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Introduction to Railroad Capacity Module 2-D

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1 Introduction to Railroad Capacity Module 2-D
4/1/2017 7:56 PM Introduction to Railroad Capacity Module 2-D Samuel L. Sogin Graduate Research Assistant University of Illinois at Urbana-Champaign © 2007 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

2 Outline Introduction Factors of capacity Mainline capacity
Yard capacity Network capacity Scheduling Economics Questions

3 Related Fields to Capacity Research
Analytics Data mining Network optimization Queuing theory Regression modeling Risk modeling Simulation Utility models

4 Railroads’ Capacity History
19th and early 20th century: Great expansion of railroads World War I: War traffic brought network to standstill due to insufficient capacity due to inefficient operations, 1920s: Relative balance between capacity and traffic levels Great Depression: Loss of traffic led to excess capacity World War II: Congestion from war traffic After WWII: Overcapacity as passenger and freight traffic declined Current: Growth in traffic and market power has permitted railroads to spend substantial amounts to remove choke points

5 More Demands on U.S. Railroad Network
Freight Growth Low Cost Transportation Reliability Intercity Passenger Trains Environment Cambridge systematics study of 2030 freight traffic without improvements Commuter Service Cambridge Systematics. (2007). National Rail Freight Infrastructure Capacity and Investment Study.

6 Problems of Capacity Shortages
Inability to handle more traffic Decreasing level of service Diminished ability to recover from a disruption Limited windows for track maintenance Crew time limitations Increase time in yards Increase cycle times All of these increase costs

7 Railroads are Capital-Intensive
The rail industry is the most capital intensive industry when compared to other capital-intensive businesses. There are numerous needs for capital dollars to maintain and expand our network to handle growth.

8 Railroads Own Expensive Assets
Track Construction ≈ $2,500,000 to $4,500,000 per mile 171,513 track miles Locomotives ≈ $1,800,000 each 23,732 locomotives Rail Car ≈ $70,000 each 580,635 railroad owned freight cars

9 Capacity Can Be Measured Anywhere
Transportation Network Railroad Network Division Subdivision Yards & Terminals Industry Facilities

10 Types of Capacity Practical Capacity: Ability to move traffic at an “acceptable” level of service Economic Capacity: The level of traffic at which the costs of additional traffic outweighs the benefits Engineering Capacity: The maximum amount moved before the system ceases to function Ultimate Capacity: The system has ceased to function and all signals are red Kahn, Ata M. Railway Capacity Analysis and Related Methodology. Ottawa, Print.

11 What Should “Capacity” Measure?
Amount Moved Utilization Reliability Sogin, Samuel L et al. “Measuring the Impact of Additional Rail Traffic Using Highway & Railroad Metrics.” Proceedings of the 2012 Joint Rail Conference. Philadelphia, 2012.

12 Railroad Capacity Metrics
Amount Moved Reliability Utilization Trains Cars Tons Revenue Tons People TEUs (Per Year) (Per Day) (Per Hour) (Per Peak Hour) Distribution of Arrival Times Average Delay Standard Deviation of Delay On Time Performance Right Car Right Train Crew Expirations Velocity Dwell time in Terminals Blocking Time Signal Wake Train Miles/Track Mile Cycle Time Sogin, Samuel L et al. “Measuring the Impact of Additional Rail Traffic Using Highway & Railroad Metrics.” Proceedings of the 2012 Joint Rail Conference. Philadelphia, 2012.

13 Important Factors of Railroad Capacity

14 Meet and Pass Single track poses significantly more challenges for capacity No longer simply limited by train spacing Must consider “meets” of trains traveling in opposite direction These impose constraints on schedule

15 Meets on Single Track T1

16 Meets on Single Track T2

17 Meets on Single Track Meet Delay T3

18 Passing on Single Track
Time Pass Delay T2

19 Track Configuration Number of tracks Siding length
Siding spacing (distance & time) Crossover spacing Single crossovers Universal crossovers Parallel crossovers Length of bottleneck section Grade Curvature

20 More track can lead to smaller delays
ST, siding every 21.4 miles bidirectional running, DT Delay (hours) directional running, DT Volume (trains/day) Kahn, Ata M. Railway Capacity Analysis and Related Methodology. Ottawa, Print.

