HS2 London – West Midlands Consultation Model Development and Baseline Report Report for HS2 Ltd In Association With Mott MacDonald April 2011

Document Control Project Title:

Model Development and Baseline Report

MVA Project Number:

C3A241

Document Type:

Report

Directory & File Name:

H:\Railair\C3A24100 HS2 London To West Midlands Public Consultation\Technical Documentation\Model Development And Baselining Report\20110412 HS2 Model Development And Baseline Report V6.3.Doc

Document Approval Primary Author:

Tony Milward

Other Author(s):

Adam Mason, Mandy Yip

Reviewer(s):

Chris Pownall, John Segal

Formatted by:

DE

Distribution Issue

Date

Distribution

Comments

1

18/03/2011

Chris Pownall

First Review

2

20/03/2011

John Segal

Second Review

3

20/03/2011

HS2

Draft Report

4

29/03/2011

HS2

Second Draft

5

06/04/2011

HS2

Third Draft

6

07/04/2011

HS2

Fourth Draft

7

12/04/2011

HS2

Final

This report, and information or advice which it contains, is provided by MVA Consultancy Ltd solely for internal use and reliance by its Client in performance of MVA Consultancy Ltd’s duties and liabilities under its contract with the Client. Any advice, opinions, or recommendations within this report should be read and relied upon only in the context of the report as a whole. The advice and opinions in this report are based upon the information made available to MVA Consultancy Ltd at the date of this report and on current UK standards, codes, technology and construction practices as at the date of this report. Following final delivery of this report to the Client, MVA Consultancy Ltd will have no further obligations or duty to advise the Client on any matters, including development affecting the information or advice provided in this report. This report has been prepared by MVA Consultancy Ltd in their professional capacity as Consultants. The contents of the report do not, in any way, purport to include any manner of legal advice or opinion. This report is prepared in accordance with the terms and conditions of MVA Consultancy Ltd’s contract with the Client. Regard should be had to those terms and conditions when considering and/or placing any reliance on this report. MVA Consultancy has agreed to this report being published on the basis that: (a) that no Third Party acquires any rights, contractual or otherwise, whatsoever against MVA Consultancy Ltd and MVA Consultancy Ltd, accordingly, assume no duties, liabilities or obligations to that Third Party, and (b) MVA Consultancy Ltd accepts no responsibility for any loss or damage incurred by the Client or for any conflict of MVA Consultancy Ltd's interests arising out of the Client's publication of this report.

2

3

Contents 1

Introduction

1.1

Background

7

1.2

The HS2 Modelling Framework

7

1.3

Summary of Model Changes since March 2010

9

1.4

Structure of Report

2

Exogenous Growth Forecasts

2.1

Introduction

12

2.2

Derivation of Rail Forecasts

13

2.3

Impact of Rail Growth Updates

16

2.4

Derivation of Road Growth

19

2.5

Derivation of GB Internal Air Demand Growth

23

2.6

Heathrow Airport Demand Model Update

24

3

Station Choice Model

3.1

Background

27

3.2

Modifications to Railplan Data

27

3.3

London Station Choice spread parameter

28

4

Changes to Transport Supply and Cost Assumptions

4.1

Introduction

30

4.2

Review of Transport Supply Assumptions

30

4.3

Corrections to Transport Supply Coding

30

4.4

Changes to do-minimum scenario to ensure model convergence

31

4.5

Highway Cost Assumptions

32

4.6

Updates to the Heathrow Airport Demand Model

32

4.7

Value of Time assumptions

32

5

Updated Base Year Validation

5.1

Background

34

5.2

PLD Rail Assignment Validation

34

5.3

PLANET South and PLANET Midland Assignment Validation

35

5.4

Conclusions

35

Appendix A – Economic Growth Assumptions Appendix B – Adjustments to Railplan data Appendix C: London Station Choice Spread Parameter Calibration Results Appendix D: Heathrow Airport Demand Model Changes

7

11

12

27

30

34

46 47 49 52

Tables Table 1.1

HS2 Modelling and Appraisal Framework Changes since March 2010

10

Table 2.1

PLANET Long Distance: Growth in Total Weekday Journeys

17

Table 2.2

Passenger Kilometres by Long Distance Franchise (PLD)

