HS2 Airport Demand Model: A Report for HS2

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HS2 Airport Demand Model (ADM):A Report for HS2

Final Report

February 2010


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The SKM logo trade mark is a registered trade mark of Sincl air Knight Merz Pty Ltd.

HS2 Airport Demand Model (ADM):A Report for HS2

Final Report

February 2010

Sinclair Knight MerzVictoria HouseSouthampton RowLondonWC1B 4EAUnited KingdomTel: +44 20 7759 2600Fax: +44 20 7759 2601Web: www.skmconsulting.com

COPYRIGHT: The concepts and information contained in this document are the property of SinclairKnight Merz (Europe) Limited. Use or copying of this document in whole or in part without thewritten permission of Sinclair Knight Merz constitutes an infringement of copyright.

LIMITATION: This report has been prepared on behalf of and for the exclusive use of SinclairKnight Merz (Europe) Limiteds Client, and is subject to and issued in connection with the provisionsof the agreement between Sinclair Knight Merz and its Client. Sinclair Knight Merz accepts noliability or responsibility whatsoever for or in respect of any use of or reliance upon this report by anythird party.


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SINCLAIR KNIGHT MERZ

PAGE 1

Contents

1. Foreword 22. Background 33. Methodology 6

3.1. Adaption of LASAM 63.2. Catchment Area 83.3. Air Passenger Segmentation 93.4. Time Period 103.5. Base Year Data 103.6. Forecast Year Data 123.7. Mode Choice Hierarchy 133.8. Cost Data 153.9. Generalised Cost Equations 183.10. New Rail Methodology 21

4. Elasticity Validation 225. Conclusion 23Appendix A

DfT Air Passenger Forecasts: Transfer Demand 24


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1. Foreword

High Speed 2 (HS2) is a proposed high speed rail link from London to the West Midlands.

For the purposes of this document it is assumed that the only potential stops will be

Manchester, Birmingham, a Heathrow Hub, London and an intermediate stop between

London and Birmingham. The provision of a link to Heathrow itself will also be considered.

The remit for HS2 is to:

operate a High Speed Rail scheme between London and the West Midlands;

provide access to Heathrow (either directly or via Heathrow Express or Crossrail);

possibly include an intermediate station (between London and Birmingham e.g. MiltonKeynes, Oxford) possibly a parkway station;

connect with HS1;

provide a case for running international services; and

provide opportunity to extend further north of Birmingham (Manchester and beyond).

SKM has been commissioned to deal with three specific segments of HS2 passenger demand

that cannot be easily represented in the Planet Strategic Model (PSM):

diversion to HS2 of current Heathrow surface access trips in the HS2 corridor

excluding trips from London1;

diversion to HS2 of air passengers that take a domestic flight to/from Heathrow and an

international flight to/from Heathrow; and

diversion to HS2 of air passengers that fly internationally from non-London UK airports

who could use HS2-HS1 as an alternative.

The first two market segments are modelled using a spreadsheet mode choice model,

drawing upon knowledge from LASAM2; this is described in Section 3. The third segment is

handled by a separate spreadsheet model, drawing heavily upon existing high speed rail links

in Europe and Asia which compete against air; this is described in a separate document3.

The base year for all cases is 2007/8; the forecast years are 2021 and 2031.

1 There are already 3 rail options (and a 4th planned) for travel between London and Heathrow, this is

not a market that HS2 is targeting.2 London Airports Surface Access Model v2, created by SKM for BAA. BAA has given permission

for the use of LASAM parameters for this project.3International Rail Travel Demand Model (IRTDM): A Report for HS2, SKM, February 2010.


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PAGE 3

2. Background

An analysis of CAA air passenger surveys from 2007 and 2008 at Heathrow Airport reveals

the mode of transport used to access the airport. Table 1 contains the mode shares for all

surface access trips to the airport as well as a breakdown by catchment area4. Car is the

dominant mode for (Non-London) areas close to the airport, while rail gains a greater mode

share as distance from the airport increases.

