铁路列车运行冲突检测与消解理论研究综述*

doi:10.16265/j.cnki.issn1003-3033.2018.S2.012

中国安全科学学报 ›› 2018, Vol. 28 ›› Issue (S2): 66-73.doi: 10.16265/j.cnki.issn1003-3033.2018.S2.012

铁路列车运行冲突检测与消解理论研究综述^*

文超^1,2,3 副教授, 杨雄¹, 黄平^1,3, 李忠灿¹, 唐优华^**1,2 高级工程师

1 西南交通大学综合交通大数据应用技术国家工程实验室,四川成都 610031;
2 西南交通大学综合交通运输国家地方联合工程实验室,四川成都 610031;
3 滑铁卢大学铁路研究中心,加拿大滑铁卢 N2L3G1

收稿日期:2018-09-30 修回日期:2018-11-15 出版日期:2018-12-30 发布日期:2020-11-11
通讯作者: **唐优华,男(1979—),浙江常山人,硕士,高级工程师,硕士生导师,主要从事综合交通大数据应用技术、交通运输安全信息技术方面的研究。E-mail:tyhctt@swjtu.cn。
作者简介:文超 (1984—),男,江西宜春人,工学博士,副教授,硕士生导师,主要从事铁路运输组织优化、交通大数据应用方面的研究。E-mail:wenchao@swjtu.cn。
基金资助:
国家自然科学基金资助(71871188, 61503311); 四川省科技厅应用基础研究项目(2018JY0567);
西南交通大学博士研究生创新基金资助(D-CX201827)。

Review on conflict detection and resolution on railway train operation

WEN Chao^1,2,3, YANG Xiong¹, HUANG Ping^1,3, LI Zhongcan¹, TANG Youhua^*1,2

1 National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University,Chengdu Sichuan 610031,China;
2 National United Engineering Laboratory of Integrated and Intelligent Transportation,Southwest Jiaotong University,Chengdu Sichuan 610031,China;
3 Railway Research Center,University of Waterloo, Waterloo N2L3G1,Canada

Received:2018-09-30 Revised:2018-11-15 Online:2018-12-30 Published:2020-11-11

摘要/Abstract

摘要： 为解决列车运行冲突管理问题,提升铁路运输组织效率,基于列车运行冲突基本概念,综述列车运行冲突检测及消解的传统数学模型及数据驱动模型;分析传统数学模型存在的不足,提出运用机器学习和深度学习方法研究列车运行冲突与检测问题的趋势。结果表明:传统数学模型大多基于抽象模型和简单假设,较难处理实践中的大尺度复杂问题,这些模型的试验结果与运输生产实践仍有较大差距;智能计算和机器学习数据驱动模型以列车运行实绩为基础,更加贴近运输生产及实践。

关键词: 铁路, 冲突检测, 冲突消解, 数据驱动, 列车运行实绩

Abstract: In order to solve the problem of train operation conflict management and improve the efficiency of railway transportation organization,the models and methods based ontraditional mathematics and driven by data on train operation conflict detection and resolution were reviewed based on the brief introduction of the basic concept of the train operation conflict. The shortcomings of traditional models were analyzed.The trend of using the machine learning and deep learning methods to detect and solve train operation conflicts were proposed.The results show that the traditional mathematical models can hardly process so much data in real-time, and there is a certain gap between experimental results from these models and actual operations. Intelligent computing and machine learning data driven model are based on train performance,and it is closer to transportation production and practice.

Key words: railway, train operation conflict detection, train operation conflict resolution, data-driven, train operation records

中图分类号:

X951

文超, 杨雄, 黄平, 李忠灿, 唐优华. 铁路列车运行冲突检测与消解理论研究综述^*[J]. 中国安全科学学报, 2018, 28(S2): 66-73.

WEN Chao, YANG Xiong, HUANG Ping, LI Zhongcan, TANG Youhua. Review on conflict detection and resolution on railway train operation[J]. China Safety Science Journal, 2018, 28(S2): 66-73.

