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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. - PowerPoint PPT Presentation
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Development of the Evaluation Process and Models for Metro System Service Stability and Efficiency
Railway Technology Research Center,National Taiwan University
Yung-Cheng (Rex) Lai
14th September, 2012
Presentation at the William W. Hay Railroad Engineering Seminar
• 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
Education
2
• 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
Research Interests
3
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 & Stability
• Capacity Management & Investment– Decision Support Framework for Strategic Capacity Planning– High Speed Route Improvement Optimizer – Optimization of Train Network Routing with Heterogeneous Traffic
4
Development of the Evaluation Process and Models for Metro System Service Stability and Efficiency
Glass Cup Theory – Tradeoff between Efficiency and Stability
5
• 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”
Evaluation Framework and Models
6
Operational Stabilityand Efficiency
System Reliabilityand Maintainability
MetroService Plan
SystemCharacteristics
System Characteristics
MetroService Plan
Historical Disturbance Data
Operational Efficiency
Operational Stability
Capacity Analysis Module Reliability Module
DowngradedCapacity
Maintainability Distribution
Reliability Distribution
NormalCapacity
Mean and Variance of the Expected Recovery Time
Percentage of the Capacity Usage
Operational Stability and Efficiency Module
UsedCapacity
Operational Efficiency- Assets Utilization Efficiency
Percentage of the Capacity Usage
NormalCapacity
Percentage of the Capacity Usage
AvailableCapacity
UsedCapacity
Normal Capacity
UsedCapacity
7
×𝟏𝟎𝟎%
Operational Stability- Expected Recovery Time
8
Disturbed Trains
Traffic Flow (Trains/hour)
T1 T2 T3 T4 T5 Time (Hour)
Normal Capacity
Downgraded Capacity
Available Capacity
Used Capacity
Disturbance
Disturbed Trains
RecoveryTime
Service Plan (headway)
RepairTime
Expected Recovery Time = Risk in Capacity Utilization
9
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
1 tF t e Failure Ratet Exposure (e.g. train-hours)
Historical Disturbance Data
Repair Time
P(x)
Repair Time Is Related to the System Maintainability• Expected recovery time inherits uncertainty from the
stochastic properties of maintainability
10
Maintainability Distribution
Evaluation Framework and Models
11
Operational Stabilityand Efficiency
System Reliabilityand Maintainability
MetroService Plan
SystemCharacteristics
System Characteristics
MetroService Plan
Historical Disturbance Data
Operational Efficiency
Operational Stability
Capacity Analysis Module Reliability Module
DowngradedCapacity
Maintainability Distribution
Reliability Distribution
NormalCapacity
Mean and Variance of the Expected Recovery Time
Percentage of the Capacity Usage
Operational Stability and Efficiency Module
UsedCapacity
A Case Study was Conducted for a Metro System• Service Plan
– Weekday service plan– Weekend service plan
• System Characteristics– 20+ intermediate stations– 2 terminal stations
12
• Historical Disturbance Data– Totally around 200 recorded
disturbances were collected for a ten-month period
Operational Stability and Efficiency
Evaluation Model
Inputs• System
Characteristics• Service Plan• Historical
Disturbance Data
Outputs• Mean and Standard
Deviation of Expected Recovery Time
• Percentage of Capacity Usage
System Map (adjusted)
13
D1 (Depot)
DR1 (Depot)
B10
B9
B9
B8
B8
B7
B7
B3
B5
B5
B4
B4
B2
B2
BR2
BR2
BR3
BR3
BR4
BR4
BR9
BR9
BR10
BR10
BR11
BR11
BR12
BR12
B6
B6
B1 BR1
BR5
BR5
BR6
BR6
BR7
BR7
BR8
BR8
Determine the Maintainability
• The classification of disturbances can facilitate the improvement of operational performance as it provides information about the sources of instability
14
Disturbance Mean Time to Repair
Train Failure Level 1 3.10 Train Failure Level 2 8.62
Loss of Electrical Power 11.01
Line Obstruction 7.89 Signal Failure 4.67
Communication Failure 13.98
Others 3.65
Probability of System Failure
• The operational stability is composed of– Severity of disturbances (Maintainability)– Frequency of disturbances (Reliability)
