Transcript MONASH UNIVERSITY

National Urban Transport Modelling Workshop, 5 March 2008
Travel Demand Management
Geoff Rose
Director, ITS (Monash)
Transport Theme Leader, Monash Sustainability Institute
www-civil.monash.edu.au/its
Institute of Transport Studies
Presentation Outline
• Introduction
• Has the scope of TDM options changed
over time?
• What range of demand responses needs
to be modelled?
• What are the variables influencing travel
choices?
• Modelling issues to be addressed
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Introduction
• TDM = Tinkering and Diddling at the Margin?
2003
2004
• Under congestion, marginal reductions in demand
can have a large impact on average cost and also
potentially on variability (system reliability)
– Demand and supply side modelling tends to focus on the
average rather than variability around the average
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Range of TDM Measures
•
Wayte’s 1991 categorisation of 4 strategy areas is still valid
– Improved Asset Utilisation
> Peak Spreading: staggered/flexible hours, cost/toll/availability differentials
> Vehicle Occupancy: carpooling, HOV lanes, park and ride
– Physical Restraint
> Area: cells, mazes, cordon collars
> Link: access metering, PT priority
> Parking Limitations: space limits & access controls
– Pricing
> Road Pricing: tolls, congestion pricing,
> Parking Prices & Taxes: fuel & parking taxes, car ownership taxes/charges
– Urban and Social Changes
> Urban Form: compact cities, efficient urban development
> Social Attitude: voluntary travel behaviour change
> Technological Change: communications substitutions
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Has the scope of TDM options changed
over time?
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•
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•
•
Emerging from Voluntary Travel Behaviour Change era
– Limited systematic attention to ‘stick’ measures, particularly parking
related, as well as broader taxes/charges
Recognise geographic range of applications spans from individual
building/site, group of sites, link, route, corridor to area/region
– Experience limited primarily to either end of the spectrum
Scope for greater packaging of TDM measures
– To address induced demand effects of infrastructure investment
– ‘Carrot’ + ‘Stick’ measures
Technology making more options feasible: pricing (HOT lanes, distance
based insurance and road pricing), access control, car-sharing
Modal coverage of TDM is changing
– No longer just road demand management also public transport
– Carpooling to increase accessibility not just manage congestion
– Walking and cycling now under the TDM tent
– Growing interest in TDM for freight
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What range of demand responses needs to
be modelled?
• Mobility and Lifestyle
– Employment, Housing, Activity program, car
ownership, IT options accessibility
• Activity and Travel Scheduling
– Acquire pre-trip information
– Activity schedule/trip frequency/no travel (teleservices), tour type, departure time, destination,
travel mode, route
• Activity and Travel Re-Scheduling
– Acquire en-route information
– Activity, destination, travel mode and route switching
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Can models capture the range of variables
influencing demand?
• Traditional inputs:
–
–
–
–
In-vehicle and out-of-vehicle time
Costs (out of pocket)
Vehicle availability
Demographic variables: gender, income, HH size, license
• Need capacity for:
– Market segmentation
> Health as a motivator for active transport choice
> Environmental awareness (climate change)
– Impact of vehicle ownership & operating costs (role of FBT)
– Changing demographics (acceptance and use of technology)
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Existing modelling capabilities
•
Factoring down vehicle trip matrix
•
•
•
Quantifies change in congestion but not the
reason for the change
Used in benefit estimation for TravelSmart
• What change in (perceived) Generalised Cost
would result in an X% reduction in car use
If the focus was market segments (work trips in
an area, school trips), could help to set targets
for TDM to design packages of measures to
achieve desired change in congestion
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Existing modelling capabilities
• Pivot point models
• Elasticity based
• CUTR Average Vehicle Ridership (AVR)
Model predicts change in AVR for a selected
incentives
• Demand for High Occupancy Toll Lanes
• Increasing experience in the private sector
modelling (particularly in the USA)
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Modelling issues requiring attention
• 24 hour assignments with time period factoring
– Difficult to examine trip timing decisions
> peak/off-peak switch: change in congestion versus
emissions versus VKT ?
– Which outputs are of interest?
• Trip chaining
• Carpooling and carsharing
• Network representation
– Zone size: intrazonal trips – school, walk and bike trips
– Links
> Local streets not coded into strategic models
> Bike paths not usually included in networks
> (Bike) congestion on on-road facilities
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Modelling issues requiring attention
• Model re-estimation
– Changes in parameter values following changes in
perceptions e.g. TravelSmart
> Value of data from TDM evaluations in Austroads
depository
• Recognising uncertainty in inputs and modelled
effects
– Scenarios and forecast ranges
• Role of hybrid models linking micro-simulation
and strategic models to vary network
magnification
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Closing comments
• Limited experience to date with modelling the
impacts of TDM initiatives
• Data from evaluations of TDM initiatives needs to
be shared to facilitate ‘model’ development
• Scope to enhance practice in the short term while
more fundamental model development required
in the longer term
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