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Yung-Cheng (Rex) Lai 14th September, 2012

Railway Technology Research Center, National Taiwan University. Development of the Evaluation Process and Models for Metro System Service Stability and Efficiency. Yung-Cheng (Rex) Lai 14th September, 2012 Presentation at the William W. Hay Railroad Engineering Seminar. Education.

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Yung-Cheng (Rex) Lai 14th September, 2012

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  1. Railway Technology Research Center, National Taiwan University Development of the Evaluation Process and Models for Metro System Service Stability and Efficiency Yung-Cheng (Rex) Lai 14th September, 2012 Presentation at the William W. Hay Railroad Engineering Seminar

  2. Education • National Taiwan University • B.A., Civil Engineering,2002 • University of Illinois at Urbana-Champaign • M.S., Civil & Environmental Engineering,2004 • University of Illinois at Urbana-Champaign • Ph.D., Civil & Environmental Engineering, 2008

  3. Research Interests • Interests: • Rail Transportation System • Railway Capacity Analysis (Service Performance & Evaluation) • Railway Operations and Management (Service Design) • Railway Safety • Techniques: • Math Programming • Heuristic or Decomposition Methods • Simulations

  4. Selected Research Topics on Rail Capacity • Capacity Evaluation & Computation • Impact of Key Capacity Factors (heterogeneity, priority, etc.) • Development of Rail Capacity Models • Capacity Utilization Efficiency & Reliability • Capacity Management & Investment • Decision Support Framework for Strategic Capacity Planning • High Speed Route Improvement Optimizer • Optimization of Train Network Routing with Heterogeneous Traffic Development of the Evaluation Process and Models to Determine Stability and Efficiency of Rail Service Plan

  5. Glass Cup Theory – Tradeoff between Efficiency and Stability • Metro System • Capacity(Metro Assets) • Used Capacity(Assets Utilization) • Available Capacity(Slacks) • System Failure(Disruption) • Glass • Size(Existing Resource) • Water Level(Resource Usage) • Empty Space(Buffer) • Vibration(Disruption) Higher Assets Utilization May Cause Lower System Stability Every System has its own “optimal balance”

  6. Evaluation Framework and Models System Characteristics MetroService Plan Historical Disturbance Data System Reliabilityand Maintainability Capacity Analysis Module UsedCapacity Reliability Module NormalCapacity DowngradedCapacity Reliability Distribution Maintainability Distribution Operational Stabilityand Efficiency Operational Stability and Efficiency Module SystemCharacteristics MetroService Plan Mean and Variance of the Expected Recovery Time Percentage of the Capacity Usage Operational Stability Operational Efficiency

  7. Operational Efficiency- Assets Utilization Efficiency Percentage of the Capacity Usage UsedCapacity NormalCapacity AvailableCapacity Normal Capacity UsedCapacity Percentage of the Capacity Usage

  8. Operational Stability- Expected Recovery Time RecoveryTime Traffic Flow (Trains/hour) RepairTime Normal Capacity Disturbed Trains Available Capacity Service Plan (headway) Disturbed Trains Used Capacity Downgraded Capacity T1 T4 T2 T3 T5 Time (Hour) Disturbance

  9. Expected Recovery Time = Risk in Capacity Utilization Metro Operation Is Not Always Under DisruptionsSystem Instability Is Introduced Through the Concept of Expected Value in Probability Theory ExpectedRecovery Time RecoveryTime Probability of System Failures Historical Disturbance Data Failure Rate Exposure (e.g. train-hours)

  10. Repair Time Is Related to the System Maintainability • Expected recovery time inherits uncertaintyfrom the stochastic properties of maintainability P(x) Maintainability Distribution Repair Time

  11. Evaluation Framework and Models System Characteristics MetroService Plan Historical Disturbance Data System Reliabilityand Maintainability Capacity Analysis Module UsedCapacity Reliability Module NormalCapacity DowngradedCapacity Reliability Distribution Maintainability Distribution Operational Stabilityand Efficiency Operational Stability and Efficiency Module SystemCharacteristics MetroService Plan Mean and Variance of the Expected Recovery Time Percentage of the Capacity Usage Operational Stability Operational Efficiency

