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題名:鐵路列車連鎖延滯之模擬模式構建與應用
作者:劉昭榮
作者(外文):Liu, Jau-Rong
校院名稱:國立交通大學
系所名稱:交通運輸研究所
指導教授:黃承傳
學位類別:博士
出版日期:2011
主題關鍵詞:鐵路系統連鎖延滯初始延滯運轉調度策略Railway systemKnock-on delayFirst delayTimetable recovery strategy
原始連結:連回原系統網址new window
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鐵路系統容量不足往往是導致列車延滯之主因,尤其在初始延滯(first delay)發生後,後續所引發的連鎖延滯(knock-on delay)擴散效應對列車正常營運之影響甚大,因此欲確保系統之可靠度及服務品質,快速有效地降低連鎖延滯一直是重要課題。為有效釐清造成連鎖延滯之複雜因素及其交互作用,本研究依據臺鐵系統之運轉特性構建一模擬模式用以推估連鎖延滯,並以臺鐵西部幹線北部路段為案例,分析連鎖延滯之各種相關問題。
本研究經蒐集臺鐵七堵─樹林路段之營運資料驗證模式的合理性後,續針對不同初始延滯程度衍生之連鎖延滯擴散,及不同運轉調度策略(timetable recovery strategy)對連鎖延滯降低進行系統分析,初步發現連鎖延滯有往下游路段擴散,並呈非線性遞增之趨勢,且各種運轉調度策略對連鎖延滯均有明顯降低效果等現象。故本研究進而分別針對列車密度、初始延滯及運轉調度策略對連鎖延滯之影響及其整體交互作用影響進行分析,並以迴歸分析方法構建列車連鎖延滯與該三項因子間之指數關係函數,以作為估算連鎖延滯的簡便工具。另為利了解初始延滯發生區位、持續時間及運轉調度策略對連鎖延滯之影響,本研究亦進行其關聯分析。由研究結果顯示,若初始延滯發生之區位愈靠近上游路段,則連鎖延滯亦將愈大,而運轉調度策略對於降低連鎖延滯之效果也愈佳。
此外,鑑於影響連鎖延滯之部分關鍵因素具有隨機特性,故為確實反映臺鐵列車實際運轉因初始延滯發生後所產生之連鎖延滯特性,及深入探討產生連鎖延滯之班表穩定度問題,本研究更進一步分析站間運轉時間及停站時間之隨機特性,除彙整七堵─新竹路段對號列車及通勤電聯車之站間運轉時間資料,另依尖、離峰時段分開彙整停站時間之隨機資料,並將其納入模擬模式推估連鎖延滯。研究結果顯示,無論就所有車站或二端末車站(七堵及新竹站)而言,其尖峰或離峰時段之連鎖延滯模擬結果皆會接近一定值。本研究所提出之分析架構及內容,除可有效釐清連鎖延滯關鍵影響因素及程度,所構建之模擬模式更可作為相關改善策略之分析工具。研究成果可作為後續營運單位排班規劃、系統可靠度分析及服務品質改善之參考。
Train delays of a railway system are affected by many factors and one of the most important factors is insufficient line capacity. Once a first delay occurs, the delay propagation (i.e., knock-on delay) always interrupts train operation. Thus, how to promptly reduce the knock-on delays becomes an important issue for providing reliable timetable and high quality of service. In order to clarify the impacts of these complicated factors and their interactions on knock-on delay, this research develops a comprehensive simulation model to estimate knock-on delays, and a rail section from northern area of Taiwan railway system is selected for case study.
This research first collects real data from the section of Cidu to Shulin of Taiwan railway system to verify and validate the model. The impacts on knock-on delays of different first delays and timetable recovery strategies are then evaluated. The results show that knock-on delay propagates toward downstream sections when a first delay occurs, and the knock-on delay increases nonlinearly toward downstream sections. In addition, timetable recovery strategies are demonstrated to have significant impacts on the reduction of knock-on delays. Based on the simulation results of the case study, regression analyses are employed to calibrate the relationships between knock-on delays and three key factors, which are train density, first delay and timetable recovery strategy. The regression models indicate that the relationship between knock-on delay and these three key factors conforms to an exponential function. This research also explores the effects on knock-on delays of different first delay locations and recovery strategies. The main findings are as follows: (1) the closer that the first delay occurs at upstream section, the greater the knock-on delays at all stations and two end stations are; (2) the effects of timetable recovery strategies are better in recovering to scheduled timetable when the first delay occurs at upstream section.
