iMOVE Australia, along with the Department of Transport and Main Roads (TMR), Queensland University of Technology and Transmax are conducting research to explore methods for optimising the algorithms that manage the effects of queues on highways. Vehicular queues are detrimental to the smooth flow of traffic on highways, which results in economic and environmental costs. The sudden encounter of the end of a queue can increase the risk of accidents, and the high speeds of highway traffic can make accidents more severe.
TMR mitigates the effects of queues by using traffic control devices such as lane use management signs, variable speed signs, ramp signals and variable message signs. TMR can reduce speed, inform drivers of the queue, or proactively reduce congestion before it builds, to help reduce these risks. These measures are managed by algorithms that adjust their parameters according to the state of the traffic on the highway, and the location of the queue.
For the algorithms behind these measures to be most effective, they need accurate and reliable data about the traffic and the queue. This data is often gathered by inductive road loops. However, the data from ground loops is limited by the fact that it is location-based. Connected vehicle technology, like that used in the Ipswich Connected Vehicle Pilot, presents an opportunity to gather real-time trajectory data directly from vehicles, which can be collected with high accuracy, from all over the highway.
This research will develop ways to improve the algorithms and develop models to automate their calibration. These will be identified by looking at fundamental traffic engineering principles, the effect and interaction of the algorithms’ parameters, and integrating group loop data and connected vehicle trajectory data. In addition, the project will identify and suggest ways in which the current procedures can be improved.