Appendix B9 - Demand model demonstration
forecasts
Sheffield & Rotherham Demand
Model (SRDM3)
Forecasting Report
Report for Sheffield City Council
July 2009
Document Control
Project Title:
FC36842 Sheffield & Rotherham Demand Model Update 2008
MVA Project Number:
C37691
Document Type:
Report
Directory & File Name:
M:\Tp\C37691 Sheffield Demand Update\WORD\Reports\C37691
Forecasting Report v3.Doc
Document Approval
Primary Author:
Pete Kidd
Other Author(s):
Alice Woolley, Abu Mamun & Matt Driver
Reviewer(s):
John Allan
Formatted by:
Leticia Rodriguez
Distribution
Issue
Date
Distribution
Comments
1
19/08/2009
John Allan, MVA
Internal Review
2
20/08/2009
Julie Meese, Sheffield City
External Review
Council
3
27/08/2009
Julie Meese, Sheffield City
Council
Final Version
Contents
1
Introduction
1.1
Context
1.1
1.1
1.2
Reference Case
1.2
1.3
This Report
1.2
2
SRTM3 Overview
2.1
Introduction
2.1
2.2
Model Overview
2.2
3
Reference Case Definitions
3.1
Introduction
3.1
3.2
Transport Strategies
3.1
3.3
Economic and Demographic Scenario
3.4
4
Reference Case Transport Outturns
4.1
Introduction
4.7
4.2
Travel Demand – Person Trips
4.7
4.3
Travel Demand – Trip Lengths
4.8
4.4
Parking
4.9
4.5
Conclusion
4.9
2.1
3.1
4.7
Tables
Table 3.1
Table 3.2
Car Occupancies by Purpose and Year
2002 Prices). Demand model segment numbers are shown in square brackets
Table 3.3
Value of Time Growth between 2008 and 2013
Table 3.4 TEMPRO Sheffield (main) Area Demand Growth Factors 2008-2013
Table 4.1
3.3
3.3
3.5
Growth in Car and Public Transport Person Trips To / From and Within
Sheffield & Rotherham 2008 – 2013
Table 4.2
3.2
Base Model Values of Time by Demand Segment (£/hr, 2008 Values and
4.7
Growth in Car and Public Transport Person Trip Kilometres To, From and
Within Sheffield & Rotherham 2008 – 2013
4.8
Table 4.3 Maximum Parking Utilisations
4.9
Figures
Forecasting Report
Figure 2.1 The Sheffield & Rotherham Transport Modelling System (SRTM3)
2.1
Figure 2.2 Sheffield and Rotherham Districts make up the Study Area
2.3
1
Summary
This report concerns the production of a 2013 Reference Case for use with the Sheffield & Rotherham
Transport Model (SRTM3). It provides an indicative example of the demand for travel in the future,
demonstrating that SRTM3 is fit for the purpose of producing future year demand forecasts.
An overview of the SRTM3 system is provided, followed by chapters setting out the assumptions included
in the reference case and the key transport outturns from a model forecast. Growth in person trip and
trip kilometres are shown to be consistent with the assumptions input to this reference case.
MVA Consultancy anticipates that this version of the reference case will not actually be used for scheme
demand forecasting and appraisal in the forthcoming business cases. Rather, a range of reference cases
for alternative years and including differing economic assumptions will be required. This forecasting
report will subsequently be extended and tailored to the specific requirements of the business cases and
will likely include a broader range of transport outturn indicators. An individual Forecasting Report will be
produced for each separate business case project.
In summary, MVA Consultancy intends that this report is viewed as a template for future forecasting
reports as it provides a structure that can be readily extended to include descriptions of a range of model
years and differing economic and transport assumptions.
Presentation of this 2013 reference case
demonstrates that SRTM3 can be used to produce intuitively plausible reference cases, which can be
adapted in the future to meet the requirements of the forthcoming business cases.