18

Table 2.3

Pre-load growth factors by region

20

Table 2.4

Change in highways growth factors: March 2011 compared to March 2010 report

21

4

Contents

Table 2.5

Highway Matrix Totals and Growth

22

Table 2.6

Growth in Long Distance Highway Journeys (PLD)

23

Table 2.7

Daily domestic passenger volumes (2021 and 2043 Reference Case)

24

Table 2.8

2020 and 2030 UK Non-Transfer Air Passenger Forecasts for Heathrow Airport (SPASM)

Table 2.9

(SPASM) Table 4.1

25

2020 and 2030 UK Transfer Air Passenger Forecasts for Heathrow Airport 26

Holyhead Service Specification (note that number of trains in each direction does not balance in actual timetable)

31

Table 4.2

Growth in Values of Time Index for Business and Leisure PLD (2002=100) 33

Table 5.1

North of Midlands Upper Screenline

36

Table 5.2

North of Midlands Lower Screenline

37

Table 5.3

Doncaster Upper Screenline

38

Table 5.4

Doncaster Lower Screenline

38

Table 5.5

Newcastle Upper Screenline

39

Table 5.6

Newcastle Lower Screenline

39

Table 5.7

South of Midlands Upper Screenline

40

Table 5.8

South of Midlands Lower Screenline

41

Table 5.9

London Termini Screenline – MOIRA

42

Table 5.10 Table 5.11

London Termini Screenline – Guard Counts PLANET South Validation Flows (07:00-10:00 arrivals in Central London, 2007)

Table 5.12

43

PLANET Midlands Validation Flows (To Birmingham New Street)

Table A1 Economic Growth Assumptions

44 45 46

Table C1

Model estimation results - Business (in minutes)

49

Table C2

Model estimation results - Leisure (in minutes)

50

Table C3

Model estimation results - Commuting (in minutes)

50

Table C4

Model estimation results - All purposes

51

Table D1

New Assumed Demand Proportions at Heathrow Terminal Areas for 2021 and 2043

52

Table D2

Fare growth

54

Table D3

Growth Indices for Parameters in ADM, 2002 = 100

54

Appendices A - Economic Growth Assumptions B - Adjustments to Railplan data C - London Station Choice Spread Parameter Calibration Results D - Heathrow Airport Demand Model Changes

Model Development and Baseline Report

5

Acknowledgement This report includes some sections authored by WS Atkins relating to work they have undertaken for HS2 Ltd. MVA and Mott MacDonald acknowledge and are grateful for their support in writing this document.

Model Development and Baseline Report

6

1

Introduction 1.1

1.1.1

Background In 2009, Atkins was appointed to develop a forecasting framework for High Speed Two Limited (HS2 Ltd.) to model and appraise options for a high speed rail link between London and the West Midlands. Outputs from that study were published in March 2010 along with a suite of technical documents describing the modelling approach. The modelling approach is briefly summarised in Section 1.2 of this document.

1.1.2

Following on from the initial study a programme of additional work was undertaken to improve the robustness of the modelling and appraisal, and update assumptions underlying the forecasts to reflect political and economic changes. This additional work was focussed on a number of areas:

1.1.3



model enhancements



changes to economic forecasts and their impact on the demand for travel



policy changes – e.g. rail fares – aviation policy



changes to underlying assumptions on supply and costs of transport



scheme changes.

Atkins were responsible for model enhancements up to the end of October 2010. This work is described in their report “Modelling and Appraisal Updates and their impact on the HS2 Business Case - A Report for HS2”.

1.1.4

In October 2010, MVA Consultancy and Mott MacDonald (MVA-MM) were appointed to further develop the model, and produce revised demand forecasts in preparation for the Public Consultation for the London – West Midlands route commencing in February 2011. The main purpose of this report is to describe the changes implemented by MVA-MM and their impacts on the business case; in addition certain changes implemented by Atkins, but not reported by them are also described.