参考文献

[1] 文超, 彭其渊, 文欢. 高速铁路列车运行冲突管理研究现状综述 [J]. 中国安全科学学报, 2010, 20(5): 140-150.
WEN Chao, PENG Qiyuan, WEN Huan. Review onconnict managemem of train operation on high-speed railway[J].China Safety Science Journal, 2010, 20(5): 140-150.
[2] 李云峰, 凌晓冬, 武小悦. 调度问题中的冲突研究 [J]. 网络与信息技术, 2007, 26(6): 41-43.
LI Yunfeng, LING Xiaodong, WU Xiaoyue. Research on conflict in scheduling problem[J]. Network and Information Technology, 2007, 26(6): 41-43.
[3] CHENG Y H, YANG L A. A fuzzy Petri nets approach for railway traffic control in case of abnormality: evidence from Taiwan railway system [J]. Expert Systems with Applications, 2009, 36(4): 8 040-8 048.
[4] GIULIARI M, PELLEGRINI F, SAVIO S. Moving block and traffic management in railway applications: the EU project COMBINE [J]. WIT Transactions on the Built Environment, 2000, 50: 11-20.
[5] BENDFELDT J, MOHR U, MULLER L. Railsys, a system to plan future railway needs [J]. WIT Transactions on The Built Environment, 2000, 50:249-255.
[6] WEN Chao, LI Jianguang, PENG Qiyuan, et al. Predicting high-speed train operation conflicts using workflow nets and triangular fuzzy numbers[J]. Proceedings of the Institution of Mechanical Engineers Part F-Journal of Rail and Rapid Transit, 2015, 229(3): 268-279.
[7] GOVERDE R M, MENG L. Advanced monitoring and management information of railway operations [J]. Journal of Rail Transport Planning & Management, 2011, 1(2): 69-79.
[8] KECMAN P, GOVERDE R M. Process mining of train describer event data and automatic conflict identification [J]. Computers in Railways XIII, WIT Transactions on the Built Environment, 2013,127:227-238.
[9] ŞAHIN İ. Railway traffic control and train scheduling based oninter-train conflict management [J]. Transportation Research Part B: Methodological, 1999, 33(7): 511-534.
[10] CORMAN F, D'ARIANO A, PACCIARELLI D, et al. Bi-objective conflict detection and resolution in railway traffic management [J]. Transportation Research Part C: Emerging Technologies, 2012, 20(1): 79-94.
[11] DOLLEVOET T, HUISMAN D, KROON L, et al. Delay management including capacities of stations [J]. Transportation Science, 2014, 49(2): 185-203.
[12] CHENG Y. Hybrid simulation for resolving resource conflicts in train traffic rescheduling [J]. Computers in Industry, 1998, 35(3): 233-246.
[13] D'ARIANO A.Innovative decision support system for railway traffic control[J].IEEE Intelligent Transportation Systems Magazine, 2009, 1(4): 8-16.
[14] RODRIGUEZ J. A constraint programming model for real-time train scheduling at junctions [J]. Transportation Research Part B: Methodological, 2007, 41(2): 231-245.
[15] MAREE L, FERREIRA L. Minimising the conflict between rail operations and infrastructure maintenance[C]. Proceedings of the Transportation and Traffic Theory in the 21^st Century, 2002: 63-74.
[16] 周磊山, 秦作睿. 列车运行计划与调整的通用算法及其计算机实现 [J]. 铁道学报, 1994, 16(3): 56-65.
ZHOU Leishan,QIN Zuorui.General algorithm and its realization on computer for the train operation adjustment system[J]. Journal of the China Railway Science, 1994, 16(3) :56-65.
[17] 周伟. 基于 DEDS 模型预测的高速列车群运行调整新方法研究 [D].西安: 西安交通大学, 1997.
ZHOU Wei. Research on the new method of operation adjustment for high-speed train group based on prediction by DEDS model[D]. Xi'an: Xi'an Jiaotong University, 1997.
[18] KRASEMANN J T. Design of an effective algorithm for fast response to the re-scheduling of railway traffic during disturbances [J]. Transportation Research Part C: Emerging Technologies, 2012, 20(1): 62-78.
[19] NARAYANASWAMI S, RANGARAJ N. Modelling disruptions and resolving conflicts optimally in a railway schedule [J]. Computers & Industrial Engineering, 2013, 64(1): 469-481.
[20] PEARSON C. Handbook of applied mathematics: selected results and methods [M]. New York: Springer Science & Business Media, 2012: 108-109.
