2 Michael Hayes Strategic Rail Authority Transport Modelling Manager SRA Transport Model Development 2004
3 This Presentation SRA transport modelling Current model development Future model development Current EMME/2 problems
4 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.
5 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.
6 SRA transport modelling Passenger demand forecasting models: PLANET North / South models PLANET Strategic model MOIRA PLATO Reliability models: Merit Railsys / Vision
7 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.
8 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.
9 SRA transport modelling MOIRA Covers all UK rail network (ten separate submodels) Full representation of all train services, with train-by- train, 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.
10 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 (???)
11 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.
12 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.
13 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.
14 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.
15 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).
16 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.
17 Current model development Being extended to PLANET Strategic model, but significant problems encountered: –Individual zone-to-zone movements are allowed to rail- head 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 point- to-point fares into account when running assignment. –Left with less than ideal combination of fares matrices combined with p/km adjustments for rail-heading.
18 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.
19 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).
20 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.
21 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 frequency- based models?
22 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.
23 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.
24 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.
25 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)?
26 Current EMME/2 problems SRAs 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
27 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?
28 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.
29 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.
30 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
32 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.
33 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.
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