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 / Cn

ij).

• 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

© Copyright TFL 2008.

National & RegionalComparative Views

SRMUrban and

Metropolitan Model

SRMInter-Zonal

Model

SRMData Editor

Urban & MetLocation Modelling

Datasets

LocationResult

Datasets

SRMNational Compiler

Inter-ZonalLocation Modelling

Datasets

ProgrammeAssistance

SRM Urban and Metropolitan Models

Change in VehicleOperating Cost

Private Travel Cost

PT Cost

VKT Change

PT PatronageChange

Change in PT ServiceTDM Infrastructure

Level

Walking and CyclingTrips ChangeCO2 Change

Change in VehicleGeneralised Cost

Change in Fares

PT Service

VKT CongestionChange

VKT at E and F

VKT SOV ChangeVKT Network Speed Change

Car Driver Trips

Car Passenger Trips

Speed

HOV StrategyLevel

NM StrategyLevel

Diversion to Walking and Cycling

Diversion from TDM WC Impact

TDM WC Impact

% VKT at E and F % SOV ChangeAverage Network

Speed Change

Or

CO2 Per Capita

% VKT at E and FAverage Network Speed% SOV

WC Trips

WC Modeshare

CO2 Per Capita

Key

Regional Targets

National EstimateTargets

User Setting

Model Output

FareboxRecovery

ITS StrategyLevelRoad Supply

PT Modeshare

CongestionRate PT Patronage PT Modeshare

WC Trips

PT Patronage

SOV VKT per Capita

WC Trips

PT Patronage

Exit

Clickable map data loading

© Copyright TFL 2008.

Exit

Adjust model settings using sliders and drop

down selections

© Copyright TFL 2008.

Exit

Consolidated Views

ExitResults

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