轨道交通中网络瓶颈对列车能耗的影响
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摘要
在现代综合交通系统中,轨道交通扮演着重要的角色,而列车信号控制系统则是轨道交通系统中的中枢系统,保证着列车安全快速的运行。目前列车信号控制系统中有固定闭塞系统和移动闭塞系统。移动闭塞系统取消了固定闭塞系统的闭塞分区,这就极大地增加了线路上列车运行的密度,提高了轨道线路的通过能力,这就使移动闭塞成为列车信号控制系统的发展趋势。同时在移动闭塞系统中列车之间的相互作用也就更加明显,如果某列车出现延迟会对后续列车造成比固定闭塞更加严重的延迟影响。本文在分析轨道交通特点的基础上建立移动闭塞系统下在车站处的元胞自动机(CA)模型,并利用所建立的模型模拟讨论了轨道交通中列车运行的各种因素与能耗的关系。主要内容包括以下几个方面：
1.介绍了移动闭塞系统的相关理论,包括移动闭塞系统的提出、基本原理以及移动闭塞系统的优点和实际应用情况,并对元胞自动机的发展史,物理定义、组成单位以及特征进行了详细的阐述,详细介绍了元胞自动机模型在交通领域中的应用。
2.根据轨道交通中移动闭塞系统的特点建立考虑列车反应时间的元胞自动机模型。通过对列车最小追踪间隔时间与列车最大速度的理论值和模拟值的对比,验证了该模型的有效性。利用所建立的元胞自动机模型探讨轨道交通流的特性。讨论了列车运行的时空图以及列车速度与时间、位置的关系；继而分析了列车停站时间、列车反应时间以及列车最大速度对列车额外能耗的影响。
3.进一步建立采用惰行策略的元胞自动机模型,利用该元胞自动机模型模拟了移动闭塞系统下列车的运行,讨论了发车间隔对列车延迟的影响,在选取适当的发车间隔时间的基础上研究了初始延迟时间对总的延迟时间的影响以及对列车能耗的影响。最后分析了存在初始延迟时间的情况下,车站停留时间以及车辆最大速度对列车平均能耗的影响。
Nowadays, in the modern public transportation system, track transportation plays an important role and the train signal control system which ensures the safety and high speed of the train is the core of it. At present, the train signal systems include the fixed block system and the moving block system. The moving block system has abandoned the block section of the fixed block system, which has greatly increased the intensity of the trains and improved the capacity of the lines. It makes the moving block system become the developmental trend of the train signal control system. Meanwhile, the interaction of the trains becomes more obvious in the moving block system. Compared with the fixed block system, the delay of a train will have more serious impact on the following ones in the moving block system. In the paper, the author sets up a cellular automata model (CA) in the stations under the moving block system based on the analysis of the characteristics of the track transportation and discusses the relations between the aspects in the track train function and the energy consumption by using the model set up in the paper. The paper mainly includes the following three parts:
1. The author introduces the related theories of the moving block system including the origin, the basic theories, the advantages and the practical applications of the moving block system. The author also explains the development history, the physical definition, the basic units, the characteristics of the cellular automaton and its application in the traffic and transportation in details.
2. The author sets up the cellular automaton model under the consideration of the reaction time of the trains according to the characteristics of the moving block system in the track transportation. The validity of the model is tested through the comparison between the minimum time interval between trains spaced by automatic block signals and the theory value as well as the analog value of the maximum speed of the train. Under the help of the cellular automaton model, the features of the track transportation are explored and the relations among the speed, the time and locations are discusses. The impact of the station dwell time, the reaction time and the maximum speed of the train on the train additional energy consumption are analyzed.
3. The author further sets up the cellular automaton model under the use of coasting strategy. The author discusses the impact of the train time interval on the time delay based on the cellular automaton model function of the train under the moving block system. By choosing the appropriate departure interval, the author has studied the impact of the first time delay on the whole time delay and the train energy consumption. Finally, the author analyzed the impact of the station standing time and the maximum speed on the average energy consumption.
1.介绍了移动闭塞系统的相关理论,包括移动闭塞系统的提出、基本原理以及移动闭塞系统的优点和实际应用情况,并对元胞自动机的发展史,物理定义、组成单位以及特征进行了详细的阐述,详细介绍了元胞自动机模型在交通领域中的应用。
2.根据轨道交通中移动闭塞系统的特点建立考虑列车反应时间的元胞自动机模型。通过对列车最小追踪间隔时间与列车最大速度的理论值和模拟值的对比,验证了该模型的有效性。利用所建立的元胞自动机模型探讨轨道交通流的特性。讨论了列车运行的时空图以及列车速度与时间、位置的关系；继而分析了列车停站时间、列车反应时间以及列车最大速度对列车额外能耗的影响。
3.进一步建立采用惰行策略的元胞自动机模型,利用该元胞自动机模型模拟了移动闭塞系统下列车的运行,讨论了发车间隔对列车延迟的影响,在选取适当的发车间隔时间的基础上研究了初始延迟时间对总的延迟时间的影响以及对列车能耗的影响。最后分析了存在初始延迟时间的情况下,车站停留时间以及车辆最大速度对列车平均能耗的影响。
Nowadays, in the modern public transportation system, track transportation plays an important role and the train signal control system which ensures the safety and high speed of the train is the core of it. At present, the train signal systems include the fixed block system and the moving block system. The moving block system has abandoned the block section of the fixed block system, which has greatly increased the intensity of the trains and improved the capacity of the lines. It makes the moving block system become the developmental trend of the train signal control system. Meanwhile, the interaction of the trains becomes more obvious in the moving block system. Compared with the fixed block system, the delay of a train will have more serious impact on the following ones in the moving block system. In the paper, the author sets up a cellular automata model (CA) in the stations under the moving block system based on the analysis of the characteristics of the track transportation and discusses the relations between the aspects in the track train function and the energy consumption by using the model set up in the paper. The paper mainly includes the following three parts:
1. The author introduces the related theories of the moving block system including the origin, the basic theories, the advantages and the practical applications of the moving block system. The author also explains the development history, the physical definition, the basic units, the characteristics of the cellular automaton and its application in the traffic and transportation in details.