Forecasting Report
i
1
Introduction
1.1
1.1.1
Context
MVA Consultancy was commissioned in autumn 2008 by Sheffield City Council to develop an
aggregate demand model covering the Sheffield and Rotherham districts, an urban
conurbation covering approximately 256 sq miles, containing 770,000 people and 435,000
jobs. It is envisaged that the model will become an essential tool for strategic policy
development across Sheffield and Rotherham over the coming years. However, the model
will be used in the first instance to investigate the following policy issues:
1.1.2
parking restriction;
formal park and ride;
major public transport infrastructure implementation;
Transport Innovation Fund (TIF) funding; and
work place parking levy within Sheffield City Centre1.
More specifically, during 2009 Sheffield and Rotherham Councils and South Yorkshire PTE
plan to use the new model to provide supporting evidence for three Major Schemes to DfT,
which will be appraised using SRTM3.
These three PT schemes primarily involve getting
people to and from Sheffield City Centre and can be summarised as follows:
Penistone Road Smart Route (Quality Bus Corridor) – the provision of bus lanes along
the A61 Penistone Road combined with junction improvements to afford increased
priority to buses as well as decrease delays for general traffic. The scheme stretches
south from Wadsley Bridge to Sheffield City Centre; and
Bus Rapid Transit Routes – two routes connecting Sheffield City Centre with
Rotherham Town Centre. The schemes use high quality vehicles with limited stops and
increased segregation.
The Northern route runs via Meadowhall and the Southern
route via Waverley.
1.1.3
The Sheffield and Rotherham Transport Model (SRTM3) has been built using MVA’s bespoke
demand modelling software, which is broadly the same software that was used for Greater
Manchester’s recent TIF bid but with some important enhancements. The key difference is
that both the highway assignment and the public transport assignment will be undertaken
outside the demand model, within the native highway and PT assignment packages. The
highway model (SRHM3) will use SATURN and the public transport model (SRPTM3) will use
VOYAGER PT. Both models have been constructed and calibrated to 2008 base year data
during early the early months of 2009. The demand model component of SRTM3 will be
known as SRDM3.
1.1.4
MVA have calibrated and validated SRTM3 for a model base year of 2008 and created a 2013
Do-minimum Reference Case. This report summarises the demand and supply inputs to the
2013 Reference Case, provides details of the transport outturns for this forecast and briefly
1
The model may be enhanced at a later date to investigate the impacts of a work place levy implemented over a wider geographical
area covering the rest of Sheffield and/or Rotherham.
Forecasting Report
1.1
1
Introduction
outlines the scheme specific methodologies that will be used in the future to produce demand
forecasts and economic appraisals.
1.1.5
Further reports providing relevant background information on the construction of this model
and its applicability for future year transport demand forecasting and appraisal are:
“SATURN Highway Local Model Calibration and Validation Report”, MVA Consultancy,
July 2009.
“VOYAGER Public Transport Local Model Calibration and Validation Report”, MVA
Consultancy, July 2009.
1.2
1.2.1
“Base Year Demand Model Matrices”, MVA Consultancy, July 2009.
“Model Development Report”, MVA Consultancy, July 2009.
Reference Case
MVA have produced a 2013 do-minimum reference case. The production of this forecast is an
important part of the validation of the SRTM3 system, providing a demand forecast for an
indicative set of demand and supply assumptions. A number of similar forecasts will be
required over the coming months for appraisal of the major scheme business cases which
will require different unconstrained demand and supply assumptions. However, this forecast
demonstrates SRTM3 is fit for the purpose of creating such reference cases and taken
together with the realism tests demonstrate that the model has been satisfactorily validated.
1.2.2
1.2.3
The various inputs to this reference case can be summarised as:
trip end forecasts from TEMPRO 5.4; and
committed transport supply interventions.
This report describes the committed transport supply inputs that have been included in the
2013 do-minimum forecasts and the methodologies that have been used to derive
unconstrained future year demand forecasts for input to this scenario. These inputs have
been input to SRTM3 and the model run to produce a constrained do-minimum demand
forecast for 2013, providing a likely view of what demand for travel will be like in Sheffield
and Rotherham in 2013. This reference case will be used in the first instance as the basis for
major scheme appraisals. This is of course a single view and MVA would expect further
variant scenarios to be constructed at a later date to allow sensitivity testing around central
scheme appraisals to be undertaken.