Table 1: Heathrow Airport Annual Surface Access Mode Shares by CatchmentArea, 2007/08 CAA Data

5

Main Mode Share

Catchment AreasAll UK

Intermediate Birmingham Manchester

Bus/Coach 11.1% 20.3% 12.9% 8.4%

Rail 8.8% 15.5% 39.9% 26.7%

Taxi 15.8% 9.8% 2.6% 25.6%

Park-and-Fly 27.3% 23.7% 19.3% 11.1%

Kiss-and-Fly 31.6% 24.4% 17.9% 23.0%

Charter Coach 3.7% 2.3% 3.3% 2.4%

Other 1.7% 3.9% 4.2% 2.9%

Total demand (over 2 years) 2,961,447 3,603,594 1,437,877 85,456,697

% of Heathrow surface accesstrips 3.5% 4.2% 1.7% 100.0%

In principle, a direct airport rail service to Heathrow Airport could be expected to attract

significantly improved rail mode share compared with the existing connecting services

through London, which are considerably longer and more complicated. Current in-vehicle

times are shown in Table 2.

Table 2: Indicative Time and Distance

In Vehicle Time (hours:mins)

Origin Destination Distance (road) CurrentRail*

CurrentCar

CurrentAir

WithHS2

Manchester London (Euston) 208 miles 2:10 3:10 - 1:30

Manchester Heathrow Airport 207miles 3:15 3:30 1:00 1:15

Birmingham London (Euston) 116 miles 1:25 2:10 - 0:55

Birmingham Heathrow Airport 115 miles 2:30 2:00 0:35 0:40

*Current rail connection is via WCML with a connection to tube at Euston

4 Refer to Section 3.2 Catchment Areafor further details5

CAA expansion, mode shares recalculated to reflect main mode rather than the final mode reportedin CAA publications


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PAGE 4

High speed rail will also compete against the domestic air market where passengers transferat Heathrow Airport for international destinations. Since there are no domestic flights from

Birmingham, East Midlands or Liverpool to Heathrow, the primary market is Manchester,

with the possibility of attracting some of the domestic air market from Newcastle, Edinburgh

and Glasgow to Heathrow, see Figure 1.

In 2008 the Manchester to Heathrow route carried 910,000 passengers (approx one third of

domestic passengers at Manchester and one sixth at Heathrow), although the total has

declined in recent years, as shown in Figure 2. This is consistent with the trend from

Newcastle, Edinburgh and Glasgow Airports (see Figure 3).

Figure 1: Domestic Air vs Rail


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PAGE 5

Figure 2: Domestic Air Passengers between Manchester and Heathrow Airports,1990-2008. Source: CAA

Figure 3: Domestic Air Passengers to Heathrow Airport, 1990-2008. Source: CAA


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3. Methodology

3.1. Adaption of LASAM

The new rail service (HS2) has been modelled along with all existing access modes to

Heathrow Airport. To facilitate the choice of mode from each origin zone, LASAM v2 was

adapted to a spreadsheet model with the following key features and simplifications:

focus on the study corridor: London West Midlands North West (excluding the

London area);

three catchment areas - Manchester, Birmingham and an Intermediate area containing

Oxford and Milton Keynes, each containing all PSM zones in those catchment areas;

retain the same hierarchical mode choice structure as LASAM;

remove Heathrow Express, Underground, RailAir Coach and Airport Transfers as main

mode options as they are only relevant to trips from London;

add HS2 as a rail sub mode;

add Air as a public transport sub mode;

retain the same sensitivity parameters as LASAM;

select an appropriate modal constant for HS2;

select an appropriate modal constant for Air; and

use one zone to represent Heathrow. The central terminal area is used as a reference for

level-of-service.

As most air passengers using Heathrow who originate in the catchment area will be

travelling on international rather than domestic flights from Heathrow, international model

coefficients and economic assumptions were adopted from LASAM rather than the domestic

equivalents.

The spreadsheet mode choice model is used to forecast the change in mode shares from a

current situation and can therefore be referred to as an incremental model. To accommodate

HS2 being a completely new service, the rail sub-nest uses an absolute model. Where the rail

mode share is less than 5% in the base year, forecasts with HS2 are instead be incremented

off the bus/coach mode share.