2. The author sets up the cellular automaton model under the consideration of the reaction time of the trains according to the characteristics of the moving block system in the track transportation. The validity of the model is tested through the comparison between the minimum time interval between trains spaced by automatic block signals and the theory value as well as the analog value of the maximum speed of the train. Under the help of the cellular automaton model, the features of the track transportation are explored and the relations among the speed, the time and locations are discusses. The impact of the station dwell time, the reaction time and the maximum speed of the train on the train additional energy consumption are analyzed.
3. The author further sets up the cellular automaton model under the use of coasting strategy. The author discusses the impact of the train time interval on the time delay based on the cellular automaton model function of the train under the moving block system. By choosing the appropriate departure interval, the author has studied the impact of the first time delay on the whole time delay and the train energy consumption. Finally, the author analyzed the impact of the station standing time and the maximum speed on the average energy consumption.
引文
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[12]K. P. Li, Z. Y. Gao and B. Ning. Cellular Automaton Model for Railway Traffic. Journal of Computational Physics.2005.209:179
[13]K. P. Li, Z. Y. Gao and B. Ning. Modelling the railway traffic using cellular automation model. International Journal Modern Physics C.2005.16:921
[14]周华亮,高自友,李克平.准移动闭塞系统的元胞自动机模型及列车延迟传播规律的研究[J].物理学报.2006.55(4)：1706—1710
[15]李峰,高自友,李克平.固定闭塞系统中列车流的特性分析.物理学报.2006.56(6)：3158—3165
[16]荀径,宁滨,李克平.网络条件下列车追踪模型及延迟传播的研究.物理学报.2007.56(9)：5158—5163
[17]肖巍,李克平.基于元胞自动机列车运行进路控制模型.科学技术与工程.2008.8(15)：4215—4220
[18]J. X. Cheng, P. G Howlett. Application of Critical velocities to the Minimisation of fuel consumption in the control of trains. Automatic.1992.28(1):165—169
[19]P. G. Howlett. Optimal strategies for the control of a train. Automatica.1996.32(4):519—532
[20]P. G Howlett, P. J. Pudney. Energy-Efficient Train Control[M].London.Springer.1995
[21]肖建.节省列车牵引能耗的最优操纵策略.现代节能.1994.10(4)：25—29
[22]金炜东,王自力,李崇维等.列车节能操纵优化方法研究.铁道学报.1997.19(6)：58—62
[23]王峰,刘海东等.列车节能运行的算法及实施技术研究.北方交通大学学报.2002.26(5)：13—18
[24]付印平,李克平.列车运行节能操纵优化方法研究.科学技术与工程.2009.9(5)：1337—1340
[25]I. A. Hansen, J. Pachl. Railway Timetable and Traffic:Analysis, Modelling and Simulation. Hamburg. Eurailpress.2008
[26]A. D'Ariano, T. Albrecht. Running Time Re-optimization During Real-time Timetable Perturbations. Southampton. Computers in Railways X. WIT Press
[27]M. Mazzarello, E. Ottaviani. A traffic management system for real-time traffic optimisation in railways. Transportation Research Part B.2007.41 (2):246—274
[28]T. Albrecht. The influence of anticipating train driving on the dispatching process in railway conflict situations. Network and Spatial Economics.2009.9:85—101.
[29]F. Corman, A. D'Ariano, D. Pacciarelli, M. Pranzo. Evaluation of green wave policy in real-time railway traffic management. Transportation Research Part C.2009.17(6):607—616
[30]汪希时,丁正庭,宁滨等.京沪线开发应用移动闭塞制度可行性研究——铁道信号部分.北方交通大学研究报告
[31]周华亮.轨道交通列车运行的元胞自动机模型及交通流特性研究.[硕士学位论文].北京.北京交通大学.2006
[32]E. F. Godd. Cellular Automata. New York. Academic Press.1968
[33]M. Gardner. The fantastic combination of John Conway's new solitaire game life. Scientific American.1970.220(4):120—123
[34]祝玉学,赵学龙(译).物理系统的元胞自动机模拟.北京.清华大学出版社.2003
[35]谢惠民.非线性科学丛书：复杂性与动力系统.上海：上海科技教育出版社.1994
[36]李才伟.元胞自动机及复杂系统的时空演化模拟.[博士学位论文].武汉.华中理工大学.1997
[37]H.Takeuchi, C. J. Goodman, S. Sone. Moving block signaling dynamics:performance measures and re-starting queued electric trains. IEE Proceedings of Electronics Power Application. 2003.150(4):483—492
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