Blog: Carnegie Mellon Methods Keep Bugs Out of Software for Self-Driving Cars

Carnegie Mellon Methods Keep Bugs Out of Software for Self-Driving Cars
Carnegie Mellon University (06/21/11) Byron Spice

Carnegie Mellon University (CMU) researchers have developed a method to verify the safety of driver assistance technologies, such as adaptive cruise control and automatic braking. The researchers developed a model of a car-control system in which computers and sensors in each car combine to control acceleration, braking, and lane changes, and used mathematical algorithms to formally verify that the system would keep cars from crashing into each other. "The system we created is in many ways one of the most complicated cyber-physical systems that has ever been fully verified formally," says CMU professor Andre Platzer. The safety verification systems must take into account both physical laws and the capabilities of the system's hardware and software. The researchers showed that they could verify the safety of their adaptive cruise control system by breaking the problem into modular pieces and organizing the pieces in a hierarchy. Platzer says that automated driving systems have the potential to save many lives and billions of dollars by preventing accidents, but developers must be certain that they are safe. "The dynamics of these systems have been beyond the scope of previous formal verification techniques, but we've had success with a modular approach to detecting design errors in them," he says.

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