15
Disturbance (failure/train-hour)
Train Failure Level 1 2.00E-04
Train Failure Level 2 2.18E-04
Loss of Electrical Power 3.12E-05
Line Obstructed 4.01E-05Signal Failure 1.42E-04
Communication Failure 7.26E-05
Others 1.58E-05
1 tF t e Failure Ratet Exposure (e.g. train-hours)
Overall Evaluation Results
16
Weekday Service Plan Weekend Service Plan
D1-bound DR1-bound Overall D1-bound DR1-
bound Overall
Expected Recovery
Time (min)
Mean 0.677 0.679 1.356 0.220 0.219 0.438
Standard Deviation 0.016 0.016 0.023 0.005 0.005 0.006
Average Operational Efficiency (%) 30.37 31.53 30.95 20.81 21.60 21.21
+210%
+46%
Substantial Increase (>200%) in Operational Instability with Relatively Small Increase (46%) in Operational Efficiency
Operational Efficiency3D-histograms (Weekend)
17
Relatively High Operational Efficiency happen at Terminal Sections and Sections near Station BR4
D1-bound DR1-bound
Relatively High Expected Recovery Time is observed at Terminal Sections and Sections near Station BR4
Expected Recovery Time3D-histograms (Weekend)
18
D1-bound DR1-bound
Operational Efficiency3D-histograms (Weekday)
19
High Operational Efficiency happen at Terminal Sections and Sections near Station BR4
D1-bound DR1-bound
Expected Recovery Time3D-histograms (Weekday)
20
Terminal Sections and Sections near Station BR4 have High Expected Recovery Time, particularly in Peak Hours
D1-bound DR1-bound
Operational Stability and EfficiencySection Perspective (Weekday)
21
DR1 = BR13
BR13 = BR12
BR12 = BR11
BR11 = BR10
BR10 = BR9
BR9 = BR8
BR8 = BR7
BR7 = BR6
BR6 = BR5
BR5 = BR4
BR4 = BR3
BR3 = BR2
BR2 = BR1
BR1 = B1
B1 = B2
B2 = B3
B3 = B4
B4 = B5
B5 = B6
B6 = B7
B7 = B8
B8 = B9
B9 = B10
B10 = B11
B11 = D10
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35Average Expected Recovery Time 2 Standard Deviaiton from the AverageOperational Efficiency
Expe
cted
Rec
over
y Ti
me
(min
)
Ope
ratio
nal E
ffici
ency
Highest Instability and Efficiency Occur at Sections near Station BR4;Uncertainty Increases with Expected Recovery Time (Variance Increases)
Operational Stability and EfficiencyTime Perspective (Weekday)
22
0:0~1:0
1:0~2:0
2:0~3:0
3:0~4:0
4:0~5:0
5:0~6:0
6:0~7:0
7:0~8:0
8:0~9:0
9:0~10:0
10:0~11:0
11:0~12:0
12:0~13:0
13:0~14:0
14:0~15:0
15:0~16:0
16:0~17:0
17:0~18:0
18:0~19:0
19:0~20:0
20:0~21:0
21:0~22:0
22:0~23:0
23:0~24:00
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7Average Expected Recovery Time 2 Standard Deviation from the AverageOperational Efficiency
Expe
cted
Rec
over
y Ti
me
(min
)
Ope
ratio
nal E
ffici
ency
Highest Instability and Efficiency Occur During Peak Hours
Means to Improve System Stability
Operational Stabilityand Efficiency
System Reliabilityand Maintainability
MetroService Plan
SystemCharacteristics
Improve Capacity (Upgrade System)
AdjustService Plan
Improve System Stability &
Maintainability
23
Evaluation of Improvements
24
0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.550
0.5
1
1.5
2
2.5
3
3.5
Daily Operational Efficiency
Daily
Exp
ecte
d Re
cove
ry T
ime
(min
)
1.356
1.083
-20%
0.31
Original
Communication System Upgraded
Conclusions
• With the proposed method, metro operators can examine and monitor the stability and efficiency of their operational plan
• Operational instability usually increases with operational efficiency, and the proposed method can help users establish and understand this relationship between stability and efficiency
• This methodology can also be used to justify whether improvement strategies are cost effective
25
Future Work
• An operational database should be established to record and continuously update the disturbance data and system characteristics so as to understand the most up-to-date system reliability status
• Future studies should focus on the determination of the optimal balance in operational stability and efficiency
26
Operational Stabilityand Efficiency
System Reliabilityand Maintainability
MetroService Plan
SystemCharacteristics
Thank you & Questions?Yung-Cheng (Rex) Lai
Assistant ProfessorRailway Technology Research Center
Department of Civil EngineeringNational Taiwan University
E-mail: [email protected]: +886-2-3366-4243