1.3
1.3.1
1.3.2
This Report
This report contains the following chapters:
Chapter 2 – Sheffield & Rotherham Transport Model (SRTM3) overview.
Chapter 3 – Reference Case Definitions.
Chapter 4 – Reference Case Transport Outturns.
Chapter 2 provides an overview of the entire Sheffield & Rotherham Transport Model
(SRTM3) system and explains how the demand model is integrated with the SATURN
Forecasting Report
1.2
1
Introduction
highway and VOYAGER PT assignment models. Chapter 3 sets out the supply and demand
assumptions which have been included in the 2013 Do-minimum Reference Case. Finally,
Chapter 4 summarises the primary transport outturns of this forecast and contains a brief
conclusion to the report.
Forecasting Report
1.3
2
SRTM3 Overview
2.1
2.1.1
Introduction
This chapter provides an overview of the modelling approach.
More detailed technical
specifications can be found in “Sheffield & Rotherham Model Development Report” dated July
2009.
2.1.2
The Sheffield & Rotherham Transport Model has been designed to focus on a study area
covering the districts of Sheffield & Rotherham. The models extend, albeit with decreasing
levels of detail, across Yorkshire, Humberside and the East Midlands.
The remainder of
Great Britain is represented at a very coarse level of detail. Computing restrictions (memory
and run times), and the availability of data on travel patterns, inevitably limit the spatial
detail to which travel can be represented, particularly outside the study area. The structure
of the SRTM3 modelling approach is illustrated in Figure 2.1.
SATURN
Highway
Assignment Model
(SRHM3)
Highway Speeds
Public Transport
Services
d
an
e
vis
Re
em
dD
sts
Co
d
e
vis
Re
De
ma
nd
sed
Re
vi
Re
vis
e
dC
os
ts
MVA Demand Model (SRDM3)
VOYAGER
Public Transport
Assignment Model
(SRPTM3)
Figure 2.1 The Sheffield & Rotherham Transport Modelling System (SRTM3)
2.1.3
The Sheffield and Rotherham Transport Model (SRTM3) has been built using MVA’s bespoke
demand modelling software, which is broadly the same software that was used for Greater
Manchester’s recent TIF bid but with some important enhancements. The key difference is
that both the highway assignment and the public transport assignment are undertaken
outside the demand model, within the native highway and PT assignment packages. The
highway model (SRHM3) uses SATURN and the public transport model (SRPTM3) uses
VOYAGER PT. Both models have been constructed and calibrated to 2008 base year data
during 2009. The demand model component of SRTM3 will be known as SRDM3.
2.1.4
The demand model has been configured to operate with the same zone system as the
assignment models. Thus, travel demand has been segmented into 525 zones, 345 of which
Forecasting Report
2.1
2
SRTM3 Overview
are within the districts of Sheffield and 150 within Rotherham. There are 23 larger buffer
zones and 7 external zones.
2.1.5
SRTM3 is a model of aggregate travel demand and supply, principally covering Sheffield and
Rotherham and its journey-to-work travel area, but also with a representation of longer
distance travel which might travel to, from and across the county. The model operates on an
iterative basis between the computation of travel demand, allocation of this demand to the
transport networks and calculation of travel times and costs.
SRTM3 produces converged
and internally consistent outputs in each of a set of test alternative transport and economic
scenarios.
Travel demand computations involve determining by which mode (car, public
transport, walk or cycle) people travel, to which destination and at which time of day.
2.1.6
Demand responses such as destination and time period choice are not represented for goods
vehicles, but route choice is represented.
2.1.7
SRTM3 outputs a set of travel demand matrices segmented by time of day, mode of travel,
geographic distribution, and reason for travel, household income and car ownership.
Money
and time costs of travelling, for each network link and zone-pair, are output from the
SATURN highway and VOYAGER public transport assignment models, providing estimates of
levels of traffic on roads within the modelled area and patronage of public transport services.
Chapters 4 of this report contain analyses derived from SRTM3 outputs including forecasts
of:
2.1.8
car and public transport person trips;
car and public person trip kilometres; and
parking demand.