The model structure, including all data inputs, is shown in Figure 4.


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PAGE 7

Figure 4: Airport Demand Model Structure

Airport Spreadsheet Model

(LASAM Incremental

Model)

CAA 2007/08 base

demand matrix and

mode shares

DfT growth forecasts

Base GeneralisedCosts

Forecast

Generalised

Costs

Forecast mode shares by

segment and zone

PSM base cost

skims

PSM forecast cost

skims with and

without HSR

Economic

Assumptions

LASAM base

cost skims


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PAGE 8

3.2. Catchment Area

The expected catchment areas for HS2 rail trips are highlighted in Figure 5. As the

catchment areas contain less than 10% of the air passengers accessing Heathrow, the number

of CAA interviews (combining 2007 and 2008) was 2,900 from Birmingham, 1,200 from

Manchester and 5,100 from the Intermediate area. The catchment areas could be extended to

any non-London zones to accommodate a change in HS2 station location.

Figure 5: HS2 Route and Catchment Areas

Note: Manchester catchment area extends northwards to include all of Scotland


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3.3. Air Passenger Segmentation

LASAM segments air passengers at Heathrow into 6 passenger segments. To limit the

segmentation of data, and to remain consistent with PSM, the Airport Demand Model has

aggregated these into the following four major segments6:

UK Business air passengers residing in the UK and travelling on business;

Foreign Business air passengers residing outside the UK and travelling on business;

UK Leisure air passengers residing in the UK and travelling for leisure purposes; and

Foreign Leisure air passengers residing outside the UK and travelling for leisure

purposes

PSM is focused on UK rail journeys and segments passengers differently to LASAM. Table3 shows the assumed equivalence between PSM and LASAM passenger segments. PSM

also provides highway and air cost skims, the passenger segments of these differ for each

mode and are described in Table 4 and Table 5.

Table 3: Equivalent Segments of Rail Passengers

PSM segment SKM equivalent segment Reason

Business, car available to / from UK Business

Foreign Business

Car available at home/workplace origin for

departing air passengers

Others, car available to / from UK Leisure

Foreign Leisure

Car available at home/workplace origin for UK

departing air passengers.

Foreign travellers have option of being dropped

off by friends/relatives (Kiss and fly)

Table 4: Equivalent Segments of Road Passengers

PSM segment SKM equivalent segment Reason

Business UK Business

Foreign Business

Same time and distance skim for all air

passengers, higher Vehicle Operating Cost

(VOC) for business segment

Other UK Leisure

Foreign Leisure

Same time and distance skim for all air

passengers, lower VOC

Table 5 Equivalent Segments of Air Passengers

PSM segment SKM equivalent segment

Business UK Business

Foreign Business

Leisure UK Leisure

Foreign Leisure

6 LASAM further splits the UK market segments into domestic and international destinations


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3.4. Time Period

PSM matrices represent an annual average weekday (16-hours) whereas LASAM models

annual air passengers by separate time periods. There are four time periods, one representing

the weekend and three to represent different time periods within a weekday. Details of the

weekday time periods and how they relate to the CAA air passengers surveys is shown in

Table 6. The overall proportion of trips by time period is for combined data for 2007 and

2008, noting that the CAA air passenger survey is on departing air passengers and then

scaled to represent all air passengers.

To be consistent with PSM, the airport spreadsheet model does not distinguish between time

periods. In order to use LASAM cost skims they are averaged using the weights listed in

Table 6.

Table 6 LASAM Time Periods (Weekdays)

Time Period Airport Entrance CAA Survey Time 2007/08Proportion

AM Peak (weekdays) 0700-1000 0900-1200 22%

PM Peak (weekdays) 1600-1900 1800-2100 17%

Interpeak (weekdays) Rest of the day Rest of the day 61%

The Airport Demand Model uses base data covering a full year. To convert this into an

annual average weekday, for output to PSM, the CAA data for 2007 and 2008 was analysedto calculate the most appropriate factor. It was found that on average 121,800 air passengers

access the airport by a surface mode on weekdays, compared to 107,900 on the weekend.