  12. A Case Study is Conducted in a Metro System in Taiwan • Service Plan • Weekday service plan • Weekend service plan • System Characteristics • 20+ intermediate stations • 2 terminal stations • Historical Disturbance Data • Totally around 200recorded disturbances were collected for a ten-month period Inputs • System Characteristics • Service Plan • Historical Disturbance Data Outputs • Mean and Standard Deviation of Expected Recovery Time • Percentage of Capacity Usage Operational Stability and Efficiency Evaluation Model

  13. Disturbances Are Classified Qualitatively and Quantitatively in This Study • The classification of disturbances can facilitate the improvement of operational performance as it provides information about the sources of instability Communication Failure Has the Largest Mean Time to Repair (The Severest Primary Impact)

  14. Severer Primary Impact Is Not Necessary for Higher Incidence • The operational stability is composed of • Severityof disturbances (Maintainability) • Frequency of disturbances (Reliability) Although Communication Failure is the Severest Disturbances Among Others, Its Incidence is the Lowest. In Contrast, Train Failure Level 2 Has the Highest Incidence

  15. Overall Evaluation Results +210% +46% Substantial Reduction (>200%) in Operational Stability with Relatively Small Changes (46%) in Operational Efficiency

  16. Operational Efficiency3D-historgrams (Weekend) Relatively High Operational Efficiency Happen at Terminal Sections and Sections Beside Station BR4 Without Peaking Phenomenon

  17. Expected Recovery Time3D-historgrams (Weekend) Like That in Weekday Service Plan, Relatively High Expected Recovery Time is Observed at Terminal Sections and Sections Beside Station BR4

  18. Operational Efficiency3D-historgrams (Weekday) D1-bound DR1-bound Relatively High Operational Efficiency Happen at Terminal Sections and Sections Beside Station BR4

  19. Expected Recovery Time3D-historgrams (Weekday) D1-bound DR1-bound Terminal Sections and Sections Beside Station BR4 Have Relatively High Expected Recovery Time, Particularly in Peak Hours

  20. Operational Stability and EfficiencySection Perspective (Weekend) Highest Instability and Efficiency Occur at Sections Beside Station BR4;Uncertainty Increases with Expected Recovery Time (Variance Increases)

  21. Operational Stability and EfficiencyTime Perspective (Weekend) Operational Stability and Efficiency Are Relatively Uniform Over the Whole Operation Period

  22. Operational Stability and EfficiencySection Perspective (Weekday) Highest Instability and Efficiency Occur at Sections Beside Station BR4;Uncertainty Increases with Expected Recovery Time (Variance Increases)

  23. Operational Stability and EfficiencyTime Perspective (Weekday) Highest Instability and Efficiency Occur During Peak Hours;The One in Evening Peak is Higher Due to Successively High Efficiency

  24. Means to Improve System Stability Improve System Stability & Maintainability System Reliabilityand Maintainability Operational Stabilityand Efficiency SystemCharacteristics MetroService Plan Improve Capacity (Upgrade System) AdjustService Plan

  25. Evaluation of System Upgrade Original Communication System Upgraded -20% 1.356 1.083 0.31

  26. Cost Effectiveness of System Upgrade Can be Examined Original Communication System Upgraded -20% 0.109 0.087 0.58

  27. Conclusions • Operational Stability usually decreases with the increase of operational efficiency, metro operators should pay attention to sections with high instability • With the proposed method, metro operators can examine and monitor the stability and efficiency of their operational plan • This methodology can also be used to justify whether improvement strategies are cost effective

  28. Recommendations • Operators should establish an operational database to record and continuously update the historical disturbance dataand system characteristics so as to understand the status of system reliability • Future studies should focus on the determination of the optimal balance in operational stability and efficiency System Reliabilityand Maintainability Operational Stabilityand Efficiency SystemCharacteristics MetroService Plan

  29. Thank you & Questions? Yung-Cheng (Rex) Lai Assistant Professor Railway Technology Research Center Department of Civil Engineering National Taiwan University E-mail: yclai@ntu.edu.tw Phone: +886-2-3366-4243

  30. Downgraded Capacity of Metro System • Capacity • The maximum number of trains that would be able to operate on a given infrastructure under a particular set of operational conditions during a specific time interval • Downgraded Capacity • The reduced capacity due to operational disruptions Station

  31. Instability Composition WeekdayService Plan Instability is Mainly from Train Failure Level 2, Accounted for 39% and 38% respectively. WeekendService Plan

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