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Michael Hayes
Strategic Rail Authority
Transport Modelling Manager
SRA Transport Model
Development 2004
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This Presentation
• SRA transport modelling
• Current model development
• Future model development
• Current EMME/2 problems
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SRA transport modelling
• The Strategic Rail Authority (SRA) is responsible for
planning the development of the UK rail network in a
multi-modal context.
• Interactions with local transport authorities in major
cities, especially London.
• Extensive private sector involvement, with
interactions involving revenues, track access charges
and subsidy / premium payments.
• Sections of the UK rail network are congested,
immense pressure to make best use of capacity.
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SRA transport modelling
Key modelling challenges:
• Crowding, especially on commuter lines into London
(some lines running at 150% of capacity).
• Reliability, both at train and at passenger levels.
• Critical examination of the value of individual rail
services where capacity is at a premium.
• In certain areas, interaction of rail network demand
with station interchange and crowding – several
stations have to be closed to avoid overcrowding.
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SRA transport modelling
Passenger demand forecasting models:
• PLANET North / South models
• PLANET Strategic model
• MOIRA
• PLATO
Reliability models:
• Merit
• Railsys / Vision
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SRA transport modelling
PLANET North / South.
• Morning and inter-peak models for North and South
of country, concentrating on short distance
movements into urban centres.
• Frequency based EMME/2 model.
• Own mode elasticities to generalised journey time.
• Crowding based on factoring in-vehicle time.
• Takes around 2 hours to run a test.
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SRA transport modelling
PLANET Strategic Model
• All day model for the UK, including road and air
movements. Designed for longer distance
movements (over about 80km)
• Frequency based EMME/2 model.
• Full mode choice procedures.
• Crowding based on factoring in-vehicle time.
• Takes around 2 hours to run a test.
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SRA transport modelling
MOIRA
• Covers all UK rail network (ten separate submodels)
• Full representation of all train services, with train-bytrain, stop-by-stop loadings, but no crowding or fares.
• Timetable-based assignment (bespoke model based
using Delphi). Time of travel based on surveys.
• Fed automatically from central timetable and ticket
data sources.
• Takes around 2 minutes to run a test.
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SRA transport modelling
PLATO
• Developed for specific lines from MOIRA
• Includes crowding algorithms to allow time-shifting.
• Requires detailed count data for calibration purposes.
• Takes around 20 minutes to run a test (???)
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SRA transport modelling
MERIT
• Strategic level reliability model.
• Uses historic delay data (by type of incident) to
predict delay minutes for an altered timetable.
• Outputs train-by-train average delay data.
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SRA transport modelling
Vision / RailSys
• Detailed reliability models.
• Use stochastic simulation of delays to calculate
average delay minutes for each service.
• Outputs train-by-train average delay data.
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SRA transport modelling
SRA modelling activities
• Models used to develop business cases for
enhancements, train service specifications,
affordability estimates, strategies and policies.
• Use a panel of six transport planning consultancies
for PLANET modelling, about the same number for
other modelling activities.
• Typically 50 to 100 commissions involving significant
modelling activity per year, around 20 involving
PLANET.
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Current model development
SRA develop PLANET demand forecasting models.
• Ongoing model enhancements, updating networks
and demand matrices based on new timetables and
latest ticket sales data (received annually).
• Detailed surveys undertaken every 10 years to
establish more detailed journey patterns, especially
those involving season ticket (travelcard) sales. Most
recent data is now available for SE England, now
reconciling with ticket data and rebasing models.
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Current model development
• Major increase in functionality has involved
development of fares functionality.
• For most journeys in UK, variety of fares available,
including time-restricted, advance-purchase and
quota-restricted tickets.
• Substantial research already undertaken on
elasticities of rail demand to change in fares,
including cross-elasticities (Passenger Demand
Forecasting Handbook Version 4 – ATOC).
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Current model development
• Fares functionality developed by MVA Consultants,
but using experience from all six Panel consultants.
• Uses fares matrix approach.
• Changes in fare levels and restrictions feed through
to a composite generalised fare.
• Change in restrictions also affects demand profile,
feeding into crowding calculations.
• Impact on overall demand is calculated as part of
overall generalised time / cost elasticity function.
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Current model development
• Being extended to PLANET Strategic model, but
significant problems encountered:
– Individual zone-to-zone movements are allowed to railhead to distant stations, so fare matrix approach is
difficult without knowledge of route assignment details.
– Although we can assume that station – station fares
are independent of route (see next), cannot take pointto-point fares into account when running assignment.