[21] D'ARIANO A, PACCIARELLI D, PRANZO M. A branch and bound algorithm for scheduling trains in a railway network[J]. European Journal of Operational Research, 2007, 183(2): 643-657.
[22] TSANG C, HO T. The conflict resolution in connected railway junctions; proceedings of the computational methods in engineering and science[C]. Proceedings of the 9th International Conference EPMESC IX, 2003:25-28.
[23] 史峰, 黎新华, 秦进, 等. 单线列车运行调整的最早冲突优化方法 [J]. 中国铁道科学, 2005, 26(1): 106-113.
SHI Feng, LI Xinhua, QIN Jin,et al. The earliest conflict optimal method for train operation adjustment on single track railway[J].China Railway Science,2005,26(1):106-113.
[24] 陈军华, 张星臣, 俞文锦. 基于稳定性的列车运行计划编制模型与算法 [J]. 物流技术, 2009, 28(3): 70-72.
CHEN Junhua, ZHANG Xingchen, YU Wenjin. Study on timetable programming model and algorithm based on stability[J]. Logistics Technology, 2009, 28(3): 70-72.
[25] 文超, 彭其渊, 陈芋宏. 高速铁路列车运行冲突管理总论 [J]. 中国安全科学学报, 2010, 20(10): 8-12.
WEN Chao, PENG Qiyuan, CHEN Yuhong. Pandect of train operation conflict management of high-speed rail [J].China Safety Science Journal,2010, 20(10): 8-12.
[26] 文超, 彭其渊, 陈芋宏. 高速铁路列车运行冲突机理 [J]. 交通运输工程学报, 2012, 12(2): 119-126.
WEN Chao, PENG Qiyuan, CHEN Yuhong. Running conflict mechanism of high-speed train [J]. Journal of Traffic and Transportation Engineering, 2012, 12(2): 119-126.
[27] 文超, 彭其渊, 陈芋宏. 高速铁路列车运行冲突判定及其实现 [J]. 西南交通大学学报, 2012, 47(5): 867-873.
WEN Chao, PENG Qiyuan, CHEN Yuhong. Judgment of train operation conflict and its implementation for high-speed railway[J].Journal of Southwest Jiaotong University, 2012, 47(5): 867-873.
[28] 文超, 彭其渊, 陈芋宏. 高速铁路单个列车运行冲突消解研究 [J]. 科学技术与工程, 2013,13(10): 2 741-2 747.
WEN Chao, PENG Qiyuan, CHEN Yuhong. Train operation adjustment based on conflict resolution for high-speed rail[J].Science Technology and Engineering, 2013,13(10): 2 741-2 747.
[29] 郭竞文. 考虑冲突不确定性的高速铁路列车运行调整优化模型 [D].北京:北京交通大学, 2016.
GUO Jingwen. Train dispatching models with probabilistic train conflicts on a high-speed railway line [D].Beijing:Beijing Jiaotong University, 2016.
[30] 吴品. 基于分支定界的列车运行实时预测调度研究 [D].北京:北京交通大学, 2012.
WU Pin. Research about branch-and-bound-based real-time train predictive scheduling [D].Beijing:Beijing Jiaotong University, 2012.
[31] 王智慧. 高速列车运行冲突检测与实时调度的模型算法与仿真平台研究[D].北京:北京交通大学, 2017.
WANG Zhihui. Study on the model algorithm and simulation platform of conflict detection and real-time scheduling for high-speed railway train operations [D].Beijing:Beijing Jiaotong University, 2017.
[32] WEN Chao. Train operation conflict management research status of high-speed railways [J].Journal of Transportation Security, 2011, 4(3): 231-246.
[33] YUAN J, HANSEN I A. Optimizing capacity utilization of stations by estimating knock-on train delays [J]. Transportation Research Part B: Methodological, 2007, 41(2): 202-217.
[34] MEDEOSSI G, LONGO G, DE FABRIS S. A method for using stochastic blocking times to improve timetable planning [J]. Journal of Rail Transport Planning & Management, 2011, 1(1): 1-13.
[35] D'ADDIO G, MAZZUCCHELLI M, SAVIO S. Automatic conflict detection and resolution in metrorail systems: evaluation approach for MARCO EU project [J]. WIT Transactions on the Built Environment, 1998, 36: 461-470.
[36] GIANNETTONI M, SAVIO S. The European project COMBINE 2 to improve knowledge on future rail traffic management systems [J]. WIT Transactions on the Built Environment, 2004, 74: 695-704.
[37] HOOGHIEMSTRA J S, KROON L G, ODIJK M A, et al. Decision support systems support the search for win-win solutions in railway network design [J]. Interfaces, 1999, 29(2): 15-32.
[38] D'ARIANO A, PRANZO M, HANSEN I A. Conflict resolution and train speed coordination for solving real-time timetable perturbations [J]. IEEE Transactions on Intelligent Transportation Systems, 2007, 8(2): 208-222.
[39] TORIUMI S, TAGUCHI A, MATSUMOTO T. A model to simulate delay in train schedule caused by crowded passengers [J]. International Reginal Science Review, 2014, 37(2): 225-244.