Taking the average weekday total and dividing by the annual total gives a conversion of

0.28% of the annual air passengers on an average weekday.

3.5. Base Year Data

A base year matrix of annual air passengers by segment, origin and mode is created by

combining surface access modes and domestic air passengers as described below. The base

matrix represents all people that could switch to HS2 in order to access Heathrow Airport.

Surface Access

CAA surface access mode shares and the overall total of air passengers at Heathrow Airport

were found to be very consistent between 2007 and 2008. Using the same process as in

LASAM, SKM allocated each air passenger a main mode of surface access based on the

combination of modes used to access the airport as stated in the CAA survey. The resulting

mode shares, excluding other modes such as walking and bicycle, are shown in Table 7.


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Table 7: Surface Access Main Mode Shares, Excluding Other Modes

Mode 2007 2008 2007/08 average

Bus/Coach 8.3% 9.0% 8.6%

Rail 26.5% 28.2% 27.3%

Taxi 26.5% 25.7% 26.1%

Park-and-Fly 12.3% 10.3% 11.3%

Kiss-and-Fly 23.0% 24.0% 23.5%

Charter Coach 2.7% 2.1% 2.4%

Airport Transfer 0.7% 0.6% 0.7%Total pax (million) 42.48 41.14 41.81

Domestic Air Access

This model only includes air passengers that are travelling via a domestic flight to Heathrow

in order to transfer onto an international flight. Those travelling to Heathrow only are

accounted for within PSM. Manchester, Edinburgh, Glasgow and Newcastle were the only

airports considered for inclusion in the model.

CAA surveys on air passengers travelling between Manchester and Heathrow Airports were

analysed to find out the proportion of number passengers transferring to another flight atHeathrow. Table 8 shows that on average in 2007/08, 65% of air passengers on the

Manchester-Heathrow route transfer to another flight at Heathrow. A small number also

connect at Manchester or both airports, these trips are ignored along with the point to point

trips.

Table 8: Domestic Air Passengers, Manchester to Heathrow

Connection type 2007 20082007/08Average

Connect at MAN 23,375 8,645 16,010

Connect at Heathrow 642,759 575,207 608,983

Connect Both Ends 11,911 4,091 8,001

Point to Point 300,075 319,602 309,838

Total 978,120 907,544 942,832

SKM analysed the CAA survey data to see if any of these trips should be excluded based on

characteristics that would suggest they would be unlikely to switch to HS2. Reasons may

include:

packaged flight deals which include the UK domestic leg at (or close to) zero fare -

although it may be possible that airlines could arrange for the domestic leg to be

provided instead by train similar to Air France;


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PAGE 12

transit passengers that do not have to leave the plane at Heathrow; and transfer passengers that have a simple connection at Heathrow, either with the same

airline or a codeshare airline.

The analysis proved inconclusive with the following findings:

all inclusive packages are on a steady decline, from 23% of transfer passengers in

2005 to 12% in 2008; and

only two airlines fly between Manchester and Heathrow (British Airways and British

Midland). These two airlines account for 48% of all flights in/out of Heathrow inferring

that a high proportion of transfer passengers will naturally (rather than by specific

choice) fly the domestic and international leg of their journey with the same airline.

For these reasons all transfer passengers have been included in the analysis.

The same detailed level of analysis was not possible on Edinburgh, Glasgow or Newcastle

Airport as CAA does not survey them as regularly as other UK airports. The last available

survey at each Airport was in 2005. Overall totals can, however, be obtained from the

Heathrow survey, as shown in Table 9. The distribution of trips by segment and zone from

the 2005 survey was applied to the 2008 total transfer passengers at Heathrow.

Table 9: Domestic Air Passengers, Edinburgh, Glasgow and Newcastle toHeathrow, 2008

Connection type Edinburgh Glasgow Newcastle

Connect at Heathrow 555,569 563,361 292,138

Connect atEdinburgh/Glasgow/Newcastle 4,824 6,140 -

Connect Both Ends 11,541 3,214 -

Point to Point 748,364 570,499 168,881

Total 978,120 907,544 942,832

3.6. Forecast Year Data

Similar to the base year matrix, a forecast matrix is required which represents all people thatcould switch to HS2 in order to access Heathrow Airport. It is a matrix of annual air

passengers by segment and origin, which is created by combining surface access and

domestic air passenger trips. The forecast data obtained is outlined below.