1.1.5

In addition, HS2 Ltd have themselves implemented some refinements to costs and certain aspects of the economic appraisal. These are documented in the HS2 Ltd’s report “A summary of changes to the HS2 Economic Case”.

1.1.6

Section 1.3 summarises all of the updates to the modelling and appraisal approach that have been implemented since March 2010, and in which of the three reports identified above these updates have been documented.

1.2 1.2.1

The HS2 Modelling Framework HS2 proposals have been assessed using a modelling framework known as the PLANET modelling framework. The PLANET modelling framework was specifically developed to assess high speed rail options across the UK, including the location of stations. A brief overview of the model is presented below.

Full details of the model are included in Atkins Model

Development Report: A Report for HS2, published February 2010.

Model Development and Baseline Report

7

0BIntroduction

1.2.2

The PLANET framework consists of three PLANET passenger demand models together with a Heathrow airport demand model integrated into a single framework. These models are:

1.2.3



PLANET Long Distance (PLD)



PLANET Midlands (PM)



PLANET South (PS)



Heathrow Airport Demand Model (ADM)

In the integrated framework the interaction between long distance and local demand is represented.

1.2.4

The framework takes into account a wide range of impacts on travel behaviour such as journey time, train service frequency, interchange (both between modes and within modes), crowding, and station access/egress times. PLANET Long Distance (PLD)

1.2.5

PLANET Long Distance (PLD) is derived from the PLANET Strategic model. It is a multi-modal model with rail, highway and GB internal air (defined below in para 1.2.11) represented. It is an all day model.

1.2.6

A station choice model (SCM) has been incorporated into this model to assess how passengers access long distance rail services in Greater London and the West Midlands. Access/egress information for the SCM is taken from local transport models in London and Birmingham; Railplan (RP – developed and owned by Transport for London) and PRISM (owned by Centro) respectively. PLANET South (PS)

1.2.7

PLANET South (PS) is a tool for modelling local movements on the London and South East rail network.

1.2.8

It is a morning peak rail-only model, and includes all local services in the south of England, as well as the strategic services from other areas into London. Demand matrices for PS are adjusted to remove any demand from zones external to a cordon depicting travel within a South East, South Central and South Western cordon. To represent passengers on strategic services in PS model runs, demand is loaded onto the network at cordon points, to ensure that crowding levels are correctly represented. PLANET Midlands (PM)

1.2.9

PLANET Midlands (PM) is similar to PLANET South, but covers a much smaller area, as the cordon used for this exercise is much tighter, only covering services that are local to Birmingham itself. Again it is a morning peak rail-only model. The extent of the model only covers broadly the West Midlands county (i.e. reaching out as far as Wolverhampton and Coventry). It is a rail-only model with strategic demand passed from PLD in the form of link based pre-loads to ensure that crowding levels are correctly represented.

8

0BIntroduction

Heathrow Airport Demand Model (ADM) 1.2.10

Two separate air passenger markets are represented within the PLANET framework.

1.2.11

GB Internal Air Demand refers to trips made by air where the ultimate starting and finishing location are both within Great Britain (i.e. not including Northern Ireland). These are trips that could be potentially attracted to rail, and as mentioned above, are therefore included in the PLD strategic model. They are not included in the ADM.

1.2.12

Transfer Air Demand refers specifically to passengers travelling to or from London Heathrow to catch flights to international destinations. These are represented in the Heathrow Airport Demand Model (ADM), along with ‘non-transfer’ passengers who are making international journeys starting at Heathrow.

This is a spreadsheet model which

predicts mode of access to Heathrow, and incorporates forecasts of future passenger throughput at Heathrow. 1.2.13

The three following examples help illustrate the distinction: 

a passenger who uses a Manchester – Heathrow flight in the course of travelling from their home in Manchester to go to a business meeting in London counts as GB Internal Air Demand; whereas



a passenger who travels from their home in Manchester and uses the same flight, but instead transfers to an international flight at Heathrow counts as Transfer Air Demand; and



a passenger who travels from their home in Manchester and uses rail or car to access an international flight at Heathrow also counts as Transfer Demand.

1.3 1.3.1

Summary of Model Changes since March 2010 Table 1.1 summarises the changes that have been made to the model and appraisal framework and where they have been documented.

