Rail Capacity Definition Stringline Diagrams Parametric Models Train Performance Calculators Train Dispatching Simulation Modeling Rail Capacity AASHTO SCORTSept 22, 2010 David Hunt of Oliver Wyman
The maximum number of trains that can be moved between two locations in a day without exceeding a predefined level of service. Suggested Definition of Rail Capacity
Line Capacity Yard Capacity Crew Capacity Equipment 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 Elements in Determining Rail 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 Some of the Factors Determining Line 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 Maximum Versus Effective Capacity
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) Stringlines
Example Stringline Transnet Freight Railroad: Witbank-Komatipoort
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
Simulation Planning Models Initial 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 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 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 Levels of Effort in Modeling Rail Capacity
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. DOTs projected demand for rail freight transportation in 2035 Used STB Waybill data, empty car estimates, and ORNL network attributes The AAR Approach to Modeling Rail Capacity National Rail Freight Infrastructure Capacity and Investment Study
AAR Study Recommended Levels of Service for Rail Source: AAR National Rail Freight Infrastructure Capacity and Investment Study, September 2007.
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.
Type of Control System CTC=Blue, ABS=Green, Manual=Red Number of Tracks Two or More Tracks=Blue, Single Track=Tan Track Attributes Were used to Determine Capacity Source: Oak Ridge National Labs rail network. Raw data not verified for accuracy.
Tracks & Control Practical Max w/Multiple Trains Types Practical Max w/Single Train Type 1 No signal ABS No signal CTC ABS CTC CTC Capacity Tables Used for AAR Study Source: AAR National Rail Freight Infrastructure Capacity and Investment Study, September 2007.
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.
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 α i, β j = coefficients … other parameters may be considered Calibrate model using: Capacity information for selected lines obtained from the simulation studies C = β 0 x (1 + β 1 N) α1 x (1 + β 2 L) α2 x (1 + β 3 S) α3 x (1 + β 4 M) α4 x … Parametric Modeling
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 Reporting Parametric Model Results Using AAR V/C
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
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 What is Computer Simulation?
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.) Train Performance Calculator (TPC) The Physics of Railroading
Inputs Track profiles: Grades and curves Speed limits Typical train and locomotive consists Outputs Unhindered speeds and times Fuel consumption Train Performance Calculator
TPCs 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 Why do we use Train Dispatching Simulation Tools?
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 Train Dispatching Simulation Software
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 Event-Based Simulation Dispatching Attributes
Across each trains 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 Dispatching Logic
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 Train Dispatching Simulation Types of Inputs
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 Special Routing Events
Stringline (time-distance plot) User configurable reports TPC profiles Track occupancy charts Animation of simulation Train Dispatching Simulation Types of Outputs
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 Types of Reports
Source: Animation of Results
Animation of Results – Yard with Industrial Leads Source: US DOT Rail Capacity Workshop, 2002.
Track Occupancy Chart Source:
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 The Iterative Planning Process Using Computer Modeling
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 The Iterative Planning Process Using Computer Modeling - 2
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 Limitations of Simulation Models