The document discusses Land Use and Public Transport Accessibility Index (LUPTAI), which measures accessibility between origins and destinations using public transport travel times and walking distances. LUPTAI is calculated for zones in a model by tracing public transport and walking routes. Accessibility indices are assigned based on combinations of public transport frequency, travel time, and walking distance. The document applies LUPTAI in a case study to analyze accessibility to schools, hospitals, shopping centers and universities under different transportation scenarios.

1. WHERE TO FROM
HERE?
Andrea Colaiacomo
A MODELLING METHODOLOGY FOR MEASURING LAND-
USE AND PUBLIC TRANSPORT ACCESSIBILITY
17 August, 2016

2. Accessibility indices – How many?

3. Accessibility indices – LUPTAI
It is then possible to compare accessibility to different type of attractions:
• Schools
• Hospitals
• Shopping centres
• Amenities
• Etc.
And assess the accessibility looking also at socio-economic variables:
• Accessibility to schools from zones with high density of young families
• Accessibility to health centres from zones with high density of elderly people
LUPTAI (Land Use and Public Transport Accessibility Index) links active and
public transport availability and key destinations.
nowherenowhere
200 trains per hour
schoolhospital
2 trains per hour



4. Accessibility indices – LUPTAI
LUPTAI is calculated starting from destinations tracing backwards to the origins
within given thresholds.
Destination
Stop within
400m (walk
egress)
Public
transport
journey
Stops within public
transport travel time
threshold
350m from the stop
plus 50m buffer (total
400m from the stop)
Source:
Land Use & Public Transport
Accessibility Index (LUPTAI) Tool - The
development and pilot application of
LUPTAI for the Gold Coast

5. Accessibility indices – LUPTAI
A series of indices (1 to 5) are then assigned to each geographical unit based on the
combinations of:
• PT frequency and walking distance
• PT travel time (by mode) and walking distance
Source:
Land Use & Public Transport
Accessibility Index (LUPTAI) Tool - The
development and pilot application of
LUPTAI for the Gold Coast

6. Accessibility indices – LUPTAI
Walk accessibility
PT accessibility
Combined accessibility
Source:
Land Use & Public Transport
Accessibility Index (LUPTAI) Tool - The
development and pilot application of
LUPTAI for the Gold Coast

7. LUPTAI and the model
OBJECTIVE:
Calculate LUPTAI using model outputs. This allows us to take in account the impact of
changes in traffic flow conditions.
FORESEEN CHALLENGES:
Model outputs are aggregated by travel zone pairs, while accessibility is typically
calculated at each individual element of the geographical grid.
Outputs used in order to calculate LUPTAI consistently in the presented methodology
are:
• Walk travel time
• PT travel time
• Walk access and egress distances

8. LUPTAI and the model
Destinations - Schools
There are
many schools
in the MSD.
Schools are
evenly
distributed
across the
MSD.
No particular
accessibility
issues are
anticipated.

9. LUPTAI and the model
Destinations – Shopping centres
Fewer in
number if
compared
with schools.
Still pretty
evenly
distributed
across the
MSD.
Some
interesting
patterns in
accessibility
are
anticipated.

10. LUPTAI and the model
Destinations – Hospitals
Hospitals are
even more
sparse than
shopping
centres.
More
hospitals are
located in the
eastern
suburbs than
to the west.

11. LUPTAI and the model
Destinations – Universities
Universities
are
concentrated
in the CBD,
with a few
exceptions.
Some
extreme
patterns in
accessibility
are
anticipated.

12. LUPTAI and the model
Base Scenario
Base scenario – Road network

13. LUPTAI and the model
Base Scenario
Base scenario – Public transport network

14. LUPTAI and the model
Accessibility to schools
Accessibility to
schools is good
every where.

15. LUPTAI and the model
Accessibility to shopping centres
Corridors with
better
accessibility start
being visible
around rail lines.

16. LUPTAI and the model
Accessibility to hospitals
Corridors are
better defined
and it is pretty
clear that
western suburbs
have lower
access to
hospitals.

17. LUPTAI and the model
Accessibility to universities
Corridors are
well defined
around rail lines.
Western suburbs
and areas
around the end
of rail line show
the lowest
accessibility
indices.

18. LUPTAI and the model

19. LUPTAI and the model
UNFORESEEN CHALLENGES
LUPTAI only includes walking distance and travel time, but it’s mostly affected by the
walking distance. This may end up in misrepresenting a change in the user behaviour.
For example in the base scenario a user may go from A to B with:
• 600m access and egress distance
• 30 minutes PT travel time
• (and 3 interchanges)
While in the project scenario a user may go from A to B with:
• 900m access and egress distance
• 30 minutes PT travel time
• (and 1 interchange)
In this case LUPTAI would show a worse accessibility index. Is this actually the case?

20. LUPTAI and the model
The way to go: use the generalised cost.
The generalised cost includes all the parameters used by the model to replicate user
behaviour:
• In-vehicle travel time
• Access / egress time
• Waiting time
• Fare factor
• Access / egress penalties
• Transfer penalties
• Stop choice and route choice parameters
An index based on the generalised cost will then be consistent with what has been
assumed to influence the user decisions.

21. LUPTAI and the model - Scenarios
Test scenario 1 – Increased frequency along Frankston line

22. LUPTAI and the model - Scenarios
Test scenario 2 – New university in Footscray
LUPTAI takes
into account
the
destinations
available. This
means that
even without
changing the PT
network,
accessibility can
be improved by
providing
services in the
right location.

23. LUPTAI and the model - Scenarios
Test scenario 1 – Change in accessibility
Even doubling
the frequency
along the
Frankston line,
accessibility
doesn’t change
significantly
with the
exception of
few zones
around the rail
corridor.

24. LUPTAI and the model - Scenarios
Test scenario 2 – Added an additional university
While adding a
new university
in Footscray
would affect a
wider area by
improving the
accessibility
from the
western
suburbs
(including
Melton and
Sunbury)

25. LUPTAI and the model
The strength of the accessibility index is that it includes the interaction between the PT
system and the available destinations.
The index could be further improved by including:
• population densities,
• crowding,
• number of accessible destinations,
• availability of additional PT modes and/or stations