9

0BIntroduction

Table 1.1

HS2 Modelling and Appraisal Framework Changes since March 2010

Report Author and Title

Changes implemented and documented

WS Atkins

Inclusion of business non-car available rail benefits 1

Modelling and Appraisal

Revision of weightings of generalised journey cost

Updates and their Impact

components1

on the HS2 Business Case

Revision of interaction between PLD and PS

- A Report for HS2

SCM changes: - address incomplete capture of local leg benefits - application of behavioural weighting to London local leg benefits - remove double weighting of local leg time transferred to PLD - apply local leg times and station shares on a production/attraction basis rather than OD - revised London local leg costs for London/W. Midlands movements - disaggregate London local leg benefits for economic appraisal - add W. Midland local leg costs to non-London movements Updates to ADM

MVA-Mott MacDonald

Updates to future year demand matrices to take account of:

Model Development and

- revised short-medium term economic growth forecasts

Baseline Report (This

- impact of Coalition government’s policy on regulated rail

Report – includes some

fares (RPI+3% for three years)

further work undertaken

- the use of DfT’s unconstrained air demand forecast rather

by Atkins not documented

than constrained for GB internal air demand

in above report)

- revised forecasts for Heathrow throughput for the ADM Further changes to the SCM: - calibration of the parameter controlling users’ sensitivity to generalised cost - adjustments to access times to reflect the relative ease of interchange at Old Oak Common compared to Euston Changes to behavioural values of time Corrections to coding of certain rail services on the West Coast Main Line (WCML) Addressing convergence problems through changes to the dominimum scenario

HS2 Ltd

Changes to capital costs

A Summary of Changes to

Changes to operating costs

the HS2 Modelling

Changes to treatment of indirect tax

Framework

Impacts of connection to HS1 Corrections to discounting

1

Though discussed in the Atkins Report, these two changes were implemented for the model runs supporting the March 2010 Report.

10

0BIntroduction

1.4 1.4.1

Structure of Report The remainder of this report is structured as follows: 

Chapter 2 explains the updates made to exogenous growth in the model.



Chapter 3 describes updates made to the SCM.



Chapter 4 describes a number of model updates to reflect changes in assumption or corrections to transport supply and costs.



Chapter 5 provides an updated validation of the base year model.

11

2

Exogenous Growth Forecasts 2.1

2.1.1

Introduction This Chapter explains the methodology for forecasting growth in the demand for travel in the markets relevant to HS2.

2.1.2

There have been a number of revisions to these demand forecasts over the course of HS2’s work, primarily to account for changes in forecast economic growth as the long term effects of the recent downturn have become apparent, but also to take into account recent changes in government policy regarding regulated rail fares.

2.1.3

Each of the PLANET models forecasts future travel behaviour by assigning input matrices of trips between different places to the transport network. These input matrices represent the total underlying market for travel, and do not take account of supply side effects, such as improvements in journey time, speed and capacity (as delivered by the WCML upgrade, for example) and constraints such as train, road and airport runway capacity. Supply side effects are applied by the model as part of the assignment process.

2.1.4

In PLD, separate 2008 input matrices are provided for each mode (rail, air, road - mainly car) and journey purpose. PM and PS each have a set of rail only matrices disaggregated by journey purpose. The derivation of these matrices are described in the Model Development Report published in March 2010.

2.1.5

Future year matrices are calculated by applying growth factors to the base year (2008) matrices – different factors can be applied to different cells to represent differences in growth between different geographical markets and journey purposes.

2.1.6

Growth factors are calculated independently for each mode, using standard DfT forecasting models, with the underlying assumptions for each mode being broadly consistent. However, because each mode is treated separately, the rail demand forecasts do not, for example, take account of changes in air or car demand, although they do take account (at least in a simple way) of trends in car costs. The air forecasts do not take account of any changes in rail or car costs or times, nor do the car forecasts take any explicit account of the effect of rail journey times, or highway congestion or fuel costs.

