Analytics Data mining Network optimization Queuing theory Regression modeling Risk modeling Simulation Utility models
19 th and early 20 th 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 1990 - Current: Growth in traffic and market power has permitted railroads to spend substantial amounts to remove choke points
Reliability Intercity Passenger Trains Commuter Service Low Cost Transportation Freight Growth Environment Cambridge Systematics. (2007). National Rail Freight Infrastructure Capacity and Investment Study.
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
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, 1979. Print.
Utilization Amount Moved 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.
Amount MovedReliabilityUtilization 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.
14 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 14
Number of tracks Siding length Siding spacing (distance & time) Crossover spacing Single crossovers Universal crossovers Parallel crossovers Length of bottleneck section Grade Curvature
Volume (trains/day) Delay (hours) directional running, DT bidirectional running, DT ST, siding every 21.4 miles Kahn, Ata M. Railway Capacity Analysis and Related Methodology. Ottawa, 1979. Print.
21 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 21
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 23
Dynamics Acceleration Braking Maximum speed Horsepower to trailing to ratio Distributed power Cargo Capacity Number of railcars Nominal capacity of railcars Height, width
-3.69- -3.08- -2.46- -1.84- -1.23- -0.61- 7,150 ton train
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
Time Distance Intermodal Amtrak Manifest Unit Origin Destination Time
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
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 Kahn, Ata M. Railway Capacity Analysis and Related Methodology. Ottawa, 1979. Print.
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
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
33 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 33 Abril, M., Barber, F., Ingolotti, L., & Salido, M. (2008). An assessment of railway capacity. Transportation Research Part E: Logistics and Transportation Review, 44(5), 774-806.
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 Computational IntensityAccuracy TheoreticalLowLow-medium ParametricMedium-highMedium SimulationVery highLow-high
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 H min = Minimum headway (minutes) 1440 min N H
Time Distance Minimum Head Way Pachl, Joern, and Thomas White. Analytical Capacity Management with Blocking Times. Transportation Research Board: 83rd Annual Meeting (2004)
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)
Siding A Siding B Time t Time 0 Time t+mTime 2t+m+t/2 Time t+m+t/2
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
Average Speed44.4 mphSpeed Ratio1.113 Priority0.342Peaking1.727 Siding Spacing7.77 milesUniformity0.49 Signal Spacing0.93% Double Track50 Krueger, H. Parametric Modeling in Rail Capacity Planning. Proceedings of the 1999 Winter Simulation Conference. Phoenix, 1999. 1194-1200. Web. 21 May 2012.
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
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
Fleeting 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
Train #300302304306308314316318320322324326328330 AM/PMAM Kenosha––––5:516:17––6:53––7:15–7:51 Winthrop Harbor––––5:596:25––7:02––7:23–7:59 Zion––––6:036:30––7:06––7:28–8:04 Waukegan4:204:585:265:546:136:39–7:097:157:20–7:377:508:12 North Chicago–5:015:295:586:166:43–7:12–7:24–7:417:538:15 Great Lakes–5:05–6:02–6:46–7:16–7:27––7:588:18 Lake Bluff4:285:105:356:066:226:50––7:247:32–7:46–8:22 Lake Forest4:315:135:396:106:266:54–7:23–7:36–7:50–8:25 Fort Sheridan–5:165:436:146:316:59––7:327:40–7:558:07– Highwood–5:195:466:176:347:02––7:367:43––8:10– Highland Park4:385:225:506:206:377:05–7:31–7:467:548:01–8:33 Ravinia–5:255:536:236:417:09–7:357:41––8:048:14– Ravinia Park–––––––––––––– Braeside–5:275:556:256:447:12––7:43–7:57–8:17– Glencoe4:435:305:586:286:477:15–7:39–7:518:00–8:208:39 Hubbard Woods–5:336:016:316:507:18–7:42––8:03–8:23– Winnetka4:475:366:046:346:537:217:31–7:487:56––8:268:43 Indian Hill–5:386:066:366:557:247:33––7:588:06–8:29– Kenilworth–5:406:086:386:577:277:35––8:008:08–8:318:46 Wilmette4:505:426:106:426:597:317:38––8:03–8:148:338:48 Evanston Central Street4:535:456:136:457:027:347:41––8:078:138:188:358:51 Evanston Davis Street4:565:496:176:487:067:387:447:517:578:11–8:228:388:54 Evanston Main Street4:585:516:196:51––7:47–8:00–8:18–8:40– Rogers Park5:025:546:236:55––7:50–8:038:158:22–8:44– Ravenswood5:075:596:297:01––7:558:018:09––8:318:50– Clybourn5:136:066:367:077:197:518:028:088:168:258:318:378:569:06 Ogilvie Transportation Center5:236:156:457:177:308:028:128:188:268:358:418:479:059:15 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, 2012. Print.