Other indicators which might usefully be extracted from the model in the future would
include:
2.2
mode share;
time of day of travel;
vehicles crossing screen lines;
road speeds and delays;
emissions of pollutants; and
public transport patronage.
Model Overview
Geographic Definition
2.2.1
The study area has been defined as the Districts of Sheffield and Rotherham.
Within the
study area, the road and public transport assignment networks are represented at a high
level of detail. This level of detail gradually diminishes across Yorkshire, Humberside, the
East Midlands and finally the rest of Great Britain. Cost skims taken from the assignment
networks are imported to the demand model and used to estimate travel choices in terms of
time and mode of travel, destination and parking location.
Forecasting Report
2.2
2
2.2.2
SRTM3 Overview
The demand model has been configured to operate with the same zone system as the
assignment models. Thus, travel demand has been segmented into 525 zones, 345 of which
are within the districts of Sheffield and 150 within Rotherham. This zone system has evolved
over several years. Since the 2005 version of the model 10 zones have been added in the
Manor Top area of Sheffield and 15 zones in the Penistone Road corridor.
Figure 2.2 Sheffield and Rotherham Districts make up the Study Area
Modelling of Transport Supply
2.2.3
The SATURN model contains a comprehensive representation of the highway network across
the Sheffield and Rotherham districts, which includes road junctions and the stretches of
road between them.
Characteristics of the road junctions, in terms of the relationship
between traffic flow and delay for each permitted turning movement are derived in SATURN.
2.2.4
For public transport, the VOYAGER model includes details of the routes, fares and
frequencies of bus, Supertram and rail services.
Highway travel times from the SATURN
model are transferred to the VOYAGER model, with a factor used to reduce car speeds to
reflect the fact buses typically travel slower than cars.
2.2.5
The SATURN and VOYAGER assignment network models are used to prepare a representation
of transport supply (travel times and costs) for the computations in the demand model.
Modelling Travel Demand
2.2.6
A significant of proportion of the travel people make is associated with a place of residence.
These journeys are represented as an array containing the number of 2-way journeys made
from the home zone to the workplace, school, shop, or other attractor. The out and return
time periods are defined for each return journey. These combinations of out and return time
Forecasting Report
2.3
2
SRTM3 Overview
periods are referred to as tours. Those journeys which are not associated with a place of
residence are stored as the number of 1-way trips between a pair of zones. Journeys are
allocated to travel demand segments which are defined by trip purpose, three bands of
household income level of the traveller, household car ownership (no car, car owning), mode
of travel and time of day.
There are also journeys made from non-home origins to non-
home destinations, in particular those made by employees in course of their employment,
denoted as employers’ business trips.
The demand for these trips is represented on an
origin-destination basis.
2.2.7
SRTM3 considers all weekday travel between 0700 and 2300 and nine distinct travel time
periods are modelled which cover over 93% of all journeys made in a day:
2.2.8
pre morning peak hour (0700-0800);
morning peak hour (0800-0900);
post morning peak hour (0900-1000);
inter peak period 1 (1000 to 1300);
inter peak period 2 (1300 to 1600);
pre evening peak hour (1600-1700);
evening peak hour (1700-1800);
post evening peak hour (1800-1900); and
off-peak period (1900-2300).
The base year highway and public transport demand data for each time period in the
demand model is built from the same travel demand database that was used to assemble the
trip matrices for the detailed highway and public transport models.
SRTM3 also includes
data for walk/cycle which were derived by applying trip rates derived from TEMPRO to a
distribution of travel devised from the National Travel Survey.
2.2.9
The future year travel demand is prepared for SRTM3 by applying separate growth factors to
the base year data for each travel demand segment. These factors are derived externally to
SRTM3 by applying forecasts of future changes in trip-ends as indicated by TEMPRO.
Model Computational Procedures
2.2.10
SRTM3 starts off by establishing the costs for the routes taken between each pair of zones by
road and public transport by running the SATURN highway and VOYAGER public transport
assignment models. Travel times and money costs between each pair of zones are estimated
for input to the demand model.
