Tài liệu Moderling Demand for Long - Distance Travel in Great Britain pdf

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iii
Preface
RAND Europe, in collaboration with Scott Wilson, were commissioned by the UK
Department for Transport to develop a model to predict demand for long-distance
passenger travel on interurban networks using road, rail and air in Great Britain. The
model will be used to appraise the impact of policies and infrastructure aimed at this
market, such as road pricing, rail fares, high-speed rail, highway construction and
operation policies, and policies directed towards domestic air travel. As part of this work a
stated preference study was undertaken to examine the propensity of travellers currently
making long-distance journeys by car, (classic) rail and air to transfer to high-speed rail
services.
Scott Wilson was the lead partner for the overall study and was responsible for
development of the transport supply networks for car, air and rail travel, and the
implementation of the final models into a user-friendly forecasting system. RAND Europe
was responsible for the estimation of the travel demand models, using both stated
preference and revealed preference data.
This report described the stated preference surveys and the analysis of these data that was
undertaken as part of this study. This report has been produced by RAND Europe.
RAND Europe is an independent not-for-profit policy research organisation that serves the
public interest by improving policymaking and informing public debate. Clients are
European governments, institutions and firms with a need for rigorous, impartial,
multidisciplinary analysis of the hardest problems they face. This report has been peer-
reviewed in accordance with RAND’s quality assurance standards (see
http://www.rand.org/about/standards/) and therefore may be represented as a RAND
Europe product.
For more information about RAND Europe or this document, please contact Peter Burge
at:
RAND Europe
Westbrook Centre
Milton Road
Cambridge CB4 1YG
England
+44 (0)1223 353 329
burge@rand.org


v
Contents
Preface iii
Table of Figures vii
Table of Tables ix
Summary xi
Acknowledgements xxiii
CHAPTER 1 Introduction 1
CHAPTER 2 Survey Design and Data Collection 3
2.1 Sampling and Survey Approach 3
2.1.1 Recruitment from the Household Survey of Long-distance
Travel 3
2.1.2 On-train Surveys 4
2.1.3 Air Surveys 5
2.1.4 Sampling Respondents for whom High-speed Rail was
Appropriate 5
2.2 Stated Preference Survey Structure 5
2.3 Stated Preference Choice Experiments 7
2.3.1 Stated Preference Choice Experiments 13
2.4 Overview of the Main Stated Choice Data 14
CHAPTER 3 Model Development 17
3.1 Introduction to Discrete Choice Models 17
3.2 Overview of Attributes Examined Within the Choice Experiments 18
3.3 Modelling Conventions Adopted 18
3.4 Steps in Model Development 19
3.4.1 Modelling Different Substitution Patterns Between Alternatives 19
3.4.2 Examining Cost Sensitivity 20
3.4.3 Testing for Non-linear Journey Time Sensitivity 21
3.
4.4 Influence of Trip Length
on Attractiveness of HSR 21
3.4.5 Investigating whether there is a Threshold in Journey Time 22
3.4.6 Accounting for Inertia 22
3.4.7 Impact of Other Service Characteristics on Mode Choice 22
3.4.8 Socio-economic Differences in Modal Preferences 24
Modelling Demand for Long- Distance Travel in Great Britain: RAND Europe
Stated preference surveys to support the modelling of demand for high-speed rail
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3.4.9 Reviewing the Mode-specific Constants 26
3.4.10 Accounting for the Repeated Measures Property of the SP Data 27
CHAPTER 4 Model Findings 29
4.1 Final Model Results 29
4.2 What Does the SP Data Reveal About Values of Time and Cost
Sensitivity? 34
4.2.1 Values of Time for Long-distance Commuters 34
4.2.2 Values of Time for Long-distance Business Travellers 37
4.2.3 Values of Time for Long-distance Trips for Visiting Friends and
Relatives and Other Leisure 40
4.3 What Does the SP Data Reveal About the Value Placed on Out-of-
vehicle Components? 45
4.3.1 Out-of-vehicle Services Components for Rail 45
4.3.2 Out-of-vehicle Services Components for Air 45
4.4 What Does the SP Data Reveal About the Value of Rail Crowding and
Reliability? 46
4.5 The Benefits of Being Able to Make Return Journey in a Day 47
4.6 Socio-economic Differences in Modal Preferences 47
4.7 Additional Non-measured Benefits of HSR 48
4.7.1 Additional Non-measured HSR Benefits for Commuters 49
4.7.2 Additional Non-measured HSR Benefits for Business Travellers 49
4.7.3 Additional Non-measured HSR Benefits for Those Travelling
for Other Leisure or Visiting Friends or Relatives 50
4.7.4 Conclusions on HSR Mode-specific Constants 50
4.8 Where Does HSR Fit in the Modal Choice Hierarchy? 51
4.
9 Other Findings
52
CHAPTER 5 Conclusions 53
5.1 Conclusions and Key Findings 53
5.1.1 Cost Sensitivity 53
5.1.2 Values of Time 54
5.1.3 Evidence for an HSR constant 54
5.1.4 The location of HSR in the choice hierarchy 54
5.2 Recommended Future Research 55
REFERENCES 57
Reference List 59
APPENDICES 61
Appendix A: Additional Models to Inform the Development of the LDM Model 63