2.1.7

The forecasts continue up to a ‘cap year’, after which there is no further growth in any mode, nor any assumed change to other factors such as rail fares; however, for appraisal purposes the value of time is assumed to increase in real terms over the 60 year appraisal period. Rather than assuming that demand grows indefinitely, applying the cap year is a proxy for the assumption that demand will eventually saturate.

2.1.8

Matrices are calculated for two future years (referred to as ‘modelled years’), the first year being shortly before scheme opening, and the second being the cap year. Demand for the intervening years is calculated by interpolation.

2.1.9

The next section describes how the rail growth forecasts have been revised since the March 2010 report in response to updates to economic forecasts and changes to the government’s fares regulation policy. Sections 2.3 and 2.4 then describe the derivation of the road and air forecasts respectively.

Model Development and Baseline Report

12

1BExogenous Growth Forecasts

2.2 2.2.1

Derivation of Rail Forecasts All forecasts of exogenous rail demand growth used in the HS2 London - West Midlands business case are based on outputs from the DfT’s EDGE 2 model.

2.2.2

EDGE applies rail demand elasticities 3 from the Passenger Demand Forecasting Handbook (PDFH) to a range of different ‘drivers’ of demand, including:

2.2.3



Changes in income (measured through growth in GDP per capita) 4 ;



population growth;



car ownership; and



fares.

Note that, strictly speaking, fares are not exogenous insofar as they are within the control of the rail industry, but in practice are heavily dependent on government policy decisions regarding fares regulation, and are thus treated in a similar way to the ‘true’ exogenous variables.

2.2.4

In keeping with WebTAG guidance (unit 3.15.4, April 2009), the exogenous (socio-economic and cross-modal) elasticities are drawn from PDFH v4.1, with fares elasticities from PDFH v4.0. The elasticity to GDP in PDFH v4.1 is a function of flow distance. For longer flows this can lead to implausibly high elasticities, for example 3.7 for London to Aberdeen. In line with DfT practice, the elasticity is capped at a value of 2.8, corresponding to 250 miles.

2.2.5

EDGE produces demand factors for (a) First plus Standard full-fares, (b) discounted (i.e. ‘Reduced’) products and (c) Season tickets that, after transformation to journey purpose, are applied as uplifts to the 2007/8 base matrices in PLANET Long Distance (PLD), PLANET South (PS) and PLANET Midlands (PM).

2.2.6

For the forecasts used in the March 2010 Report, demand was assumed to grow up to a cap year of 2033. Since that report, assumptions regarding two important drivers of rail demand have changed: 

forecasts of economic growth obtained from the Office of Budgetary Responsibility (OBR) predicted a slower recovery from the recession than in previous forecasts up to 2015/ 16, and, in agreement with DfT, we have assumed slower growth in the medium to long term; and



as part of the October 2010 spending review, regulated rail fares will be permitted to rise at the faster rate of RPI+3% for the three years starting in 2012, rather than the RPI+1% rate that currently applies.

2.2.7

Figure 2.1 compares the economic forecasts used for the March 2010 with those used in the current update. A Table of the GDP data inputs to the model is presented in Appendix A.

2

Exogenous Demand Growth Estimation. ‘Exogenous’ is synonymous with ‘beyond rail industry control’. However, fares’ effects are also

included. 3

Elasticities measure the sensitivity of rail demand to a one per cent change in a given demand driver. For example, a GDP per capita

elasticity of 2.0 indicates that when per capita incomes increase by 1%, rail demand increases by 2%. 4

Note that for Commute trips, employment is used as the driver rather than GDP per capita.

13

1BExogenous Growth Forecasts

Figure 2.1 GDP per capita forecasts 1.8 1.7 Index (2007/8=1.0)

1.6 1.5 1.4

March 2010 Report ‐ HMT with recession [Aut 09]

1.3 1.2 1.1 1.0

This Report ‐ OBR [Budget June 10] to 2015/16, DfT/HMT 2016/17 onwards

0.9

20 07 / 20 08 09 /1 20 0 11 / 20 12 13 /1 20 4 15 /1 20 6 17 / 20 18 19 /2 20 0 21 / 20 22 23 /2 20 4 25 /2 20 6 27 / 20 28 29 /3 20 0 31 / 20 32 33 /3 20 4 35 /3 6