21 Two Separate Single Track Lines
High-volume route Each railroad was operating single track with passing sidings between St. Louis and Texas Elimination of bi-directional running was one of the big pay-offs in the UP-SP merger

22 Directional Running After Merger
Eliminate “meet delay”

23 Maintenance Factors Track quality Inspection frequency
Track failure frequency Maintenance scheduling Length Frequency Surfacing cycles Tie life (Concrete or wood) Rail life Dynamic defect detection of rolling stock & track

24 Train Types Dynamics Acceleration Braking Maximum speed
Horsepower to trailing to ratio Distributed power Cargo Capacity Number of railcars Nominal capacity of railcars Height, width

25 Influence of HPT on Acceleration Distance
-3.69- -3.08- -2.46- -1.84- -1.23- -0.61- 7,150 ton train

26 Train Interactions Number of trains per day or per hour
Traffic mixture Priority differentials: Sacrificing the performance of one train type (freight) to preserve the on time performance of a preferred train type (passenger). Speed differentials: Train that operate at different speeds that can cause passing conflicts Scheduling Directional fleeting: Decrease meet delay by only operating in one direction for an interval Type fleeting (time windows): Decrease delays of different trains interacting with each other by separating the traffic type by time of day Concentration of trains due to the railroad network design

27 The Impact of Different Type of Trains
Destination Intermodal Unit Amtrak Manifest Distance Origin Time Time

28 Signaling Method of operation (YL, TWC, CTC)
Presence of ABS (Automatic block signaling): Allows for closer train spacing and higher speeds Signal spacing: Gives information more frequently on the block occupancy Signal aspects: Gives more accurate speed control to following trains allowing for tighter spacing Presence of power switches: Eliminates the need to stop to operate switches Advanced control systems Cab signaling Moving block PTC Method of operation Yard limits (Restricted speed) Track warrant control Centralized traffic control

29 Yards Length of yard leads
Total time that yard processes use the mainline Crew changes Size of receiving and departure yards Number of tracks Length of tracks Method of operation Yard limits (Restricted speed) Track warrant control Centralized traffic control Kahn, Ata M. Railway Capacity Analysis and Related Methodology. Ottawa, Print.

30 Options to increase line capacity
Operations options: Increase average speed Reduce traffic peaking Reduce the variability in speed Reduce number of meets & passes Increase length & weight of trains Infrastructure options: Line (links): Add or lengthen passing sidings Additional tracks Junctions (nodes): Add classification tracks Extend yard lines Improve junction design Grade separation

31 Unlike highways, there is no standard railroad capacity model
The complex nature of railroad operations and limited research funding has prevented a universal capacity model from being developed Currently several different models are in use

32 Different Traffic Characteristics will change the Maximum Volume
Acceptable Delay

33 Level of Service to measure Capacity
Higher delays correspond to a lower level of service (LOS) Maximum theoretical volumes are never reached to increase level of service of traffic Metric: Delay Abril, M., Barber, F., Ingolotti, L., & Salido, M. (2008). An assessment of railway capacity. Transportation Research Part E: Logistics and Transportation Review, 44(5),

34 Railroad Capacity Models
Computational Intensity Accuracy Theoretical Low Low-medium Parametric Medium-high Medium Simulation Very high Low-high Analytical Simplest Models Can be computed manually for simple networks Parametric Identify critical parametric relationships and focus on the key elements of line capacity Estimates theoretical and practical throughput Simulation Closest representation of actual operations Data intensive, not practical for network modeling

35 Theoretical: Maximum Throughput Computation
The maximum traffic flow that a rail line can accommodate under ideal condition Where: N = Number of trains per day 1440 = Number of minutes in a day Hmin = Minimum headway (minutes) 1440 N = H m i n

36 Theoretical: Blocking Time Model
Distance Minimum Head Way Time Pachl, Joern, and Thomas White. “Analytical Capacity Management with Blocking Times.” Transportation Research Board: 83rd Annual Meeting (2004)

37 Theoretical: Single Track Capacity (Poole)
Calculated headway in single track with passes C = Capacity in trains per day 1440 = Number of minutes per 24 hours t = Minutes to travel between sidings t/2 = Average dwell time waiting for opposing train to arrive m = Delay for each meet due to braking, entering the siding, running the length of the siding, leaving the siding and accelerating to full speed 2 = number of trains per pair Poole, EC. “Costs--A Tool for Railroad Management.” (1962)

