The traditional way of developing vehicles is to base progress on earlier models and gradually add new functions, but this technique may not work when developing future autonomous vehicles, according to Chalmers University of Technology researcher Ola Benderius.
Benderius leads researchers in developing a self-diving truck as part of the Grand Cooperative Driving Challenge, a European Union project and competition in which 10 to 15 universities compete against each other with autonomous vehicles.
The Chalmers team views the self-driving vehicle as more like a biological organism than a technical system. "A biological system absorbs information from its surroundings via its senses and reacts directly and safely," Benderius says. He says all of the information the truck compiles from sensors and cameras is converted into a format resembling the way in which animals interpret the world via their senses, enabling the truck to react to unexpected situations.
In order to achieve this goal, the researchers are developing small and general behavior blocks that make the truck react to various stimuli. The truck is programmed to constantly keep all stimuli within reasonable levels. The researchers say the truck can continuously learn to do this as efficiently as possible, making the framework extremely flexible and good at managing sudden and new dangers.
The truck's software, called OpenDLV, is being developed as open source code.
From Chalmers University of Technology
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