0.8

2.2.8

Both of these changes have the effect of slowing the rate of forecast rail demand growth. Rather than retaining the 2033 cap year, HS2 Ltd took the view that demand was more likely to reach saturation at a particular level of demand, rather than at a particular point in time, so a later cap year has been determined. This cap year has been defined as the year that gives the same level of growth in rail demand in the markets most relevant to HS2 as was previously achieved by the cap year in earlier model runs. Specifically, this is measured by the total flow on the WCML immediately south of Rugby. For the work published in March 2010, the flow on this link was forecast to be 39,000 passengers each way per day in the cap year. The updated forecasts in this report have therefore been capped at the point at which the same flow is obtained with the lower rate of demand growth. Figure 2.2 illustrates the concept.

14

1BExogenous Growth Forecasts

Figure 2.2 Impact of slower economic growth and revised fares assumptions on rail demand growth

Daily average PLD demand on Rugby-Coventry link

45000 40000 35000 HS2 Demand Model Analysis, February 2010 Economic Case, February 2011

30000 25000

growth period extended

20000

Cap demand level

15000 10000 5000 0 2000

2010

2020

2030

2040

2050

Year

2.2.9

Note that, other than during the 2012-2015 RPI+3% period, we adopt a modelling assumption that rail fares are assumed to increase at a rate of RPI+1% up to the cap year. The effect of delaying the cap year is therefore to extend the period over which the RPI+1% assumption applies, which in itself dampens demand and further contributes to the delay in achieving the cap demand level 5 . As the RPI+1% continues for additional years, this means that the average fare (and hence total revenue) is higher in the current cap year of 2043 than in that of the March 2010 forecasts (2033).

2.2.10

Having defined the cap year, the annual rate of growth for other rail and other modes is calculated and hence the level of demand in the model adjusted to reflect the change to this cap year. The average annual growth rates are:

2.2.11



PLANET South

1.14%



PLANET Midlands

1.06%.

The update work was started by Atkins prior to the October 2010 Spending Review, and therefore initially only sought to incorporate the revised economic growth. A new run of EDGE was undertaken for 2021 and an initial revised cap year of 2036. The cap year was determined on the basis of year in which the level of economic growth that had been expected by 2033 in the previous economic forecasts was achieved, and not on the basis set out in para 2.2.7.

2.2.12

The 2036 matrices were subsequently adjusted to incorporate the revised fares regulation assumption, continuing RPI+1% fare growth up to the cap year, and implement the

5

Note that work described in the March 2010 report, the cap year was moved from 2031 to 2033 to proxy for slower economic growth,

but in that analysis the extension of the period of the RPI+1% fare increase was not assumed.

15

1BExogenous Growth Forecasts

improved capping methodology. As a result, the following uplift factors were applied to 2036 EDGE matrices:

2.2.13

PLD Rail

1.130

PLANET South

1.044

PLANET Midlands

1.048

The first forecast year 2021 is retained.

However, (negative) uplift factors needed to be

applied to the rail matrices to reflect the impact of RPI+3% fares growth (i.e. an additional 2% p.a. fares growth on top of the 1% p.a. already assumed) between 2012 and 2015. A fares elasticity was applied from PDFH v4.0 to calculate three single factors, one for each of the matrices. The resulting factors were:

2.3

PLD Rail

0.943

PLANET South

0.967

PLANET Midlands

0.965

Impact of Rail Growth Updates Growth in Reference Case PLANET matrices (2007/8 to 2021 and 2043)

2.3.1

The tables below show the growth in total journeys from 2007/8 after assignment to the three PLANET models’ networks. Table 2.1 summarises certain key rail zone to zone movements in the PLD matrices. Trips in PLD are summed across trips produced at each end of the PLD flow. Higher growth rates for longer-distance flows are consistent with the PDFH forecasting framework, where income elasticities are highest for long-distance flows greater than 200 miles.

