Big picture transport planning
When precision fails and
approximation succeeds
Transport planning and models
• Transport planning - the operation,
management and adjustment of the
transport system
• Quantified techniques (analysis
assessment and forecasting) are needed
• Models of different types are available to
assist these processes
Problems
• Transport planning has not delivered on
broader objectives
• One reason for this is the reliance on
narrowly focused models
• Another reason is the failure to apply
strategic techniques to assist in seeing
the big picture
Results
• The effect of current transport modelling
efforts in NZ has been to perpetuate
‘business as usual’
• This means that most trends (emissions,
delay, reliability, choice, accessibility,
equity) will continue to move in the wrong
direction
• New national targets for transport will not
be achieved using current approaches
Does it have to be this way?
• No
• Providing there is a commitment to better
analysis, assessment and forecasting
• Many techniques and models already exist
– but they need to be well developed and
appropriately applied
Conventional models (1)
• Conventional transport models may cover
3 stages: trip generation / attraction, trip
distribution, and trip assignment. 4 stage
models also have a mode split function.
• 3 and 4 stage models use distribution
functions such as (Tij = αPiPj / Cnij).
• Responsiveness is often poor - induced or
suppressed demand is not allowed for –
and ‘implied elasticities’ may be weak
Conventional models (2)
• Conventional transport models are good at
predicting ‘business as usual’ (expected
land-use, population, car ownership and
on the basis of current policies and prices)
• They are used to test policies, strategies,
packages and programmes.
Conventional models (3)
• Many models are single stage and only
deal with traffic engineering issues.
• Models are used to provide information for
economic appraisal – the benefit cost ratio
– very influential in decision making
• 1 stage models – often appear to be very
precise – especially micro-simulation –
very impressive visually and useful for
sorting out some issues – but not all
Strategic gap
• Improvements in modelling are underway
at the regional and local levels – although
these will not cover all needs
• But there is currently a modelling ‘void’ at
the inter-regional and national levels
• It takes time for a national modelling
capability to be developed
Simplified demand modelling
• Conventional transport models are based
on detailed representations of transport
networks and on current behaviour
• Simplified demand modelling is much
coarser grained but has more flexibility to
consider behavioural responses – and
could be said to represent ‘5th stage’
modelling
Strategy review model
• An example of a simplified demand model
is the strategy review model (SRM)
developed in 2008 in NZ
• SRM builds on current model outputs
• Based on elasticities, cross elasticities,
diversion rates and impact factors
• It has been applied at the local, regional
and national level for sensitivity testing
and policy development purposes
Modelling Framework
SRM
Data Editor
Urban & Met
Location Modelling
Datasets
Programme
Assistance
SRM
Urban and
Metropolitan
Model
Location
Result
Datasets
Inter-Zonal
Location Modelling
Datasets
SRM
Inter-Zonal
Model
SRM
National
Compiler
National & Regional
Comparative Views
© Copyright TFL 2008.
SRM Urban and Metropolitan Models
PT Service
PT Cost
Change in PT Service
TDM Infrastructure
Level
Private Travel Cost
Change in Fares
Or
Farebox
Recovery
Change in Vehicle
Generalised Cost
PT Modeshare
Change in Vehicle
Operating Cost
Diversion from
TDM WC Impact
TDM WC Impact
Diversion to
Walking and Cycling
Walking and Cycling
Trips Change
PT Patronage
Change
Congestion
Rate
Key
PT Modeshare
PT Patronage
CO2 Change
VKT Change
User Setting
CO2 Per Capita
CO2 Per Capita
WC Trips
Model Output
WC Modeshare
Regional Targets
National Estimate
Targets
Road Supply
VKT Congestion
Change
% VKT at E and F
% VKT at E and F
VKT at E and F
NM Strategy
Level
HOV Strategy
Level
ITS Strategy
Level
VKT Network
Speed Change
VKT SOV Change
Average Network Speed
per Capita
% SOV
SOV VKT
% SOV Change
Car Driver Trips
Car Passenger Trips
Average Network
Speed Change
Speed
Exit
Clickable map
data loading
© Copyright TFL 2008.
Exit
Adjust model settings
using sliders and drop
down selections
© Copyright TFL 2008.
Exit
Consolidated
Views
Exit
Results
summarised
for modelled
periods
Targets, BAU
and modelled
impact
Exit
Sample Comparative Views
Comparing regional outcomes
 Walking and Cycling by Location
 PT Patronage by Location
 SOV VKT per capita by Location
 VKT at E and F by Location
 Speed by Location
 CO2 Volume by Location
 Per Capita Co2 by Location
 Per Capita PT Patronage by Location
 Per Capita VKT at E and F
 Per Capita Walking and Cycling Trips by Location
 PT Modesplit by Location
 Walking and Cycling Modesplit by Location
 Car Driver Modelsplit by Location
 Car Passenger Modesplit by Location
 Per Capita Co2 Target by Location
 Per Capita PT Trips Target by Location
 Per Capita Walking and Cycling Trips Target by Location
The future? (1)
• Role of mathematicians in supporting the
development of new techniques especially in the field of simplified demand
modelling
• Especially in terms of how the robustness
and validity of models can be improved
• One example, the treatment of arc-based
elasticities.
The future? (2)
• Role of operational research in optimising
target profiles.
• Maximising the good (public transport,
walking and cycling)
• Minimising the bad (travel time variability,
single occupant vehicles, emissions)
• Within given constraints – such as cost
and funding
Public transport example