Train #304306308310312314316318320322324326328330 AM/PMAM Kenosha6:006:056:116:226:316:386:456:537:007:077:147:217:287:36 Winthrop Harbor6:126:17--6:436:506:577:057:127:19-7:33-7:48 Zion6:166:216:26-6:476:547:017:097:167:237:297:37-7:52 Waukegan6:256:306:35-6:567:037:107:187:257:327:387:46-8:01 North Chicago--6:406:487:01----7:37--7:548:06 Great Lakes--6:456:53-7:12----7:46-7:59- Lake Bluff--6:49-7:097:16-7:297:367:457:50-8:038:14 Lake Forest-6:426:526:597:12-7:237:32-7:487:537:59-8:17 Fort Sheridan6:40---7:167:217:27-7:427:52-8:038:08- Highwood6:426:47-7:03-7:23----7:58-8:10- Highland Park-6:506:58-7:207:267:317:397:467:558:018:06-8:23 Ravinia6:466:53-7:08--7:347:427:49---8:15- Ravinia Park-------------- Braeside6:476:54-7:09--7:35-----8:158:25 Glencoe6:506:56--7:23-7:377:447:51-8:05-8:188:28 Hubbard Woods-6:597:037:13-7:32-----8:128:21- Winnetka6:54-7:067:167:28----8:02--8:248:32 Indian Hill6:56-7:087:18----7:56--8:158:26- Kenilworth---7:20---7:497:588:058:108:17-- Wilmette6:597:047:11-7:317:36-7:51--8:128:198:298:36 Evanston Central Street--7:147:247:34-7:457:54-8:088:15-8:328:39 Evanston Davis Street-7:097:177:27--7:487:57-8:118:188:248:35- Evanston Main Street---7:30-7:437:51-8:058:14-8:27-8:43 Rogers Park7:077:13-7:337:437:467:54-8:08-8:23--- Ravenswood7:11-7:247:37-7:50--8:12--8:328:42- Clybourn7:16--7:42-7:55-8:08-8:23---- Ogilvie Transportation Center7:247:277:367:507:548:038:088:168:238:318:378:448:548:59 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, 2012. Print.
Scheduled 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
Project selection models Determining the cost of congestion Determining the capacity of a railroad line Base train equivalence Other operating metrics
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
Abril, M, F Barber, L Ingolotti, and MA Salido. 2008. An assessment of railway capacity. Transportation Research Part E: Logistics and Transportation Review 44 (5): 774-806. S Chultz A Ndreas T Anner, and Ralf Bornd. 2005. An Auctioning Approach to Railway Slot Allocation An Auctioning Approach to Railway Slot Allocation. Management 45 (October): 163-197. Cambridge Systematics. 2007. National Rail Freight Infrastructure Capacity and Investment Study. Carey, M. 1994. Stochastic Approximation to the Effects of Headways on Knock-On Delays of Trains. Transportation Research Part B: Methodological 28 (4): 251-267. Dingler, Mark, Amanda Koenig, Sam Sogin, and Christopher P L Barkan. 2010. Determining the Causes of Train Delay. In AREMA Annual Conference Proceedings. Orlando. Dingler, Mark, Yung-Cheng Lai, and Christopher P.L. Barkan. 2009. Impact of Train Type Heterogeneity on Single-Track Railway Capacity. Transportation Research Record: Journal of the Transportation Research Board 640 (2117): 41-49. Gorman, Michael F. 2008. Statistical Estimation of Railroad Congestion Delay. Transportation Research Part E. Harrod, Steven. 2009. Capacity factors of a mixed speed railway network. Transportation Research Part E 45 (5): 830-841 Ireland, Phil, Rod Case, John Fallis, and Jason Kuehn. 2003. Perfecting the Scheduled Railway: Model-Driven Operating Plan Development. System: 1-28. Kahn, Ata M. 1979. Railway Capacity Analysis and Related Methodology. Ottawa.
Krueger, H. 1999. Parametric Modeling in Rail Capacity Planning. In Proceedings of the 1999 Winter Simulation Conference, 1194-1200. Phoenix. Leilich, Robert H. 1998. Application of Simulation Models in Capacity Constrained Rail Corridors. In Proceedings of the 30th conference on Winter simulation, 1125-1133. Lu, Quan, Maged Dessouky, and Robert C Leachman. 2004. Modeling Train Movements Through Complex Rail Networks. Computer 14 (1): 48-75. Martland, Carl D, Patrick Little, and Joseph M. Sussman. 1994. Service Management in the Railroad Industry. Transportation Research Board. Mattsson, LG. 2007. Railway capacity and train delay relationships. Critical Infrastructure. Pachl, Joern. 2009. Railway Operation and Control. 2nd ed. Mountlake Terrace: VTD Rail Publishing. Pachl, Joern, and Thomas White. 2004. Analytical Capacity Management with Blocking Times. Transportation Research Board: 83rd Annual Meeting. Petersen, ER. 1987. Design of single-track rail line for high-speed trains. Transportation Research Part A: General 21 (1). Poole, EC. 1962. Costs--A Tool for Railroad Management.
Preston, John, Graham Wall, Richard Batley, J Nicolás Ibáñez, and Jeremy Shires. 2009. Impact of Delays on Passenger Train Services. Transportation Research Record: Journal of the Transportation Research Board (2117): 14-23. Sogin, Samuel L, Christopher P.L. Barkan, Yung-Cheng Lai, and Mohd Rapik Saat. 2012. 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. 2011. Simulating the Effects of Higher Speed Passenger Trains in Single Track Freight Networks. In Proceedings of the 2011 Winter Simulation Conference, 3679-3687. Phoenix Sogin, Samuel L., Brennan M Caughron, and Samantha G Chadwick. 2012. 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. 2006. Reliability and heterogeneity of railway services. European Journal Of Operational Research 172: 647-665. White, Thomas. 2006. Examination of Use of Delay as Standard Measurement of Railroad Capacity and Operation. In Transportation Research Board: 85th Annual Meeting. Washington, D.C.
58 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 61801 (847) 899-2711 It is the authors 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. 58