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Rail Capacity Definition Stringline Diagrams Parametric Models Train Performance Calculators Train Dispatching Simulatio PowerPoint Presentation
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Rail Capacity Definition Stringline Diagrams Parametric Models Train Performance Calculators Train Dispatching Simulatio

Rail Capacity Definition Stringline Diagrams Parametric Models Train Performance Calculators Train Dispatching Simulatio

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Rail Capacity Definition Stringline Diagrams Parametric Models Train Performance Calculators Train Dispatching Simulatio

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  1. Modeling Rail Capacity • Rail Capacity Definition • Stringline Diagrams • Parametric Models • Train Performance Calculators • Train Dispatching Simulation AASHTO SCORT Sept 22, 2010 David Hunt of Oliver Wyman

  2. Suggested Definition of Rail Capacity The maximum number of trains that can be moved between two locations in a day without exceeding a predefined level of service.

  3. Line Capacity Yard Capacity Crew Capacity Equipment Capacity Elements in Determining Rail Capacity Line Capacity: number of tracks; type and spacing of control system; number, spacing, and length of sidings; mix of train types; operating and maintenance plans Yard Capacity: total acreage; number of tracks; container storage slots Crew Capacity: available crew starts; yard crews; maintenance crews Equipment Capacity: locomotives; railcars; containers/trailers This presentation will focus on line capacity

  4. Some of the Factors Determining Line Capacity • Physical Track Layout • Number of tracks • Type of signals • Number and spacing of sidings • Operating Plan • Schedules • Type of service • Train makeup • Number and horsepower of locomotives • Train length and weight • Geography • Mountains • Tunnels • Bridges

  5. Maximum Versus Effective Capacity • Transportation firms can never utilize a facility 100% of the time • Maintenance • Weather • Peaking of traffic volumes • Disruptions and recoverability • Normal variability in operational conditions • Industry practices call for standards to maintain fluidity of operations and avoid major issues at chokepoints • Useable (effective) capacity is 70% to 80% of the maximum (theoretical) capacity • Utilizing the capacity buffer between effective and maximum capacity results in deferred maintenance, reduced ability to react to variability with increasing recovery time, significant reduction in reliability

  6. Stringlines • Graphical depiction of a timetable • Provides a visual representation of trains scheduled to operate on a corridor • Typically show stations (space) along the y-axis and time along the x-axis • Also referred to as time-space and time-distance diagrams • Have many uses: • Identification of schedule conflicts (meets/passes) • Identification of slots for new service • Scheduling track maintenance • Resource planning (crews, locomotives)

  7. Example Stringline Transnet Freight Railroad: Witbank-Komatipoort

  8. Stringlines are a Primary Analytical Tool Used Worldwide Example from Kazakhstan Temir Zholy Green & Blue = Passenger, Red = Freight, Brown = Locals • Software Products Allow: • Selecting timeframes, corridors, and trains • Building or adjusting schedules by adding and dragging strings

  9. Levels of Effort in Modeling Rail Capacity Initial Estimation Planning Models Simulation • “Back of the envelope” methods • Expert with basic knowledge of number of tracks, type of signals, and special conditions (e.g. mountainous terrain) • Useful for quick assessment of a single corridor or facility • Variety of methods, requires more data than back of the envelope but less than a full simulation • Parametric (statistical based) models stem from 1975 FRA work and the CN model (Krueger, 1999) • “Paper” simulations (now evolved to spreadsheets) are also used for capacity estimation • Uses a commercial rail simulation product (RTC, RAILS, FastTrack) • Requires precise network layout (tracks, sidings, interlockings, signals, etc.) • Requires knowledge of operating plan: trains that will be run and schedules • Initial setup is expensive

  10. The AAR Approach to Modeling Rail Capacity National Rail Freight Infrastructure Capacity and Investment Study • Requested by the National Surface Transportation Policy and Revenue Study Commission • Commissioned by the AAR • Prepared by Cambridge Systematics, Inc. • Purpose was to estimate the rail freight infrastructure improvements and investments needed to meet the U.S. DOT’s projected demand for rail freight transportation in 2035 • Used STB Waybill data, empty car estimates, and ORNL network attributes

  11. AAR Study Recommended Levels of Service for Rail Source: AAR “National Rail Freight Infrastructure Capacity and Investment Study”, September 2007.

  12. Forecasted Growth of Freight Trains Per Day 2035 – Based on US DOT Freight Analysis Framework Source: AAR “National Rail Freight Infrastructure Capacity and Investment Study”, September 2007.

  13. Track Attributes Were used to Determine Capacity Type of Control System CTC=Blue, ABS=Green, Manual=Red Number of Tracks Two or More Tracks=Blue, Single Track=Tan Source: Oak Ridge National Labs rail network. Raw data not verified for accuracy.

  14. Capacity Tables Used for AAR Study Source: AAR “National Rail Freight Infrastructure Capacity and Investment Study”, September 2007.

  15. Future Volumes Compared to Current Capacity 45% of Network at Level of Service E or F Source: AAR “National Rail Freight Infrastructure Capacity and Investment Study”, September 2007.