2.2.11
The model then predicts the choices made by travellers between each pair of zones in terms
of:
what time of day to travel;
which travel mode to use;
where to travel to; and
for car users, where to park.
Forecasting Report
2.4
2
2.2.12
SRTM3 Overview
Each of these choices is modelled as a function of the time and money cost of each
alternative, eg car, public transport, park-and-ride or walk.
2.2.13
An iterative approach is taken to balancing the supply and demand for travel between each
pair of zones, for each travel mode and section of network, and time of day. The iterative
procedure is repeated until a target level of convergence between supply and demand is
reached and is determined by comparing travel cost changes between iterations.
Forecasting Report
2.5
3
Reference Case Definitions
3.1
3.1.1
Introduction
In this chapter, the key assumptions included within the 2013 do-minimum reference case
are described.
These assumptions fall into two categories: transport supply changes and
economic scenario assumptions. The highway supply network is assumed to be unchanged
from the 2008 base model.
Similarly, no transport changes to public transport or slow
modes have been assumed.
3.1.2
The base year SRDM3 demand matrices have been adjusted using TEMPRO 5.4 trip-end
forecasts to produce ‘unconstrained’ future year demand matrices for input to the demand
model. These demand matrices are unconstrained in the sense that they do not reflect the
impacts of traffic congestion or changes in the real cost of travel for different modes. For
example, due to changes in fuel efficiency or public transport fares. When the SRTM3 model
system is run it produces a ‘constrained’ future year demand forecast, which reflects changes
in travel cost between the current model year and the base year.
3.1.3
MVA Consultancy’s experience is that the DfT requires central demand forecasts consistent
with TEMPRO. TEMPRO contains demand forecasts built from their standard forecasts of
population, jobs and car availability. Growth above the level in TEMPRO implies inward
migration of jobs or people from another area and DfT are wary of having forecasts from
around the country that are inconsistent because each authority claims the jobs and people
will move to their area. The DfT insisted on TEMPRO forecasts for the recent studies we have
been involved in, including Waverley Link Road, the Regional Planning Assessment for the
railway in Yorkshire and the Humber, and Greater Manchester’s bid to the Transport
Innovation Fund. It is therefore prudent to proceed with demand forecasts that are
consistent with TEMPRO.
3.2
Transport Strategies
Transport Supply
3.2.1
No transport supply changes have been included in the reference case. This is the case for
highway, public transport and slow modes.
Car Occupancy
3.2.2
Car occupancy values have been derived from TAG Unit 3.5.6. Values are input into SRDM3
separately for business, commute and other purposes as shown in Table 3.1.
Forecasting Report
3.1
3
Reference Case Definitions
Table 3.1 Car Occupancies by Purpose and Year
Purpose
2008
2013
Business
1.203
1.198
Commute
1.143
1.139
Other
1.687
1.667
Value of Time
3.2.3
The approach to deriving values of time in 2008 was based on TAG Unit 3.12.2 which in turn
draws upon research undertaken for the DfT by the University of Leeds and Dr John Bates.
In summary, a sample of National Travel Survey (NTS) data was obtained and re-weighted
to be representative of planning data characteristics for Sheffield and Rotherham zones.
Values of time were then estimated for each trip using the zonal income data obtained from
CACI Ltd.
3.2.4
Values of time for employer’s business were taken directly from TAG Unit 3.12.2 as the NTS
Survey sample didn’t contain sufficient observations for this purpose.
3.2.5
Values of time for each demand segment in the base model are shown in Table 3.2. Note
that values for employer’s business segments have not been split by income group.