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Surface Access

The Department for Transport (DfT) provided forecasts for the number of non-transfer air

passengers at Heathrow, segmented by zone and segment for 2020 and 20307. These

forecasts were used to represent 2021 and 2031.

Domestic Air Access

The Department for Transport (DfT) provided forecasts for the volume of domestic air travel

from UK airports to Heathrow for 2020 and 2030. Only air passengers from Manchester,

Edinburgh, Glasgow and Newcastle that transfer to another flight at Heathrow were

included. These forecasts were used to represent 2021 and 2031. Note that the number of

transfer passengers has dropped considerably in the DfT forecasts as shown in Table 10.Further discussion of this issue can be found in Appendix A.

Table 10: Transfer Air Passengers at Heathrow Airport

Airport 2008 - CAA 2020 - DfT 2030 - DfT

Edinburgh 555,569 343,635 371,390

Glasgow 563,361 288,015 448,980

Manchester 608,983 330,413 429,696

Newcastle 292,138 292,369 384,797

Total 2,020,051 1,254,432 1,634,863

3.7. Mode Choice Hierarchy

PSM cannot supply separate skims by each existing rail type; it can, however, supply skims

with and without HS2 so that the new rail mode can be modelled separately. To

accommodate this, all existing rail modes are combined and referred to as standard rail. This

combined mode uses the LASAM modal constant for standard rail, as the majority of the trip

is made on this mode. HS2 uses the modal constant for Non-London Heathrow Express

passengers8.

The airport spreadsheet model has adopted the same tree structure as LASAM with the

following modifications:

RailAir Coach (overall 0.6% mode share) treated as standard rail;

Passengers arriving at the airport by London Underground or Heathrow Express are

modelled as standard rail;

Air added to PT (or equivalent) nest;

HS2 added to the rail sub-nest (an absolute nest);

7 All forecast data is from the Central demand case, for the central "s12s2" runway development

scenario as reported in the DfT's 'UK Air Passenger Demand and CO2 Forecasts, January 2009.

8 No recent research into modal constants for long distance high speed rail services could be found.


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Charter Coach fixed at the 2007/8 mode share by zone (overall 3.0% mode share); Other modes (3% mode share) ignored; and

Air Transfer9

not modelled as it is not valid within the catchment area.

The resulting mode choice hierarchy for each passenger segment is shown in Figure 6 -

Figure 8. The added modes (HS2 and Air) are highlighted in each diagram.

Figure 6: UK Business Mode Choice Hierarchy

Rail Park andFly

Kiss andFly

Bus/Coach

StandardRail

HighSpeed2

TaxiAir

Figure 7: Foreign Business Mode Choice Hierarchy

Kiss andFly

Rail Bus/Coach

Park andFly

StandardRail

HighSpeed2

Taxi Air

Other

9

The Air Transfer mode refers to air passenger transfers by designated coach between Heathrow,Gatwick and Stansted airports.


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Figure 8: Leisure Mode Choice Hierarchy

Kiss andFly

Rail Bus/Coach

Park andFly

StandardRail

HighSpeed2

Taxi

Air

PT

3.8. Cost Data

To ensure the Airport Demand Model is as compatible with PSM as possible, where

available, cost skims from PSM are used in preference to those from LASAM. A detailed list

of the rail cost skims and how they are used in the LASAM generalised cost equations is

provided in Table 11. Similarly, highway cost skims are described in Table 12 and air cost

skims in Table 13.


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Table 11 Components of Generalised Cost - Rail

PSM Cost

Component

Description SKM equivalent

Rail Fare () Average yields by journey purpose produced in Atkins EDGE model

based on inputs from NMF (DfT) revenue and journey data.