[40] GOVERDE R M, DAAMEN W, HANSEN I A. Automatic identification of route conflict occurrences and their consequences [J]. Computers in Railways XI, 2008, 103: 473-482.
[41] DAAMEN W, GOVERDE R M, HANSEN I A. Non-discriminatory automatic registration of knock-on train delays [J]. Networks and Spatial Economics, 2009, 9(1): 47-61.
[42] SCHAEFER H, PFERDMENGES S. An expert system for real-time train dispatching [J]. WIT Transactions on The Built Environment, 1994, 7: 27-34.
[43] CHIANG T, HAU H, CHIANG H M, et al. Knowledge-based system for railway scheduling [J]. Data & Knowledge Engineering, 1998, 27(3): 289-312.
[44] ŞAHIN İ. Markov chain model for delay distribution in train schedules: assessing the effectiveness of time allowances [J]. Journal of Rail Transport Planning & Management, 2017, 7(3): 101-113.
[45] WEN Chao, LI Jianguang, PENG Qiyuan, et al. Predicting high-speed train operation conflicts using workflow nets and triangular fuzzy numbers [J]. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 2015, 229(3): 268-279.
[46] FAY A. A fuzzy knowledge-based system for railway traffic control [J]. Engineering Applications of Artificial Intelligence, 2000, 13(6): 719-729.
[47] MILINKOVIĆ S, MARKOVIĆ M, VESKOVIĆ S, et al. A fuzzy petri net model to estimate train delays [J]. Simul Model Pract Th, 2013, 33:144-157.
[48] ZHUANG He, FENG Liping, WEN Chao, et al. High-speed railway train timetable conflict prediction based on fuzzy temporal knowledge reasoning [J]. Engineering, 2016, 2(3): 366-373.
[49] KE B R, LIN C L, CHIEN H H, et al. A new approach for improving the performance of freight train timetabling of a single-track railway system [J]. Transportation Planning and Technology, 2014, 38(2): 238-264.
[50] 王鹏玲, 马磊, 王青元, 等. 基于 Petri 网列车群模型的列车运行冲突分析 [J]. 铁道学报, 2015, 37(3): 1-7.
WANG Pengling, MA Lei, WANG Qingyuan, et al. Analysis of train operation conflict based on train group model using Petri nets[J].Journal of the China Railway Society, 2015, 37(3): 1-7.
[51] CORMAN F, D'ARIANO A, HANSEN I A, et al. Optimal multi-class rescheduling of railway traffic [J]. Journal of Rail Transport Planning & Management, 2011, 1(1): 14-24.
[52] MAZZARELLO M, OTTAVIANI E. A traffic management system for real-time traffic optimisation in railways [J]. Transportation Research Part B: Methodological, 2007, 41(2): 246-274.
[53] D'ARIANO A, PRANZO M. An advanced real-time train dispatching system for minimizing the propagation of delays in a dispatching area under severe disturbances [J]. Netw Spat Econ, 2009, 9(1): 63-84.
[54] GOVERDE R, HANSEN I. TNV-Prepare: analysis of Dutch railway operations based on train detection data [J]. Computers in Railways, 2000, 7: 779-788.
[55] KECMAN P, GOVERDE R M. Process mining of train describer event data and automatic conflict identification [J]. Computers in Railways XIII, WIT Transactions on the Built Environment, 2013, 127: 227-238.
[56] ZHU T, MERA J M, SUAREZ B, et al. An agent-based support system for railway station dispatching [J]. Expert Systems with Applications, 2016, 61: 39-52.
[57] ZHU T, DE PEDRO J M M S. Railway traffic conflict detection via a state transition prediction approach [J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 18(5): 1 268-1 278.
[58] 铁信. 瑞士联邦铁路自适应列车运行调整系统ADL [J]. 现代城市轨道交通, 2018(2): 76.
TIE Xin. Adaptive train operation adjustment system (ADL) of Swiss federal railways[J]. Modern Urban Transit, 2018(2): 76.
[59] GHOFRANI F, HE Q, GOVERDE R M, et al. Recent applications of big data analytics in railway transportation systems: a survey [J]. Transportation Research Part C: Emerging Technologies, 2018, 90:226-246.

铁路列车运行冲突检测与消解理论研究综述^*

Review on conflict detection and resolution on railway train operation

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