|
|
Scheduling of high-speed rail traffic based on discrete-time movement model |
Sun Ya-Hua (孙亚华), Cao Cheng-Xuan (曹成铉), Xu Yan (许琰), Wu Chao (吴超) |
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China |
|
|
Abstract In this paper, a new simulation approach for solving the mixed train scheduling problem on the high-speed double-track rail line is presented. Based on the discrete-time movement model, we propose control strategies for mixed train movement with different speeds on a high-speed double-track rail line, including braking strategy, priority rule, travelling strategy, and departing rule. A new detailed algorithm is also presented based on the proposed control strategies for mixed train movement. Moreover, we analyze the dynamic properties of rail traffic flow on a high-speed rail line. Using our proposed method, we can effectively simulate the mixed train schedule on a rail line. The numerical results demonstrate that an appropriate decrease of the departure interval can enhance the capacity, and a suitable increase of the distance between two adjacent stations can enhance the average speed. Meanwhile, the capacity and the average speed will be increased by appropriately enhancing the ratio of faster train number to slower train number from 1.
|
Received: 13 March 2013
Revised: 08 May 2013
Accepted manuscript online:
|
PACS:
|
05.40.-a
|
(Fluctuation phenomena, random processes, noise, and Brownian motion)
|
|
05.60.-k
|
(Transport processes)
|
|
89.40.Bb
|
(Land transportation)
|
|
Fund: Project supported by the National Basic Research Program of China (Grant No. 2012CB725400), the National Natural Science Foundation of China (Grant No. 71131001-1), and the Research Foundation of State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, China (Grant Nos. RCS2012ZZ001 and RCS2012ZT001). |
Corresponding Authors:
Cao Cheng-Xuan
E-mail: cxcao@bjtu.edu.cn
|
Cite this article:
Sun Ya-Hua (孙亚华), Cao Cheng-Xuan (曹成铉), Xu Yan (许琰), Wu Chao (吴超) Scheduling of high-speed rail traffic based on discrete-time movement model 2013 Chin. Phys. B 22 120501
|
[1] |
Kraft E R 1987 Transp. Res. Forum 28 263
|
[2] |
van Dijk N M 1993 Oper. Res. Proceedings 523
|
[3] |
Iyer R J and Ghosh S 1995 IEEE Tran. Vehicle Tech. 44 180
|
[4] |
Chang C and Sim S S 1997 IEE Proc.-Electr. Power Appl. 144 65
|
[5] |
Howlett P G and Cheng J 1997 J. Aust. Math. Soc. B 38 388
|
[6] |
Howlett P G 2000 Ann. Oper. Res. 98 65
|
[7] |
Huisman T and Boucherie R J 2001 Transp. Res. Part B 35 271
|
[8] |
Chang C and Xu D 2002 IEE Proc.-Electr. Power Appl. 147 206
|
[9] |
Ning B, Li K and Gao Z 2005 Int. J. Mod. Phys. C 16 1793
|
[10] |
Effati S and Roohparvar H 2006 Appl. Math. Comput. 175 1415
|
[11] |
Szpigel B 1973 Opns. Res. 72 343
|
[12] |
Sauder L and Westerman W M 1983 Interf. 13 24
|
[13] |
Higgins A, Kozan E and Ferreira L 1996 Transp. Res. Part B 30 147
|
[14] |
Dorfman M J and Medanic J 2004 Transp. Res. Part B 38 81
|
[15] |
Li K and Gao Z 2006 Int. J. Mod. Phys. C 17 1349
|
[16] |
Li K and Gao Z 2007 Simul. Model. Pract. Th. 15 1156
|
[17] |
Li K, Gao Z and Yang L 2007 Sci. China Ser. E 50 765
|
[18] |
Li F, Gao Z, Li K and Yang L 2008 Transp. Res. Part B 42 1008
|
[19] |
Yang L, Li F, Gao Z and Li K 2010 Chin. Phys. B 19 100510
|
[20] |
Wang M, Zeng J, Qian Y, Li W, Yang F and Jia X 2012 Chin. Phys. B 21 070502
|
[21] |
Zhou H, Gao Z and Li K 2006 Acta Phys. Sin. 55 1706 (in Chinese)
|
[22] |
Xun J, Ning B and Li K 2007 Acta Phys. Sin. 56 5158 (in Chinese)
|
[23] |
Wang H and Qian Y 2008 Rail Transp. Econ. 30 82 (in Chinese)
|
[24] |
Xu Y, Cao C, Li M and Luo J 2012 Commun. Theor. Phys. 58 847
|
No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
Altmetric
|
blogs
Facebook pages
Wikipedia page
Google+ users
|
Online attention
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
View more on Altmetrics
|
|
|