38 Poole Methodology Siding A Siding B Time 0 Time t Time t+m
Time t+m+t/2 Time 2t+m+t/2

39 Parametric Models Parametric Model are based off statistical analysis of operating or simulation data Key infrastructure and operating parameters are identified to predict a delay-volume curve Attributes include Average speed Speed ratio Priority Peaking Siding spacing and uniformity Percent double track Signal spacing

40 CN Parametric Model Example
Average Speed 44.4 mph Speed Ratio 1.113 Priority 0.342 Peaking 1.727 Siding Spacing 7.77 miles Uniformity 0.49 Signal Spacing 0.93 % Double Track 50 Krueger, H. “Parametric Modeling in Rail Capacity Planning.” Proceedings of the 1999 Winter Simulation Conference. Phoenix, Web. 21 May 2012.

41 Railway Simulation Tools
Calculates train movements and makes decisions under the same rules as railroad dispatchers They account for different equipment types, train consists, train handling characteristics, terrain and track conditions Common uses of Simulation Tools: Develop operating plans Diagnose bottlenecks and recommend schedule changes Evaluate various capital improvement scenarios Assess the impact of adding new trains to a network

42 Rail Traffic Controller
Developed by Eric Wilson from Berkeley Simulation Software Emulates a dispatcher controlling train movements across a network based on train priority Integrated train performance calculator Inputs: track, signals, trains, and schedule Output: delay, average velocity, on time performance

43 RTC Animation

44 Yard Models Logan, P. (2006a). People, Process, and Technology – Unlocking Latent Terminal Capacity. Transportation Research Board 85th Annual Meeting presentation, January 24, 2006.

45 Yard Models (Simulation)
FlexsimCT. “Flexsim CT intermodal rail yard transfer simulation model.” YouTube, 2010.

46 Network Models Capacity planning Train routing Crew planning

47 Scheduling Fleeting Express scheduling
Type: Reduce delays due to different train types operating on the same line Direction: Reduce delays on single tracks lines by reducing the meet delay Express scheduling Decrease travel time by bypassing intermediate station and terminals Minimize conflicts with trains in the same direction

48 Existing Schedule Train # 300 302 304 306 308 314 316 318 320 322 324 326 328 330 AM/PM AM Kenosha 5:51 6:17 6:53 7:15 7:51 Winthrop Harbor 5:59 6:25 7:02 7:23 7:59 Zion 6:03 6:30 7:06 7:28 8:04 Waukegan 4:20 4:58 5:26 5:54 6:13 6:39 7:09 7:20 7:37 7:50 8:12 North Chicago 5:01 5:29 5:58 6:16 6:43 7:12 7:24 7:41 7:53 8:15 Great Lakes 5:05 6:02 6:46 7:16 7:27 7:58 8:18 Lake Bluff 4:28 5:10 5:35 6:06 6:22 6:50 7:32 7:46 8:22 Lake Forest 4:31 5:13 5:39 6:10 6:26 6:54 7:36 8:25 Fort Sheridan 5:16 5:43 6:14 6:31 6:59 7:40 7:55 8:07 Highwood 5:19 5:46 6:34 7:43 8:10 Highland Park 4:38 5:22 5:50 6:20 6:37 7:05 7:31 7:54 8:01 8:33 Ravinia 5:25 5:53 6:23 6:41 7:35 8:14 Ravinia Park Braeside 5:27 5:55 6:44 7:57 8:17 Glencoe 4:43 5:30 6:28 6:47 7:39 8:00 8:20 8:39 Hubbard Woods 5:33 6:01 7:18 7:42 8:03 8:23 Winnetka 4:47 5:36 6:04 7:21 7:48 7:56 8:26 8:43 Indian Hill 5:38 6:36 6:55 7:33 8:06 8:29 Kenilworth 5:40 6:08 6:38 6:57 8:08 8:31 8:46 Wilmette 4:50 5:42 6:42 7:38 8:48 Evanston Central Street 4:53 5:45 6:45 7:34 8:13 8:35 8:51 Evanston Davis Street 4:56 5:49 6:48 7:44 8:11 8:38 8:54 Evanston Main Street 6:19 6:51 7:47 8:40 Rogers Park 5:02 8:44 Ravenswood 5:07 6:29 7:01 8:09 8:50 Clybourn 7:07 7:19 8:02 8:16 8:37 8:56 9:06 Ogilvie Transportation Center 5:23 6:15 7:17 7:30 8:41 8:47 9:05 9:15 B.C. Sogin, Samuel L, Brennan M Caughron, and Samantha G Chadwick. “Optimizing Skip Stop Service in Passenger Rail Transportation.” Proceedings of the 2012 Joint Rail Conference. Philadelphia, Print.

