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

Modeling Rail Capacity

AASHTO SCORT Sept 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 StringlineTransnet Freight Railroad: Witbank-Komatipoort

Stringlines are a Primary Analytical Tool Used WorldwideExample 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

SimulationPlanning 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. DOT’s 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 CapacityNational Rail Freight Infrastructure Capacity and Investment Study

> 1.00Unstable flows; service break down conditions

Above CapacityF

0.8 to 1.0

Very heavy train flow with very limited capacity to accommodate maintenance and recover from incidents

At CapacityE

0.7 to 0.8

Heavy train flow with moderate capacity to accommodate maintenance and recover from incidents

Near CapacityD

0.4 to 0.7C

0.2 to 0.4B

0.0 to 0.2Low to moderate train flows with capacity to accommodate maintenance and recover from incidents

Below Capacity

A

Volume/Capacity RatioDescriptionLOS Grade

> 1.00Unstable flows; service break down conditions

Above CapacityF

0.8 to 1.0

Very heavy train flow with very limited capacity to accommodate maintenance and recover from incidents

At CapacityE

0.7 to 0.8

Heavy train flow with moderate capacity to accommodate maintenance and recover from incidents

Near CapacityD

0.4 to 0.7C

0.2 to 0.4B

0.0 to 0.2Low to moderate train flows with capacity to accommodate maintenance and recover from incidents

Below Capacity

A

Volume/Capacity RatioDescriptionLOS Grade

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 Day2035 – Based on US DOT Freight Analysis Framework

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

Type of Control SystemCTC=Blue, ABS=Green, Manual=Red

Number of TracksTwo 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 16 20

1 ABS 18 25

2 No signal 28 35

1 CTC 30 48

2 ABS 53 80

2 CTC 75 100

3 CTC 133 163

Capacity Tables Used for AAR Study

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

Future Volumes Compared to Current Capacity45% 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 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 …

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

Speed Limit

Actual Speed

Train Performance CalculatorGraphical Output

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

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 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

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 SimulationTypes 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 SimulationTypes 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: www.berkeleysimulation.com

Animation of Results

Animation of Results – Yard with Industrial Leads

Source: US DOT Rail Capacity Workshop, 2002.

Track Occupancy Chart

Source: www.berkeleysimulation.com

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 ProcessUsing 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 ProcessUsing 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