Maximising Infrastructure Investment with Smart Motorway Management

Motorways are the arteries of a city. Poorly functioning motorways create congestion, frustration and ultimately impact negatively on the economy. It has been recognised that the most effective way to get the most out of city motorways is to create a mathematical model. A fully developed model operating with real time data could actually predict the traffic scenarios and explore the effects of implementing various measures to resolve potential congestion problems.

The 'Maximising Infrastructure Investment with Smart Motorway Management' project intends to model the precinct of Gateway Motorway in the vicinity of Brisbane Airport to the Port of Brisbane Motorway. This model will demonstrate how effective control methods may be applied in the model to increase traffic volume and density without causing congestion. This project is a component of a larger project that is planned to:

1. Demonstrate predictive traffic modelling by utilising real time data from appropriate feeds to
2. populate the model of the airport precinct;
3. Model the motorways in the South East Queensland region from the Gold Coast to the Sunshine
4. Coast and out to Ipswich; and
5. Implement an actual predictive model for management of South-East Queensland motorways

This project has significant support from the Queensland Department of Main Roads, with the provision of two staff and data,

Smart motorways and QCIF

QCIF’s initial role in this project is primarily to ensure that the Technology Infrastructure is appropriate for the modelling task to be undertaken, and to assist with visualisation of the models. The funding for the infrastructure will be provided by QCIF and a resource will be funded to ensure that the simulation models from the software packages are effective in demonstrating the managed motorway concept and implications of it operations.

Participants

Professor Phil Charles
Director of Centre for Transport Strategy
School of Engineering, University of Queensland