Forecasting Report
3.2
3
Reference Case Definitions
Table 3.2 Base Model Values of Time by Demand Segment (£/hr, 2008 Values and
2002 Prices). Demand model segment numbers are shown in square brackets
Purpose
3.2.6
Low Income
Medium Income
High Income
HB Work no car
3.03 [1]
4.76 [2]
7.78 [3]
HB Work 1+ car
3.80 [4]
5.68 [5]
8.32 [6]
HB Employer’s Business no car
18.60 [7]
HB Employer’s Business 1+ car
18.60 [8]
HB Education no car
2.99 [9]
3.44 [10]
3.59 [11]
HB Education 1+ car
3.93 [12]
3.78 [13]
4.34 [14]
HB Shop no car
2.89 [15]
3.80 [16]
3.68 [17]
HB Shop 1+ car
3.43 [18]
4.29 [19]
4.81 [20]
HB Other no car
5.23 [21]
6.51 [22]
8.32 [23]
HB Other 1+ car
5.23 [24]
6.51 [25]
8.32 [26]
NHB Employer’s Business no car
18.60 [27]
NHB Employer’s Business 1+ car
18.60 [28]
NHB Other no car
4.42 [29]
6.09 [30]
7.39 [31]
NHB Other 1+ car
4.35 [32]
5.39 [33]
6.25 [34]
Consistent with TAG Unit 3.5.6, values of working time have been increased in line with GDP
per capita whilst values for other purposes are related to changes in GDP per capita with an
elasticity of 0.8. Value of time growth rates are shown in the table below.
Table 3.3 Value of Time Growth between 2008 and 2013
Range of Years
2008-2013
Forecasting Report
Work VOT Growth
Non-Work VOT Growth
10.9%
8.7%
3.3
3
Reference Case Definitions
Public Transport Fares
3.2.7
For bus and light rail services, public transport fares have been assumed to increase in line
with RPI, whilst for heavy rail, public transport fares have been assumed to rise at 1% per
annum above the growth in RPI.
Parking Supply
3.2.8
The scale of parking opportunities available within the Sheffield parking area has been
assumed to be unchanged in 2013.
However, parking charges have been assumed to
increase in line with RPI.
3.3
3.3.1
Economic and Demographic Scenario
A single economic and demographic scenario has been developed to date for use with
SRTM3, which forms the basis of the 2013 Reference Case. This scenario has been derived
using trip ends extracted from TEMPRO 5.4 and provides a possible view of the world in that
year.
Application of TEMPRO Growth Factors
3.3.2
3.3.3
Trip ends were extracted from TEMPRO 5.4 at the following level of segmentation:
base model and future forecast year;
21 TEMPRO areas;
production and attraction;
business, commute and other purposes;
main mode (car, PT, walk/cycle); and
household car ownership (no car, car owning).
These trip ends were used to produce growth factors which were then applied on a zonal
basis in the following way:
trip-end attraction factors applied to adjusting the pattern of growth by attraction;
trip-end production factors applied to adjust the pattern of growth by production, thus
controlling the total level of growth to the growth in productions.
3.3.4
For areas within the Sheffield & Rotherham districts, trip ends were extracted at the most
disaggregate level possible with spatially more aggregate data used for areas beyond the
study area. Data was extracted at district level for the other districts in South Yorkshire,
County level for remaining areas in the buffer area and GB level for the 7 external zones.
The 21 areas were:
Anston, Dinninton & Laughton Common;
Aughton;
Barnsley;
Beighton;
Forecasting Report
3.4
3
3.3.5
Reference Case Definitions
Chapeltown;
Chesterfield;
Doncaster;
GB;
Maltby;
Mosborough Highlane (main);
Nottinghamshire;
Oughtbridge and Wharnclliffe Side;
Rawmarsh;
Rotherham;
Rural Rotherham;
Rural Sheffield;
Sheffield (main)
Sheffield (part of)
Stocksbridge
Swinton
Wath Upon Dearne
By way of example, table 3.4 shows the trip end 2008-2013 growth factors derived for zones
within the Sheffield (main) area, which were applied to the base year demand. These factors
reflect the assumption of increasing levels of car ownership across Sheffield as well as the
differential modal trip rates forecast by the National Travel Survey.