Rail Fare converted

to pence

In Vehicle Time

(mins)

Time spent on the train. In Vehicle Time

(mins)

Auxiliary Transit

Time (mins)

For Heathrow trips the auxiliary transit time includes car access time

to the station or PT access time to the station (it also includes tube

transfer times between terminals in London). It also potentially

includes PT transfer times at the destination end, i.e. the distance

from the station to the airport terminals, or requirement to transfer.

Access time + Walk

time

Total Wait Time

(mins)

40% of headway. Increased to 50% to

be consistent with

LASAM, capped at

40min

Rail Only

Boardings

This is the average number of trains required to get from A to B.

Using the tube to transfer between stations is included in the "aux

transit time", and not counted as a boarding.

Interchanges = rail

only boardings 1

Bus Add Crowd

Time

Skim of PDFH crowding function (minutes) Not included

Table 12 Components of Generalised Cost - Highway

PSM Description LASAM equivalent

Vehicle

Operating Cost

A combination of fuel and non-fuel operating costs, related

to distance and average speed.

Vehicle Operating

Cost

Auto Times

(mins)

Time spent in the car. Time

Auto Distance

(kms)

Highway distance. Distance

Table 13 Components of Generalised Cost - Air

PSM Description LASAM equivalent

Air fares () One way fares. Air fare

In Vehicle Time

(mins)

Time spent in the plane. In Vehicle Time

Auxiliary Transit

Time (mins)

Car time +park/access penalties + VOCs. Access

Wait Time

(mins)

Time spent in airport waiting. Wait time


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PAGE 17

Table 13 shows that the PSM Air skims do not include the check-in time. This is aconsiderable amount of waiting time which needs to be included in the generalised cost

equation. LASAM applies a distribution of lead times to simulate the time it takes an

arriving air passenger between entering the terminal entrance and the plane departure time.

Separate distributions are applied for business and leisure passengers; leisure passengers

typically arrive at the airport earlier. To simplify this procedure the average lead time has

been extracted from LASAM and used in the Airport Demand Model. The implemented

values are shown in Table 14.

Table 14: Assumed Check-In Times

Segment Departure Lead time

Business 1hr 45minLeisure 2hr 15min

Since transfer passengers are modelled, there is a possibility that this check-in time is being

double counted for some passengers who have a streamlined check-in at Heathrow Airport.

PSM contains a mode choice model. However, it does not include coach due to unreliable

coach travel data being available and the hypothesis that existing coach travellers would

not switch to high speed rail where a rail alternative is already available which they have

chosen not to use.

The Airport Demand Model does model coach trips. There are twice as many coach trips inthe study area compared to all surface access trips to the airport (16%), this figures is almost

on a par with the number of rail trips from the study area (17%). Coach cost skims are

derived from LASAM by aggregating time periods and applying the following assumptions:

2008 coach level of service from LASAM used as a base;

no changes assumed to coach services in the catchment area in 2021/31;

headway, access time and number of interchanges remain unchanged;

base coach fares grown to forecast year using growth rates that SKM agreed upon with

DfT for the recent Stansted Airport Planning Application;

base coach IVT grown to forecast year using growth in highway times by zone; and

where the PSM zoning system is more detailed than LASAM, the same cost is allocatedto each PSM zone. Where LASAM is more detailed the costs from the most populous

LASAM zone is applied.

PSM outputs highway times and vehicle operating costs, but it does not provide information

on associated charges such as taxi/minicab fares and airport parking charges. Parking

charges, parking duration and group size are applied by passenger segment as per LASAM.

Taxi/Minicab fares are extracted from LASAM as follows:

assume that no one uses the more expensive black cab from Non London zones (as

LASAM), only Minicab;

fare is the same regardless of time of day;


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PAGE 18

adopt base Minicab fares collected in August 2008 by SKM and used in LASAM; and base fares grown to forecast year using WebTAG growth rates.

