Presentation give to the Transport Statistics Users Group, London, 18 January 2012

1. Accessibility in forecasting and
appraising the wider consequences
of transport change
David Simmonds
TSUG, 18 January 2012

2. Modelling land-use/transport interaction
Demographic scenario Economic scenario
Forecast land-
use data
Base
year LAND-USE TRANSPORT
data Forecast
transport
costs, traffic
Transport plans
Planning policies

3. Modelling land-use/transport interaction
Demographic scenario Economic scenario
Forecast land-
use data
Base
year LAND-USE TRANSPORT
data Forecast
transport
costs, traffic
LUTI models
Transport plans
Planning policies

4. Modelling land-use/transport interaction
Demographic scenario Economic scenario
Forecast land-
use data
Base
year LAND-USE TRANSPORT
data Forecast
transport
costs, traffic
Land-use change indicators
Transport plans
Planning policies

5. Types of accessibility measures
• Time or distance threshold eg number of unskilled jobs within 30
minutes
• Size threshold eg time within which 5,000 unskilled jobs can be
reached
• Average time or cost eg average time to any one of the pubs in
Cambridge
• Choice-weighted size measures eg Hansen accessibility scores
• Utility- or choice-based eg expected cost (or generalised cost) of
travel to unskilled jobs, taking account of the traveller’s
preference for easier journeys

6. Types of accessibility measures
• All of these integrate a lot of data
• All of them can exist in “origin” or “destination” forms ie
– number of jobs within 30 minutes
– number of workers within 30 minutes
– (also known as “active” and “passive”)
• Threshold-based measures are easy to explain but
– difficult to justify the threshold
– tend to be lumpy in zonal models

7. Accessibility in modelling
• Because of the theoretical and practical difficulties with
thresholds (and because time to all destinations is usually
irrelevant), accessibility calculations in land-use modelling are
usually in the utility-based form
• Technically this is the logsum measure derived from a logit model
of destination choice:
1    
Ai = D 
ln ∑W j exp ( −λ gij )  − K 
D J
−λ   j
 



8. Utility-based accessibility
• The utility-based accessibility is an estimate of the expected
generalised cost of a particular kind of trip, eg
– non-car-owner travel to unskilled jobs
– car-owner travel to comparison shopping
• Takes account of the generalised cost of travel (so combines cost,
time and inconvenience) and of the distribution of the
opportunities

9. Utility-based accessibility
• Avoids thresholds – all opportunities count though furthest ones
may make a negligible contribution
• Can readily be extended to deal with mode and other choices (eg
time of day)
• Has the useful characteristic that improving any mode, or adding
more opportunities in any location, will either improve
accessibility or leave it unchanged
• Just as an illustration that this complex formula produces
meaningful results, the following slide shows utility-based
accessibility across the Glasgow area, for car-owners’ access to
lower-level white-collar jobs:

11. Empirical effect of accessibility
• Price analysis – often based on distance from city centre or
distance from station/intersection etc, but analysis using utility-
based accessibility has found it to be small but significant
component of house prices
• Household moves – accessibility found to be a small but significant
component in choice of where to live

12. Use of accessibility measures in DELTA land-use
models
• Household location is influenced by a mixture of different utility-
based origin accessibility measures
– the mix and weighting of measures depends on the type of
household
• Employment location is influenced by a mixture of utility-based
measures
– destination accessibilities for how easily each zone can be
reached by workers (by socio-economic group)
– destination accessibilities for how easily each zone can be
reached by customers (for retail and similar sectors)
– origin accessibilities for how easily other businesses can be
reached (including goods delivery where appropriate)
• Also use Hansen-type size measures in economic modelling.

13. Accessibility and appraisal (1)
• Changes in utility-based accessibility weighted by number of
people affected are related to the consumer-surplus changes
measured in conventional Transport Economic Efficiency analysis
• Two main differences:
– TEE is typically uses the numbers of trips, forecast forward
from “observed” base year matrices, whilst accessibility-based
appraisal would use “expected” trips from the destination
choice model
– accessibility-based appraisal can take account of changes in
attractiveness of destinations

14. Accessibility and appraisal (2)
• Conventional TEE can’t take account of land-use changes eg
– households moving from major cities to surrounding towns/countryside as a
result of suburban rail electrification
– decline in city/town centres as a result of road improvements encouraging
greater use of edge-of-town or out-of-town shopping, entertainment etc.
• Accessibility-based calculations could contribute to dealing with
this.

15. Further reading
• There are papers about many of our DELTA-based LUTI models on the
Publications page of our website, including for example papers on work in
– Greater Manchester
– South Essex.
• We produced a detailed review of “Accessibility as a criterion for project
and policy appraisal” for DETR – seems to be lost from DfT websites, but
available from the author on request
• Developing ideas on transport appraisal which can take account of land-
use/transport interactions: notes available on request.
Thank you for your attention!
david.simmonds@davidsimmonds.com
www.davidsimmonds.com