Table 3.4 TEMPRO Sheffield (main) Area Demand Growth Factors 2008-2013
Demand
Car
PT
Walk/Cycle
Segment
Commute
Business
Other
Commute
Business
Other
Commute
Business
Other
No car
0.984
0.985
0.979
0.916
0.954
0.896
0.922
0.954
0.927
Car owning
1.105
1.106
1.099
1.028
1.071
1.006
1.035
1.071
1.040
No car
0.975
0.979
0.971
0.921
0.958
0.906
0.930
0.954
0.927
Car owning
1.095
1.099
1.091
1.035
1.075
1.017
1.044
1.072
1.041
Productions
Attractions
Forecasting Report
3.5
3
Reference Case Definitions
Major Attractors
3.3.6
No separate assumptions have been assumed for other major attractors of demand such as
hospitals or the Universities.
Freight Growth
3.3.7
Freight growth factors for 2008 to 2013 for light and other goods were derived from the
National Transport Model. The factors used were:
Light goods 1.134; and
Other goods 1.027.
Forecasting Report
3.6
4
4
Reference Case Transport Outturns
Reference Case Transport Outturns
4.1
4.1.1
Introduction
This chapter summarises the key changes from 2008 to 2013 in public transport and
highways demand for the Reference Case.
A description of the Reference Case was
presented in Chapter 3.
4.1.2
4.2
4.2.1
The following impacts are presented in this chapter:
car and public transport person trips;
car and public person trip kilometres; and
parking demand.
Travel Demand – Person Trips
Production of a future year SRTM3 forecast involves first applying demand growth factors
derived from TEMPRO to produce an unconstrained demand forecast. This matrix is then
input to SRTM3 creating a constrained forecast, reflecting the growth-limiting impacts of
highway congestion and public transport crowding. In this section, demand changes forecast
by TEMPRO relative to the base demand matrices are presented, as well as those forecast by
SRTM3.
4.2.2
As shown in Table 4.1, TEMPRO forecasts car trips to grow by 9.2% 2008 to 2013 to, from
and within Sheffield & Rotherham whilst SRTM3 forecasts 9.8% growth. In contrast, the level
of growth for car trips wholly within the study area is forecast to grow by 9.5% in TEMPRO
and by less in SRTM3 8.9%. The impact of SRTM3 on car trips to, from and within the study
area is to increase average trip length, redistributing trip ends from within the study area to
outside. In fact trip ends outside the study area are forecast to grow by 14% in SRTM3,
which is higher than the TEMPRO forecast of 8%. These results indicate that the distribution
model is drawing trips out of the study area, reflecting the tendency for car trip length to
increase over time as vehicle operating costs continue to fall in real terms.
Table 4.1 Growth in Car and Public Transport Person Trips To / From and Within
Sheffield & Rotherham 2008 – 2013
Car
Public Transport
Walk/Cycle
TOTAL
Forecasting Report
TEMPRO Forecast
SRTM3 Forecast
9.2%
9.8%
-3.0%
0.2%
0.8%
-0.5%
5%
6%
4.7
4
4.2.3
Reference Case Transport Outturns
For public transport, TEMPRO forecasts trips to, from and within the study area to decrease
by 3.0%, whereas the outturn forecast from SRTM3 is for these trips to increase by 0.2%.
This result is a little surprising as it suggests that the historic declines in public transport
demand brought about through higher car ownership are not necessarily going to continue.
The primary driver for this is the fares assumption which has been included in the reference
case. Bus and Supertram fares have been assumed to increase at RPI and rail fares by
RPI+1%. As value of time is forecast to increase by greater than RPI+1% this means that all
public transport fare are assumed to decrease in real terms in the model. Given that the
likely response of bus operators seeking to maintain revenues with the advent of the Senior
Citizens Concessions Scheme may well be to increase fares, MVA would suggest that
increasing all public transport fares by RPI+1% would be a more appropriate assumption and
propose to include this assumption in future versions of the reference case.
4.2.4
Finally, the TEMPRO forecast for walk/cycle demand suggests an increase of 0.8% whereas
SRTM3 suggests a decrease of -0.5%. The impact of SRTM3 is to shift walk/cycle trips to
public transport as public transport fare reduce in real terms over time.
4.2.5
As a result of the changes in car and public transport demand discussed in previous
paragraphs, public transport mode share decreases from 11.4% in 2008 to 10.8% in 2013.