To clarify the stochastic nature of the key factors affecting knock-on delays and to evaluate timetable stability, this research also collects the running time and dwell time data of Cidu-Hsinchu section for express and commuter trains respectively for further analysis. The result shows that the knock-on delays at all stations and two end stations during peak and off-peak hours converge to constant values respectively. In summary, this research proposes a framework and a simulation model which can be applied to analyze the impacts on knock-on delay by all kinds of changes in infrastructures, operational situations and controlling strategies. It is expected that the results can be beneficial to timetable scheduling, system reliability analysis and service quality improvement.
中文部分
1.李治綱、陳朝輝、簡聰裕(民91),「捷運鐵路列車延滯事件發生後行車調度策略之模擬分析」,運輸計劃季刊,第31卷,第2期,頁299-322。
2.李治綱、鍾志成、林杜寰、張仕龍、張恩輔、陳一昌、張開國、吳熙仁(民98),「公共運輸之安全績效:臺灣鐵路管理局之個案分析」,運輸計劃季刊,第38卷,第4期,頁381~406。
3.邱戊吉(民99),應用Max-Plus代數分析鐵路時刻表穩定性,國立交通大學交通運輸研究所碩士論文。
4.交通部運輸研究所(民94),軌道容量研究-臺鐵系統容量模式之建構分析(一)。
5.交通部運輸研究所(民96),運輸系統容量分析暨應用研究─軌道系統(1/4)。
6.交通部運輸研究所(民97),運輸系統容量分析暨應用研究─軌道系統(2/4)。
7.交通部運輸研究所(民98),運輸系統容量分析暨應用研究─軌道系統(3/4)。
8.交通部運輸研究所(民100),軌道系統容量與可靠度分析研究(1/3)。
9.周斯畏(民91),物件導向系統分析與設計使用UML與C++,臺北市:全華科技圖書股份有限公司。
10.周學怡(民86),列車運行計畫之可靠性分析,國立成功大學交通管理科學研究所碩士論文。
11.黃哲旭(民85),捷運鐵路列車模擬模式之研究,國立成功大學交通管理科學研究所碩士論文。
12.黃範哲(民90),高速鐵路系統運轉整理之研究,國立成功大學交通管理科學研究所碩士論文。
13.黃承傳、劉昭榮(民100),「鐵路列車密度與初始延滯以及調度策略對連鎖延滯之影響分析」,運輸計劃季刊,第40卷,第1期,頁63-98。
14.謝興盛(民92),捷運列車延誤時班距調整模式之模擬分析-以臺北捷運中、高運量系統為例,國立成功大學交通管理科學研究所博士論文。
15.簡聰裕(民89),捷運系統運轉整理之研究,國立成功大學交通管理科學研究所碩士論文。
16.楊立安(民96),臺灣鐵路運轉整理之研究,國立高雄第一科技大學運籌管理系碩士論文。
17.陳朝輝(民97),應用物件導向模式技術於捷運系統運轉整理之模擬分析,國立成功大學交通管理科學研究所博士論文。
18.陳英相與張仁城(民86),鐵路運轉規章(含概要、大意),臺北,千華圖書出版事業有限公司。
19.張恩輔(民91),捷運系統運轉整理之模擬分析,國立成功大學交通管理科學研究所碩士論文。
20.賴勇成、李宗晏、劉牧阡、陳冠廷(民99),「臺鐵時刻表穩定度與效率評估」,第25屆中華民國運輸學會論文集。

英文部分
1.Barter, W. M. (1998), “Application of Computer Simulation to Rail Capacity Planning”, Computers in Railways VI, pp. 199-211.