49 Genetic Algorithm Schedule
Train # 304 306 308 310 312 314 316 318 320 322 324 326 328 330 AM/PM AM Kenosha 6:00 6:05 6:11 6:22 6:31 6:38 6:45 6:53 7:00 7:07 7:14 7:21 7:28 7:36 Winthrop Harbor 6:12 6:17 - 6:43 6:50 6:57 7:05 7:12 7:19 7:33 7:48 Zion 6:16 6:21 6:26 6:47 6:54 7:01 7:09 7:16 7:23 7:29 7:37 7:52 Waukegan 6:25 6:30 6:35 6:56 7:03 7:10 7:18 7:25 7:32 7:38 7:46 8:01 North Chicago 6:40 6:48 7:54 8:06 Great Lakes 7:59 Lake Bluff 6:49 7:45 7:50 8:03 8:14 Lake Forest 6:42 6:52 6:59 7:53 8:17 Fort Sheridan 7:27 7:42 8:08 Highwood 7:58 8:10 Highland Park 6:58 7:20 7:26 7:31 7:39 7:55 8:23 Ravinia 6:46 7:08 7:34 7:49 8:15 Ravinia Park Braeside 7:35 8:25 Glencoe 7:44 7:51 8:05 8:18 8:28 Hubbard Woods 7:13 8:12 8:21 Winnetka 7:06 8:02 8:24 8:32 Indian Hill 7:56 8:26 Kenilworth Wilmette 7:04 7:11 8:19 8:29 8:36 Evanston Central Street 7:24 8:39 Evanston Davis Street 7:17 7:57 8:11 8:35 Evanston Main Street 7:30 7:43 8:27 8:43 Rogers Park Ravenswood 8:42 Clybourn Ogilvie Transportation Center 8:16 8:31 8:37 8:44 8:54 8:59 B.C. Sogin, Samuel L, Brennan M Caughron, and Samantha G Chadwick. “Optimizing Skip Stop Service in Passenger Rail Transportation.” Proceedings of the 2012 Joint Rail Conference. Philadelphia, Print.

50 Types of Operations Scheduled Hold-For-Traffic Hybrid Systems
All train movements are planned and followed precisely Commuter, inter-city passenger trains Some freight trains Hold-For-Traffic Wait for the necessary traffic threshold to run a train Grain, coal and other bulk trains Hybrid Systems

51 Economics Project selection models Determining the cost of congestion
Determining the capacity of a railroad line Base train equivalence Other operating metrics

52 Economics of Railroad Capacity
Marginal Revenue Marginal Cost

53 Research Needs Models that capture yard-mainline interaction
Predicting the impact of higher speed passenger and freight trains on the same corridor Creating new theoretical & parametric models

54 References (1)  Abril, M, F Barber, L Ingolotti, and MA Salido “An assessment of railway capacity.” Transportation Research Part E: Logistics and Transportation Review 44 (5): S Chultz A Ndreas T Anner, and Ralf Bornd “An Auctioning Approach to Railway Slot Allocation An Auctioning Approach to Railway Slot Allocation.” Management 45 (October): Cambridge Systematics National Rail Freight Infrastructure Capacity and Investment Study. Carey, M “Stochastic Approximation to the Effects of Headways on Knock-On Delays of Trains.” Transportation Research Part B: Methodological 28 (4): Dingler, Mark, Amanda Koenig, Sam Sogin, and Christopher P L Barkan Determining the Causes of Train Delay. In AREMA Annual Conference Proceedings. Orlando. Dingler, Mark, Yung-Cheng Lai, and Christopher P.L. Barkan “Impact of Train Type Heterogeneity on Single-Track Railway Capacity.” Transportation Research Record: Journal of the Transportation Research Board 640 (2117): Gorman, Michael F “Statistical Estimation of Railroad Congestion Delay.” Transportation Research Part E. Harrod, Steven “Capacity factors of a mixed speed railway network.” Transportation Research Part E 45 (5): Ireland, Phil, Rod Case, John Fallis, and Jason Kuehn “Perfecting the Scheduled Railway : Model-Driven Operating Plan Development.” System: 1-28. Kahn, Ata M Railway Capacity Analysis and Related Methodology. Ottawa.