4.3
4.3.1
Travel Demand – Trip Lengths
This section presents similar results to the preceding section, but focuses on person trip
kilometres, given that there are differences in average trip length by mode, and that future
planning assumptions may have differential impacts on average trip length by mode.
4.3.2
Trip kilometres are forecast to increase at a faster rate than trips (see Table 4.2). This is
because car operating costs per kilometre are forecast to reduce in real terms over time
(TAG 3.5.6, Section 1.3), whilst values of time increase (TAG 3.5.6, Section 1.2), and thus
the perceived importance of operating costs reduces. These operating costs are greatest for
long journeys. Car trip kilometres grow by 13% to 2013. By contrast there is much lower
growth rates forecast for public transport trip kilometres to 2013 (1.3%) and walk/cycle
(0.0%).
Table 4.2 Growth in Car and Public Transport Person Trip Kilometres To, From and
Within Sheffield & Rotherham 2008 – 2013
TEMPRO Forecast
SRTM3 Forecast
8.8%
13.0%
-1.1%
1.3%
Walk/Cycle
1.0%
0.0%
TOTAL
7.2%
11.0%
Car
Public Transport
Forecasting Report
4.8
4
Reference Case Transport Outturns
4.4
Parking
4.4.1
As car trips are forecast to increase, demand for parking in Sheffield & Rotherham urban
centres would also be expected to increase. SRDM3 includes a parking model covering
Sheffield City Centre and the Peripheral Parking Zones and indeed demand for parking is
seen to increase in these areas by 2013.
4.4.2
Table 4.3 shows the change in the all day maximum utilisation for car parks in 2013 relative
to the 2008 base year, where car parks typically reach their maximum utilisation midmorning once the commuters have arrived for the day. Interestingly, this reveals that
existing spare capacity is likely to be sufficient to accommodate increased demand for
parking over the next 5 years.
Table 4.3 Maximum Parking Utilisations
Sector
Maximum
Maximum
Utilisation in
Utilisation in
Base
2013
18,678
68%
78%
15%
Broomhall
2,172
74%
80%
8%
Broomhill
3,616
75%
81%
9%
922
0%
60%
0%
2,994
83%
89%
7%
1,136
100%
100%
0%
North
5,237
88%
97%
10%
Sharrow Vale
2,435
58%
63%
9%
South
2,261
100%
100%
0%
39,451
74%
81%
10%
Capacity
City Centre
Crookesmoor
Highfield
Netherthorpe/
Upperthorpe
All
4.5
4.5.1
% Change
Conclusion
This report describes the input assumptions and the transport outturns of an indicative 2013
reference case. Trip end forecasts taken from TEMPRO were used to factor the 2008 base
year demand matrices, producing unconstrained 2013 demand matrices for input to the
transport model. A demand forecast was subsequently produced using these matrices, given
a set of supply assumptions. Modal trip and trip kilometres outturns from the 2013 forecast
model were shown to be consistent with the input demand and assumptions about future
highway and public transport supply.
Forecasting Report
4.9
4
4.5.2
Reference Case Transport Outturns
In particular, assumptions about the likely level of public transport fares in the future have
significant bearing on forecast public transport demand outturns. This assumption is
therefore crucial to the outcomes of scheme demand forecasting and appraisal. MVA
Consultancy recommends that future reference cases contain an assumption of public
transport fare growth of RPI+1% for all sub-modes of PT. It is thought this would be a more
appropriate assumption, reflecting the requirement of bus operators to respond to reduced
revenues resulting from the Senior Citizens Concessions Scheme.
4.5.3
This report provides a template for future forecasting reports, which will be required for each
of the forthcoming business cases, describing the input assumptions and transport outturns
for a range of model years. These forecasts will include specific assumptions with regard to
the additional travel demand associated with new developments and a significant work
programme is underway to incorporate such demand assumptions, whilst controlling demand
growth totals to those forecast by TEMPRO.
4.5.4
Finally, taken together with the Model Development Report (July 2009), this report
demonstrates that SRTM3 is fit for its primary purpose of scheme demand forecasting and
appraisal.
Forecasting Report
4.10
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