3.9. Generalised Cost Equations

The components of generalised cost described in section 3.8 are combined to form the

generalised costs by mode, segment and zone using the following equations:

UK Business Passengers Generalised Cost Formulae

Rail (L,S,X): .)(*)(

X/L/M/HInterchZ

DFareAccessWalkWaitTime

R

p+++++

Bus/Coach:

.)(*)(

X/L/M/HInterchZ

D

FareAccessWaitTimeB

p+

+++

Taxi:

)(

X/L/M/H

DN

FareTimep

+

Park and Fly:

)(

)(

X/L/M/H

DN

VCostPCostTime

p

++

Kiss and Fly:

Air:

)(

).2 X/L/M/H

D

N

Time

N

VCostPCostTime dp

+

++

)(D

FareAccessWaitTimep +++

where D = Highway Distance, = 0.4 and N = Group Size

UK Leisure Passengers Generalised Cost Formula

Rail (L,S,X):

.)(*)(

X/L/M/HInterchZ

D

FareAccessWalkWaitTimeR

p+

++++

Bus/Coach:

.)(*)(

X/L/M/HInterchZ

D

FareAccessWaitTimeB

p+

+++


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PAGE 19

Taxi:

)(

X/L/M/H

DN

FareTimep

+

Park and Fly:

)(

)(X/L/M/H

DN

VCostPCostTimep

++

Kiss and Fly:

Air:

)(

)(.35.0 2X/L/M/H

D

TimeN

Time

N

VCostPCostTime dp

++

++

)(D



Foreign Business Passengers Generalised Cost Formulae

Rail (L,S,X):

.)(*)(

X/L/M/HInterchZ

D

FareAccessWalkWaitTimep+

++++

Bus/Coach:.)(*

)(

X/L/M/HInterchZ

D

FareAccessWaitTimep ++++

Taxi:

)(

X/L/M/H

DN

FareTimep

+

Park and Fly:

)(

)(X/L/M/H

DN

VCostHireCostTimep

++

Kiss and Fly:

Air:

)(

)(.2 X/L/M/H

D

NTime

NVCostPCostTime dp

+

++

)(D




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The generalised cost parameters used in the formulae are given in Table 15 below for boththe base year and forecast future year (2031).

Table 15: Generalised Cost Parameters

2008 2031

UK

Business

UK

Leisure

Non-

UK

Business

Non-

UK

Leisure

UK

Business

UK

Leisure

Non-

UK

Business

Non-

UK

Leisure

Value of time (Heathrow) p/min 73.60 27.01 64.77 26.97 110.90 37.52 97.63 37.46

Vehicle operating cost p/km 11.79 5.39 5.39 5.39 10.54 4.81 4.81 4.81

Time coefficient (p) 0.18 0.20 0.22 0.25 0.18 0.20 0.22 0.25

Wait coefficient 0.49 0.55 0.47 0.66 0.49 0.55 0.47 0.66

R_Walk coefficient 0.17 0.25 0.22 0.30 0.17 0.25 0.22 0.30

Access coefficient 0.55 0.96 0.93 1.17 0.55 0.96 0.93 1.17

Rail Interchange coefficient 0.81 0.61 0.44 0.74 0.81 0.61 0.44 0.74

Bus Interchange coefficient 1.63 0.90 0.44 1.09 1.63 0.90 0.44 1.09

K&F time coefficient 2 (d) 0.13 0.22 0.02 0.10 0.13 0.22 0.02 0.10

K&F time coefficient 3 - 0.001 - 0.002 - 0.001 - 0.002

Distance exponent 0.40 0.50 0.40 0.50 0.40 0.50 0.40 0.50

3.10. New Rail Methodology

Where the rail share is less than 5% in the base year for a particular zone, forecasts with HS2

are incremented off the base bus/coach mode share for that zone. Note that if HS2 is not in

the forecast scenario then this methodology is not used.


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4. Elasticity Validation

To test that the model produces sensible results, a number of sensitivity tests have been run

and compared against equivalent runs using the full version of LASAM. As HS2 is not

coded in LASAM, the most comparable test is a 2008 run. Even though the two models have

different input costs skims (except for bus and taxi) the resulting elasticities are expected to

be consistent within the catchment area, as defined in Figure 5. The results are shown in

Table 16 with the Airport Demand Model showing sensitivity levels similar to LASAM.