vii
Table of Figures
Figure S.1: Introduction and example choice screen for Experiment 1, all
existing modes xiv
Figure S.2: Introduction and Example Choice Screen for Experiment 2, All
Existing Modes Plus High-speed Rail Alternative xv
Figure S.3: SP Tree Structure xxi
Figure 2.1: Introduction and Example Choice Screen for Experiment 1, All
Existing Modes 11
Figure 2.2: Introduction and Example Choice Screen for Experiment 2, All
Existing Modes Plus High-speed Rail Alternative 13
Figure 3.1: SP Tree Structure 20
Figure 4.1: Commute VOT for those with an Annual Household Income up to
£40,000 (2008 prices) 34
Figure 4.2: Commute VOT for those with an Annual Household Income
between £40,000 and £50,000 (2008 prices) 35
Figure 4.3: Commute VOT for those with an Annual Household Income of
£50,000 or above (2008 prices) 35
Figure 4.4: Commute VOT for those with Unknown Annual Household
Income (2008 prices) 36
Figure 4.5: WebTAG-recommended Values of Time for Commute Travel 37
Figure 4.6: EB VOT for those with an Annual Household Income up to
£30,000 (2008 prices) 38
Figure 4.7: EB VOT for those with an Annual Household Income of £30,000 ~
£75,000 (2008 prices) 38
Figure 4.8: EB VOT for those with an Annual Household Income of £75,000
or above (2008 prices) 39
Figure 4.9: EB VOT for those with unknown Annual Household Income (2008
prices) 39
Figure 4.10: VFO VOT for those with an Annual Household Income under
£10,000 (2008 prices) 41
Modelling Demand for Long- Distance Travel in Great Britain: RAND Europe
Stated preference surveys to support the modelling of demand for high-speed rail
viii
Figure 4.11: VFO VOT for those with an Annual Household Income between
£10,000 and £20,000 (2008 prices) 41
Figure 4.12: VFO VOT for those with an Annual Household Income between
£20,000 and £75,000 (2008 prices) 42
Figure 4.13: VFO VOT for those with an Annual Household Income between
£75,000 and £100,000 (2008 prices) 42
Figure 4.14: VFO VOT for those with an Annual Household Income over
£100,000 (2008 prices) 43
Figure 4.15: VFO VOT for those with an unknown Annual Household Income
(2008 prices) 43
Figure 4.16: WebTAG-recommended Values of Time for Other Leisure Travel 44
Figure 4.17: SP Tree Structure 51



ix
Table of Tables
Table S.1: Breakdown of SP Interviews by Mode and Survey Approach xii
Table S.2: Breakdown of SP Interviews by Mode and Trip Purpose xiii
Table S.3: Trading Exhibited by Respondents in SP Exercises xvi
Table S.4: Attributes Examined in SP Choice Experiments xvi
Table S.5: Value of Being Able to Make a Return Journey in a Day xix
Table S.6: Socio-economic Differences in Modal Preferences xix
Table 2.1: Stated Preference Survey Quotas by Journey Purpose and Mode 3
Table 2.2: Attributes and Levels for the SP Choice Experiments 9
Table 2.3: Breakdown of SP Interviews by Mode and Survey Approach 14
Table 2.4: Breakdown of SP Interviews by Mode and Trip Purpose 15
Table.2.5: Trading Exhibited by Respondents in SP Exercises 16
Table 2.6: Reported Switching to HSR in First Choice Scenario in SP2 16
Table 3.1: Attributes Examined in SP Choice Experiments 18
Table 3.2: SP Sample Proportions by Mode for Each Purpose 27
Table 3.3: NTS Weights by Mode for Each Purpose Applied to SP Sample 27
Table 4.1: Model Fit Statistics 30
Table 4.2: Final Models for Commute Trips 31
Table 4.3: Final Models for Employer’s Business Trips 32
Table 4.4: Final Models for VFO Trips 33
Table 4.5: Value of Access and Egress Time Relative to In-vehicle Time 45
Table 4.6: Value of Rai
l Interchanges Relative to Rai
l In-vehicle Time (mins) 45
Table 4.7: Value of Frequency of Rail Services Relative to Rail In-vehicle Time
(mins per additional train/hr) 45
Table 4.8: Value of Air Wait Time Relative to Air In-vehicle Time 46
Table 4.9: Value of Rail Crowding (mins) 46
Modelling Demand for Long- Distance Travel in Great Britain: RAND Europe
Stated preference surveys to support the modelling of demand for high-speed rail
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Table 4.10: Value of Rail Reliability Relative to Rail In-vehicle Time 47
Table 4.11: Value of Being Able to Make a Return Journey in a Day 47
Table 4.12: Socio-economic Differences in Modal Preferences 48
Table 4.13: Structural Nesting Parameters (thetas) 51
Table A.1: Additional Business Models Estimated for Testing in RP Model
Development 64
Table A.2: Additional Business Models Estimated for Testing in RP Model
Development 65


