What Role Will Software Testing Play in Autonomous Vehicle Design?

Dan Ammann, former CEO of Cruise — General Motors Co.’s autonomous vehicle unit — once said: “When you’re working on the large-scale deployment of mission critical safety systems, the mindset of ‘move fast and break things’ certainly doesn’t cut it.”

To describe the technology environment of autonomous vehicles as complex is a wild understatement. To start with, the software behind self-driving cars must work reliably, integrate seamlessly with other technology, perform well in a variety of high-stakes environments and other requirements typical of mission-critical technology. And it only becomes more complex from there.

When on the road, self-driving cars must also account for hazards, weather conditions, other vehicles, and the personalities of the drivers behind them, to name just a few of the myriad safety considerations. The latter is something scientists at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) attempted to solve by using machine learning to help cars predict motorists’ behavior and avoid those determined to be selfish or egotistical.

It’s an interesting concept, and worth considering how the approach could be incorporated into autonomous vehicle testing and deployment. However, it also underscores just how much work remains until self-driving vehicles reach an inflection point in the marketplace.

From our perspective as leaders in intelligent test automation, it seems pretty clear that testing must play a central role at every stage of the process.

Learn more about how Eggplant helps companies in the automotive sector modernize their testing approach, and you can also read about our work with mission-critical technology like NASA’s Orion spacecraft here.

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