Two further elasticities were calculated from the ADM base model to access the sensitivity

of the model to changes in Air fare and Air IVT, see Table 17.

Table 16: Elasticities from LASAM and ADM

Sensitivity

All Zones Catchment Area LASAMEstimationReportLASAM LASAM ADM

All rail demand to All rail fare -0.25 -0.70 -0.30 -0.20 to -0.28

All rail demand to All rail IVT -0.45 -0.70 -0.61 -0.37 to -0.52

Car demand to Car time -0.49 -0.49 -0.54 -0.23 to -0.42

Table 17: Elasticities from LASAM and ADM

Sensitivity Catchment Area All Non-London ZonesAir demand to Air fare -0.22 -0.23

Air demand to Air IVT -0.05 -0.06


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PAGE 23

5. Conclusion

LASAM has been adapted to a simplified spreadsheet format so that it can be used to predict

the mode choice made by air passengers to access Heathrow Airport. Two modes, Air10

and

HS2, which are not modelled in LASAM, have been included. One of the key simplifications

is that it only represents air passengers that originate from Non-London areas.

Base and forecast cost skims for rail, car and air are taken from PSM and are the key input to

the spreadsheet. Cost skims for other modes such as coach and taxi are provided from

LASAM as a fixed input for each forecast year. The spreadsheet model has been set up to

allow different HS2 routes can be tested, although it was calibrated based on the assumption

of HS2 passing through the West Midlands up to Manchester.

The model produces forecasts of air, car, standard rail, high speed rail and bus demand by

zone, business and leisure passenger segments and direction for an annual average weekday.

10 Domestic air travel


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Appendix A DfT Air Passenger Forecasts:Transfer Demand

All forecast data is from the central demand case, for the central "s12s2" runway

development scenario as reported in the DfT's 'UK Air Passenger Demand and CO2

Forecasts, January 2009.'

DfT expect to see all transfer passengers grow at Heathrow at significantly slower rates than

direct point to point traffic. The DfTs forecasting consultants have provided the following

explanation for this phenomenon (in descending order of importance):

The DfT forecasts are constrained to runway capacity. As underlying demand exceedscapacity at Heathrow a "shadow cost" or fare premium is imposed on each air transport

movement (ATM) using a Heathrow runway. This shadow cost is distributed among all

passengers on the aircraft: therefore passengers on large fully loaded aircraft will pay

less per head than those on smaller aircraft. Long haul routes will therefore do relatively

better as constraints "bite". Domestic transfer passengers face a double shadow cost

because a single transfer trip is charged twice for runway use, once on the domestic leg

and once on the international leg. One of the legs will also by definition be on a smaller

domestic aircraft with higher shadow costs per head. Shadow costs can cause the trip to

either re-route away from the congested hub or be suppressed from travelling altogether.

Sensitivity to shadow costs varies by passenger purpose - leisure passengers with lower

values of time being more sensitive. Shadow costs are modelled at Heathrow from 2006-

2030 and because of the growth in underlying demand are not cleared by the

introduction of the new runway in 2020.

The DfT models all major UK airports and routeings via the three largest continental

hubs. The passenger to airport allocation procedures examine the viability of transfer

passengers switching to direct flights from the regional airports or alternatively

transferring to an alternative hub e.g. Amsterdam, Paris or Frankfurt. Neither the

regional airports nor the overseas airports have shadow costs so direct routes and use of

foreign hubs becomes progressively more attractive as the Heathrow (and other London

area) shadow costs rise. Where a direct route from a regional airport does not exist at

present, a route viability test checks for the future viability of the route in every

modelled year given the potential to "claw back" transfer passengers from the London

hubs, thereby potentially further decreasing the attractiveness of the London hubs. The surface access inputs to the airport to passenger allocation process take account of

changes to future airport accessibility by road and rail. Improvements to the West Coast

Main Line are included in the forecast years but not in the base. This will make a surface

journey to Heathrow relatively more attractive than a domestic air journey from certain

ground origins in the forecast years.

Documents

HS2 Airport Demand Model: A Report for HS2