2.Braalund, U., Lindberg, P.O., Nou, A. and Nilsson, J.E. (1998), “Railway timetabling using Lagrangian Relaxation”, Transportation Science, Vol. 32(4), pp.358-369.
3.Briggs, K. and Beck, C. (2007), “Modeling Train Delays with Q-exponential Functions”, Physica A: Statistical Mechanics and its Applications, Vol. 378, Issue 2, pp. 498-504.
4.Carey, M. (1999), “Ex ante Heuristic Measures of Schedule Reliability”, Transportation Research Part B, Vol. 33, pp. 473-494.
5.Carey, M. and Carville, S. (2000), “Testing Schedule Performance and Reliability for Train Stations”, Journal of the Operational Research Society, Vol. 51, pp. 666-682.
6.Carey, M. and Crawford, I. (2007), “Scheduling Trains on a Network of Busy Complex Stations”, Transportation Research Part B, Vol. 41, pp. 159-178.
7.Chakroborty, P. and Vikram, D. (2008), “Optimum Assignment of Trains to Platforms under Partial Schedule Compliance”, Transportation Research Part B, Vol. 42, pp. 169-184.
8.Chang, S. C. and Chung, Y. C. (2005), “From Timetabling to Train Regulation – A New Train Operation Model”, Information and Software Technology, Vol. 47, pp. 575-583.
9.Chang, Y. H., Yeh, C. H. and Shen, C. C. (2000), “A Multiobjective model for Passenger Train Services Planning: Applications to Taiwan’s High Speed Rail Line”, Transportation Research B, Vol. 34, pp.91-106.
10.Chen, B. and Harker, P.T. (1990), “Two-moment estimation of the delay on single-track rail lines with scheduled traffic”, Transportation Science, Vol. 24, No. 4, pp. 261-275.
11.Chen, C.H., Lee, C.K. and Chang, E.F. (2003), “Simulation Analysis on the Dispatching Operation of Rapid Rail Transit”, Journal of the Eastern Asia Society for Transportation Studies, V.5, pp323-338.
12.Cheng, Y. (1996), “Optimal train traffic rescheduling simulation by a knowledge-based system combined with critical path method,” Simulation Practice and Theory, Vol. 4, pp.399-413.
13.Cheng, Y. (1998), “Rule-based train traffic reactive simulation model,” Applied Artificial Intelligence, Vol.12, pp.5-27.
14.Corman, F., D’Ariano, A., Pacciarelli, D. and Pranzo, M. (2010), “A Tabu Search Algorithm for Rerouting Trains during Rail Operations”, Transportation Research Part B, Vol. 44, pp. 175-192.
15.EuROPE-TRIP (2000), Ferrovie dello Stato Spa - Divisione Infrastruttura, European Railways Optimisation Planning Environment - Transportation Railways Integrated Planning, Final Report, Roma Italy.
16.Fay, A. (2001), “A Fuzzy Petri Net approach to decision-making in case of railway track closures,” IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th, Vol.5, pp.2858-2863.

17.Ferreira, L. and Higgins, A. (1996), “Modelling Reliability of Train Arrival Times”, Journal of Transportation Engineering, Vol. 122, pp. 414-420.
18.Goverde, R.M.P. (2005), “Railway Timetable Stability Analysis Using Max-Plus System Theory”, Transportation Research Part B, Vol. 41, pp. 179–201.
19.Hansen, I. A. (2000), “Station Capacity and Stability of Train Operations”, Computers in Railways VII, pp. 809-816.
20.Hansen, I. A. and Pachl, J. (2008), Railway Timetable & Traffic: Analysis – Modelling – Simulation, Railway Gazette, Hamburg Germany.
21.Higgins, A., Kozan, E. and Ferreira L. (1995), “Modeling Delay Risks Associated with Train Schedules”, Transportation Planning and Technology, Vol. 19, Issue 2, pp. 89-108.