55 References (2) Krueger, H Parametric Modeling in Rail Capacity Planning. In Proceedings of the 1999 Winter Simulation Conference, Phoenix. Leilich, Robert H Application of Simulation Models in Capacity Constrained Rail Corridors. In Proceedings of the 30th conference on Winter simulation, Lu, Quan, Maged Dessouky, and Robert C Leachman “Modeling Train Movements Through Complex Rail Networks.” Computer 14 (1): Martland, Carl D, Patrick Little, and Joseph M. Sussman “Service Management in the Railroad Industry.” Transportation Research Board. Mattsson, LG “Railway capacity and train delay relationships.” Critical Infrastructure. Pachl, Joern Railway Operation and Control. 2nd ed. Mountlake Terrace: VTD Rail Publishing. Pachl, Joern, and Thomas White “Analytical Capacity Management with Blocking Times.” Transportation Research Board: 83rd Annual Meeting. Petersen, ER “Design of single-track rail line for high-speed trains.” Transportation Research Part A: General 21 (1). Poole, EC “Costs--A Tool for Railroad Management.”

56 References (3) Preston, John, Graham Wall, Richard Batley, J Nicolás Ibáñez, and Jeremy Shires “Impact of Delays on Passenger Train Services.” Transportation Research Record: Journal of the Transportation Research Board (2117): Sogin, Samuel L, Christopher P.L. Barkan, Yung-Cheng Lai, and Mohd Rapik Saat Measuring the Impact of Additional Rail Traffic Using Highway & Railroad Metrics. In Proceedings of the 2012 Joint Rail Conference. Philadelphia. Sogin, Samuel L., Christopher P.L. Barkan, and Mohd Rapik Saat Simulating the Effects of Higher Speed Passenger Trains in Single Track Freight Networks. In Proceedings of the 2011 Winter Simulation Conference, Phoenix Sogin, Samuel L., Brennan M Caughron, and Samantha G Chadwick Optimizing Skip Stop Service in Passenger Rail Transportation. In Proceedings of the 2012 Joint Rail Conference. Philadelphia. Vromans, Michiel J C M, Rommert Dekker, and Leo G Kroon “Reliability and heterogeneity of railway services.” European Journal Of Operational Research 172: White, Thomas Examination of Use of Delay as Standard Measurement of Railroad Capacity and Operation. In Transportation Research Board: 85th Annual Meeting. Washington, D.C.

57 Questions?

58 Copyright Restrictions and Disclaimer
Presentation Author Samuel L. Sogin Graduate Research Assistant Rail Transportation and Engineering Center Civil & Environmental Engineering Department University of Illinois at Urbana-Champaign 1203 Newmark Civil Engineering Lab, B118 Urbana, IL (847) It is the author’s intention that the information contained in this file be used for non-commercial, educational purposes with as few restrictions as possible. However, there are some necessary constraints on its use as described below. Copyright Restrictions and Disclaimer: The materials used in this file have come from a variety of sources and have been assembled here for personal use by the author for educational purposes. The copyright for some of the images and graphics used in this presentation may be held by others. Users may not change or delete any author attribution, copyright notice, trademark or other legend. Users of this material may not further reproduce this material without permission from the copyright owner. It is the responsibility of the user to obtain such permissions as necessary. You may not, without prior consent from the copyright owner, modify, copy, publish, display, transmit, adapt or in any way exploit the content of this file. Additional restrictions may apply to specific images or graphics as indicated herein. The contents of this file are provided on an "as is" basis and without warranties of any kind, either express or implied. The author makes no warranties or representations, including any warranties of title, noninfringement of copyright or other rights, nor does the author make any warranties or representation regarding the correctness, accuracy or reliability of the content or other material in the file.

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