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WHERE TO FROM
HERE?
Andrea Colaiacomo
A MODELLING METHODOLOGY FOR MEASURING LAND-
USE AND PUBLIC TRANSPORT ACCESSIBILITY
1...
Accessibility indices – How many?
Accessibility indices – LUPTAI
It is then possible to compare accessibility to different type of attractions:
• Schools
• ...
Accessibility indices – LUPTAI
LUPTAI is calculated starting from destinations tracing backwards to the origins
within giv...
Accessibility indices – LUPTAI
A series of indices (1 to 5) are then assigned to each geographical unit based on the
combi...
Accessibility indices – LUPTAI
Walk accessibility
PT accessibility
Combined accessibility
Source:
Land Use & Public Transp...
LUPTAI and the model
OBJECTIVE:
Calculate LUPTAI using model outputs. This allows us to take in account the impact of
chan...
LUPTAI and the model
Destinations - Schools
There are
many schools
in the MSD.
Schools are
evenly
distributed
across the
M...
LUPTAI and the model
Destinations – Shopping centres
Fewer in
number if
compared
with schools.
Still pretty
evenly
distrib...
LUPTAI and the model
Destinations – Hospitals
Hospitals are
even more
sparse than
shopping
centres.
More
hospitals are
loc...
LUPTAI and the model
Destinations – Universities
Universities
are
concentrated
in the CBD,
with a few
exceptions.
Some
ext...
LUPTAI and the model
Base Scenario
Base scenario – Road network
LUPTAI and the model
Base Scenario
Base scenario – Public transport network
LUPTAI and the model
Accessibility to schools
Accessibility to
schools is good
every where.
LUPTAI and the model
Accessibility to shopping centres
Corridors with
better
accessibility start
being visible
around rail...
LUPTAI and the model
Accessibility to hospitals
Corridors are
better defined
and it is pretty
clear that
western suburbs
h...
LUPTAI and the model
Accessibility to universities
Corridors are
well defined
around rail lines.
Western suburbs
and areas...
LUPTAI and the model
LUPTAI and the model
UNFORESEEN CHALLENGES
LUPTAI only includes walking distance and travel time, but it’s mostly affected...
LUPTAI and the model
The way to go: use the generalised cost.
The generalised cost includes all the parameters used by the...
LUPTAI and the model - Scenarios
Test scenario 1 – Increased frequency along Frankston line
LUPTAI and the model - Scenarios
Test scenario 2 – New university in Footscray
LUPTAI takes
into account
the
destinations
...
LUPTAI and the model - Scenarios
Test scenario 1 – Change in accessibility
Even doubling
the frequency
along the
Frankston...
LUPTAI and the model - Scenarios
Test scenario 2 – Added an additional university
While adding a
new university
in Footscr...
LUPTAI and the model
The strength of the accessibility index is that it includes the interaction between the PT
system and...
Where to from here? – a modelling methodology for measuring land-use and public transport accessibility in Melbourne
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Where to from here? – a modelling methodology for measuring land-use and public transport accessibility in Melbourne

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Andrea Colaiacomo

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Where to from here? – a modelling methodology for measuring land-use and public transport accessibility in Melbourne

  1. 1. WHERE TO FROM HERE? Andrea Colaiacomo A MODELLING METHODOLOGY FOR MEASURING LAND- USE AND PUBLIC TRANSPORT ACCESSIBILITY 17 August, 2016
  2. 2. Accessibility indices – How many?
  3. 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. 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. 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. 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. 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. 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. 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. 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. 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. 12. LUPTAI and the model Base Scenario Base scenario – Road network
  13. 13. LUPTAI and the model Base Scenario Base scenario – Public transport network
  14. 14. LUPTAI and the model Accessibility to schools Accessibility to schools is good every where.
  15. 15. LUPTAI and the model Accessibility to shopping centres Corridors with better accessibility start being visible around rail lines.
  16. 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. 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. 18. LUPTAI and the model
  19. 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. 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. 21. LUPTAI and the model - Scenarios Test scenario 1 – Increased frequency along Frankston line
  22. 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. 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. 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. 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

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