– Left with less than ideal combination of fares matrices
combined with p/km adjustments for rail-heading.
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Current model development
• Other problem includes premium fares:
– In certain areas, fast services and local services have
different fares. Passengers often use local services to
connect onto fast services.
– Each of the fares are set by different Train Operating
Companies (TOCs) – up to 25 TOCs have “own TOC
only” tickets. Impractical to increase number of
assignments by factor of 25 (or more).
– Issue remains largely unresolved, with work-arounds
for specific examples in individual areas.
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Current model development
• PLANET models have been audited, and incremental
assignment replaced by iterative assignment.
• Detailed measure of convergence based on change
in generalised costs.
• Mode choice iteration for all models, taking into
account crowding effects on mode choice.
• Some development of standard ENIF outputs (mostly
by Matt Carlson, Arup).
• Transit line editing tool (MS Access-based, developed
by Matt Carlson, Arup).
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Future model development
Areas of development:
• Interface with timetable-based assignment tools
(MOIRA).
• Conversion to ticket-based model, with assignments
reflecting ticket restrictions.
• Interface with standard rail industry timetable and
reliability tools.
• Incorporation of reliability into demand forecasting
models.
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Future model development
Interface with MOIRA:
• Increasing need to understand impacts of scheme at
individual station and train level.
• Substantial development of MOIRA expected
(probably £500k - £1m over next five years).
• Is there a way of gaining best value from both
detailed timetable-based and strategic frequencybased models?
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Future model development
Conversion to ticket-based model:
• Most demand information comes directly from ticket
sales information, factored by survey information.
• Important to allocate ticket revenue to routes, not just
passengers.
• Lots of ticket restrictions – difficult to incorporate in
assignment routines.
• Would add substantial value to existing fares
modelling work.
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Future model development
Interface with timetable and reliability tools:
• Enables editing of transit lines in user-friendly way,
eliminates possibility of demand modellers
“misunderstanding” service specifications.
• Will enable automatic updates of networks in models
– substantial cost savings.
• Could be either EMME/2 based or Visual Basic.
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Future model development
Incorporation of reliability into models:
• Impact of Edinburgh – London train running late is
much greater for Edinburgh passengers than for
Peterborough – London passengers (frequent
services already operate Peterborough – London).
• Outputs of reliability models tend to be average
lateness for each train service – need to know
individual lateness before averaging to calculate
impact on passengers.
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Future model development
Incorporation of reliability into models:
• How do you incorporate reliability within assignment?
• Is it better to model at a strategic level (PLANET) or
detailed timetable level (MOIRA)?
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Current EMME/2 problems
SRA’s preferred areas of EMME/2 development:
• Flexibility in assignment, including ability to skim
multiple additional attributes.
• Better transit line editing tools.
• Make Enif interface more user friendly (subject to
separate presentation!!)
• Timetable based assignment process
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Current EMME/2 problems
Assignment flexibility:
• Assigning demand on logit curve of generalised costs
of routes. Example Bradford – London, 1 direct
service, 15 services with one change – should they
all have equal demand?? Would also help premium
fares problem.
• Assignments need to include combination of boarding
and alighting node attributes (for fares work).
• Or even separate fares input?
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Current EMME/2 problems
Assignment flexibility:
• Why not some module that estimates time-slice
demand matrices based on boarding / alighting time
profiles at stations, combined with all-day O-D
information?
• Why can you only skim one attribute during
assignments? Easy win, and would cut model run
times substantially.
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Current EMME/2 problems
Transit Line Editing:
• Need look-up for transit lines with simple interface
and ability to directly edit – through Access-type
interface?
• Current “interactive” tool is difficult to use when
multiple transit lines use same segment.
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Current EMME/2 problems
Enif:
• SRA have great need for straightforward examination
of (for example) loadings on groups of transit lines.
• Previous versions of ENIF require expert knowledge
for even basic tasks – e.g. how many people are
using a particular set of transit lines is not an obvious
task from the manual.
• Outputs need to incorporate relationships between
graphical objects and links
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Current EMME/2 problems
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Current EMME/2 problems
Timetable based assignments:
• EMME/2 lags behind other timetable-based
assignment models.
• Should be a way of estimating time-specific demand
by using arrival and departure profiles at stations,
together with (non-time specific) origin-destination
matrices.
• Should be a way of using continuous profiles rather
than discrete slices.
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Summary
• Significant SRA model development over last two
years.
• Excellent work by our supporting consultants.
• Expectations of SRA clients is rising – need our
models (and supporting software) to keep track.
www.sra.gov.uk