T70588), and 1000 Plan for Foreign Talent (No. WQ20123400070).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Xu, X., Yang, L., Gao, Z. et al. Simulations for train traffic flow on single-track railways with speed limits and slopes. J Simulation 11, 346–356 (2017). https://doi.org/10.1057/s41273-016-0040-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1057/s41273-016-0040-y