Using Transport Models to Evaluate Energy, Climate Change and Air Quality Impacts

Energy: Strategic transport models output vehicle flows and average link speeds on road and public transport network links. Flows are usually categorised by vehicle type, typically passenger cars; and commercial vehicles (disaggregated by light, medium and heavy commercial vehicles), as well as bus flows and bus speeds. Average speed and fuel consumption relationships may be used to estimate total fuel consumption on each link. National evaluation guidelines in Australia recommend typical values for a number of evaluation parameters, including fuel consumption estimation.

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Dealing with Uncertainty in Travel Demand Forecasting

Sources of error

When forecasting for the medium to long term we need to be clear in acknowledging that we are dealing with an uncertain future. There are a number of factors which may contribute to errors and uncertainty in forecasts. Sources of uncertainty when forecasting travel demand include:

Demographic and socioeconomic input data: employment and population market segments; economic activity: impacts on drivers for freight and passenger demand.

Assumptions about physical networks (base year and future projects): observed counts may affect model calibration and validation; road and public transport network assumptions.

Values of travel time (VTT): strategic transport models use an imputed VTT for each main trip purpose. VTT are usually estimated from the coefficients of mode choice models.

Time of day effects: factors are usually used for different time periods, (peak, daily, weekly, monthly, and annually), based on historical data. Such factors will not deal with peak spreading or mixes in the traffic composition. Methods to model time-of-day choice explicitly are beginning be implemented in practice.

Optimism bias: Use should be made of strategic transport models to investigate the impact of proponent optimism bias on overall results. Patronage optimism bias should be examined using sensitivity testing.

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US Report identifies travel demand modelling shortcomings

The US Transportation Research Board has recently conducted a major study into the state-of-practice of travel demand forecasting theory and application in that country.

TRB Special Report 288, Metropolitan Travel Forecasting: Current Practice and Future Direction, examines metropolitan travel forecasting models that provide public officials with information to inform decisions on major transportation system investments and policies.

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Microsimulation as a Planning, Operations and Training Aid for Incident Management

The methodology for this study includes a literature review and a modelling case study of the West Gate Freeway in Melbourne. A microsimulation model was set up using AIMSUN NG for the study area. It is concluded that significant resources are required in setting up a microsimulation model for incident analysis. Once set up and … Read more