22.Higgins, A. and Kozan, E. (1998), “Modeling Train Delay in Urban Networks”, Transportation Science, Vol. 32, No.4, pp.346-357.
23.Huisman, T. and Boucherie, R. J. (2001), “Running Times on Railway Sections with Heterogeneous Train Traffic”, Transportation Research Part B, Vol. 35, pp. 271-292.
24.Hwang, C. C. and Liu, J. R. (2010), “A Simulation Model for Estimating Knock-on Delay of Taiwan Regional Railway”, Journal of the Eastern Asia Society for Transportation Studies, Vol.8, pp. 1082-1097.
25.Jong, J.C., Lin, T. H., Lee, C. K. and Hu, H. L. (2010), “The Analysis on Train Reliability of Taiwan High Speed Rail”, Proceedings of 12th COMPRAIL Conference, Wessex Institute of Technology, pp. 169-180.
26.Mattsson, L. G. (2004), “Train Service Reliability - A Survey of Methods for Deriving Relationships for Train Delays”, Written at the Request of the Swedish Institute for Transport and Communications Analysis, Stockholm Sweden.
27.Middelkoop, D. and Bouwman, M. (2000), “Train Network Simulator for Support of Network Wide Planning of Infrastructure and Timetables”, Computers in Railways VII, pp. 267-276.
28.Middelkoop, D. and Bouwman, M. (2002), “Testing the Stability of the Rail Network”, Computers in Railways VIII, pp. 995-1002.
29.Missikoff, M. (1998), “An Object-oriented Approach to an Information and Decision Support System for Railway Traffic Control,” Engineering Applications of Artificial Intelligence, Vol.11, pp.25-40.
30.Murray, A. T. and Grubesic, T. H. (2007), Critical Infrastructure Reliability and Vulnerability, Springer Berlin Heidelberg.
31.Nelson, D. and O'Neil, K., (2000) “Commuter Rail Service Reliability On-Time Performance and Causes for Delays”, Transportation Research Record, Vol. 1704, pp. 42-50.
32.Nie, L. and Hansen, I. A. (2005), “System Analysis of Train Operations and Track Occupancy at Railway Stations”, European Journal of Transport and Infrastructure Research, Vol. 5, No. 1, pp. 31-54.
33.O’Dell, S. and Wilson, N.H.M. (1999), “Optimal Real-time Control Strategies for Rail Transit Operations during Disruption”, In Computer Aided Transit Scheduling, Wilson, N.H.M. (Ed.), pp.299-323, Springer-Verlag.
34.Olsson, Nils, O.E. and Haugland, H. (2004), “Influencing Factors on Train Punctuality—Results from Some Norwegian Studies”, Transport Policy 11, pp. 387-397.
35.Parkinson, T. (1996), “Rail Transit Capacity”, Transportation Research Board, National Academy Press.
36.Rebreyend, P. (2005), “DisTrain: A simulation tool for train dispatching,” Proceedings of 8th International IEEE Conference on Intelligence Transportation Systems Vienna, Austria, pp.801-806.
37.Rietveld, P., Bruinsma, F. R. and Van Vuuren, D. J. (2001), “Coping with Unreliability in Public Transport Chains: a case for the Netherlands”, Transportation Research Part A, Vol. 35, 539-559.
38.Vromans, M. J., Dekker, R. and Kroon, L. G. (2006), “Reliability and Heterogeneity of Railway Services”, European Journal of Operational Research, Vol. 172, pp. 647-665.
39.Won, H.S., Kyung, S. C. and Sung, M. R. (2001), “An Analysis of Railroad Skip Stop System without Siding Track”, 9th World Conference on Transport Research.
40.Yuan, J. and Hansen, I. A. (2007), “Optimizing Capacity Utilization of Stations by Estimating Knock-on Train Delays”, Transportation Research Part B, Vol. 41, pp. 202-217.
41.Zhu, P. and Schnieder E. (2000), “Determining Traffic Delays through Simulation”, In Computer-Aided Scheduling of Public Transport, Braunschweig, Germany, pp387-397.

 
 
 
 
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