16

1BExogenous Growth Forecasts

Table 2.1

PLANET Long Distance: Growth in Total Weekday Journeys

Key HS2 zone to zone

2007/8

2021

movements

demand

demand

Birmingham - Central

%

2043

Growth

demand

% Growth

2007/8 -

2007/8 -

2021

2043

6,600

8,200

23%

15,200

129%

6,000

7,500

24%

14,900

147%

4,800

5,600

18%

10,500

120%

Glasgow - Central London

900

1,200

30%

2,400

174%

Liverpool - Central London

2,400

2,900

19%

5,500

127%

Newcastle - Central London

2,700

3,400

26%

7,000

158%

Edinburgh - Central London

2,000

2,700

34%

6,400

213%

London Manchester - Central London Leeds - Central London

2.3.2

Note that the definitions of zones for the cities used in the above table are larger than those used in the March 2010 Atkins report, so the numbers and growth rates are not directly comparable.

2.3.3

The overall growth to 2043 is broadly similar to that seen up to 2033 in the March 2010 report because the demand cap is applied at a particular level of demand. However, updates to the economic forecasts used since the March 2010 report have not only affected the overall level of forecast growth, but also the forecast relative growth rates between different parts of the country. In most cases this has led to relatively minor differences in growth, but in the case of Leeds, where the economic growth forecasts are now markedly lower, as a consequence the forecast growth on this route has reduced significantly. While this does not significantly impact the London West Midlands business case, it is being examined as part of ongoing work on routes north of Birmingham. Growth by TOC: PLANET Long Distance

2.3.4

Table 2.2 shows the growth in reference case long-distance demand as measured by the change in assigned passenger kilometres by long-distance TOC. These figures exclude local demand modelled in the regional sub-models. These results are consistent with the matrix growth rates reported in Table 2.1, noting that overall growth in passenger kilometres will be lower than the growth rates reported in Table 2.1 as these passenger kilometre figures are for all flows and not just those to/from Central London (where growth is highest).

17

1BExogenous Growth Forecasts

Table 2.2

Passenger Kilometres by Long Distance Franchise (PLD)

TOC

2008

2021

%

2043

growth Intercity East

% growth

14,677,000

17,378,000

18%

32,724,000

123%

3,105,000

3,713,000

20%

6,573,000

112%

3,735,000

4,166,000

12%

7,167,000

92%

14,134,000

16,913,000

20%

29,907,000

112%

Cross Country

8,172,000

8,450,000

3%

11,673,000

43%

Trans Pennine

4,179,000

4,636,000

11%

6,646,000

59%

Coast, plus Open Access Greater Western (South Wales and Cotswold Routes only) East Midlands (Midland Main Line service) Intercity West Coast

2.3.5

It should be noted that: 

East Coast figures include the open-access operators (Hull Trains and Grand Central) that currently operate on the East Coast Main Line, as well as the East Coast franchise;



Cross Country and West Coast figures for 2008 have been adjusted to account for the transfer of Birmingham - Scotland services from the former to the latter TOC between model years. This adjustment enables the growth rates to be representative of exogenous demand impacts only;



Cross Country figures have also been adjusted as far as possible to other aspects of franchise remapping during this period (i.e. the transfer of Birmingham – Stansted Airport and Nottingham – Cardiff services), but changes to individual services means that base year demand is not exactly comparable to future year demand, and growth for this franchise is understated; and



Great Western figures only include flows modeled in PLD. The majority of flows on GW are modeled in PLANET South, with only flows to South Wales and the Cotswolds modeled in PLD

2.3.6

Long distance growth is lower on the Midland Mainline as flows are generally of a shorterdistance than on either the East Coast or West Coast routes, so are affected by the lower short-distance elasticities, as noted above.

18

1BExogenous Growth Forecasts

2.3.7

CrossCountry and Transpennine growth rates are lower than other long-distance franchises as they do not serve London, where demand growth is forecast to be higher than the rest of the country.

2.4 2.4.1

Derivation of Road Growth Road demand is included in the PLD model in two ways: 

long distance (>30km) road passenger demand (predominantly car) is provided in matrix format in a similar manner to rail and air (note any demand within a single zone is excluded); and



in addition, a pre-load representing shorter distance traffic (