xi
Summary
Background
The UK Department for Transport is developing a model (LDM) to predict passenger
demand for long-distance travel, which will be used to examine a number of policy
interventions including demand for high-speed rail (HSR), among policies which will
influence long-distance car, classic rail and air demand.
In the context of the LDM study, long-distance journeys are defined as (one-way) journeys
over 50 miles.
In the summer of 2008, a study was undertaken to examine the feasibility of developing a
multi-modal model of long-distance travel (Scott Wilson et al., 2008). Since then, phases 1
and 2 of model development have been undertaken, using National Travel Survey (NTS)
data on long-distance travel for estimation of the travel demand model. In the Phase 2
study it was recommended that a Stated Preference (SP) study be undertaken to provide
current evidence on the likely propensity of car, classic rail and air travellers to transfer to
HSR, thus requiring SP surveys with car, classic rail and air travellers who have made long-
distance journeys.
The specific objectives of the SP study were to:
• collect background information on a recently made long-distance journey;
• in the context of that journey, provide (parameter) values for the different service
components in the mode choice modelling process that underpins the LDM
demand forecasts, including:
o values of time, and to test whether these vary differentially by mode of
travel
o cost sensitivity, and to test whether these vary by income group and
distance
o out-of-vehicle components, such as frequency, interchanges and
access/egress time
o rail service components, such as rail reliability and crowding
o whether there exists an additional preference for HSR, over classic rail,
above that which can be measured by service attributes;
• quantify where HSR fits in the modal choice hierarchy;
• collect background information on travellers’ socioeconomic characteristics,
attitudes and travel preferences, and quantify the impact of these on demand for
HSR.
Modelling Demand for Long- Distance Travel in Great Britain: RAND Europe
Stated preference surveys to support the modelling of demand for high-speed rail
xii
Sampling and Survey Approach
The stated preference choice exercises were based around a possible high-speed rail system
linking London and Scotland via the west and east coast, with a number of intermediate
stops at major cities. The survey was targeted at travellers making journeys within this
corridor so that the survey could be centred on an existing long-distance journey to
strengthen the realism of the choices considered. Respondents were making long-distance
trips for commuting, business, visiting friends or relatives (VFR) or other leisure purposes
(which when treated in combination with VFR trips are referred to as VFO) were
recruited. The sample included those currently travelling by car, rail or air.
Respondents were recruited through a number of avenues:
• Rail and car travellers were recruited through a large-scale random sample of
households where at least one household member had recently made a long-distance
journey within the relevant corridor; the subsequent surveys were undertaken using
phone-post, e-mail and internet-phone methodology.
• On-train CAPI surveys were undertaken with rail travellers.
• CAPI surveys with air travellers were undertaken at airports.
• Because of concerns that the necessary sample of car (and rail) travellers would not
be met through the household survey an additional sample of telephone numbers,
geographically representative of the British population, was purchased and used to
recruit individuals who had made long-distance journeys by car and rail within the
relevant corridor.
Quotas set for each mode were met. Table S.1 summarises the number of surveys
undertaken by each methodology, for each mode of travel.
Table S.1: Breakdown of SP Interviews by Mode and Survey Approach

Existing mode of travel
Total

Car Rail Air
Survey approach
Phone
(from household survey)
838 288 1,126
Phone
(additional sample)
165 30 195
On train 705 705
At airport 1,019 1,019
Total 1,003 1,023 1,019 3,045

The SP survey inclusion criterion requiring the possibility of a sensible high-speed rail
option in the stated preference choice exercises made it difficult to recruit respondents who
were making long-distance commute trips, for example people commuting from the South
West, the South and the East to London were out of scope for the SP survey because they
were not travelling within the corridor being considered. As a result only 100 commuters
were interviewed (it is noted that commuting trips by air were defined as out of scope