  16. Parametric Modeling • One form of a parametric model: • Where: • C = maximum capacity in trains/day • N = number of tracks • L = type of control system (categorical variable) • S = average spacing between sidings • M = mix of train types • αi, βj = coefficients • … other parameters may be considered • Calibrate model using: • Capacity information for selected lines obtained from the simulation studies C = β0 x (1 + β1 N)α1 x (1 + β2 L)α2 x (1 + β3 S)α3 x (1 + β4 M)α4 x …

  17. Reporting Parametric Model Results Using AAR V/C • Establish the level of service for each rail line: • Where: • R = volume to capacity ratio, from which the level of service (LOS) is determined • V = volume in trains/day • C = maximum capacity in trains/day • Identify potential chokepoints: • Lines with a LOS of “D”, “E”, or “F”, using the AAR capacity scale • Other special considerations (e.g. tunnels, bridges) R = V / C

  18. The Canadian National parametric model is the best known example It was designed for single track corridors Does not handle complex track configurations FRA has sponsored research into improving parametric models for more complex track layouts Parametric models are best used for high-level national or regional modeling to identify potential problem areas Detailed capacity analysis is done with simulation Limitations of Parametric Models

  19. What is Computer Simulation? • Set of simplifying mathematical assumptions that attempt to duplicate actual train operations • The simulation should allow a comparison of the current actual train operation with alternative assumptions about: • Changes in the number of trains • Changes in the types of trains • Changes in the schedules of trains • Changes to the physical plant

  20. Train Performance Calculator (TPC) The Physics of Railroading • Objectives • Determine Minimum Run Time (unobstructed) on a specific route for specific train characteristics • Develop run time information for use as input to dispatching simulation models • Estimate fuel consumption • Uses • Provides key component analysis for schedule preparation • Determines effect of line speed changes on run time • Determines effect of train consist changes • Locomotive (tractive effort characteristics, etc.) • Cars (weight/braking characteristics, etc.)

  21. Train Performance Calculator • Inputs • Track profiles: Grades and curves • Speed limits • Typical train and locomotive consists • Outputs • Unhindered speeds and times • Fuel consumption

  22. Train Performance Calculator Graphical Output

  23. Why do we use Train Dispatching Simulation Tools? • TPC’s only provide the expected operational characteristics for a free-running train without regard to: • Meets and passes with other trains • Capacity for schedule adherence • Train priorities • Train density and characteristic mix • Physical plant • Main track work

  24. Train Dispatching Simulation Software • Main objective: a mathematical approximation of operational results for a given set of variables based on a reasonable dispatching algorithm • Logic attempts to realistically replicate decisions by a “good” dispatcher (not an optimal one) • Other objectives: • Reliable, repeatable results • Ease of use • Minimize or automate input data • User-friendly input procedures • Comprehensive user interface • Externally usable results

  25. Event-Based Simulation Dispatching Attributes • Dispatcher logic • Follows rules - preferences - dynamic priorities • Might lower the priority for high priority train running late • Might raise the priority for low priority train if crew close to exceeding hours • Variable - limited outlook • Anti-lock-up logic • All moves tested before implementation • When move is rejected, next most preferable move is selected

  26. Dispatching Logic • Across each train’s look-ahead, conflicts are identified • If there are any, all “reasonable” resolution options are identified • Each option for resolution is “costed” using user defined delay costs. These costs dynamical change as the simulation runs. • Penalties are added for less preferred moves such as changing tracks, entering siding, etc. • Options are sorted by “cost” • Each option is submitted to the anti-lock-up logic until one is accepted • The necessary moves of that option are implemented in the simulation

  27. Train Dispatching Simulation Types of Inputs • Infrastructure • Plant • Signals • Traffic • Operating characteristics • Which trains are running • Train priorities • Train size and power • Route (including reverse moves if applicable) • Time of operation • Schedule based and non-schedule based

  28. Special Routing Events • Replicate track maintenance • Remove track/control point from service • Apply/remove temporary speed restrictions • Replicate train work at a location • Train delay(s) • Train characteristics • Train connections • Replicate passenger operation • Schedule train(s) departure times • Specify a route or track

  29. Train Dispatching Simulation Types of Outputs • Stringline (time-distance plot) • User configurable reports • TPC profiles • Track occupancy charts • Animation of simulation

  30. Types of Reports • Individual train ”logs" • Scheduled & unscheduled delays • In total • By train type • By location • Statistical analyses • Distribution of trip times • Locomotive-miles • Distribution of delays • Used to determine if plant is balanced • Operating costs • Timetables

  31. Animation of Results Source: www.berkeleysimulation.com

  32. Animation of Results – Yard with Industrial Leads Source: US DOT Rail Capacity Workshop, 2002.

  33. Track Occupancy Chart Source: www.berkeleysimulation.com

  34. The Iterative Planning Process Using Computer Modeling • Develop “base case” traffic • Track configuration, signals & other physical attributes • Operating plan • Develop alternative scenarios (changes to physical plant or operating plan) • Compare alternative scenario to base, or to other alternative

  35. The Iterative Planning Process Using Computer Modeling - 2 • Inject track maintenance and operating failures at critical points, and determine if plant still works. • If not, refine plant some more and re-run • First without perturbations • Then with perturbations • Select alternatives that meet operating objectives • If none, refine alternatives & re-run • Balanced plant is achieved when delays are evenly distributed

  36. Limitations of Simulation Models • Data and time intensive • Must validate to actual • Yard operations are modeled separately (hump operations, intermodal lifts, etc.) • Resource constraints (crews, locomotives, etc..) are largely ignored • Models do not look beyond study area to the rest of the network • Even detailed simulation requires simplifying assumptions