Project tests whether autonomous cars can handle Australia’s tough roads

QUT researchers will take an Artificial Intelligence (AI) system on a road trip of south-east Queensland to ensure the autonomous cars of the future will be smart enough to handle tough Australian road conditions.

Professor Michael Milford will lead a team of researchers from the Australian Centre for Robotic Vision in the project, which involves a driver taking an electric Renault fitted with high-tech sensors and computers on a 1200km road trip including a wide range of road and driving conditions.

The project is part of the Cooperative and Highly Automated Driving pilot run in partnership with Queensland Department of Transport and iMOVE Cooperative Research Centre.

Milford said engineers at QUT’s research engineering facility have developed a research car platform equipped with a range of camera and LIDAR sensors used on autonomous vehicles.

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“As we drive, AI will watch and determine if it could perform the same as a human driver in all conditions.

“The big problem that faces autonomous vehicles right now is that at the moment they don’t drive as well as humans in all possible conditions.

“We’re targeting how the car might use infrastructure, such as lane markings and street signage, to help it to drive well,” said Milford.

Minister for Transport and Main Roads Mark Bailey said understanding AI technology was an important step towards getting automated cars on Queensland roads.

“This road trip will help us gain a better understanding of our future infrastructure needs.

“I’m looking forward to seeing the QUT researchers’ results from the 1200km road trip,” said Bailey.

Milford said current autonomous car systems, when faced with some of the road conditions Australian drivers deal with daily, either refused to go into autonomous mode or hand control back to a human driver.

This research project will look at how an autonomous vehicle’s artificial intelligence systems copes with Australian road conditions in four main areas: lane markings, traffic lights, street signs and how to determine a vehicle’s exact position despite errors that occur with GPS systems in highly built-up urban areas or poor reception areas such as tunnels.

The pilot project is part of the Queensland government’s wider Cooperative and Automated Vehicle Initiative.

Expected to run for 12 months, the Pilot will assess the degree to which modern sensors and AI techniques used on autonomous vehicles can interpret and understand signage and road markings to inform future development and investment in infrastructure.

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